Structural Mechanics Simulations Research Articles

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

Additive Manufacturing and Mechanical Properties of Auxetic and Non-Auxetic Ti24Nb4Zr8Sn Biomedical Stents: A Combined Experimental and Computational Modelling Approach

The effect of plaque deposition (atherosclerosis) on blood flow behaviour is investigated via computational fluid dynamics and structural mechanics simulations. To mitigate the narrowing of coronary artery atherosclerosis (stenosis), the computational modelling of auxetic and non-auxetic stents was performed in this study to minimise or even avoid these deposition agents in the future. Computational modelling was performed in unrestricted (open) conditions and restricted (in an artery) conditions. Finally, stent designs were produced by additive manufacturing, and mechanical testing of the stents was undertaken. Auxetic stent 1 and auxetic stent 2 exhibit very little foreshortening and radial recoil in unrestricted deployment conditions compared to non-auxetic stent 3. However, stent 2 shows structural instability (strut failure) during unrestricted deployment conditions. For the restricted deployment condition, stent 1 shows a higher radial recoil compared to stent 3. In the tensile test simulations, short elongation for stent 1 due to strut failure is demonstrated, whereas no structural instability is noticed for stent 2 and stent 3 until 0.5 (mm/mm) strain. The as-built samples show a significant thickening of the struts of the stents resulting in short elongations during tensile testing compared to the simulations (stent 2 and stent 3). A modelling framework for the stent deployment system that enables the selection of appropriate stent designs before in vivo testing is required. This leads to the acceleration of the development process and a reduction in time, resulting in less material wastage. The modelling framework shall be useful for doctors designing patient-specific stents.

Generative learning‐based model for the prediction of 2D stress distribution

AbstractIn this study, we introduce a Generative learning‐based approach to accelerate Finite Element simulations. The aim is to explore the ability of a Generative learning‐based approach to predict the output of Finite Element simulations. Often, the drawback of classical regression models is that they are bound to the distribution of training data and cannot extrapolate outside of the training domain. In the current study, to overcome this, we propose a Generative Adversarial Network (GAN) based approach for learning to infer structural mechanics simulations. GANs have the ability to learn the underlying distribution of data and can efficiently extrapolate outside the training range. We train the proposed network on data obtained from classical Finite Element simulations based on linear elastic and Johnson‐Cook plasticity models. The goal here is to understand the ability of a GAN to replace FEM by incorporating the underlying mechanics knowledge into the network to enhance the generalizing ability of the network for various materials on various loading and boundary conditions. We propose an encoder‐decoder‐like U‐Net generator architecture with activated skip connections and a PatchGAN‐based discriminator that discriminates based on local patches of data leading to a more robust critique for the generator. The advantage of the proposed framework is that it takes inputs such as the nodal information, their corresponding edges, nodal coordinates and the boundary conditions for each particular node from a Finite Element pre‐processor and computes the von Mises stress at each node as output that can be read by a Finite Element post‐processor. Also, the novelty of the proposed GAN is that, unlike the existing literature, it takes nodal values such as applied Boundary conditions and coordinates as inputs instead of images and performs nonlinear regression with Finite Element data and gives von‐Mises stresses at each node as output.

Iterative solution of spatial network models by subspace decomposition

We present and analyze a preconditioned conjugate gradient method (PCG) for solving spatial network problems. Primarily, we consider diffusion and structural mechanics simulations for fiber based materials, but the methodology can be applied to a wide range of models, fulfilling a set of abstract assumptions. The proposed method builds on a classical subspace decomposition into a coarse subspace, realized as the restriction of a finite element space to the nodes of the spatial network, and localized subspaces with support on mesh stars. The main contribution of this work is the convergence analysis of the proposed method. The analysis translates results from finite element theory, including interpolation bounds, to the spatial network setting. A convergence rate of the PCG algorithm, only depending on global bounds of the operator and homogeneity, connectivity and locality constants of the network, is established. The theoretical results are confirmed by several numerical experiments.

FERMI: Fusion Energy Reactor Models Integrator

The Fusion Energy Reactor Models Integrator (FERMI) is an integrated simulation environment under development for the coupled simulation of the plasma, first wall, and blanket of fusion reactor designs. The FERMI goals are to shorten the overall design cycle while guaranteeing unprecedented accuracy, thus integrating fusion design activities, facilitating an optimal reactor design, and reducing development risks. These goals are achieved by coupling single-physics solvers into a multiphysics simulation environment (FERMI). The Integrated Plasma Simulator (IPS)–FASt TRANsport (IPS-FASTRAN) simulation framework is used for the following: plasma physics, MCNP/Shift codes for neutron and photon transport, OpenFoam for computational fluid dynamics and magnetohydrodynamics (MHD), HyPerComp Incompressible MHD solver for Arbitrary Geometry (HIMAG) for dual-coolant lead-lithium (DCLL) blankets, and DIABLO for structural mechanics simulations. These codes are coupled using the open-source library named precise Code Interaction Coupling Environment (preCICE). FERMI’s features are tested with the analysis of the liquid immersion blanket (LIB) [proposed in the Affordable Robust Compact (ARC)–class tokamak design], the DCLL blanket [proposed in the Fusion Pilot Plant (FPP) design], and other benchmark cases. The calculated figures of merit are the tritium breeding ratio, material activation, displacements per atom, shutdown dose rate, heat deposited in the vacuum vessel and blanket, temperature hot spots, and displacements caused by swelling and creep. A critical technical problem is multiphysics code coupling, which is tackled here, and the first three-dimensional (3D) simulations of the DCLL-FPP and LIB-ARC blankets are presented. To the authors’ knowledge, FERMI represents the first effort to perform 3D simulations of nuclear fusion first wall and blankets in a fully coupled multiphysics manner.

Multiscale model for ultrashort pulsed parallel laser structuring—part II. The macroscale model

The increasing pixel density in displays demands high quality in the production of fine metal masks (FMMs). The production process of FMMs boils down to structuring tiny holes in thin metal sheets or foils. The manufacturing requirements of FMMs are high precision in terms of the hole geometry to let enough light escape from each diode and high productivity to produce the required amount. To achieve both objectives, high power ultrashort pulse (USP) lasers can be utilized. Because USP lasers fall short of the productivity requirements, they are combined with multibeam scanners. During production, the multibeam scanners deposit a lot of heat in the metal foil, which can ultimately yield temperature-induced distortions. To understand and finally avoid such distortions, a process simulation is sought. In a preceding study, the structuring of a single hole (the microscale) was investigated, but due to the large differences in the time and spatial scales involved, it was not feasible to simulate the production of the whole part (the macroscale). Within this treatise, a multiscale approach that takes into account the necessary information from the microscale to describe temperature-induced distortions on the macroscale is described. This approach targets laser ablation processes with pulse durations ranging from picoseconds up to nanoseconds provided the ablation is not melt-driven. First, a representative volume element (RVE) is generated from the results of the microscale model. Then, this RVE is utilized in the thermo-elastic structural mechanics simulation on the macroscale. The multiscale model is validated numerically against a hole-resolved computation, which shows good agreement. Naturally, the simulation is highly dependent on the microscale model, which in turn depends on the material properties. To handle material changes well, an experimental calibration has to be performed. This calibration is not part of this treatise, but it will be described in a future publication. In addition to the calibration process, the validation with experiments will be conducted in future research. Additionally, the authors envision the automation of the whole process, resulting in a first-time-right approach for the development of FMMs. Finally, the procedure might be extended to the requirements of other filtration purposes.

Multiscale agent-based modeling of restenosis after percutaneous transluminal angioplasty: Effects of tissue damage and hemodynamics on cellular activity

BackgroundRestenosis following percutaneous transluminal angioplasty (PTA) in femoral arteries is a major cause of failure of the revascularization procedure. The arterial wall response to PTA is driven by multifactorial, multiscale processes, whose complete understanding is lacking. Multiscale agent-based modeling frameworks, simulating the network of mechanobiological events at cell-tissue scale, can contribute to decipher the pathological pathways of restenosis. In this context, the present study proposes a fully-automated multiscale agent-based modeling framework simulating the arterial wall remodeling due to the wall damage provoked by PTA and to the altered hemodynamics in the post-operative months. MethodsThe framework, applied to an idealized femoral artery model, integrated: (i) a PTA module (i.e., structural mechanics simulation), computing the post-PTA arterial morphology and the PTA-induced damage (ii) a hemodynamics module (i.e., computational fluid dynamics simulations), quantifying the near-wall hemodynamics, and (iii) a tissue remodeling module simulating cellular activities through an agent-based model. ResultsThe framework was able to capture relevant features of the 3-month arterial wall response to PTA, namely (i) the impact of the PTA-induced damage and altered hemodynamics on arterial wall remodeling, including the local intimal growth at the most susceptible regions (i.e., elevated damage levels and low wall shear stress), (ii) the lumen area temporal trend resulting from the interaction of the two inputs, and (iii) a 3-month lumen area restenosis of ∼25%, in accordance with clinical evidence. ConclusionsThe overall results demonstrated the framework potentiality in capturing mechanobiological processes underlying restenosis, thus fostering future application to patient-specific scenarios.

A small‐scale creep test for calibrating an efficient lifetime model for high pressure turbine blades

AbstractJet engines of airplanes are designed such that in some components damage occurs and accumulates in service without being critical up to a certain level of damage. Since maintenance, repair, and component exchange are very cost‐intensive, it is necessary to predict efficiently the component lifetime with high accuracy. A former developed lifetime model, based on interpolated results of aerodynamic and structural mechanics simulations, uses material parameters estimated from literature values of standard creep experiments. For improved accuracy, an experimental procedure is developed for the characterization of the short‐time creep behavior, which is relevant for the operation of turbine blades of jet engines. To consider microstructural influences resulting from the manufacturing of thin‐walled single crystal turbine blades, small‐scale specimens from used turbine blades are extracted and tested in short‐ and medium‐time creep experiments. Based on experimental results and literature values, a creep model, which describes the fracture behavior for a wide range of creep loads, is calibrated and is now used for the lifetime prediction of turbine blades under real loading conditions.

Hybrid IGA-FEA of fiber reinforced thermoplastic composites for forward design of AI-enabled 4D printing

Fused deposition modeling (FDM)-based 4D printing uses thermoplastics to produce artifacts and requires computational analysis to assist its design processes of complex geometries. Previously, finite element analysis (FEA) has been used to simulate 4D printing deformations, and its accuracy has been computationally and experimentally verified. However, using FEA also leads to several limitations, such as geometric approximation error and the computational time-cost due to the high degrees of freedom. To address these issues, this paper introduces isogeometric analysis (IGA) into the deformation simulations and propounds a composite design by hybridizing FEA and IGA elements to reduce the number of degrees of freedom while maintaining the simulation accuracy. Moreover, since the hybrid IGA-FEA method used for modeling 4D printing structure deformation excludes real-time interactivity, we develop a polycube-based random forest regressor machine learning (ML) model to learn the IGA-FEA-based structural mechanics simulations and provide fast deformation predictions. Given the input actuator block distribution and geometry configurations, our well-trained model can predict the residual stress-induced deformation behaviors of mesh-like thermoplastic composite structures. With an error less than 0.11% and computation speed 20 times faster than hybrid IGA-FEA simulations, our model can create real-time (0.93 s) and truthful (99.89% accuracy) results. The effectiveness of the proposed model is demonstrated with several complex design examples. We believe the presented workflow effectively combines IGA, FEA, ML, and 4D printing to provide a powerful computational tool that enriches the 4D printing design tool box, and brings huge application potentials.

Bayesian inverse uncertainty quantification of the physical model parameters for the spallation neutron source first target station

The reliability of the mercury spallation target is mission-critical for the neutron science program of the spallation neutron source at the Oak Ridge National Laboratory. We present an inverse uncertainty quantification (UQ) study using the Bayesian framework for the mercury equation of state model parameters, with the assistance of polynomial chaos expansion surrogate models. By leveraging high-fidelity structural mechanics simulations and real measured strain data, the inverse UQ results reveal a tight posterior distribution for the tensile cutoff threshold, the mercury density, and the mercury speed of sound. The updated distributions do not necessarily represent the nominal mercury physical properties, but the ones that fit the strain data and the solid mechanics model we have used, and can be explained by three reasons. First, the limitations of the computer model or what is known as the “model-form uncertainty” that would result from numerical methods and physical approximations. Second, is the biases and errors in the experimental data. Third, is the mercury cavitation damage that also contributes to the change in mercury behavior. Consequently, the mercury equation of state model parameters try to compensate for these effects to improve fitness to the real data. The mercury target simulations using the posterior parametric values result in an excellent agreement with 88% average accuracy compared to experimental data, 6% average increase compared to reference parameters, with some sensors experiencing an increase of more than 25%. With a more accurate strain response predicted by the calibrated simulations, the component fatigue analysis can utilize the comprehensive strain history data to evaluate the target vessel’s lifetime closer to its real limit, saving tremendous target cost and improving the design of future targets as well.

Aeroelastic simulations of a delta wing with a Chimera approach for deflected control surfaces

A numerical tool for the computation of aircraft control surface aerodynamics with flexibility effects is presented. The solution is based on coupled Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) simulations embedded in the multidisciplinary simulation environment SimServer. In SimServer, the DLR-TAU Code is utilized to obtain the CFD solution by solving the Reynolds-Averaged Navier–Stokes (RANS) equations. Structural displacements are computed with a modal solver. The Chimera implementation of SimServer, suited for hybrid grids, is applied to model the control surfaces. Numerical simulations with the flexible Chimera method are performed for the Model53 wing configuration, which is a generic delta wing with a deployed slat as well as an inboard and outboard trailing edge flap. Aerodynamic and aeroelastic simulations at high dynamic pressure q=45 kPa and transonic speed {text {Ma}} = 0.8 are performed for several angles of attack 10^circ le alpha le 25^circ and flap deflection angles -30^circ le delta le 30^circ. The effect of structural deformations on the flow field and control surface effectiveness are analyzed and compared to computations of components treated fully rigid. At the targeted freestream condition M=0.8 and {text {Re}}=15.1 times 10^7, the flow field around the Model53 configuration is characterized by the interaction of vortices and shock waves. The results of the lift and pitching moment coefficient for the rigid and flexible configuration revealed the importance of taking the structural flexibility into account in order to obtain more accurate results for the considered range of flap deflections. Furthermore, the computational effort of the aerodynamic and aeroelastic simulations are evaluated. The increase in computational effort is shown to be adequate for the given increase in accuracy.

In‐process image of machine tools – Transient‐thermal and dynamic simulation of moving structures

AbstractThe aim of structural mechanics simulation is to better represent the working accuracy of machine tools. The visualization is done in process, that is, during the machine movement. It is realized by reading out the control values and the subsequent simulation of the structural–mechanical behavior of the machine. This procedure allows deviations in the working accuracy outside the control loop to be taken into account, which cannot be detected by the measuring system. This allows an improved statement on the achievable working accuracy and enables the operator to react to any deviations in the machine accuracy. In contrast, the thermal behavior of machine tools focuses on an observation level which is characterized by long and strongly varying time constants. In contrast to process control, the term “thermal real time” addresses the seconds to hours range. For the implementation, a three‐axis demonstrator machine with discrete elements was modeled.

Fibrin prestress due to platelet aggregation and contraction increases clot stiffness

Efficient hemorrhagic control is attained through the formation of strong and stable blood clots at the site of injury. Although it is known that platelet-driven contraction can dramatically influence clot stiffness, the underlying mechanisms by which platelets assist fibrin in resisting external loads are not understood. In this study, we delineate the contribution of platelet-fibrin interactions to clot tensile mechanics using a combination of new mechanical measurements, image analysis, and structural mechanics simulation. Based on uniaxial tensile test data using custom-made microtensometer and fluorescence microscopy of platelet aggregation and platelet-fibrin interactions, we show that integrin-mediated platelet aggregation and actomyosin-driven platelet contraction synergistically increase the elastic modulus of the clots. We demonstrate that the mechanical and geometric response of an active contraction model of platelet aggregates compacting vicinal fibrin is consistent with the experimental data. The model suggests that platelet contraction induces prestress in fibrin fibers and increases the effective stiffness in both cross-linked and noncross-linked clots. Our results provide evidence for fibrin compaction at discrete nodes as a major determinant of mechanical response to applied loads.

Buckling of boron nanotubes under axial compression: Insights from molecular mechanics and continuum mechanics

The buckling behaviours of boron nanotubes (BNTs) are investigated in this paper by using molecular structural mechanics (MSM) simulations and elastic shell models. Two types of BNTs (α and χ-BNTs) whose structures are proven to be thermally stable in first-principles molecular dynamics simulations are considered in the study. Our MSM results show a shell-to-column buckling mode transition occurring in BNTs with increasing aspect ratio. The critical buckling force of the column buckling of long BNTs significantly decreases as the aspect ratio grows, while that of the shell buckling of short BNTs is almost independent of the aspect ratio. MSM simulations also show that α and χ-BNTs both have anisotropic elastic properties. As a result, the simple Donnell shell model previously employed in other tubular nanomaterials becomes inapplicable in describing the buckling behaviours of the present BNTs. Under this circumstance, we propose an orthotropic elastic shell model to consider the anisotropy of elastic properties in the continuum mechanical modelling of BNTs. Through the orthotropic elastic shell model, the buckling behaviours of α and χ-BNTs are found to have different relations with their chirality, which is attributed to different anisotropy features observed in the elastic properties of these two BNTs.

Structural mechanics modeling reveals stress-adaptive features of cutaneous scars.

The scar is a predominant outcome of adult mammalian wound healing despite being associated with partial function loss. Here in this paper, we have described the structure of a full-thickness normal scar as a "di-fork" with dual biomechanical compartments using in vivo and ex vivo experiments. We used structural mechanics simulations to model the deformation fields computationally and stress distribution in the scar in response to external forces. Despite its loss of tissue components, we have found that the scar has stress-adaptive features that cushion the underlying tissues from external mechanical impacts. Thus, this new finding can motivate research to understand the biomechanical advantages of a scar in maintaining the primary function of the skin, i.e., mechanical barrier despite permanent loss of some tissues and specialized functions.

Global Design of a Waveguide X-Band Power Amplifier

The design and the fully coupled Thermodynamic and Structural Mechanics simulation of a Spatial Power Amplifier are described in this paper. The amplifier is realized in a WR90 waveguide, employing Fin-Line Transitions and Monolithic Microwave Integrated Circuit Solid State Power Amplifiers. Global performances of active devices and combining structure have a critical dependence to the thermo-mechanical condition of operation. The temperature alterations and thermal expansions, related to the power dissipation of the devices, have been analyzed in order to lead the amplifier at extreme power output, avoiding malfunctions. The proposed analysis accounts for the effects of different distributions of heat flux and stresses as a consequence of the different power consumption of the Driver and Final stage transistors. The amplifier combines 16 active devices of 7.9 W maximum power output with a power dissipation of 20 W, heating the transistor channel to140° and deforming the mechanical structure to 4.9µm with a maximum stress of 0.41 GN/m2. A maximum power output of 112W with a Return Loss greater than 12 dB in the whole X-Band is ensured

Analysis on Thermal-Force Coupling Performance of a Vehicle IGBT Packaging Module

Based on the basic theory of thermodynamics and finite element, the thermal characteristics and structural mechanics simulation are carried out taking an automobile IGBT packaging module as the research object. Then the distribution of temperature, thermal stress and deformation of IGBT are obtained. The thermal force coupling performance of the structure is judged according to the analysis results, so as to provide theoretical reference for the design and selection of subsequent radiators.

Study on the Material Mechanical Properties of Aquaculture Net Cage

Due to the typhoon impacts, aquaculture net cages may be exposed to the risk of structural failure as a far-reaching aquaculture equipment. In addition, the fatigue problem of key components due to long-term marine alternating loads can not be ignored. The method is developed independently on processing samples of cage for testing its performance parameters, among which the fatigue Wohler curve is S = -1.022ln (N) + 22.201. By adapting the following methods: Mechanical test, Equivalent load finite element simulation and Full field finite element simulation respectively is verified each other, and the error is less than 5%. The key nodes of the stress concentration of the floating frame are mainly the welding point, the mooring point and the edge area of the I-beam frame at both sides. The damage of the cage which caused by tensile and bending loads should be considered at the same time. And the tensile strength 22.12 MPa and the bending strength 30.58 MPa could be taken as the evaluation standard for the elastic to plastic deformation. Structural fracture occurs when the elongation at break exceeds 340.18%. The fatigue of the cage is mainly because the stress is much greater than the fatigue limit 3.38 MPa. The material model test combined with structural mechanics simulation provides the basis for guiding the structural optimization design of the cage.

A Method for Large-Scale Parallel Simulation of Reactor Structural Mechanics

The structural mechanics simulation in reactor is an extremely complicated problem, which includes statics, fluid-induced vibration and wear. Because the entire structural mechanics simulation require dividing into 10 billion mesh elements, and then a large number of equations are generated to solve, the demand for high performance computing is urgent. Therefore, we conduct researches on E-class supercomputers, including reactor core geometric modeling, tens of billions of meshing, addition of physical parameters, regional decomposition, and solution of ultra-large sparse matrix equations. Furthermore, we propose a parallel workflow design, function design and architecture design scheme for large-scale parallel simulation of Generation IV reactors structural mechanics based on E-class supercomputer. By combining and optimizing of existing meshing tools and matrix equation solving methods, and finally verified its feasibility and correctness through calculation examples. In addition, the efficiency of the large-scale parallelism has also been significantly improved.

Advanced model order reduction and artificial intelligence techniques empowering advanced structural mechanics simulations: application to crash test analyses

This paper proposes a general framework for expressing parametrically quantities of interest related to the solution of complex structural mechanics models, in particular the ones involved in crash analyses where strongly coupled nonlinear and dynamic behaviors coexist with space-time localized mechanisms. Advanced nonlinear regressions able to proceed in the low-data limit, enabling to accommodate heterogeneous parameters, will be proposed and their performances evaluated in the case of crash simulations. As soon as these parametric expressions will be determined, they can be used for generating large amounts of realizations of the quantity of interest for different choices of the parameters, for supporting data-analytics. On the other hand, such parametric representations allow the use advanced optimization techniques, evaluate sensitivities and propagate uncertainty all them under the stringent real-time constraint.