A new open-source framework for multiscale modeling of fibrous materials on heterogeneous supercomputers
This article presents MuMFiM, an open-source application for multiscale modeling of fibrous materials on massively parallel computers. MuMFiM uses two scales to represent fibrous materials such as biological network materials (extracellular matrix,...
On why mesh untangling may not be required
Generating tangle-free high-quality hexahedral meshes is an ongoing challenge. Tangled meshes, i.e., meshes containing negative Jacobian elements, are unsuitable for finite element (FE) simulations as they lead to erroneous results. Consequently, ...
Seventeen criteria for evaluating Jacobian-based optimization metrics
There are far too many quality and optimization metrics in the meshing literature than are needed. The situation with Target Matrix Optimization Paradigm (TMOP) is the same, because it is all too easy to invent new metrics. How does one go about ...
Isogeometric analysis of shear-deformable, in-plane functionally graded microshells by Mindlin’s strain gradient theory
This paper proposes a general strain-gradient and shear-deformable isogeometric microshell formulation based on the complete Mindlin’s form II strain gradient theory (SGT) and Reissner–Mindlin shell model for the static and dynamic analyses of in-...
Nonlinear finite element treatment of unsymmetric laminated composite shells
The concentration of the current contribution is on the geometrically nonlinear analysis of laminated composite shells employing the finite element method. For this purpose, the use is made of a higher-order shell model with extensible directors ...
Predictive performance enhancement via domain-adaptive designable data augmentation and virtual data-based optimization
In this study, we present a methodology for deriving an optimal performance design in a new domain using a designable generative adversarial network (DGAN) structure based on domain-adaptive designable data augmentation (DADDA). In a generative ...
A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data
- Guillermo Lorenzo,
- Angela M. Jarrett,
- Christian T. Meyer,
- Julie C. DiCarlo,
- John Virostko,
- Vito Quaranta,
- Darren R. Tyson,
- Thomas E. Yankeelov
A hybrid ensemble-based automated deep learning approach to generate 3D geo-models and uncertainty analysis
There is an increasing interest in creating high-resolution 3D subsurface geo-models using multisource retrieved data, i.e., borehole, geophysical techniques, geological maps, and rock properties, for emergency managements. However, dedicating ...
A ready-to-manufacture optimization design of 3D chiral auxetics for additive manufacturing
The 3D chiral-type auxetic metamaterials have attracted massive attention in both academia and engineering. However, the complex deformation mechanism makes this kind of metamaterial hard to be topologically devised, especially in the 3D scenario. ...
A double-loop Kriging model algorithm combined with importance sampling for time-dependent reliability analysis
In Kriging model-based time-dependent reliability analysis algorithm, double-loop one (DLK) needs partial candidate sample pool (CSP) combination of random input and time variable, while single-loop one (SLK) needs complete CSP combination, thus ...
Application of the Bezier integration technique with enhanced stability in forward dynamics of constrained multibody systems with Baumgarte stabilization method
This paper deals with the study and application of a numerical integration scheme based on the Bézier curves to obtain stable and accurate solutions of the governing differential–algebraic equations (DAEs) of constrained multibody systems. For ...
A material/element-defined time integration procedure for dynamic analysis
In this paper, an effective and highly versatile locally-defined time-marching procedure is proposed for dynamic analysis. In this novel technique, the time integration parameters of the method are specified at an element level, adapting ...
Parameterization-based neural network: predicting non-linear stress–strain response of composites
Composite materials like syntactic foams have complex internal microstructures that manifest high-stress concentrations due to material discontinuities occurring from hollow regions and thin walls of hollow particles or microballoons embedded in a ...
Modified bond-based peridynamic approach for modeling the thermoviscoelastic response of bimaterials with viscoelastic–elastic interface
This study investigates the constitutive relationships for a modified bond-based peridynamic (MBB-PD) model to analyze bimaterial structures with a viscoelastic component subjected to mechanical and thermal loads. The hereditary integral ...
Topology optimization for transient thermoelastic structures under time-dependent loads
Most of the previous topology optimization methods for thermoelastic structures use steady-state heat transfer and static equations, which are not applicable to time-dependent loads. In this article, a generic topology optimization method ...
A novel peridynamic fatigue crack propagation model based on two-parameter remaining-life formulation
A novel peridynamic fatigue model is introduced that incorporates the R-ratio effects on fatigue crack growth using a two-parameter remaining-life formulation. The remaining-life formulation is expressed as a function of two independent ...
Automatically imposing boundary conditions for boundary value problems by unified physics-informed neural network
Exact boundary conditions (BCs) imposition technique is widely used in physics-informed neural networks (PINNs) for solving boundary value problems (BVPs). In this regard, the selection of trial function satisfying essential BCs becomes hard to ...
Manipulating the loss calculation to enhance the training process of physics-informed neural networks to solve the 1D wave equation
The application of physics-informed neural networks (PINNs) to address problems involving partial differential equations (PDEs) is increasing. However, PINNs still need lots of enhancement to become reliably robust, as they are prone to fail in ...
An integrated topology and shape optimization framework for stiffened curved shells by mesh deformation
Topology and shape optimization (TSO) is a powerful technique for achieving high-stiffness configurations of stiffened curved shells. However, it presents a challenge to obtain stiffener layouts that satisfy manufacturing constraints using ...
Concurrent multiscale topology optimization of hollow structures considering geometrical nonlinearity
Lattice materials and hollow structures possess excellent mechanical properties, which are beneficial to satisfy the lightweight demands of the products, especially for the large deformation situation. Therefore, a concurrent topology optimization ...
A Gaussian–cubic backward substitution method for the four-order pure stream function formulation of two-dimensional incompressible viscous flows
In this study, a novel meshless collocation method based on the Gaussian–cubic hybrid kernel function in conjunction with the ghost-points method and the general Newton–Raphson method is proposed for solving the four-order stream function ...
Simulations of modulated plane waves using weakly compressible smoothed particle hydrodynamics
Extreme waves, also known as ‘rogue waves’, have posed considerable challenges to maritime traffic over some time. Efforts have been directed at investigating the mechanisms governing these extreme energy localizations in oceanic environments. ...
Sonics: develop intuition on biomechanical systems through interactive error controlled simulations
- Arnaud Mazier,
- Sidaty El Hadramy,
- Jean-Nicolas Brunet,
- Jack S. Hale,
- Stéphane Cotin,
- Stéphane P. A. Bordas
We describe the SOniCS (SOFA + FEniCS) plugin to help develop an intuitive understanding of complex biomechanics systems. This new approach allows the user to experiment with model choices easily and quickly without requiring in-depth expertise. ...
Preserving superconvergence of spectral elements for curved domains via h- and p-geometric refinement
Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the ...
Data assimilation for real-time subsurface flow modeling with dynamically adaptive meshless node adjustments
Over the past few decades, various inverse modeling and data assimilation techniques have been proposed to integrate observed data into subsurface flow models for optimal parameter estimation. In practice, subsurface flow models are often ...
General resource manager for computationally demanding scientific software (MARE)
Today’s supercomputers power scientific calculations in very different areas, ranging from nanotechnology to climate studies and astronomy. Research groups in nascent areas of science and engineering develop their own scientific software, since it ...
Moving mesh method with variational multiscale finite element method for convection–diffusion–reaction equations
The solutions tend to have large gradients, discontinuities, or sharp layers for convection-dominated convection–diffusion–reaction equations. Many studies have demonstrated the advantages of moving mesh and variational multiscale finite element ...
Non-local modelling of multiphase flow wetting and thermo-capillary flow using peridynamic differential operator
Interfaces in multiphase flows are affected by surface tension, and when temperature gradients occur in the flow domain, tangential surface tensions along the interface also arise. As the behaviour of fluids contacting on a solid surface is also ...