Transportation Energy and Dynamics

Transportation plays a substantial role in the modern world; it provides tremendous benefits to society and imposes high economic, social, and environmental costs. Sustainable transport planning requires integrating environmental, social, and economic factors to develop optimal solutions to our many pressing issues, especially carbon emissions and climate change. This book explores sustainable development and transportation concepts, describes practical techniques for a comprehensive evaluation, provides tools for multi-modal transport planning, and presents innovative mobility management solutions to transportation problems. Moreover, it focuses on accessibility rather than mobility, emphasizes the need to expand the range of options and impacts considered in the analysis, and provides practical tools to allow planners, policymakers, and the general public to determine the best solution to the transportation problems facing a community.

Decarbonization of the transportation sector is a crucial concern in order to mitigate climate change and reduce the dependency on fossil fuels. The contribution of the transportation sector to global greenhouse gas emissions accounts for about one-fourth. In spite of the fact that the rail sector is considered the most energy-efficient and environmentally friendly transportation mode, diesel still dominates as fuel. Toward to the net-zero greenhouse gas emissions target by 2050, the rail industry needs to deploy sustainable technologies for locomotives. The electrification of locomotives is costly, and battery-powered trains, as well as hydrogen trains, are not yet feasible for long-distance journeys. However, the utilization of biodiesel blends is the most promising option in the short-to-medium term allowing the use of the current diesel fleet. Biomass conversion technologies for biodiesel production from non-edible sources could promote the sustainability of biodiesel adoption in railway transport. The current chapter highlights recent trends of biodiesel-blended powered trains over the world focused on feedstock availability, blending limits, infrastructure, and maintenance cost indicating their potential for a prompt shift to a sustainable railway sector.

During the movement of heavy-haulers trains, longitudinal oscillations occur, accompanied by significant longitudinal forces. In some cases, for example, in case of violation of the traction control technology of locomotives, the values of these forces reach values that can cause damage and destruction of autocoupler devices of wagons and train rupture, which is a serious violation of traffic safety. In some cases, the problem is complicated by the factor of fatigue wear, which has a significant impact on the resistance of components to mechanical stress. Also, in addition to dynamic forces, slowly changing quasi-static forces are also dangerous, which can cause cars to be squeezed out of the track and derail them. In the work, longitudinal oscillations arising in a train are investigated using mathematical modeling methods. To solve the problems considered, a multi-mass model of the train was used, taking into account the nonlinear and nonlinearizable characteristics of the absorbing devices of the automatic couplers, the nonlinear nature of the change in the resistance forces acting on the train, and the location of the train on several elements of the track profile. An assessment of the stability reserves against squeezing was performed, when calculating which the vertical and lateral forces of interaction between the wagon wheel and the rail are taken into account. Based on the research carried out, the concept of constructing a system for automatic control of the speed of a freight train is proposed; for this purpose, a system of criteria is proposed to assess the quality of control of the speed of a freight train from the point of view of traffic safety, recommendations are given on the structure of the speed control loop, and the method of selecting the parameters of the speed control law using multi-criteria optimization methods is considered.

A gangway system is a flexible connector fitted to the end of a railway coach, enabling passengers to move from one coach to another without danger of falling from the train. Recently, a gangway system with an added interior plate is gradually being applied to urban railroad vehicles, and various types have been developed and applied to the corresponding vehicles according to the types of urban railroad vehicles in each country. In the case of gangways with interior plates, it is gradually expanding because it is advantageous for insulation, sound absorption performance, and passenger safety. Interior plates are widely used as interior materials for railway vehicles including gangways and generally have requirements such as mechanical properties and fire safety performance. In particular, the interior plate for gangway must be designed to flexibly withstand movements such as yaw, pitch, lateral, vertical, and roll, so the mechanical strength requirements are variously defined. In this study, related international standards were analyzed to derive the required strength requirements for the interior plate for rolling-type gangway, which is being developed for the application of urban railroad vehicles in Korea, and mechanical strength analysis was performed through the finite element analysis (FEA) accordingly. Experiments were also performed to obtain the mechanical properties of the fiber reinforced plastics (FRP) interior plates manufactured through the application of aramid-based materials for fire safety. As a result of performing the FEA in boundary conditions derived from the EN 16286-1 standard, it was confirmed that the FRP interior plate under development can be applied to the rolling-type gangway of urban railroad vehicles.

This study examined the operation and patronage dynamics of the Lagos Shuttle Train Services, the only intra-urban rail transit in Nigeria, a country of over 200 million people. Using multistage sampling, six sets of respondents were surveyed over two survey periods—before the onset and in the wake of COVID-19. Two key-informant interviews and four sets of questionnaires were administered. Participant observation was used to complement the data obtained. The interviewees were the Head of Operations Department and a senior staff member of the Nigerian Railway Corporation (NRC). Three sets of questionnaires were administered on all the 20 engineers, 79 conductors, and 14 ticket vendors in the employ of NRC, while the fourth set of questionnaires was administered on 216 passengers selected from both the Mass Transit Trains (MTT) and the Diesel Multiple Unit (DMU) trains operated along the Lagos Shuttle Train Services’ corridor. Findings revealed that the operation dynamics of the Lagos Shuttle Train Services comprise both desirable and undesirable factors that could enhance and undercut, respectively, the effectiveness of its service. On the other hand, its patronage dynamics were found to reflect the socio-economic and locational attributes as well as the aspirations and desires of passengers. The study concluded that if the operation and patronage dynamics of the Lagos Shuttle Train Services were improved on, passengers’ welfare and NRC’s effectiveness would be enhanced with many beneficial spin-offs. Towards this end, workable policy recommendations were proffered.

Rapidly rising economies and urbanization have immensely increased the energy concerns in transportation sector. The road transportation system is unable to provide long-term solutions to these problems due to raging fuel prices, rising environmental concerns, and worsening traffic congestion as a result of the increasing private vehicle ownership. Thus, to improve the energy security in this sector, emphasis must be given to the development of mass rail transit systems. The actual challenge lies in developing such rail transit systems that can reduce the dependency on road transport with lesser carbon footprints. However, conventional rail transit systems based on rotary motors possess many limitations in terms of speed, efficiency, automation, and sustainability. The development of a linear motor-based high-speed rail transportation system can provide a viable solution to these problems. The use of linear motors in these systems offers many advantages as compared to rotary motor-based conventional rail transportation systems. Being fully electrified, such a system also decreases the dependency on oil products making it a greener and more contemporary alternative to conventional rail transportation systems. This chapter gives a basic understanding of high-speed rail transportation systems. It describes the various constituents of high-speed rail transportation systems in detail, with a focus on the advancement attained by different countries in this technology, to make the system efficient and sustainable. This chapter also highlights the relevance of linear motor-based high-speed rail transit systems in today’s scenario. A comparison of these technologies to analyze their applicability in context with India is also discussed.

The European Community has developed a real turning point in the common rail transport policy by defining new ambitions to rebalance sustainably the sharing between modes of transport, develop intermodality, fight congestion, and finally place safety at the heart of European action. To consolidate the usual methods of railway safety analysis, this chapter proposes two complementary railway safety assessment methods based on AI techniques and in particular on machine learning (ML). The study seeks to exploit, by machine learning, the lessons resulting from “Experience Feedback” (REX) in order to help and assist safety experts, technical investigators, and certification bodies to assess the level of safety of a new rail transport system. Unfortunately, safety in rail transport improves essentially on the basis of in-depth knowledge of accidents and incidents resulting from “experience feedback”. As stipulated by European regulations, all players in rail transport and in particular infrastructure managers and railway undertakings are obliged to set up a system of “experience feedback” in order to understand the causes and the seriousness of the consequences engendered by rail accidents and incidents. So, the knowledge of accidents and incidents results essentially from the contribution of lessons learned and experiences acquired. To explain and understand the causes and circumstances of accident risks and therefore at least avoid the reproduction of similar accidents, we have oriented our study toward the use of approaches derived from AI and machine learning. From experience feedback, the main objective is to exploit a set of insecurity events in order to anticipate and prevent the reproduction of the risks of accidents or similar incidents and possibly to discover and identify new scenarios of potential accidents liable to jeopardize safety. This chapter proposes a new hybrid method based on three machine learning algorithms. The first stage of acquiring knowledge led to the development of two accident scenario databases. The first base relates to the analysis of “functional safety”, and the second base relates to the analysis of the “security of critical software”. The second step, which is based on a concept classification algorithm, makes it possible to group the accident scenarios into coherent classes such as the class relating to train collision or derailment problems. For each class of accident or incident scenarios, the third step implements a learning technique based on production rules in order to identify some relevant safety rules. In the fourth step, the previously generated production rules are transferred to an expert system in order to deduce the potential accident risks. Finally, a case-based reasoning (CBR) system makes it possible to search, on the basis of “experience feedback”, for the cases closest to this new risk of accident and proposes the most appropriate prevention or protection measures.

This graduation project/thesis is aimed at predicting the land values after the introduction of Mumbai–Ahmedabad High-Speed Rail (MAHSR) in the cities having the High-Speed Rail (HSR) stations. Evidences from various countries are collected and studied in order to understand the effect of population on land value and determining the relationship between them, through predictive regression analysis. After the quantitative analysis, other factors like accessibility and other physical attributes like location, density, and working population have been studied in order to conclude the population spread over the various cities under study with the rising industrial growth and employment opportunities. Research recommendations that include topics of technological implementation, sustainable development, and land use planning are included in order to gain the maximum benefits out of the implementation of High-Speed Rail in the route.

This chapter discusses a novel mathematical model for estimating the regenerative braking effectiveness of Indian locomotives equipped with the regenerative braking system. It is proven on Indian rails for a WAP-7 locomotive. The necessity for an additional energy recovery mechanism in the locomotive mechanical model is discussed in this study. The present energy reliance of AC-powered Indian locomotives has been examined. To research the electrical energy flow and electric machinery in an AC locomotive, the essential components of a modern electric rail vehicle, a WAP-7 locomotive, were chosen. The phenomena of energy recovery while braking has been explained using regenerative energy generation and electrical braking of an AC locomotive. To better comprehend the mathematical modelling of an AC locomotive, a traditional mechanical model based on the WAP-7 locomotive was used. The new model has been simulated on Shatabdi Express, train no. 12010 running from Ahmedabad Junction to Mumbai Central. The effect of gradient on the recovered energy has been calculated and compared with five levels of gradients, viz. 1 in 400,300,200,150 and 100. Simulation of the mathematical model has been carried out using Python in Microsoft Visual Studio. The simulation results have been discussed with the flywheel models and the energy efficiency achieved.

A modern railway train is a complex mechanical system, the movement of which is determined by mechanical, dynamic, electrical, and thermodynamic processes. It is necessary to consider analytical models of varying degrees of complexity of their oscillations and interaction with the railway track to solve numerous problems regarding the dynamics of rail vehicles. Often there is a need to take into account the longitudinal forces transmitted to the railcar from neighboring railcars, as well as their components in the vertical and horizontal transverse directions. These forces can be obtained from the solution of the train dynamics problem and then used to study the dynamics of a single railcar. However, in a number of papers, analytical models appear in which the problems of train dynamics and spatial oscillations of a railcar are combined together. When combining the problems solved in the dynamics of the train and the spatial oscillations of a single railcar, the studied rail vehicle is considered according to the full design scheme and neighboring ones according to the simplified one. The spatial oscillations of a train of freight railcars moving along a section of the track with vertical and horizontal irregularities are described in the presented analytical model.

Environmental pollution is one of the major disadvantages of fossil fuel and their derivatives, but alternative energy resources have performed better in this area. A well-known example within these alternative energy sources that can increase total available energy for human’s consumption is biomass, and it has been proven to be the most important renewable energy source. Its benefits include reduced emission, ease of growth (agricultural materials), more available when compared to non-renewable sources of energy and can be directly used by local methods. Biomass wastes heating is a major energy generation process. Processes that use heat on biomass wastes to generate energy are termed thermochemical conversion processes. The use of wood that store chemical energy in cooking is as far back as the creation of the world. Thermochemical conversion of biomass releases products which are extremely best when compared with other renewable energy source finding usefulness in automobile, power, chemical, production, and biomaterials industries. Pyrolysis is a heating process whereby carbon-based matter (organic material) such as lignocellulosic agricultural waste is heated to 450 °C and above in a non-O₂ atmosphere, e.g., N₂ atmosphere. Oxygen or air supports biomass combustion to generate heat, steam, and electricity. Gasification occurs at > 650 °C; it is a method of converting biomass waste into energy with the sole purpose of generating syngas useful for combustion, heating, and electricity generation. Liquefaction is a method of converting coal/biomass to petroleum through series of chemical reactions. Bio-oil, syngas, and char are useful products with stored chemical energy obtained from via thermochemical conversion. Biochemical conversion of biomass refers to the gradual and continuous release of biofuel from biomass waste through the activity of microorganisms and enzymes. Thermal and biochemical conversions are suitable processes to tap unused energy in largely available lignocellulosic biomass wastes to reduce reliance on the use of non-renewable fossil fuels as source of energy.

Manufacturing process management signifies a massive stage in the pursuit to connect product design with production digitally, so as to enhance information quality and decrease the time-to-market. In this era of virtualization where product and process data are transferred across sectors electronically manufacturing process management (MPM) is making huge strides in sending out the right product with the manufacturer’s major focus on eliminating all kinds of waste in the plant without compromising on the quality. The main advantage of MPM is that it betters the production efficiencies resulting from more firmly designed and managed processes. MPM applications deliver analytical and data administration abilities needed by organizations to transfer to mixed model production systems to diminish work-in-process (WIP) or in-process-inventory (IPI), complete products inventory, and progress whole product quality and manufacturing sensitivity. The present amount of earth resources human beings are using is not justifiable, and it will disturb the environment in numerous ways. Manufacturing is a huge resource-consuming activity, it is significant to contemplate sustainability at all stages of product life cycle which are being made. Life cycle investigation is a recognized technique to find the ecological effect of the manufacturing. So as to include ecological necessities into manufacturing practices a totally different means of thought process needs to be employed by the investigators. Sustainable or green manufacturing is today attainable goal and various zones within manufacturing are profited through this. The current article is aimed at discussing how the advancements of traditional manufacturing techniques have improved and also the takeover of modern manufacturing methods and their processes management to reduce waste, scrap, etc., and contributing toward environmental sustainability.

Heavy metals usually exist in the crust of the earth. It has certain compositions in the localities which result in the structural disparity with the surrounding concentrations. It has traced on the amount of the respect to the living organisms that are related to the metabolic activities. The highly soluble ways to meet the extremely toxic yet perilous contaminants of the eater have included the activities where the metals are released into the environment. They are leached into the underground waters along with the depositing the aquifers. The surface water might run out of the potential contaminants for the environmental metals. Heavy metals have potential contaminants for environment has to make the trophic transfer in food chains take place. The heavy metals dependency has added on the relative oxidation state where physiological bio-toxic effects can enter to the world. The toxic compounds such as arsenic, cadmium, lead have altered the productive functioning of the bio-reactions. This has led to the production of the mutagenic, carcinogenic, and genotoxic effects to the occurrence and allocation in the heavy metals. The impact of the environment has added on the toxicological measures in the environment. The study further focused on the occurrence and allocation of heavy metals along with the possible eco-friendly remedies in the environment.

Transport takes place on four main elements: Air, rail, road, and sea. The question of which of these four elements is more environmentally friendly is a subject that has been studied frequently. In order to give a full answer to such a question, all modes of transport (including vehicles of transport) must be comprehensively examined from a life cycle perspective. In this study, the CO₂eq, which is identified as the greenhouse gas impact of different greenhouse gases is measured from the CO₂ unit, emissions of the four modes of transport in the case of carrying 1 tkm of unit load, which means the transport of 1 t of cargo at a distance of 1 km, were calculated. The first reason for choosing only CO₂eq emissions is that the method used calculates only CO₂eq emissions, while the second reason is that global warming is the most important environmental impact category for different transport modes. Calculations were made according to the Intergovernmental Panel for Climate Change (IPCC) method, which considers only CO₂eq emissions and thus can be accepted more accurate than other methods, and life cycle approach and the effects were measured at 20-, 100-, and 500-year periods, which are called individualistic, hierarchist, and egalitarian, respectively. Accordingly, maritime transport is the most environmentally friendly mode of transport in all three periods, and air transport has the largest share in greenhouse gas production. The main aim of the study is to draw attention to the life cycle perspective in the calculation of greenhouse gas emissions and to compare the short-, medium- and long-term effects of transportation modes both with themselves and with each other.

Single-span mobile aerial ropeways, formed by two autonomous self-propelled units connected by a single rope system on the basis of wheeled chassis of high load capacity and cross-country ability, are a promising type of transport equipment for the sustainable development of hard-to-reach territories that do not have the necessary transport and logistics infrastructure. They can also be effectively used for rapid deployment during transport operations in the foci of natural or man-made disasters. The chapter presents the main promising types of structural design of autonomous units (with a central, end and remote locations of the end tower; with lifting of the end tower by means of a hydraulic cylinder, folding rod and two-stage installation) and options for placing multi-axle wheeled chassis on the bearing frame of the main technological equipment of the ropeway for various installation options and fixing in the working position of the end tower. The principles of operation of these units at the stage of deployment from the transport position to the working position and the stage of regular operation are described. A comparative analysis of the functional advantages of the considered types of autonomous units is carried out. The chapter will be of interest to researchers and production specialists in the field of design and operation of transport rope systems.

The primary purpose of this research is to investigate the analysis of a turbocharger turbine wheel with the goal of optimising its design and its use of materials. The static, computational fluid dynamics (CFD), and thermal analyses of the turbine blades that make up the turbine phase of a turbocharger are the focus of this work. The blades are responsible for extracting strength from the high-temperature and high-strain gas that was created with the assistance of the combustor. Most of the time, the turbocharger is the element that limits the turbine's potential. In order for turbine blades to thrive in this harsh environment, it is common practise to make use of uncommon materials such as special alloys and a wide variety of innovative cooling technologies. Some of these ways include inner air channels, boundary layer cooling, and thermal barrier coatings. In this project, a turbine blade is developed and modelled using the 3D modelling programme CREO, and then analysed using the software ANSYS 14.5. To improve the effectiveness of the cooling, the base of the blade has been redesigned to accommodate the new configuration. The selection of materials is of the utmost significance since the design of turbomachinery is notoriously complicated, and the efficiency of the machine is inextricably linked to the performance of its constituent parts. In this research, two distinct types of fluid flow conditions, namely laminar and turbulent flow, are taken into consideration for both the original models and the modified versions of those models. The optimisation process involves experimenting with several types of materials, such as chromium steel, titanium alloy, and nickel alloy, on the turbine blades for both designs. This is done by doing coupled field analysis (static and thermal).

The process of maintenance is always considered to be a huge driver of costs in all industries. Depending on the industry, maintenance activities can account for 15–70% of the total production costs. Despite that, most of the industries still rely upon maintenance policies that are outdated and severely inefficient from a time and money point of view. In this context, the railway industry is no exception. Maintenance of high-value assets of Indian Railways is still done primarily through conventional maintenance practices. This causes the production time to go down and the overall quality of the components to deteriorate. On the other hand, there is ample research work being done to explore the details of several other maintenance policies. One of the most efficient and highly preferred maintenance policies is predictive maintenance. This study reviews existing literature on predictive maintenance and its implementation in the railway industry and identifies gaps and prospects for further research. The objective of this study is to begin with understanding the current maintenance policies used by Indian Railways, and then go about outlining the potential advantages of implementing predictive maintenance. To signify the importance of predictive maintenance, an analysis is performed over real-world data of rolling stock by training a machine learning model over the data and predicting the Remaining Useful Life of the components. The model is trained using a type of Recurrent Neural Network, known as Long Short-Term Memory networks. This training is carried out by a regression algorithm. Finally, the predictions from the model are plotted and compared with the actual data, to indicate the efficacy of the model. After interpreting the findings of the plot, it is concluded that such predictive maintenance systems could be installed in the rolling stock operated by the Indian Railways, as it would impact the overall availability and efficiency of the assets and boost the operations of the organization.

When cities across the world expand and people’s mobility rises, so does the number of cars on the road. As a consequence, officials are facing an increasing number of problems in terms of road traffic control. As a result, there are more road chaos, more deaths, and waste. Despite the advancement of advanced traffic control systems and other vehicle-related technology, accidents remain a leading cause of death. As a result, a standard method for injury prevention must be created. For example, in most metropolitan environments, traffic congestion may be alleviated by route planning in real time. However, developing an efficient route planning algorithm to achieve globally optimal vehicle control remains a challenge, particularly when drivers’ tastes are taken into account. Also, intelligent transportation systems (ITS) are an effective implementation of Cyber-Physical Systems (CPS) that enhance driving safety by advising drivers of hazards with alerts in advance. The efficacy of warnings must be assessed to facilitate ITS communication. This analysis aimed to create a scale to assess warning usefulness, or how effective a warning is at avoiding accidents in general. The Verbal Alert Utility Scale (VWUS) was validated in a virtual driving environment using a driving simulator. The VWUS had decent split-half reliability with a Spearman-Brown coefficient of 0.873, according to the reliability report. The significant prediction of safety benefits suggested by variables such as decreased kinetic energy and collision rate confirmed the predictive validity of VWUS in calculating the efficacy of verbal alerts. This scale is a better way to test the general effectiveness of verbal alerts in transmitting related dangers in intelligent transportation networks than doing experimental experiments. This scale can be used to enhance the nature of ITS alarms and thereby increasing transportation safety. The scale’s uses in nonverbal alarm scenarios, as well as the new scale’s shortcomings, are also discussed.

Digital transformation in a supply chain can have far-reaching payoffs ensuring a smoother interface among all the stakeholders for seamless delivery. A Digital Supply Chain is an efficient way to leverage new methods to deal with changing customer expectations and importance of visibility across the supply chain. Recent literature discusses the importance of Digital Supply Chain and its applications. This paper aims at developing a framework for future research and practice. Interpretive structural modelling is used in this paper to create a hierarchical structural model that demonstrates the mutual dependency of the challenges in implementing digital transformation across supply chains. These challenges are graphically represented based on their driving force and dependency using cross-impact matrix multiplication applied to classification analysis.

Logistics is all about making decisions based on the impact of real or potential risks and opportunities, faster than one’s competitors. Logistics and supply chain networks are being modified to be agile, innovative, cheaper, and sustainable. Organizations must tackle volatile demand, uncertain supply, and constrained capacity to survive; hence, applying Industry 4.0 processes could improve production design and business models. The need for speed is the sole reason which has led to the digitization of freight logistics processes. The chapter elucidates the evolution of the concept, the characterization of the different components, and enabling technologies that are necessary to build a Digital Twin. Further, it discusses the role of this technology in making sustainable decisions in various sectors ranging from material to medical sciences. Based on the various aspects of Digital Twins covered, it examines if this technology is a viable opportunity to venture into freight logistics policy-making and infrastructure planning.