Data-driven material modeling techniques have gained significant attention due to their ability to capture complex constitutive behaviors beyond the limitations of classical material models. Physics-augmented neural networks (PANNs), which embed physical constraints directly into their architecture, combine the flexibility of machine learning with the reliability required for engineering simulations. This work presents an approach to integrate such network architectures into the explicit finite element solvers Simcenter Radioss and OpenRadioss (Siemens). A framework for transferring pretrained network architectures and their parameters to a standalone user material routine is developed. Networks are trained using PyTorch, though the procedure can be adapted to other frameworks such as TensorFlow, enabling the use of PANNs within existing finite element technology without requiring specialized solvers. Particular emphasis is placed on computational efficiency. The influence of network architecture on simulation performance is investigated, and strategies for reducing evaluation costs while preserving accuracy are discussed. Specifically, replacing the SoftPlus activation function with SQuarePlus is shown to reduce computational cost. A publicly available GitHub repository automates the generation of Fortran user material routines, requiring only the specification of the network architecture and trained parameters. An example impact simulation demonstrates that the generated PANN user material reproduces the nonlinear behavior characteristic of hyperelastic materials under large strains, providing a practical route toward machine-learning-based constitutive models in explicit finite element simulations.

Rubber materials are nowadays indispensable in many applications, particularly as a key component in tires. The optimization of material properties is a central focus, aiming to create an optimal property profile for the material's intended use. A common method for achieving this is blending rubber components. Often, this results in a heterogeneous microstructure, where the individual phases of the material are separated. Furthermore, an interphase region arises between the phases due to overlapping of the polymer chains and the resulting physical interactions, which has a significant impact on the viscoelastic behavior of the rubber blend. It severely impedes the experimental characterization, in particular Dynamic Mechanical Thermal Analysis (DMTA) measurements, since the two individual glass transitions of the phases do not allow for a standardized construction of a master curve in the frequency domain. This leads to the conclusion that investigating the viscoelastic material behavior through material modeling and numerical simulations can yield valuable results. With Atomic Force Microscopy (AFM) images of microstructures at different blend ratios of the constituents serving as the starting point, the material modeling of a rubber blend will be carried out. Various analytical homogenization methods will be considered for modeling the interphase. Image manipulation of the AFM images will be performed using a Gaussian filter to blur the images and thus adjust the interphase width. In the context of numerical simulation, the viscoelastic material behavior will be investigated in the frequency domain, and the characteristic storage and loss moduli for different rubber morphologies will be determined.

Heterogeneity of microstructure is a key factor for dynamic-mechanical behavior of materials. For rubber, mostly development of domains consisting of different polymer types allow us to design high-tech materials. Such polymer blend systems can combine rubber-specific benefits of decisive significance for application performance. Generally, fillers like carbon black or silica are used to enhance ultimate properties, like tensile strength or wear resistance. In polymer blends, distribution of filler particles toward domains of various composition defines the quality of the material used. An already proven model for determining filler distribution based on experimental measurements was optimized and applied for the blend system made of natural rubber and styrene butadiene rubber, whose blend ratio, filler content, and type were varied systematically in fine steps. The model focuses on temperature function of loss modulus at glass transition, of which heterogeneous blend systems have two separated at different temperatures. The modulus contribution occurring in the temperature range between these was previously interpreted as a small layer between domains of different types called interphase, which is preferentially enriched with filler before other phases and therefore has very high filler loads. However, investigations using atomic force microscopy have shown no concentration of filler particles at phase boundaries but decreasing domain size in areas of high filler concentration. Fining of phase morphology due to filler particles indicates compatibility improvement of both polymers, so that the filler acts as a compatibilizer. The influence of the filler on miscibility is tremendous. With high filler loads in silica-filled blend systems, instead of two separate glass transitions a single, very wide, plateau-like glass transition occurs.

The numerical investigation of acoustic damping materials, such as foams, constitutes a valuable enhancement to experimental testing. Typically, such materials are modeled in a homogenized way in order to reduce the computational effort and to circumvent the need for a computational mesh that resolves the complex micro-structure. However, to gain detailed insight into the acoustic behavior, e.g., the transmittance of noise, such fully resolved models are mandatory. The meshing process can still be drastically simplified by using a fictitious domain approach. We propose the finite cell method, which combines the fictitious domain approach with high-order finite elements and resolves the complex geometry using special quadrature rules. In order to take into account the fluid-filled pores of a typical damping material, a coupled vibroacoustic problem needs to be solved. To this end, we construct two separate finite cell discretizations and prescribe coupling conditions at the interface in the usual manner. The only difference to a classical boundary fitted approach to vibroacoustics is that the fluid-solid interface is immersed into the respective discretization and does not correspond to the element boundaries. The proposed enhancement of the finite cell method for vibroacoustics is verified based on a comparison with commercial software and used within an exemplary application.

The present work attempts to study the cooling characteristics of 7050 aluminium alloy under semi-solid conditions during the jet impingement quenching. An aluminium plate heated to 485 degrees C (10% liquid fraction) is prone to hot cracks, causing large fluctuations in the temperature data. The 2-D direct heat transfer problem is formulated with the finite element technique, and moving boundary conditions are applied to simulate the quenching process. The heat flux is estimated from the boiling curve parameters (Qmax, TDNB, TLeid) by matching the simulated and experimental temperature data. The cracks are incorporated as the interface elements in the finite element domain along with the phase change model to simulate the heat transfer phenomena. The influence of phase change and hot cracks on heat transfer is studied in detail with static and dynamic cracking conditions. The parity plot reveals that experimental and simulation results are in good agreement for uncracked plates, with an error range of +/- 3% and R2 = 0.9987. Phase change incorporation improves the simulation results for cracked plates, reducing the error range from +/- 10% (without phase change) to +/- 5% (with phase change) along with R2 values of 0.9929 and 0.9863, respectively. The Boiling curve parameters for the cracked plate are found to be Qmax: 7.2 MW/m2, TDNB: 190 degrees C, and TLeid: 450 degrees C. Further, the findings show that the crack originates in the impingement zone of the quenched side of the plate.

An investigation was conducted to examine the photothermal and thermomechanical effects of short-pulse laser irradiation on normal tissues. This study analyzed the impact of short-pulse laser radiation on the heat-affected region within tissues, taking into consideration a set of laser variables, namely wavelength, intensity, beam size, and exposure time. The beam size ranged between 0.5 and 3 mm, and the intensity of the laser radiation ranged from 1 to 5 W/mm2 at wavelengths of 532 and 800 nm. A three-layered, three-dimensional model was implemented and studied in a polar coordinate system (r = 10 mm, z = 12 mm) in COMSOL Multiphysics (version 5.4, COMSOL Inc., Stockholm, Sweden) to perform numerical simulations. The Pennes bioheat transfer model, Beer-Lambert, and Hooke’s law are integrated to simulate the coupled biophysics problem. Temperature and stress distributions resulting from laser radiation were produced and analyzed. The accuracy of the developed model was qualitatively verified by comparing temperature and mechanical variations following the variations of laser parameters with relevant studies. The results of Box-Behnken analysis showed that beam size (S) had no significant impact on the response variables, with p-values exceeding 0.05. Temperature (Tmax) demonstrates sensitivity to both beam intensity (I) and exposure time (T), jointly contributing to 89.6% of the observed variation. Conversely, while beam size (S) has no significant effect on stress value (Smax), wavelength (W), beam intensity (I), and exposure time (T) collectively account for 71.6% of the observed variation in Smax. It is recommended to use this model to obtain the optimal values of the laser treatment corresponding to tissue with specified dimensions and properties.

Numerical simulation has great potential to provide a more comprehensive understanding of human impact response to injury mechanisms. Finite Element (FE) models are used as a tool to study human injuries in greater detail, for example, the THUMS (Total Human Model Safety of TOYOTA) model, which is widely used as a reliable human model in different fields to predict human injuries such as fractures, internal organ damage, and brain tissue injuries. However, no available FE model can be used to simulate human-robot collisions based on standards ISO/TS 15066 and the biomechanical characteristics of human soft tissues in vivo. The authors have developed a head model based on the structures (dimensions and anatomy) of the THUMS head model, specifically designed to simulate impact loads on the masticatory muscles. Based on medical imaging (MRI) data, the soft tissues at the location of the masticatory muscles in the THUMS head are transformed from monolayer to multilayer, that is, a composite geometry of skin-fat-muscle each with its own material model and parameters. The model was optimized and validated using the experimental data from the Fraunhofer IFF subjects study, which determined biomechanical thresholds for specific body locations in ISO/TS 15066 under dynamic collisions.

The application of immersed boundary methods in static analyses is often impeded by poorly cut elements (small cut elements problem), leading to ill-conditioned linear systems of equations and stability problems. While these concerns may not be paramount in explicit dynamics, a substantial reduction in the critical time step size based on the smallest volume fraction χ of a cut element is observed. This reduction can be so drastic that it renders explicit time integration schemes impractical. To tackle this challenge, we propose the use of a dedicated eigenvalue stabilization (EVS) technique.The EVS-technique serves a dual purpose. Beyond merely improving the condition number of system matrices, it plays a pivotal role in extending the critical time increment, effectively broadening the stability region in explicit dynamics. As a result, our approach enables robust and efficient analyses of high-frequency transient problems using immersed boundary methods. A key advantage of the stabilization method lies in the fact that only element-level operations are required.This is accomplished by computing all eigenvalues of the element matrices and subsequently introducing a stabilization term that mitigates the adverse effects of cutting. Notably, the stabilization of the mass matrix Mc of cut elements – especially for high polynomial orders p of the shape functions – leads to a significant raise in the critical time step size Δtcr.To demonstrate the efficiency of our technique, we present two specifically selected dynamic benchmark examples related to wave propagation analysis, where an explicit time integration scheme must be employed to leverage the increase in the critical time step size.

Due to their ease of use and low cost, passive damping methods are a preferred mean for the reduction of noise in many engineering applications. This applies in particular to foam materials, which exhibit good acoustic and mechanical damping properties. The selection of suitable materials is usually carried out experimentally and can be very labor-intensive and time-consuming. For this reason, it is helpful to develop qualified numerical methodsthat can be used for material design and selection. Hence, foam materials must be characterized experimentally in order to enable a later comparison with vibroacoustic simulations. This contribution, therefore, aims at providing suitable parameters for the use in numerical analyses and their validation. Firstly, the microstructure of a foam specimen is captured by means of a CT scan. In addition to providing the geometry for the multi-physics simulations, this measurement is also used to determine characteristic foam features, for example, strut thickness and pore size distribution. In the second step, the frequency-dependent stiffness and damping properties of the material are determined by a special experimental setup utilizing an electrodynamic shaker. Here, the dynamic system is approximated as a single-mass oscillator, which is sufficiently accurate for low frequencies. These properties will later be used in the numerical model to evaluate different parameter identification approaches. In the third and last step of the experimental campaign, measurements with an impedance tube are conducted to obtain the coefficient of absorption. This material parameter is particularly suitable for comparing experiments and simulations. Finally, the correlation between the experimental results is examined to provide a deeper understanding of the foam materials.

Foamed materials are widely used to reduce noise due to their comparably good acoustic damping behavior. However, out of a large variety of these materials a suitable candidate has to be identified for each application. This is a challenging process that is typically guided by experiments and experience. While numerical simulations could support these experiments and reduce the effort to a great extent, no suitable discretization approach has yet been established that can fully capture the complex geometry of the foam. A fully resolved model is desirable in order to yield reliable predictions that can then be used to establish homogenized models. We established a monolithic coupling approach based on the finite cell method (FCM) that realizes a vibroacoustic simulation in this sense. The fluid and the structure domain are discretized by Cartesian grids and the geometry defined based on computed tomography scans is accounted for during the quadrature of the weak form. Our simulation in the time domain makes use of explicit time marching schemes and is therefore limited by a critical time step size. This is known to be arbitrarily low for discretizations with the FCM containing cells with arbitrarily small support. As a remedy against this we use the classical α $\alpha $ -stabilization technique and investigate its potentials and limitations.

This research aims to study the mechanical behavior of the materials most commonly used in crankshaft manufacturing by designing a four-piston crankshaft, analyzing the stresses and displacements resulting from the applied load, and determining vibration frequencies. Additionally, this study examines the thermal behavior of the crankshaft. For this purpose, a three-dimensional model of the crankshaft was designed using CATIA V5 R18 software, and finite element analysis was subsequently performed using ANSYS 2019 R1 software under static, dynamic, and thermal conditions with four different materials in various orientations. To verify the effectiveness of the proposed design, it was compared with a reference design in terms of stresses and displacements. This study also explores improvements in crankshaft geometry and shape. The results indicate that selecting the appropriate material for the working conditions and optimizing the geometry and shape enhance engine performance and reduce the crankshaft’s weight by 20%. The findings were validated by comparing the designs, which support increased productivity and improved durability.

Flow diverter implantation has emerged as a highly effective treatment for cerebral aneurysms. However, the variability in patient-specific vascular anatomy necessitates detailed pre-operative planning to mitigate potential complications arising from standard, one-size-fits-all devices. To address these challenges, robust predictive simulation tools are essential for optimizing flow diverter design and implantation strategies tailored to the unique characteristics of each patient's anatomy. This study focuses on developing an advanced numerical simulation tool for modeling the mechanical behavior of braided flow diverters during crimping and navigation through patient-specific vasculature. Using isogeometric analysis (IGA) with NURBS-based representations in LS-Dyna, the intricate deformations of the flow diverter wires during catheter crimping are captured with high accuracy. The patient-specific vessel geometries, derived from imaging data, are integrated into the model to account for variations in vascular structure, ensuring precise alignment and controlled navigation of the device. The navigation process relies on optimizing the central axis of the blood vessel to minimize torsional stress on the flow diverter, reducing the risk of device malfunction or failure during deployment. By incorporating patient-specific information, such as vessel curvature and tortuosity, the simulation tool enables the prediction of potential issues, thus allowing for intervention planning that is tailored to individual anatomy. This patient-specific approach enhances the safety and efficacy of flow diverter implantation and serves as a foundation for improved device design prior to prototype development.

This article discusses physics-augmented neural network approaches in the field of hyperelastic material modeling. Physical conditions such as objectivity, material symmetry, or a stress– and energy-free reference configuration are considered in the construction of the neural networks. In addition, a new approach for stress normalization is proposed. The neural network is used to learn the behavior of Yeoh's constitutive model with sparse data. Finally, the trained networks are incorporated into a three-dimensional finite element framework and compared with the classical material model in terms of accuracy. The paper demonstrates the ability of physics-augmented neural networks to model hyperelastic materials using a small amount of data that could be generated by experiments. Compared to the classical constitutive laws of Yeoh's model, our trained material showed no material instabilities that could occur due to poorly chosen material parameters.

A fabrication methodology for piezoelectric motors based on multiple unimorph arms at the mesoscale is proposed. The combination of laser micromachining and lamination steps allows for a stator with a diameter of 9 mm and a thickness of 0.267 mm to be batch manufactured. This design is investigated via a finite element analysis where it is shown that the contact condition between the stator unimorph arms and rotor is dependent on the input drive frequency. The fabricated stator is then characterized experimentally where it is shown that a shift in the sinusoidal drive frequency from 3220 Hz to 3900 Hz results in a change to the rotational direction of the rotor from the positive to the negative direction. The torque of the motor is evaluated numerically to demonstrate the performance of the mesoscale piezoelectric motor in both rotational directions.

A particle damper is a passive damping device, which relies on the high dissipation properties of granular materials. During structural vibration, kinetic energy transfers to the particle damper, initiating collisions among particles and with cavity walls. This interaction results in friction-based dissipation, leading to a reduction in the supporting structure’s vibration amplitude. The granular materials enclosed in the particle dampers undergo significant dynamic loads over the course of their lifespan. The consistent dynamic stress encountered by granular materials might alter the vibration attenuation capability of a particle damper. Therefore, it is crucial to examine the vibration mitigation performance of a particle damper after subjecting it to substantial dynamic loads before implementing it in real-world applications. Hence, the present contribution aims to experimentally investigate the vibration attenuation capability of particle dampers subjected to dynamic loading at 85 million, 165 million, and 330 million cycles. Furthermore, the particle dampers under investigation have also been exposed to a temperature cyclic load ranging from 30 °C to 120 °C. The experimental investigation shows that there is no negative effect on the vibration mitigation performance of the particle dampers before and after being subjected to high-impact dynamic loads and temperature fluctuations. Therefore, the granular material used in designing the particle dampers, which was studied in our previous work and subjected to long-term durability testing in the current contribution, proves to be a favorable choice. It offers advantages in terms of vibration reduction capability, reduction in additional mass, and resilience to negative effects from dynamic loading and temperature cycles.

This study delves into an in-depth examination of the biomechanical characteristics of various materials commonly utilized in the fabrication of artificial ankle joints. Specifically, this research focuses on the design of an ankle joint resembling the salto-talaris type, aiming to comprehensively understand its performance under different loading conditions. Employing advanced finite element analysis techniques, this investigation rigorously evaluates the stresses and displacements experienced by the designed ankle joint when subjected to varying loads. Furthermore, this study endeavors to identify the vibrating frequencies associated with these displacements, offering valuable insights into the dynamic behavior of the ankle joint. Notably, the analysis extends to studying random frequencies across three axes of motion, enabling a comprehensive assessment of directional deformities that may arise during joint function. To validate the effectiveness of the proposed design, a comparative analysis is conducted against the star ankle design, a widely recognized benchmark in ankle joint prosthetics. This comparative approach serves dual purposes: confirming the accuracy of the findings derived from the salto-talaris design and elucidating the relative efficacy of the proposed design in practical application scenarios.

Virtual planning is ideally suited for maxillofacial operations as it allows the surgeon to assess the bony and critical neurovascular structures and enables him to plan osteotomies and fracture reductions. This study aims to propose the use of titanium-based patient-specific implants (PSI), along with virtual surgical planning to assess the advantages and the complications in a case of orbital reconstruction. A three-dimensional model of the skull was generated using computed tomography (CT) data of a female patient using Mimics software (version 19, Materialize, Leuven, Belgium). Numerical PSI models were designed using 3-Matic software (version 13, Materialize, Leuven, Belgium) and the non-affected orbit as a template. Surgical virtual planning showed the suitability of the use of the numerical models in traumatic surgical rehabilitation. Moreover, the digital printing process enabled the trial of the designed PSIs on the patient’s face before the surgery. Reconstruction Biomechanical studies are an essential part of understanding the limits of maxillofacial traumas. The surgical results confirmed the virtual predictions, and the orbital reconstruction seems to be more enhanced and facilitated.