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Engineering with Computers OnlineFirst articles

Generalizing CAS elements to overcome locking in -continuous cubic NURBS-based discretizations

  • Original Article

Continuous-assumed-strain (CAS) elements have been recently developed to overcome locking in $$C^1$$ C 1 -continuous quadratic NURBS-based discretizations. In this work, we generalize CAS elements to overcome locking in $$C^1$$ C 1 -continuous …

Feed-forward neural networks as a mixed-integer program

  • Original Article

Deep neural networks (DNNs) are widely studied in various applications. A DNN consists of layers of neurons that compute affine combinations, apply nonlinear operations, and produce corresponding activations. The rectified linear unit (ReLU) is a …

Helmholtz-x : Parallelized adjoint open source solver for the thermoacoustic Helmholtz equation

  • Open Access
  • Original Article

We create and describe an inhomogeneous Helmholtz equation solver, helmholtz-x, written in an open-source framework. The mesh is generated with Gmsh and the solver uses DOLFINx and UFL from FEniCSx. The performance, validity, stability and …

A boundary-based fourier neural operator (B-FNO) method for efficient parametric acoustic wave analysis

  • Open Access
  • Original Article

Repetitive wave analysis is required in various applications involving parametric analyses across different settings. However, traditional numerical methods based on domain discretization become computationally impractical due to the large number …

Effective perpendicular boundary conditions in phase-field models using Dirichlet boundary conditions

  • Original Article

The primary objective of this study is to present the temporal and spatial evolution dynamics of two- and three-dimensional phase-field models with Dirichlet boundary conditions on arbitrary shaped domains. We consider the Allen–Cahn (AC) …

Human-augmented topology optimization design with multi-framework intervention

  • Original Article

This paper proposes a topology optimization approach that allows human augmentation in the optimization process. The approach aims to leverage the experience and expertise of designers, enabling them to make real-time adjustments and have direct …

Toward engineering lattice structures with the material point method (MPM)

  • Open Access
  • Original Article

This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice …

A cyclical fast iterative method for simulating reentries in cardiac electrophysiology using an eikonal-based model

  • Open Access
  • Original Article

Computer models for simulating cardiac electrophysiology are valuable tools for research and clinical applications. Traditional reaction–diffusion (RD) models used for these purposes are computationally expensive. While eikonal models offer a …

B-spline-based material point method with dynamic load balancing technique for large-scale simulation

  • Open Access
  • Original Article

In this study, a dynamic load-balancing (DLB) technique based on the sampling method is developed for MPMs using higher-order B-spline basis functions for parallel MPI calculations based on domain decomposition, in order to perform large-scale …

Development of a personalized fluid-structure interaction model for the aorta in human fetuses

  • Original Article

Fluid-structure interaction (FSI) modeling, a technique widely used to enhance imaging modalities for adult and pediatric heart diseases, has been underutilized in the context of fetal circulation because of limited data on flow conditions and …

A waveguide port boundary condition based on approximation space restriction for finite element analysis

  • Original Article

A waveguide port boundary condition (WPBC) based on the restriction of the approximation space is presented in the context of Finite Element Analysis. As well as efficiently truncating the computational domain in the same manner as the traditional …

Elementary-level intrusive coupling of machine learning for efficient mechanical analysis of variable stiffness composite laminates: a spatially-adaptive fidelity-sensitive computational framework

  • Open Access
  • Original Article

Mechanical analysis of the complex configurations of composite laminates can be computationally prohibitive based on accurate higher-order theories, especially when the analyses involve multiple realizations corresponding to different sets of …

A first order FEM-based formulation for the analysis of molecular structures with bonded interactions

  • Original Article

In this paper we present a formulation, denoted as the Molecular Element Method, that allows, given a certain force field, the possibility of performing a first order analysis as is common in structural mechanics. The stiffness matrices have been …

Differentiable neural-integrated meshfree method for forward and inverse modeling of finite strain hyperelasticity

  • Original Article

The present study aims to extend the novel physics-informed machine learning approach, specifically the neural-integrated meshfree (NIM) method, to model finite-strain problems characterized by nonlinear elasticity and large deformations. To this …

RFF-meshing: a parallel and anisotropic quad-dominant mesh generation framework based on Riemann frame field

  • Original Article

Compared to triangular meshes, quadrilateral meshes offer numerous advantages, such as enhanced fitting accuracy, the capacity to maintain geometric features, and alignment with specific problem orientations. However, there is currently no …

The simulation of spatio-temporal neural field equations with delay depending on the position of neural fibers using the Galerkin method based on moving least squares

  • Original Article

One of the most significant domains in neurodynamics revolves around models founded on neural field equations (NFEs), commonly referred to as Amari’s equations. These equations intricately depict neural activity within individual neural fields and …

A physics preserving neural network based approach for constitutive modeling of isotropic fibrous materials

  • Original Article

We develop a new neural network based material model for discrete fibrous materials that strictly enforces constitutive constraints such as polyconvexity, frame-indifference, and the symmetry of the stress and material stiffness. Additionally, we …

Asynchronous parallel reinforcement learning for optimizing propulsive performance in fin ray control

  • Open Access
  • Original Article

Fish fin rays constitute a sophisticated control system for ray-finned fish, facilitating versatile locomotion within complex fluid environments. Despite extensive research on the kinematics and hydrodynamics of fish locomotion, the intricate …

Study of steady two-dimensional advection–diffusion equation with stratification using second-kind shifted Chebyshev polynomials

  • Original Article

This study investigates the steady two-dimensional (2D) distribution of suspended sediment concentration in an open channel turbulent flow, utilizing five eddy viscosity profiles incorporating the stratification effect. In addition to three …

Integrating analytical and machine learning methods for investigating nonlinear bending and post-buckling behavior of 3D-printed auxetic tubes

  • Original Article

This study focuses on two primary objectives regarding 3D-printed tubular metastructures. Firstly, it investigates the nonlinear mechanical bending and post-buckling characteristics of re-entrant perfect and imperfect auxetic tubes analytically.