Recent Advances in Materials and Manufacturing Technology

The EN8 carbon steel (unalloyed) was machined at different machining conditions in a lathe. The Indoloy IK-20 tungsten carbide tool was used for the dry turning of the material. The true stress–true strain curve for the material was obtained and the stress–strain relationship was obtained as σ = 850.48εn. The von Mises stresses (VMSs) were determined for different experimental parameters. The collected chips for all the machining conditions were examined under the scanning electron microscope (SEM). The mechanism of chip formation was identified by observing the SEM images for the chips. The mechanism was further established with reference to the extent of von Mises stress generation. The mechanism of chip formation depends upon the experimental parameters. The machining chips were formed by successive lamellar shear sliding with and without the presence of dislocation. The von Mises stress increases during the lamellar shear sliding chip formation at the higher strain rate. The chip formation was influenced by the crack formation at higher speed and feed to reduce the level of von Mises stress.

A Titanium superalloy BT20L is machined using electrical discharge machining (EDM). In this research paper, parameter optimization for material removal rate (MRR), surface roughness (SR), tool wear rate (TWR) and radial overcut (ROC) is done using the Jaya algorithm (JA). The objective is to maximize the MRR and to minimize SR, ROC and TWR. Response Surface Methodology is used to create a regression model which is used for single and multi-objective optimization. Jaya algorithm is run for 100 iterations for each objective function. Each objective function is tested three times using the Jaya algorithm. It has been found that the Jaya algorithm produces similar optimum solutions in each run. Multi-objective optimization (MOO) is used to optimize multiple responses at the same time. To solve the multi-objective optimization problem, a combined objective function equation is developed that combines four objectives into a single equation. This single equation is used for optimization, which is similar to single-objective optimization. JA is used to optimize the parameters of this MOO.

The evolution of machine learning techniques has generated creative solutions for smart cities, by which a life of human life can be easier. Amid the growing transportation data, the accurate traffic flow prediction has become a great requirement and hence regarded as an important for so many cites of reasonably a good size, which is a matter of worry which creates obstacle to continuous urban development. Nowadays, transportation data are exploding in the nature of big data. Presently, available traffic flow prediction models are less effective for many real-world applications. A short time ago, Intelligent Traffic System using deep learning has surfaced as a constructive and fruitful tool to lessen urban congestion and accurate traffic flow forecast. This study’s objective is to provide a thorough, well-organized assessment of the literature, which will include 29 publications from 2014 that were pulled from Web of Science, Scopus, and ScienceDirect. The extracted information includes the gaps, limitations, and future scopes for accurate and effective traffic movement prediction. Our research reflects that Convolutional Neural Network (CNN), Stacked Autoencoder (SAE), Long Short-Term Memory or hybrid are ML techniques that have been used frequently for the better and improved performance. In this paper, the proposed techniques are compared with shallow and traditional models. The Authors believe that this study provides an efficient manner for traffic estimation in smart cities.

Normalizing is a widely used heat treatment process for steel to induce desired mechanical and microstructural properties. In the present investigation, P91 martensitic steel was subjected to normalizing, followed by deep cryogenic soaking (DCS) using a muffle furnace and liquid nitrogen chamber. The specimens were reheated in the temperature range of 980–1150 °C and held isothermally for 10–135 min to homogenize the temperature. It is further subjected to air cooling at room temperature followed by deep cryogenic cooling at a temperature of − 196 °C for a time of 30 min in liquid nitrogen. The volumetric % of retained austenite (RA) envisages a logarithmic inclination with increasing austenitizing time for both “normalized” and “normalized followed by DCS” samples. It is ascribed to the steady reduction in thermal stability of the reversed austenite which was obtained at the elevated temperature during the austenitizing. However, the trend did not show either a constant (after reaching critical condition) or decreasing nature; therefore, it is suggested that the thermal equilibrium was not achieved. The variation in hardness also envisages a logarithmic inclination. The reduction in carbide stability at elevated austenitizing temperature (AT) and extensive recovery at the larger austenitizing time leads to reducing the hardness during the process.

The P91 martensitic steel is one of the most extensively used materials in engineering applications which is used to completely transform into martensite during normalizing. In the present investigation, P91 martensitic steel samples were subjected to “tempering” using a muffle furnace. The X-ray diffraction (XRD) spectra showed an increased peak intensity and displacement of peak angles with increasing tempering temperature (tempering-T) and holding time which indicated that the martensitic lattice was in a stressed state because of carbon saturation. An increasing peak for precipitates with an increasing tempering temperature and time (tempering-TT) was also obtained. A decrease in hardness and an increase in the impact toughness with increasing tempering-T were observed during tempering. For a given tempering temperature, the hardness decreased with holding time and it reciprocated to nearly constant values indicating that the equilibrium condition was also reciprocating. However, the impact toughness of the material was increased with tempering-T and holding time but did not reciprocate to constant/nearly constant which indicated that the equilibrium envisages impact toughness was not achieved. The volumetric fractions of precipitates of carbides/nitrides were also higher at the elevated tempering-T, and for a given temperature, it increased with time. The hardness was decreased and impact toughness was increased with increasing Hollomon–Jaffe tempering parameter. The equivalent hardness–toughness values were obtained after tempering at different conditions considering closer values of the Hollomon–Jaffe tempering parameter and a specific hardness was obtained at a combination of lower tempering-T and holding time (of 60 min) provided the similar tempering parameter considering the equivalent (to hardness) impact toughness (of 172 J) when tempering was done at the higher temperature for 10 min.

Friction Stir Processing (FSP) is a well-established solid-state severe plastic deformation surface alteration procedure. Fabrication, processing, and synthesis of materials with just surface alterations are all parts of FSP. As a result, the metal's base characteristics are preserved, and the result is a surface composite. FSP has lately been popular for producing surface composites that improve the tribological, mechanical, and microstructural properties of certain metals. Alloys of aluminum are used widely due to their light weightiness and corrosion resistance. AA2014 is used in the aircraft and automotive industries for its good machinability properties and good strength-to-weight ratio. In the current experiment, FSP was employed to produce a surface composite of AA2014 by using hybrid nano-sized SiC–CNT reinforcement. The number of passes has an important impact in determining the qualities of the surface composite in FSP. This paper examines the effect of the number of passes while keeping rotational and traversal speeds constant during FSP. After the experiment, analysis was carried out for microhardness and tribological properties. One-, two-, and three-pass FSPs were used to process the AA2014. The properties of the base metal, one-pass, two-pass, and three-pass Friction Stir Processed (FSPed) specimens were studied and compared by performing the experiment three times. From the average results of conducted experiments, it can be deduced that by increasing the number of passes, the microstructure improves in addition to improved coefficient of friction (COF), microhardness, and wear resistance for prepared specimens.

Rapid growth in the construction sector in India is leading to the scarcity of natural materials required for construction. In the process, construction and demolition waste is also generated. Disposal and management of C&DW are posing as major issue in the construction sector. In construction activities, use of recycled concrete aggregate can help in addressing these issues. For suitable and sustainable applications of recycled concrete aggregate, its properties and performance in concrete are studied in this research work. Particle size distribution and water absorption of recycled concrete aggregate extracted from construction and demolition waste are determined. High water absorption of 4.62% of RCA is obtained. Compressive strengths of concrete with various mix proportions using recycled concrete aggregate are studied. Recycled aggregate concrete made with full substitution of natural coarse aggregate with coarse-recycled concrete aggregate achieved characteristic compressive strength of 30 MPa. A numerical analysis is performed on experimental values of strength. Single-factor ANOVA method is used for test results after 28 days of curing. ANOVA results show that 100% replacement of natural aggregate with cRCA using IS design is fully acceptable as a sustainable alternative to conventional concrete.

The polymer matrix composites exhibit better mechanical properties. However, still there exist some mechanical failures under specific structural applications like aerospace, automobile, and shipbuilding. To overcome the above-said mechanical failures, the nanofiller was intercalated with epoxy polymer matrix at different wt%. It is expected that the high specific surface area and wrinkled surface morphology of nanofillers would lead to a better reinforced interface. The current study focuses on the effect of different wt% of nano-TiO2 filler in the epoxy polymer matrix on the hardness of the nanocomposites. The nanoparticles were mixed with the epoxy polymer matrix through mechanical stirring, followed by magnetic stirring and ultrasonication. The presence of nanofillers in the epoxy matrix was confirmed through XRD, SEM–EDS, and FTIR analysis. The hardness test was conducted to obtain the increment in the hardness of the nanocomposites. It is observed that there is a substantial increment of hardness in the nanocomposites with the increase in nano-TiO2 content.

The addition of nano particles in polymer matrix composites gives better strength by decreasing the crack propagation in polymer matrix nanocomposites. In this study, the mixing of nano-SiO2 fillers was done by a mechanical, magnetic stirrer and followed by probe sonication for different time periods. Epoxy/silica nanocomposites having 1 wt%, 2 wt%, 3 wt%, 4 wt% of nano-SiO2 were prepared experimentally. The samples were characterized using XRD, SEM–EDS, and FTIR, to know the presence of nano-SiO2 in the nanocomposites. The effect of cure and uncure of the composites on the microhardness was studied. It is observed that the incorporation of nanosilica in epoxy matrix increases the microhardness. Furthermore, the effect of curing has improved the hardness of nanocomposites.

In the rapidly advancing and spontaneous manufacturing industry, optimizing methods in machining processes is critical for a production plant to adapt efficiently to intense competitiveness and rising global demand for premium products. Optimization techniques in machining processes are regarded as a critical instrument for the continuous enhancement of quality of output. These methods involve the modeling of parameters and their relationships and the calculation of optimal processing conditions. But, identifying ideal machining conditions using cost-effective mathematical models is a complicated research endeavor, and modeling and optimization approaches have experienced significant growth and extension over time. The strategic vision of numerous modeling and optimization methodologies in machining processes has been assessed in this paper.

Friction welding is a solid-state joining process that is widely used in leading industries such as automotive and aerospace, where complex parts play an important role. It is a low-cost process in which temperatures increase but do not reach melting points, unlike fusion welding, and with small temperature fields, heat-affected zones (HAZs) are much narrower. Contact zone temperatures, frictional heat generation, and flow characteristics all play important roles in determining the ideal weld zone. That is why research into friction behaviour, joining behaviour, and temperature modelling is considered necessary. This research establishes a comparison between finite element analysis (FEA) and experimental study in order to encapsulate the correct welding parameters as well as determine the temperature fields, and heat distribution flow stresses at the required zones.

The microstructural developments of stir-cast (SC) and squeezed stir-cast (SSC) AZ91 Mg-alloy have been examined in this study under variable dry-sliding wear conditions. Tribological tests have been investigated on tribo-testing (pin-on-disk) arrangement with an applied load of 50N at a fixed sliding speed of 3 m/s under an atmospheric environment. The result of delamination of sub-surfaces of SC-AZ91 Mg-alloy reveals a high wear rate with a low friction coefficient. Also, the originations of cracks around the interfaces of SC-AZ91 Mg alloy have been observed in-between the primary alpha-Mg phase and discrete beta-Mg17Al12 phase. In contrast, the result of delamination of sub-surfaces of SSC-AZ91 Mg-alloy experiences a low rate of wear and a high friction coefficient. This is due to the induced friction which trends minimizes the loss of wear rate and formed a barrier of (material removal) wear debris near the sub-surface area of SSC Mg-specimen. Thus, the evaluated results demonstrate an inverse relation in-between the wear rate and coefficient of friction of SC and SSC-AZ91 Mg-alloys.

Reinforced concrete structures play an increasingly important role in civil and industrial construction, along with the technology of new concrete materials. With adequately designed layered or in-filled sections, crack resistance can be improved, along with the shear and flexure behaviour of the beam member. In the present work, the bending stresses, shear stress and deflection of the simply supported homogeneous beams with conventional solid concrete and brick-filled layered composite beams are analysed using ANSYS 2021 R2 software and compared. The results show that the shear and flexural behaviour is sufficiently improved for a layered beam filled with bricks. Fewer stresses were observed near the neutral axis due to the replacement of lightweight material like bricks in the mid portion. With a brick fill beam, the structure weight reduces and achieves economy.

Effects of dean no. (De) of annulus side (1300–2200) and inclination angle (β) (0–180°) of inner tube on annulus side Nusselt no. (Nua) and friction factor (fa) in eccentric (e = 0, 0.5, 2, 3.5 mm) tube in tube helical coil heat exchanger is investigated. Ethylene glycol (EG) and air are used as cold fluid and hot fluid on inner and annulus side, respectively, using k−ε standard model. Result shows that on increasing De, Nu increases but f decreases. Highest value of Nu is achieved for eccentric helical coil tube in tube (β = 0°, e = 2) in De = 2200, which is 1.05 and 1.01 times higher than concentric helical coil tube in tube (HCTT) and straight concentric tube in tube. Also, the effect of De is analyzed on thermo hydrodynamic index (η). On increasing De, η decreases slightly, but it is higher for HCTT. On increasing β (e = 2), Nua decreases but fa increases by 4.9, 4.2, 3.38, 1.75%, and 3.89, 5, 6.43, 7.38%, respectively. η value decreases slightly. Similar results also calculated at e = 0.5, 3.5 mm.

Numerical analysis of thermal performance of solar heater with the roughness equipped on one of the surface. Here triangular-shaped channel is used and fluid used in air. In this research work, various geometry of roughness elements (such as triangular, rectangular, semicircular, square, and trapezoidal) are taken in order to study their effect on heat transfer in turbulent regime (4000 < Re < 20,000) in triangular duct solar heater. ANSYS 18 is used for simulation purpose under steady-state condition. Excellent enhancement in performance of 2.76 is found at Re = 20,000 in trapezoidal rib (h/w = 2). The best values of TPP found on varying roughness geometry are 2.56 for triangle (h/w = 2), 2.54 for rectangle (h/w = 2), 2.4 for rectangle (h/w = 0.67), 2.06 for square, and 1.96 for semicircular rib at Re = 20,000.

Structural analysis is a significant part of the strategy and advancement of the aircraft structure. For smooth flight, the design of aircraft wings, which is one of the important parts, is very essential. Apart from this, the selection of material is also an important factor for the design. In the past research, all the structural design and modal proposed were with aluminium. In our research, we would like to explore with titanium alloy. Different views of the air foil wing were developed by using solid works, and modal analysis was done by using Ansys. The modes of vibration, with its corresponding natural frequency and mode shapes, also found out.

An adapted stir casting technique was employed to synthesize Al6082 composites embedded with 0, 0.3, 0.6, 0.9, and 1.2 wt.% of MWCNTs. As-cast composites were then heat treated with oil quenching to enhance their resistance against compressive loading. The microstructure of heat-treated nanocomposites was examined using an optical microscope, while energy dispersive X-Ray spectrometer (EDX) was employed to evaluate the presence of elements. Microstructural examination showed the grain refinement with MWCNTs up to 0.9 wt.% and agglomeration with 1.2 wt.% of MWCNTs. Maximum improvement in compressive strength was displayed by Al6082 composites incorporated with 0.9 wt.% of MWCNTs. These nanocomposites showed 80.9% enhancement over as-cast alloy in non-heat-treated condition, while 81.67% enhancement was shown over peak-aged Al alloy in the heat-treated condition.

Image processing has been shown to be a useful tool for analysis in a variety of domains and applications. Many machining parameters, such as machining time and cutting speed, side cutting edge angle, true rake angle, depth of cut, nose radius, feed rate, and so on, influence to machined surfaces. Analysis of machined surfaces aids in forecasting whether a component will succeed or fail when placed into operation. This study proposes to focus on a review of image processing applications.

Emergency medical professionals who lack subspecific musculoskeletal knowledge view emergency X-rays often out of need and wrong fractures represent approximately four of every five diagnostic mistakes in certain EDs documented.The experts use the X-ray picture to analyse the broken arm. The detection of manual cracks is repeated, and the risk of error is high. A possible solution to this problem is computer-based detection systems, which can provide clinicians with a second, confident opinion quickly. This paper presents an approach for detecting arm bone fractures based on data normalisation and CNN classification in recent advances in deep learning and the artificial intelligence subfield. The proposed CNN also examines positive or negative expectations of arm cracks, and proposed scheme is capable of achieving an average accuracy of 76.15%. The classification is carried out by the convolution neural network (CNN).

Composite materials have been found to be the top most choice among different manufacturing industries against the conventional metal components. Their excellent properties in terms of strength, rigidity, light weight, corrosion resistance, impact resistance, and durability have proved to be the most promising material in the global market. Currently, composites are gaining more attention from different researchers and academicians due to improved sustainable performances in varied areas of application (automobile, aerospace, marine, transport, construction, biomedical, and sports). The presence of the constituent fibres along with different manufacturing techniques largely decides the performance of the composite materials. An overview of different manufacturing techniques is undertaken to select the best-suited technique to develop fibre-reinforced polymer (FRP) composite for wide range of applications. The effect of symmetrical/usymmetrical stacking sequence on mechanical and tribological properties of fibre-reinforced polymer composites has been investigated successfully.

The EDM is generally used in the drilling hole having high aspect ratio. However, in the deep drilling, the machining speed may decrease or even stop due to aching phenomenon. This is because of improper debris removal from the spark-gap zone. Improper flushing decreases material removal rate, surface finish and also increases machining time and chances of secondary arching and short circuiting. In order to increase the flushing during machining process and to improve the machining parameter, better understanding of the dielectric distributions and flow directions is required. Recent trends and understanding in the field of flow simulation in EDM process have been reported in present paper.

Aluminium metal matrix composites are widely used in the aerospace and automotive industries due to their light weight, increased strength, corrosion resistance, and high toughness. The hybrid metal matrix composite is made up of three (3) constituents: Al 7075, SiC, and graphite. Al 7075 is used for high strength and good corrosive resistance, SiC strengthens the reinforced particles, and graphite improves the welding properties. In this study, the stir casting process is used to fabricate hybrid metal matrix composites (MMC), i.e., Al7075/SiC/graphite, with different weight fractions of SiC and a constant 1 wt.% of graphite. This hybrid metal matrix composite has been subjected to a variety of tests, including tensile, hardness, and toughness tests. The impact strength of the composite increases to 42%–56% when 0.5, 1.0, 1.5, and 2 wt% SiC is added to the base alloy, while the graphite constant remains constant at 1 wt%. Similarly, tensile strength is increased by 43%, and Rockwell hardness strength is increased by 11%. In the hybrid MMC, microstructure analysis is also performed at various SiC compositions.

The cold spray process is a high-impact coating deposition technology that deposits powder particles on the substrate surface that range in size from microns to nano. Since the spray particles are not melted during the cold spray process, their physical and chemical characteristics are preserved in their original state. The cold spray process characteristics make it special and ideal for several engineering applications. This is a novel technology, and marginal data is available as latest. Around three decades ago, this technique was developed, but it has yet to establish itself as a feasible industrial technology. As a result, commercialization of this coating method will necessitate efforts as well as support from public and private sources. Cold spray is likely to become a feasible coating technique all over the world in the next decade. This paper briefly covers the cold spray coating methods, including their working principle, types, parameters, applications and challenges. The outcome of this study is that using a cold spray procedure improves coating quality.

In this paper, the typical uniaxial compression test of a cylindrical specimen has been modeled using the finite element method. Ideal cases for compression testing have been developed using only the specimen model under load and displacement-controlled test conditions. The results of these cases show that the displacement boundary condition is closer to the strength of material data. Therefore, the finite element model of the actual compression test setup consisting of the cylindrical specimen and platens has been analyzed for displacement-controlled test conditions. The frictional contact conditions between specimen and platens have been modeled using different values of friction coefficient representing smooth and rough contacts. The contact tractions at the specimen-platen interfaces and the corresponding states of stress and displacement in the specimen have been obtained under these actual test conditions. All these results help in understanding and addressing the ‘barreling,’ commonly found in the uniaxial compression testing of cylindrical specimens. The presented results also suggest that the radial motion must be allowed at the specimen-platen interfaces for developing uniform uniaxial compression in the entire specimen—a valuable input for designing a new compression platen.

The use of biodegradable metallic materials for implants is growing in popularity within the biomaterials industry due to their superior mechanical properties and degradation rates compared to polymeric materials. Zinc and its alloys have been studied in recent years as possible candidates for biodegradable stent applications. This study aims to formulate and evaluate a new series of Zn–Ti/Cu alloys with the goal of finding an alloy that meets the standard mechanical properties required for biodegradable implants. The alloys were produced using vacuum induction melting, and various experiments were conducted to determine the effect of adding titanium and copper on the mechanical properties of zinc. The study looked at factors such as microstructure, mechanical properties, cytotoxicity, and antibacterial properties. The results showed that copper provided improved cytocompatibility and effectively eliminated bacterial reactions, and the mechanical results indicated that zinc-copper alloys had greater strength than other alloys. Thus, it can be concluded that Zn–Ti/Cu alloys are a viable option for biodegradable implant applications.

The paper demonstrates the analysis of cantilever beam having dissimilar modularity in tensile and compressive tests liable with thermal and mechanical loading. The prime objective is to evaluate the governing differential equations to determine the displacements of the bimodular beam under combined loading of thermal and mechanical loading. The relation between change in temperature for conduction and convection for particular value of length of cantilever beam has been assessed.

The significance and use of UAVs/drones in the healthcare sector has increased drastically since the onset of the COVID-19 Global Pandemic. Hence, we studied the field of UAVs and alongside fabricate our own model, which could help in transport of medicines/medical equipment. Our primary aim is to do a case study about the use of drones in this field and then design a drone according to the findings of the case studies. We’ve used SOLIDWORKS and Ansys for design and analysis. Other applications, control technology, and the principles behind the flight of drone have also been covered.

Hybrid metal matrix composites are well known for a variety of cutting-edge applications in the domain of automotive, aerospace, agricultural machinery, electronics equipment, and turbine blades, among others. These materials outperform metals and alloys in terms of good strength, lesser density, low coefficient of thermal expansion, and high wear resistance. In this study, different amounts of WS2 (0.75%, 1%, and 1.5%) were used to make an Al7075 alloy matrix reinforced with 10% SiC at a constant proportion. Additionally, a CNC electric discharge machine was used to assess the composite's machinability. The input parameters like wt.% of WS2, current, voltage, and pulse on time have been considered to form a Taguchi-based L9 array which is designed to perform a set of experiments. Responses like metal removal rate, radial overcut, surface roughness, and tool wear rate have all been studied to determine the impact of machining parameters. The regression mathematical model has been generated by using Minitab 18 software for all four responses. Simultaneously, multi-objective genetic algorithm has been employed by using MATLAB to get optimal parameters.

Over the past decades, there has been a drastic growth in additive manufacturing which is also referred to as 3D printing. The ability of 3D printing to lay material in a 3-D matrix with great precision, even with the most intricate designs, is quickly making them mainstream in production, industrial, academics, medicine, dentistry, biomedical and other sectors. Although there has been vast development, great potential lies ahead in increasing its versatility in promising fields like bio-printing, hybrid 3-D printing and many more. Owning the potential to fabricate patient-specific designs and medical devices at a practical cost within a suitable time, 3D bioprinting is establishing itself as a dominant technology for the new era medical revolution. However, bioprinting being a budding field lacks in diversity of bio-printable materials or 3D inks and the compatibility of these inks with the current printing techniques. This study objects to highlight the current developments in bio-printing ink and factors affecting it’s printability. A brief overview of ink requirements for current printing techniques is also provided.

The primary goal of the article is to build a robot that can locate and extinguish the fire on its own. Minor human errors cause fires in industry, commercial spaces, and hospitals, among other places. Between 2010 and 2014, more than 1.2 lakh people perished in India as a consequence of fires, according to the National Crime Records Bureau (NCRB). Fire detecting and extinguishing robots are being developed to help in firefighting without the need for human involvement. There are several firefighting devices available for clearing out wildfires and carrying out flames in residential areas. The robot we have described here might be used to stop fires from spreading in their initial stages. Such robots might carry out activities like fire detection and total destruction without endangering the lives of the firefighters or creating hazardous situations. Robotics technology has improved to the point that it is now feasible to replace humans with robots in firefighting. Because of a lack of technological innovation, firefighting has frequently proven dangerous, resulting in severe and devastating losses. The robot is built using various components and for the movement of the robot two DC motors and a castor wheel at the front. To power the robot, a 12 V battery is utilized, and then, a 12 V DC pump for suction and a servo motor for axial spraying of water are employed. Several sensors are linked to the Arduino Uno board. A software called Arduino IDE is used to write the programming language that is utilized to provide inputs to the robot from sensors.

Since the early twenty-first century, noise convention around airport have turn into more stringent due to the environmental impact that noise pollution has on the general public as the future development of the aircraft industry become constrained by its noise emission, engine manufacturer has work in a new solution to trim down the jet overall noise. Aircraft noise, which radiates from the exhaust of an airplane engine, is a major factor in aircraft noise. The present provision in the ability of passive aircraft sound diminution technology is represented by chevron nozzles. This type of nozzle marks triangular grooves in the nozzle trailing edges that improve mixing between the jet and the ambient air to yield a speedy decay of the jet aircraft plume, consequently reducing jet noise. In this research, the N10 chevron nozzle is designed with various angle change model analyses and compared with the N8 chevron nozzle which is similar to the chevron nozzle installed in the trailing edge of the nozzle used in Bombardier CRJ900. Different models have been studied based on the geometric parameter of the chevron to acquire efficient blueprint constraints of chevrons in the nozzle. The selective design in N8 and N10 V-shape chevron nozzle with tip angle 60° were modeled in CATIA, were analyzed in ANSYS fluent software. During the investigation, acoustics power level of individual’s model is considered at takeoff because the thrust needs more during takeoff of aircraft as compared to cruise for obtaining an efficient model.

In this study, epoxy-based partially biodegradable sustainable hybrid bio-composites are synthesized by using a mixture of Human Hair Fiber (HHF), Luffa Cylindrica (LC) and various weights as filler (0, 10, and 20 wt% of Incense stick ash (ISA)) via ultrasonicator assisted hand lay-up procedure. The machinability of the fabricated composites is investigated through the Abrasive Jet Machining (AJM) process. The experimentations are planned as per Taguchi’s L9 orthogonal array design of experiment (DOE) by considering the pressure, stand-off distance, composite type, and abrasive type as the controllable process parameters. The rate of material removal (RMR), overcut (OC), and surface roughness (Ra) are considered to be the machinability indicators. The optimal process parameter settings that will result in the minimum OC, minimum Ra, and maximum RMR are determined for individual output responses by S/N ratio analysis. Further, a multi-criteria decision-making method, TOPSIS is implemented to perform multi-objective optimization. The assortments of optimum conditions obtained are justified by performing confirmatory tests. The optimum parameter obtained for the simultaneous optimization of output responses are 20 wt% ISA-filled composite, 3 bar pressure, 5 mm stand-off distance, and silicon carbide (300 µm) as the abrasive particle.

In order to convert solar energy into thermal energy, solar air heater (SAH) is commonly used. These are used to convert the solar radiation into heat of working fluid. The effect of various geometric constraints on the friction characteristics and heat transfer (HT) of a SAH has been studied. The paper aims to introduce the various parameters that are involved in the analysis of HT enhancement of SAH. There are various techniques that are involved in the analysis of HT enhancement of SAH. One of these is the use of a passive method, which involves the use of turbulators, ribs or fins on the surface. SAHs that are roughened can improve their HT properties compared to their plain counterparts. This is because the various surface patterns and shapes used in their design can help improve their performance. There have been many different sorts of studies conducted on the many facets of these HT augmentation approaches. Studies showed that combining the roughening process with a rough absorber plate can improve the performance of SAH duct. The goal of this study is to identify the most appropriate roughness component for solar air duct that can meet the different operating conditions. The findings of this study can be used to design and construct enhanced SAH duct system.

The world is evolving with new technology, and people are becoming smart each and every day with science and technology. Smartness comes with complications, and these complications are needed, to solve the everyday problems of industry and society. Materials technology is also advancing, and smart materials are developed at a fast rate. Smart materials increase the efficiency of machinery. Self-healing materials are one category of the advanced materials. Self-healing materials increase the life span of components and also reduce the chances of catastrophic failure that is also helping in providing safety for the operator. Reducing the frequent intervention of human operators and also lessening the maintenance cost. Typical microscopic methods such as optical for maintenance purposes and scanning electron microscopy as well as analytical and spectroscopic methods like nuclear magnetic resonance spectroscopy (NMR), atomic force microscopy (AFM), Fourier-transform infrared radiation (FTIR), and Raman spectroscopy employed for the evaluation and monitoring of self-healing effect are presented in the current chapter. In the self-healing concept, two methods are used to make materials self-healable, i.e. extrinsic and intrinsic strategies. In this chapter, recent progress in the extrinsic self-healing composites has been reported.

Austempered ductile cast iron (ADI) has attracted considerable interest in recent years because of its excellent properties, such as high strength with good ductility. There are different components of automobile which is made of ADI. Austempered ductile iron (ADI) is produced by an isothermal heat treatment. Tempering is an effective method to increase the toughness and decrease the hardness of ADI. In the present research, the transformation of ADI was investigated after applying various tempering temperatures of Spheroidal Graphite (SG). The mechanical property such as hardness of ADI samples was measured and the microstructure of ADI samples was analysed. It is observed that the ADI has better mechanical properties than SG iron. Therefore, ADI iron can be used in automotive and other structural engineering applications where the design requires better mechanical properties than SG iron.

The addition of fiber and nanofiller into the polymer resin improves the wear, tensile strength, hardness and flexural properties of the composite. Optimization technique is the process of analyzing the optimum value of the tribological and mechanical properties of the composites. In this review paper study, the effect of different parameter on wear and strength of different hybrid composites. For analyzing the performance of the composite different techniques such as Taguchi orthogonal array and ANOVAs variance technique were used with the help of Minitab software. The results show that the new technique gives the better result as compare to experimental analysis results.

Solar is an eternal source of energy and has provided opportunities to utilize this energy to cater to various human needs. India being a tropical country has ample scope to harness this energy. The heating of water for various needs can be utilized by solar water heaters. Here, the effect of wind speed has been taken into consideration for optimizing the tilt angle’s collector plate. The experiment is conducted at the lab of the Mechanical Engineering Department, Jabalpur Engineering College, Jabalpur. The experimental setup for solar heater analysis is supplied by ecosense sustainable solutions pvt ltd [1]. The data is collected for a mass flow of 4 lit/min for heat transfer between collector tubes. We analyzed variations in the wind like 2.2 m/s, 3.4 m/s, 3.7 m/s, and 4.4 m/s. Wind speed is controlled by the fan which is installed near the flat plate collector, which can be also regulated by the regulators and provide desired wind speed. The data is analyzed to measure the heat loss by the collector in terms the heat loss coefficient at the top surface of the collector plate. Data is also analyzed for the changes in temperature for the inlet temperature and outlet temperature of the water, at least heat loss coefficient at wind flow at various said conditions.

Nowadays, the development speed of computer technology is accelerating, and in the process, the game industry has developed into an emerging entertainment industry with a large market in my country. With the rapid development of the game industry, some related technologies also show a trend of rapid development. The main purpose of this paper is to study the application of artificial intelligence pathfinding algorithm in 3D game development strategy optimization system. This paper firstly studies pathfinding and analyzes basic mobile pathfinding, simple obstacle-avoiding pathfinding, and waypoint pathfinding; then introduces the A* algorithm, including three types of heuristic functions: Manhattan distance, Chebyshev distance, and Euclidean distance. After testing various search algorithms without obstacles and with obstacles, the experiments show that the A* algorithm is the most suitable for game pathfinding operations. The game path, it searches, is very smooth and intelligent, and the consumption is very high less CPU time.

With the development of society, people have higher requirements for the environmental quality of garden landscape space. Among them, garden landscape design is an important link, and the optimization design of garden landscape space environment is already an emerging field. The optimization design of the garden landscape space environment can improve the hard pavement in the garden through reasonable planning and combination of each functional zone in the garden and improve its performance and economic benefits. At the same time, interactive genetic algorithm is an optimization method that is based on natural evolution and genetics and has been popular in the fields of scientific research and engineering design in recent decades and has good development prospects. Due to its effectiveness, feasibility, and low cost, this algorithm is widely used in modern intelligent buildings. It can be said that this algorithm is a relatively novel method in the optimization design of garden landscape space environment. Compared with traditional mathematical calculation methods, it has fast calculation speed and high precision. At the same time, it can study the evolutionary laws of natural species by simulating the process of biological evolution. In the design and planning of garden landscape, interactive genetic algorithm is an important, novel, efficient, and effective tool for solving optimization problems. This article adopts experimental analysis method and data analysis method to explore the effectiveness of interactive genetic algorithm in the optimization design of garden landscape space environment, which is conducive to solving many problems in traditional garden landscape space design. According to the experimental results, as the evolutionary algebra increases, the individual fitness value gradually increases, indicating that the quality of the population continues to improve. This reflects that the algorithm has good algorithm performance and optimization efficiency, and it is also more convenient for the development of garden landscape space environment optimization design work.

Since the twentieth century, great changes have taken place in the global climate. Global warming has become one of the global environmental problems attracting worldwide attention. Global warming will have a huge impact on the climate. We collect the values of the global average temperature from 2012 to 2021. Considering the influence of earth's heat absorption, heat dissipation, and ocean surface temperature on the climate, we predict the future average temperature of the earth by the grey prediction model. The results show that the global average temperature is on the rise. We must establish a global partnership for climate governance in order to effectively alleviate the dilemma of climate governance and fully show its strong driving force for development and broad prospects for development. The global partnership for climate governance is playing an increasingly prominent role in global climate governance.

This paper takes the one-five-storey building as the empirical research object. Constructs a 3D model of the building by modelling the building with BIM technology, and combines Pathfinder and PyroSim simulation analysis to conclude that compared with anyone who has not been through an evacuation drill (hereinafter referred to as group A), people who have been through evacuation drills (hereinafter referred to as group B) who have been through evacuation drills more calmly during evacuation and are able to make better judgments after participating in evacuation drills several times, and compared with group A, saving 45 s in escape time in the same environment (assuming the same number of group A and group B).

With the process of urbanization and the rapid economic development, high-rise buildings are gradually increasing. It poses a big challenge to fire and rescue problems. At the time of the fire, for a more efficient evacuation, reduce the panic of the trapped people, reduce the blindness caused by disorderly command, improve the survival rate, minimize the damage from a fire based on the idea of indoor positioning technology and mobile terminal technology. Through the relative ratio of Japanese evacuation time calculation and Pathfinder evacuation simulation, the side reflects the urgency of the current demand for intelligent evacuation. Combining indoor positioning technology and mobile terminal technology. ability to schedule according to big data information, accurate positioning, spread out the people, plan the best escape route for the trapped people, and avoid greater casualties caused by congestion. It is of great significance for high-rise evacuation and fire safety.

Nowadays, the information systems in public areas are separated and unrelated, and the various systems are not related to each other. But at the same time, employees are required to operate all systems in an orderly manner, which leads to the trouble of frequent system switching. Therefore, in order to simplify the work process and facilitate the operation of the staff, this article briefly outlines the technologies that can be used in system development. It briefly analyzes each technology, and then explains the reasons for choosing that technology for the system.

In recent years, neural network is a computational model that imitates animal neural structure and adopts the form of connection. The neural network consists of multiple neurons, grouped by layer, and the neurons in each layer are connected with other layers. In the forward reasoning operation, the output of the previous layer is taken as the next layer. The deep learning method uses a general learning process to learn feature representation from data and extract more effective image feature information, which surpasses the original manually designed image feature extraction method and has strong nonlinear modeling ability. With the continuous deepening of research, deep learning technology has achieved remarkable results in image classification, object detection, image segmentation, and other computer vision fields. Perovskite solar cells are solar cells that use perovskite type organic metal halide semiconductors as light absorbing materials and belong to the third generation of solar cells. The development of perovskite solar cells is in good condition, but there are still some key factors that may restrict the development of perovskite solar cells: 1. The stability of batteries. 2. The absorption layer contains soluble heavy metal Pb. 3. The theoretical research of perovskite solar cells needs to be enhanced.

Plastic has the advantages of high specific strength, good processing characteristics, good corrosion resistance, and good performance design. It also has the performance requirements of some mechanical parts, which can save cost and facilitate molding and manufacturing. The demand for plastic applications is growing day by day, and it is widely used in various industries, such as household appliances, automobiles, decoration, aerospace. At present, most plastic parts are processed by traditional injection molding. The processed products are not only high precision, but also have strong consistency. This paper simulates the injection molding of thin-walled porous plastic parts based on Moldflow synergy software, and uses ABB industrial robot to carry out automatic handling of processed plastic parts.

With the development of switching power supply technology and the advent of new power electronic devices, switching power supply is becoming more and more high-frequency and modular. In the switching power supply circuit, the driver circuit is located between the main circuit and the control circuit, and has the function of amplifying the control circuit signal to drive the power transistor. Therefore, a drive circuit which can reduce power loss and more integrated becomes particularly important. Aiming at the high power, low loss, integration, and other aspects of switching power supply, this paper designs a DC-DC converter switching power supply driver circuit based on the two terminal push–pull topology. The circuit includes bridge rectifier circuit, 7815 voltage stabilizing circuit, optocoupler circuit, and feedback circuit. After voltage stabilizing, filtering and amplification, the input AC power is output through 6N137 coupler to achieve the amplification of control signal. B882 and D772, two opposite polarity power transistors, are used in the push–pull amplifier circuit. In the operation of the circuit, B882 and D772 transistors only conduct one at a time, which reduces the conduction loss and improves the output efficiency. The power amplifier circuit of output transformer is omitted in this circuit, which makes the circuit structure more portable and conducive to the integration of the circuit.

The C-NCAP management rules (version 2021) stipulates that in the part of occupant protection, the technical requirements for additional points of the side air curtain are modified from the additional points of 3 points of the side air curtain in version 2018 to the penalty points of version 2021, that is, the side air curtain meets the three technical requirements of appearance size, deployment shap, and dynamic protection. At the same time, the air curtain with pressure holding performance on the side air curtain shall be given an extra score of 2 points.

Public space (PS) is an indispensable event place in everyday life. With the advancement of society, the structure of PS is increasingly complex, and the public's demand for booting systems is getting bigger. However, compared with developed countries, my country still has a gap in the field of public spatial guidance system design. This paper selects the medical PS as the main body, combined with the characteristics of the hospital's functional districts, and analyzes the behavior characteristics and psychological activities of the user in the hospital building environment, which will discuss and analyze the interaction. In this paper, in the field research process of the status quo of each hospital, select some users as a research object, collect and classify data on the use of the guidance system in medical PS. Due to the lack of existing boot systems in my country, this paper selects a three-way hospital as an object of design practices, analyzes the space of behavioral habits and behavioral types; design the guidance system of medical PS, verify the feasibility of the boot system. This paper analyzes and summarizes the design issues of medical PS guidance systems by combining theoretical and practice, intended to explore some effective design methods and evaluation criteria to improve the effectiveness of PS guidance systems.

Due to the complexity of deep foundation pit engineering, the theoretical calculation and design of deep foundation pit are not perfect at this stage, and it is difficult to design by quantitative analysis, so it must be corrected by management means to control, which makes the position of deep foundation pit engineering monitoring in deep foundation pit engineering especially important. The purpose of this paper is to study the design of information construction management system of deep foundation pit project based on BIM technology. The construction of foundation pit displacement monitoring basic database is carried out based on SQLServer2008 database management system, and the unified management of foundation pit displacement monitoring spatial data and attribute data is realized. Finally, the development of Windows desktop system for foundation pit monitoring data management and analysis was carried out based on VisualStudio2010 development platform using C# programming language, and the applicability of the system was proved through the application of engineering examples.

In order to ensure the rationality of the landscape design of characteristic towns, it is of great practical significance to simulate the planning effect. The purpose of this paper is to study the construction of a landscape simulation design system for characteristic towns based on improved fish swarm algorithm. The town landscape simulation system is designed, and the realization of the system relies on the improved fish swarm algorithm. Finally, the efficiency of the system is tested in this paper, and the test results show that, although most of the time is spent in the building generation phase, the overall computation time is within acceptable limits.

This article reviews the entire process from 5G spectrum planning to the introduction of international standards and then achieving large-scale commercialization. This article summarizes the key technologies and application scenarios of 5G and finally analyzes and predicts the future development and application prospects of 6G.

Firefighting equipment, as the material basis for firefighting safety in buildings, plays an important role in firefighting and rescue work. Ensuring its smooth and effective operation is an important prerequisite for smooth fire-fighting work. Therefore, regular maintenance and proper management of firefighting equipment are required to ensure its normal operation and use. The main purpose of this paper is to use GeoMap to study the management system of electric firefighting equipment. This paper analyzes the main principles of the system construction and the overall demand analysis and designs the system frame. The economics of firefighting equipment management is also analyzed. The research results show that the operation and maintenance cost of the ultra-fine dry powder fire extinguishing device is the highest because the fire-extinguishing device needs to be replaced at least every ten years, followed by maintaining the high-pressure water mist fire extinguishing system. The lowest is a water mist spray fire extinguishing system.

With the advancement of rural power grid reform, there are still regional power quality problems that cannot be resolved. During peak periods of power consumption, low voltage problems cannot be avoided in a few areas. Good power quality can ensure the safe and stable operation of the power grid, reduce various hazards and economic losses, and generate good economic benefits. It can be seen that the research on mobile peak shaving equipment has obvious theoretical significance. The purpose of this paper is to study the mobile peak shaving equipment based on the rural network line. Taking the research on mobile peak shaving equipment in Taiwan as the main line, the current research and application status of various peak shaving equipment at home and abroad is described in detail, and the advantages of mobile peak shaving equipment are analyzed. By studying the current situation of power quality problems in Taiwan area, a mobile peak shaving equipment for power quality management in Taiwan area is used. Power quality control is carried out in the station area where the line loss is large and the reactive power and under-compensation are serious, causing the terminal voltage to be low.

For promoting the coordinated development of clean energy and power grids, this paper took large-scale adoption of wind and solar energy as planning goals and establishes a collaborative planning approach for power lines and storage configuration, which specifically considering of the operating peculiarity of power storage unit and power line planning to minimize line number, the equivalent power storage cost each year and abandoned wind and solar power cost, established a collaborative planning model for power lines and storage configuration that could improve the ability to accept wind and solar on a large scale. The calculation examples based on IEEE RTS-24 node system showed that the proposed optimization method was effective, and the overall economic efficiency of the system and the consumption of renewable energy under collaborative planning.

Aiming at the low utilization rate of steel cutting raw materials, a simple and efficient filling algorithm is proposed. For steel, it is necessary to cut in the row direction first and then cut the remaining part in the column direction after it cannot be cut. The two cuts are repeated until the steel cannot be cut, and the best cutting scheme of the steel is obtained. This process is realized by filling algorithm. Finally, the above process is circulated, and the cutting scheme is required to be obtained in the traversal. The minimum consumption of raw materials is the first priority, and the highest yield is the second priority. Numerical experiments prove the feasibility and superiority of the filling algorithm.

Substation is an important part of the power network, and it is the junction between transmission and distribution. Regularly monitor the power design of the substation preparation for inspections is an important guarantee for its safe and stable operation. With the continuous improvement of the automation level of substations, the traditional manual inspection operation method is gradually being replaced by the drone inspection operation method. This paper focuses on the research of UAV cooperative inspection trajectory planning based on ant colony algorithm, summarizes some of the difficulties faced by UAV cooperative inspection trajectory planning at this stage, and then introduces some problems related to ant colony algorithm optimization. A simulation experiment is performed to verify the optimization of the algorithm. The experimental results show that the algorithm in this paper is more effective than the traditional algorithm in searching for the minimum track cost. Compared with the traditional algorithm, the value of the minimum track is reduced by about 20.

With the rapid development of my country's economy, the process of urban–ruralization is also accelerating. At the same time, the requirements of urban and rural construction and planning on the power system continue to increase. However, most of my country's urban and rural areas have serious drawbacks in urban and rural power grids. Therefore, it needs to be studied. Moreover, with the advancement of urbanization, it is necessary to integrate power grid construction with urban–rural planning. This article mainly applied the method of field investigation and comparison to the integrated design of urban and rural planning and power grid planning and studied the feasibility of auxiliary systems. The survey shows that the annual growth rate of space load can reach more than 21%, and people are using more and more electricity. This is enough to explain the improvement of the quality of life of urban and rural people and the increase in electricity demand. Therefore, it is necessary to study the connection of urban and rural planning based on GIS and the auxiliary planning system of power grid planning.

With the rapid development of artificial intelligence technology and robotics today, the research on biped robots and walking stability has always been one of the frontier topics, attracting countless researchers to join them. Machine learning is a statistical learning method that studies the way that computers imitate human learning behavior and accumulate experience and continuously improves and optimizes its own performance. It is one of the main concerns and research issues of biped robot walking stability. The purpose of this article is to study the walking stability of biped robots based on machine learning algorithms. This paper analyzes the factors that affect the walking stability of the biped robot and summarizes the conditions for the walking stability of the biped robot from two parts: ZMP and the center of the ground projection point. In this paper, through the constraints that the biped robot should meet during the walking process, the time construction method, the spatial cubic spline interpolation method, and the three-dimensional linear inverted pendulum method are used to plan the walking mode of the biped robot, and the robot computer simulation is used to compare the superiority of the three methods. The simulation results show that the maximum offset of the biped robot ZMP using the sequential function construction method, the spatial spline interpolation method, and the inverted pendulum gait planning method are 0.221, 0.169, and 0.057 m. It can be seen that when the biped robot is walking, it will be more stable to use the inverted pendulum gait planning method.

Information-based project management is a brand-new way to manage and control project progress, which can expand thinking and vision, cultivate systematic thinking and a realistic and pragmatic work style, and improve the efficiency of project progress management. With the development of various technologies in the information age, the traditional method of engineering project documentation is no longer suitable for the needs of the new era. The main purpose of this paper is to carry out research on the design of power transmission and transformation engineering management system on the basis of distributed load balancing. This paper mainly conducts an in-depth study on the construction process of power transmission and transformation projects. Combined with the characteristics of power transmission and transformation project file management, the load balancing scheduling algorithm is improved. Experiments show that the load balancing threshold should have sufficient accuracy and can reasonably judge and divide the load status of distributed nodes in the cluster.

Computer technology is developing rapidly, and image recognition systems are becoming more and more important in human life. People obtain data through visual sensors and transmit it to the brain. The key to image recognition is to establish an efficient, real-time, and accurate three-dimensional digital model. However, due to different environments and backgrounds and noise interference factors, there is inevitably a certain degree of difference in the processing process, so the efficiency is low and unstable, which causes the recognized image to be too blurred, which affects the actual work’s efficiency. The response time of the system (TS) is 36, 39, 26, and 51 ms, and the recognition accuracy rates are 96, 93, 89, and 91%, respectively. It can see that the response time of this experimental test is relatively short and the image recognition accuracy is high, which can meet the basic requirements of intelligent image recognition.

Shape memory alloy is a kind of smart material with shape memory effect and superelastic effect. It has been widely used in many fields such as aerospace, architectural structure, medical instruments, and so on. With the diversification of shape memory alloy materials, it is urgent to accurately describe the thermodynamic coupling constitutive equation of shape memory alloy and conduct numerical simulation to achieve high probability prediction of the behavior of shape memory alloy under thermal–solid coupling load. In this paper, the thermodynamic constitutive equations of shape memory alloys are presented, and the phase transformation-induced conditions and process of shape memory alloys are described in detail. By writing a user-defined subroutine UMAT in Abaqus, the shape memory alloy wire was simulated by uniaxial stretching, and the accuracy of the subroutine was verified by comparing the simulation results with the experimental results. By giving the material parameters of shape memory alloy material under uniaxial tension, finite element simulation was carried out on the assembly process of pipe joint in hydraulic system, the stress cloud diagram and phase transformation process during expansion loading and unloading were observed, and the inner diameter changes of SMA pipe joint after expansion loading and unloading were predicted. The results show that the numerical simulation results are in good agreement with the experimental data, and the subroutine written with the constitutive model mentioned in this paper can be used to simulate the assembly process of shape memory alloy material in hydraulic system.

With the rapid development of society and economy, the efficient use of energy is becoming increasingly important, and my country is rich in WH resources. Vigorously developing and promoting WH recovery and utilization technology has very important practical significance for the high quality of economic development. The main purpose of this paper is to study and analyze the performance of the low temperature dual pressure WHPG system, and to optimize and improve it on the original basis. In this paper, the WH flue gas of a micro-combustion turbine is used as the heat source, and the dual-stage organic Rankine cycle (DORC) system is taken as the research object, and the research on the WHPG of the DORC system is carried out. Experiments show that, taking the working fluid n-Heptane as an example, when the sum of the pinch point temperature (PPT) difference of the evaporator increases from 30 to 60 K, the optimal power generation cost LEC of the system increases from 0.1327 to 0.1593 $/kW·h. The economy is getting worse and worse, and the corresponding optimal PPT difference ratio k is reduced from 1.75 to 0.75.

An autonomous vehicle is a vehicle that can actively perceive the environment and drive autonomously without human intervention. With the advancement of technological innovation and industrial transformation, autonomous driving technology is also constantly maturing. The main purpose of this paper is to design and study the path of vehicle autonomous driving based on the AdaBoost algorithm. A vision-based adaptive multi-vehicle target tracking algorithm is proposed. The classification of different sensor vehicle detection algorithms is analyzed. An adaptive Kalman filtering vehicle filter with an online statistical module of target noise characteristics is established. It effectively improves the accuracy and stability of target tracking in dynamic multi-vehicle scenarios. For the system performance detection of different light scenes, experiments show that the detection rate in low-light scenes can still reach more than 80%, and better detection results can still be obtained.

Aiming at the disadvantages of traditional learning algorithms, we use computer technology and methods to solve the problem of TBM program. Based on reinforcement learning algorithm, this paper mainly uses computer-aided theoretical knowledge to build a relationship model between parameter distribution, constraint conditions and feedback variables in reinforcement learning process, and uses MATLAB to compare and analyze the learning results with the test data to verify whether the optimization scheme meets the target requirements and whether the performance indicators such as the effect meet the requirements, Thus, the optimal solution is determined as the basis of the final decision. Finally, the experimental data show that the optimized learning algorithm can improve the convergence speed and stability compared with the optimized learning algorithm. At the same time, it accelerates the calculation speed, and has better performance and practicality.

China has learned from the experience of carbon emission reduction in various countries in the world, which is conducive to finding a reasonable and effective reference path for its own emission reduction. We first use the LMDI to decompose and compare the changes in carbon emission drivers in different countries, then use ridge regression to explore the key influencing factors, and analyze the similarities and differences of the influencing factors of carbon emissions in major countries. The conclusions show that: (1) From the perspective of LMDI decomposition, economic growth and population size are the key factors to increase carbon emissions, and there are differences in the impact of industrial structure, energy intensity, and energy carbon intensity, and the carbon emissions of various countries are affected by the “wild goose model”. (2) From the perspective of ridge regression analysis, economic growth is the main driving carbon emissions in all countries; energy intensity and energy carbon intensity are the reason that inhibit carbon emissions; and the impact of population size and industrial structure in different countries varies.

With the increase of attention to smart grid, the construction of Smart Substation has attracted more and more attention. The intelligence of substation has become a trend. It is also very important that Relay Protection (RP) can ensure the safe and stable operation of Smart Substation equipment. Based on this, this paper studies and analyzes the stability of RP in Intelligent Substation (IS) and discusses the principle and structural characteristics of IS, the design principle of RP, and the basic scheme of RP configuration in IS; according to the stability judgment basis of RP, the simulation experiment is carried out to verify the stability criterion after the removal of interpole short-circuit fault and the RP action time of interpole short-circuit fault and single-pole grounding fault. Through calculation, it can be concluded that under the large disturbance condition of interpole short circuit, the bus voltage can remain stable, and its voltage range meets the voltage variation range of the stability region after the removal of interpole short-circuit fault. And after the RP acts correctly, the system can restore stability. It is fully confirmed that the RP of IS has good stability, which has certain reference and guiding significance in practical engineering construction.

According to the theory of transient electromagnetic method (TEM) and its signal characteristics, a data collector for time-domain airborne electromagnetic weak signals is designed and implemented. The system uses floating-point amplification technology to dynamically amplify the weak signal and uses CPLD as the decoding control circuit and DSP as the main controller to process the sampling data. The system has a dynamic range of up to 144 dB and a sampling rate of 100 kHz, which meets the requirements of the channel for receiving electromagnetic signals for high-speed and high-precision sampling data. The research results of time-domain electromagnetic domain have been successfully applied to mineral exploration.

The traditional anti-islanding monitoring and regulation of photovoltaic microgrid are mainly a single-node regulation mode, with weak communication networking function, low degree of automation and relatively lagging information management. According to the information management requirements of anti-islanding monitoring of modern microgrid, based on the technical framework of Internet of Things, this paper designs and implements an anti-islanding monitoring system of microgrid based on Internet of Things. The anti-islanding monitoring system of photovoltaic microgrid based on CC-link industrial fieldbus has the functions of remote and on-site parameter modification, dynamic display, fault analysis and so on. The results show that the system can stably realize the centralized and remote control of monitoring of microgrid, improve the production and information management level of enterprises, reduce labor costs and save energy and consumption significantly.

With the popularity of smart terminals, people are gradually starting to sense mobile IoT systems, but it is not yet possible to completely eliminate factors such as noise interference and visual bias, which lead to misdirected sensors, misinformation, mislocalized targets, and inability to perform accurate identification. Therefore, the researchers propose a new algorithm, a multivariate hierarchical decision tree model based on edge analysis. In this method, the image contains a large number of feature points related to robot-related performance indicators as a feature that is highly correlated and can effectively describe the object. The correlation between objects is analyzed, thereby realizing the next prediction and decision-making of the intelligent terminal of mobile objects. In this paper, firstly, the design principle of network multi-level hierarchical perception model is studied, and then the multi-level decision tree model based on support vector machine is studied, and the algorithm is validated with experiments; secondly, the design of mobile IoT region segmentation algorithm is studied in this paper, and the experimental validation results show that the multi-level hierarchical decision tree model based on edge analysis has better performance in dealing with uncertain information, while the mobile IoT smart terminals can effectively handle uncertain information; finally the algorithm is designed to predict the miscommunication rate better.

Using UAV to accurately and quickly realize the three-dimensional modeling of power tower is an effective measure to promote the construction of smart grid. A tower target recognition algorithm based on yolov5 is presented to solve the problem of inaccurate tower 3D perception recognition by UAV. By improving the internal structure of the residual block to reduce the impact of steel intersection on the identification results and improve the accuracy of the algorithm, the exponential linear unit function is used as the activation function to accelerate the convergence speed of the network and improve the robustness of the algorithm, so as to realize the rapid and accurate identification of key points of power towers. By comparing the fast R-CNN and EfficientDet target detection methods through experiments, the improved algorithm has improved the recognition accuracy to a certain extent. The model maintains the lightweight characteristics of yolov5 and has a good prospect in application deployment.

This paper uses the SE-DEA model to measure the logistics efficiency of eight districts and counties in Xi'an from 2011 to 2018 and analyzes their time series evolution characteristics, combined with the Malmquist index model to decompose the efficiency and dynamic analysis of the logistics of districts and counties. Finally, the FCM algorithm is used to classify the inputs and outputs of Xi'an urban counties. The results show that the average logistics efficiency of Xi'an from 2011 to 2018 was 1.033, the overall efficiency level was higher, and the “W” type change trend was shown. The number of districts and counties with an efficiency value greater than 1 increased from 3 in 2011 to 6 in 2018, and the difference in logistics efficiency between districts and counties increased first and then gradually decreased. The FCM algorithm divides the eight districts and counties into high, medium and low input areas and high and low output areas, and the logistics efficiency of Xi'an has not developed extremely, avoiding the development trend of Matthew effect.

In today's society, with the logistics industry playing an important role in economic development, its development speed and efficiency are becoming higher and higher. Therefore, how to effectively reduce costs and improve service quality has become a competitive advantage of enterprises. For all stored procedures in the warehouse, picking process is the longest of all stored procedures. Therefore, based on the improved ant colony algorithm (ACA), this paper studies the logistics picking path optimization. Firstly, this paper studies the traditional ACA, then optimizes it on the basis of the algorithm, and finally tests the robustness of the algorithm. The test results show that the optimized ACA has strong robustness to the random generation of path and the random sampling of the volume of goods to be picked.

With the development of the automotive industry and the advancement of artificial intelligence technology, the human vision of driverless cars is gradually becoming a reality. However, the current level of self-driving technology is immature, and the self-driving car must be able to handle emergency situations when it leaves the laboratory and enters the bus. The main purpose of this paper is to study the design and implementation of the automatic braking system of automobiles based on the multi-objective capture algorithm. Aiming at the typical dangerous situation of high-speed collision avoidance, this paper proposes a design scheme of a collision avoidance system for autonomous vehicles and studies its important basic theories and key technical issues involved in motion control and decision-making. The experiment found that in the case of emergency braking, 95% of drivers can achieve an average braking efficiency of 0.49 g, and the maximum reduction can reach 0.87 g. The average deceleration of the driver is 0.32 g, and the maximum deceleration is 0.63 g. The results show that it is often difficult for the driver to fully utilize the braking force of the vehicle.

With the development of microelectronics technology, computer technology, and new application technology, the design of electronic system becomes more and more complex and complex. With the frequent use of electronic systems, many parts will have multiple failures, thus reducing or losing the default performance of the system, and even causing major accidents. This technique has been widely used in the field of error detection due to its strong production process, close to arbitrary operation, training ability, and self-adaptation ability. This paper proposes two new intelligent diagnosis methods by using the method of mechanical learning sparse autoencoder and wavelet transform, and the fault diagnosis of electronic engineering equipment system. At the same time, the stochastic resonance model is improved to make the extracted fault features more obvious, and the effectiveness of the newly proposed algorithm is verified through the fault diagnosis example of the electronic engineering equipment system. The experiment proved that in the 10,000 simulated fault detection, the machine learning algorithm with resonance model of intelligent fault diagnosis system diagnosis accuracy and diagnosis time is much higher than other distribution models.

Because of the availability of IoT and the affordability of image sensors, several picture databases have been developed for use in a variety of contexts. The need to provide effective picture retrieval search techniques that satisfied the requirement of users is increased by these image databases. The semantic break among low-level characteristics and visuals of human judgments has received a lot of attention and effort in the quest to enhance content-based picture retrieval methods. This study evaluates, analyses, and contrasts the most recent state-of-the-art CBVIR field approaches during the previous six years in the light of the expanding body of research in this area. A performance evaluation, contemporary low-level feature abstraction techniques, machine learning algorithms, similarity measurements, plus an introduction to the CBVIR framework are also included in this study to serve as further inspiration.

After half a century of development, artificial intelligence technology has been preliminarily mature, and it has ushered in a stage of rapid development in the twenty-first century. Artificial intelligence has injected new impetus into health care, the Internet, manufacturing, and logistics, which have given these industries an opportunity for rapid development. Especially in the logistics industry, automatic vehicles, AGV, and intelligent picking have applied a large number of artificial intelligence technologies, bringing more changes to all aspects of logistics, improving efficiency, and reducing costs. In addition, AI will play a role in more aspects of logistics in the future, especially in data mining, machine vision, machine deep learning, and natural speech processing to open up more efficient ways to make “data-driven logistics” a reality. This paper shows the application and reform of artificial intelligence to the logistics industry from two dimensions, namely the application of artificial intelligence existing technology in the field of logistics and the promotion of the development of artificial intelligence to the development of logistics and the resulting development trend of intelligent logistics.

The sustainable development of urban construction, optimizing the construction of drainage pipe system is the premise to ensure the sustainable development of water ecological environment. The purpose of this paper is to study the optimization algorithm of building drainage system based on isotope tracking method. Taking the groundwater in the B area of M city as the research object, using hydrochemistry and isotope tracer technology, the migration and transformation laws of main anions and cations in the multi-media of the water system were studied, and the understanding of the water environment problems in the M city area was deepened. The optimization of the building drainage system has laid a certain scientific basis. The results of the research on the Sr isotope in the groundwater in M city and surrounding areas show that: M city and surrounding groundwater have different recharge sources, and their isotopic characteristics have great changes. Drainage pipeline system optimization design, the sewage interception main pipes in City M are divided into two major systems: south and north. The total length of the sewage interception main pipes is 10,365 m.

Due to the production of plastic products with complex shapes, the plastic injection moulding manufacturing method has recently received a lot of attention. In order to improve manufacturing performance, the cycle time for the injection moulding process has been reduced, the defect known as dimensional warpage that results from temperature differences inside the mould has been reduced, and the mechanical tensile strength of the material has been increased so that it cannot warp easily. Warpage is a dimensional flaw of the product; hence, a longer cycle time is needed. We risk a decline in production if we do this. Additionally, a superior product should have a higher tensile strength. A suitable experimental design is prepared using the Taguchi orthogonal array to determine the trade-off analysis between quality and productivity. The Taguchi orthogonal array is used to select an appropriate experimental design, and utilizing the experimental data, the entropy measurement method is then used to look into the choice of response behaviour. The utility idea is then used to determine how the processing parameters connect to the various process.

BaTiO3 (BT) and Ba(Zr0.15Ti0.85)O3 (BZT15) thin films grown on Pt/Ti/SiO2/Si(100) substrates were made up of Sol–gel method. The BZT thin films with x = 0.15 exhibited enhanced dielectric and ferroelectric properties. The large remanent polarization, high dielectric constant, and low dielectric loss of the material are 10.9 μC/cm2, 1004, and 0.03, respectively, for the BZT15 films. The BZT15 film exhibited 49% high tunability at 275 kV/cm electric field and 1 MHz measurement frequency. These results indicate that we have successfully deposited high quality and potential materials for dielectric applications.

Historically, agriculture has been handled manually. It is important that agriculture follows the global trend toward new technology and applications. Internet of Things (IoT) is a significant aspect of smart agriculture. Data about agricultural areas can be gathered using IoT sensors. We have suggested a smart agriculture and IoT system that uses automation. Using wireless sensor networks, this IoT-based farm monitoring system produces reports by several sensors located at various nodes and sends it via wireless transmission. A DC motor, temperature, moisture, and water level sensors, as well as the Blynk app, are all parts of the NodeMCU-powered IoT system for smart agriculture. The IoT-based farm monitoring system begins up with a check of the moisture level, humidity, and water level. It sends an SMS alerting the phone of the levels. Sensors detect a dip in the water level and promptly activate water pump. The standard technique of farming is replaced by smart agriculture with IoT, which is more user-friendly, affordable for farmers, and lowers crop and water waste.

Cu(In,Ga)Se2 (CIGSe) thin film solar cell (TFSC) is an emerging photovoltaic technology with lab-scale device efficiency surpassing 23% and monolithically integrated module efficiency ranging from 17–19%; it is anticipated to meet escalating global electricity demand. The division of a large photovoltaic cell into serially interconnected smaller devices is known as monolithic integration. To reduce shunting losses, a monolithic integration configuration of CIGSe TFSC comprising stacks of Al:ZnO/i:ZnO/CdS/CIGSe/Mo/Glass is adapted, often by combination of laser-mechanical scribing operations during the device fabrication process. The traditional mechanical scribing procedure, which engages sharp ceramic tips, is sluggish (< 0.2 m/s) and produces broader scribing widths (> 100 µm). The module's scribing area is a dead zone and a loss of active photovoltaic region that must be minimized. Given this, we report rapid (1 m/s) nanosecond pulsed fiber laser-driven micro-patterning of CdS/CIGSe/Mo/Glass (P2 scribing) and Al:ZnO/i:ZnO/CdS/CIGSe/Mo/Glass (P3 scribing) stacks, which replaces typical sub-optimal mechanical scribing. The electrical, morphological and compositional analysis of scribed structures confirmed a significant reduction in scribe widths (< 50 µm) using a laser with 1064 nm wavelength and pulse width 25 ns, a commonly utilized configuration for scribing of Mo thin film electrodes. The process eventually reduces the dead zone and increases the overall active area in the module.

Quality enhancement of micro-hole in laser drilling of thermoset-based composites is a prime focus of the researchers in recent times. When lasers are used to drill holes in polymer composites, the heat-affected zone and taper are the most important quality parameters. Dispersing thermally conductive fillers across polymer composites to increase their heat transmission properties during laser drilling is one of the potential ways that can be used to reduce the heat-affected zone. In this study, an effort has been made to investigate the taper and the heat-affected zone during pulsed Nd:YAG laser micro-drilling on a 3 mm thick epoxy-based nanocomposite specimen with optimum 6 wt.% of carbon black and further optimize them using gray relational analysis and response surface methodology. Input variables such as cutting speed, lamp current, pulse frequency, and air pressure have been experimentally changed for 27 combinations that are developed with the help of Box–Behnken design. A confirmatory test has been carried out with the optimal parameter setting thus obtained to validate the optimum results.

The main aim of this article is to conduct the static structural analysis of below knee prosthetic leg using finite element analysis (FEA). The structure of below knee prosthetic joint consists of six main components: Socket, Pylon/Shank, Frontal, Hind Calcaneus, Feet joint, Universal joint. Initially, the below knee prosthetic leg was modeled using Creo software. Furthermore, an ANSYS Workbench 2022 R2 was used to perform a finite element analysis of below knee joint model. Static structural analysis is carried out with different loads of magnitudes 50N, 60N, 70N, 80N, 90N which was applied on the inner surface of the socket. The result shows that the finite element model imparting the induced stress distribution in the prosthesis to ensure its safe performance in the fatigue life has been developed.

Sustainability is the approach to obtain overall efficiency in manufacturing by achieving economic, ecological and societal benefits. This experimental research presents a concise comparative investigation on machinability characteristics of high-strength grade hardened steel (AISI 4340) through dry and MQL environments for sustainability. Surface characteristics and machinability studies such as white layer, surface topology, chip morphology, surface roughness and tool wear/tool life were investigated under both the environments. Tool life under MQL is 32.3% higher compared to dry condition at cutting speed of 50 m/min, feed rate of 0.08 mm/rev and depth of cut of 0.1 mm, respectively. In another setting of cutting speed of 100 m/min, feed rate of 0.04 mm/rev and depth of cut of 0.1 mm, tool life under MQL condition is 39.6% more than dry condition. Phenomenon like abrasion, diffusion, notching, chipping and built-up edge is reported as principal wear mechanism. Detailed investigation is still needed for sustainable machining using nano-assisted MQL environments.

The reinforcing of natural fibre and fillers in polymer resin is the most recent development in the production of sustainable composites. Banana fibre and marble dust powder (MDP), two naturally occurring ingredients, are utilized to improve the characteristics of polymers. The current study looked into how banana fibre and MDP affected epoxy resin. MDP-filled (0, 2, 4, 6, and 8 wt%) banana fibre (25 wt%) with epoxy resin (75, 73, 71, 69, and 67 wt%) is produced using the hand lay-up technique, and its mechanical behaviour is examined. The tensile, flexural, and impact test specimens were made and put through testing in accordance with ASTM specifications. The Vickers hardness of epoxy increased each condition of MDP's reinforcement and up to 6 wt% of MDP's tensile, flexural, and impact characteristics. Tensile strength for unfilled polymer composites is roughly 56.21 MPa, however, when MDP is added, the strength rises (76.51 MPa). While, when initially compared with specimens, the tensile modulus of the MDP-filled composite increases in a linear fashion up to 8 wt% (2.61 GPa) (0, 2, 4, and 6 wt%). Flexural strength (96.28 MPa) improves up to 6 wt% when MDP is added to the composite, whereas flexural modulus (4.31 GPa) improves up to 8 wt%. The impact energy and Vickers hardness number (VHN) values are found to be 84 VHN and 3.6 J, respectively, for 6 and 8 wt.% MDP-filled composites.

Due to the challenging issues like high heat generation concerned with hardened steel machining, therefore cutting fluid has been used for removing the more higher cutting temperature. Furthermore, use of nanolubrication system makes the cutting environment more sustainable. The present work represents the impacts of cutting parameters such as cutting speed, feed rate, depth of cut and LRT 30 mineral oil-based ZrO2 nanofluid concentrations in hard turning of AISI D2 steel. The ZrO2 nanofluid was first time implemented for cooling purpose in hard turning application. The performance was examined by taking average surface roughness, tool flank wear, cutting power and cutting temperature results. Experimental results found that the 0.20% nanofluid concentration was the better choice among all adopted weight concentrations (0.05%, 0.2% and 0.5%) of nanofluid. Abrasion, cutting edge chipping and adhesion were found to be the principal wear mode. Also, acceptable range of surface roughness (0.498–0.665 micron) was seen in the entire investigations.

In this paper, development and D.C. conductivity behavior of nano zinc particle-reinforced polyester gradient composite are discussed. Nano zinc particle-reinforced polyester composites having 5 wt.% of nano zinc particle and polyester resin were developed. D.C. conductivity calculation was performed on the gradient composites by using an Electrometer apparatus from 25 °C–170 °C. It was concluded that D.C. conduction decreases on enhancement of distance in the route of centrifugation force, which confirmed the configuration of gradient structure of the composites. D.C. conductivity increased on improving in nano zinc particle concentration. Calculation of activation energy values was calculated by using the Arrhenius equation for specimens 1, 2, 3, and 4 is 0.41, 0.48, 0.72, and 0.84 eV, respectively, which exhibit ionic conduction.

In this research article, a 2 mm thick Ti–6Al–4V titanium alloy sheet was exposed to an experimental investigation of the overlapped multipass laser transformation hardening (LTH) for the specific instance of a uniformly intense, CW spherical beam travelling at a constant speed utilizing a 2 kW Nd:YAG laser. Two sets of laser process parameters were selected and optimized through experiments: (1) High laser process parameter (HLPP), Lp = 800 W, Ss = 3000 mm/min, Fp = −10 mm, with heat input 180 J/cm, and (2) Low laser process parameter (LLPP), Lp = 600 W, Ss = 2000 mm/min, Fp = −10 mm, with heat input, Hi 160 J/cm and 180 J/cm, respectively, both with the same Fp = −10 mm. The Vickers microhardness of a Ti–6Al–4V titanium alloy as received is 328 HV. The maximum values of Vickers microhardness were found in the all the regions of hardened bead than in the bulk material, respectively. The higher values of 450 HV and 445 HV were investigated on the top surface for both higher and lower laser processing parameters, respectively. A significant improvement in corrosion and wear resistance of the laser hardened surface of Ti–6Al–4V in contrast to parent material can be attributed to the excellence properties of the dissolution of minute quantities of carbon, nitrogen and oxygen during the formation of hard martensitic α′ (or transformed β).

Global warming has emerged as a very serious issue, and it demands immediate reduction of greenhouse gases. Energy generation sources are prime causes of greenhouse gases. Clean energy generation is of utmost requirement to cope up with greenhouse gases emission. In this direction, the Hydroelectric Cell (HEC), a device that produces clean and green energy from water splitting without use of electrolyte, acid/alkali, heat/light is a unique invention. The strategically synthesized oxygen-deficient nanoporous metal oxide used in HEC splits H2O molecules to form OH− and H+ ions, which are collected by Zn anode and Ag inert cathode affixed onto metal oxide pellet. Hydroelectric cell generate current and voltage due to redox reaction, which sustains by continuous dissociation of physiosorbed water due to the electric field generated in the nanopores. In this work, we have reported the effect of Mg doping in ZrO2 for boosting the performance of ZrO2 based hydroelectric cell. The molar ratio of dopant and ZrO2 has been taken (0.1:0.9) and synthesized by a solid-state reaction route. The Zirconia and Zr(1−x) Mg(x)O2(x = 0, 0.1)-based HEC of one inch 2 area generated maximum short circuit current of 10.4 mA, 14.7 mA and open cell-voltage 0.920 V, 0.90 V, respectively. Phase formation and strain developed in the lattice of Zr1−xMgxO2(x = 0, 0.1) has been confirmed by X-ray diffraction pattern. The porous microstructure of the samples has been confirmed by scanning electron microscope. The Nyquist plot of the cells confirmed the ionic diffusion by water dissociation. HEC polarization behavior with increase in current has been analyzed by V–I plot. It has been found that magnesium substitution in ZrO2 induces microstrains, dislocations in ZrO2 lattice thus defects are created to dissociate more water molecules. Increased current and voltage in MgxZr1−xO2-based hydroelectric cells will play a huge role in diminishing greenhouse gas effect.

The aim of this short review is to determine the tribological behaviour of epoxy composites containing different filler materials. The study gives the information about the effect of different fibres or nanoparticles on the wear and frictional properties of epoxy composites. It is determined that the reinforcement of different fibres improved the wear as well as mechanical behaviour but sometimes it may show some negative effect also. The nanoparticles also improve the tribological properties of epoxy nanocomposites. The amount of nanoparticles from a certain limit, diminish the wear properties of different nanocomposites also. The composites having hybrid reinforcement improves wear and mechanical behaviour more compare to individual ones. The bonding of matrix and filler gives the main impact on the wear properties of polymer composites. So that it is a great challenge for developing new epoxy composites for better wear characteristics for different tribological application.