Article
Biology
Abbish Kamalakkannan, Peter R. Johnston, Barbara M. Johnston
Summary: Accurate values for cardiac bidomain conductivities are crucial for computational studies, and a protocol presented in this paper demonstrates a more accurate retrieval method using an additive Gaussian noise model. Comparison of prefabricated electrode arrays showed that a rectangular 128-electrode array was more capable of retrieving cardiac conductivities than other tested arrays, suggesting its use in experimental trials.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Biochemical Research Methods
Yuli W. W. Heinson, Julie L. L. Han, Emilia Entcheva
Summary: This study presents a low-cost compact mapping system for all-optical cardiac electrophysiology in human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs). The system uses oblique transillumination, low-cost cameras, and off-the-shelf components to capture voltage, calcium, and mechanical waves. It can help uncover the action of cellular uncoupling agents and has potential for future imaging of thicker tissues.
JOURNAL OF BIOMEDICAL OPTICS
(2023)
Article
Mathematics, Applied
C. D. Marcotte, M. J. Hoffman, F. H. Fenton, E. M. Cherry
Summary: The reconstruction of unobserved electrical excitation patterns in cardiac medicine plays a crucial role in leveraging computational models. In this study, we used experimental optical-mapping recordings of a canine ventricle to guide a local ensemble transform Kalman filter data assimilation scheme. The results show that explicitly including information about the stimulation protocol can slightly improve the confidence and reliability of the ensemble reconstruction over time. We also examined the efficacy of stochastic modeling additions to the assimilation scheme using experimentally derived observation sets.
Article
Physiology
Manuel Marina-Breysse, Alba Garcia-Escolano, Joaquin Vila-Garcia, Gabriel Reale-Nosei, Jose M. Alfonso-Almazan, Ping Yan, Jorge G. Quintanilla, Leslie M. Loew, Peter Lee, David Filgueiras-Rama
Summary: Experts from various disciplines are collaborating to better understand heart disease using techniques such as optical mapping, which has led to the development of a complete and low-cost research tool. The goal is to make this powerful tool more accessible to clinical scientists and students for cardiac electrophysiology research, providing high-resolution data on key parameters in isolated hearts to facilitate translational research.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Cardiac & Cardiovascular Systems
Peter Lee, Luqia Hou, Faisal J. Alibhai, Rasha Al-attar, Ana Simon-Chica, Andres Redondo-Rodriguez, Yilin Nie, Maria Mirotsou, Michael A. Laflamme, Gayathri Swaminath, David Filgueiras-Rama
Summary: The development of a scalable and high-throughput optical mapping robot allows for accelerated measurement of electrophysiological parameters in cardiac diseases. This system can simultaneously measure multiple key electrophysiological parameters with high spatiotemporal resolution. By applying this system to cardiac monolayers/tissue-constructs, a better understanding of ion-channels and fibrillation dynamics is achieved. The system is fully automated, requires no human intervention, and is cost-effective.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2023)
Article
Cardiac & Cardiovascular Systems
Jairo Rodriguez Padilla, Robert D. Anderson, Christian Joens, Stephane Masse, Abhishek Bhaskaran, Ahmed Niri, Patrick Lai, Mohammed Ali Azam, Geoffrey Lee, Edward Vigmond, Kumaraswamy Nanthakumar
Summary: This study compared the accuracy of two-dimensional (2D) and three-dimensional (3D) conduction velocity (CV) algorithms in heart models, and examined the influence of mapping resolution on the results. The findings showed that 2D CV was significantly higher than 3D CV, and increased as the resolution decreased.
Article
Cardiac & Cardiovascular Systems
Jan Lebert, Namita Ravi, George Kensah, Jan Christoph
Summary: Measurement of action potentials or calcium transients in contracting cardiac tissues through optical mapping is challenging due to motion artifacts. Recently, numerical motion tracking and stabilization has been shown to effectively inhibit motion artifacts and allow precise measurements. However, the field is still developing and currently used by few laboratories.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Engineering, Mechanical
Linhe Zhu, Tianyu Yuan
Summary: In this paper, a rumor propagation model with secondary transmission mechanism is established to investigate the inhibitory effect of media refutation on rumor propagation. Parameter identification of the system is achieved through three algorithms. The research results indicate that the Projected Gradient Method can effectively identify the patterns of unknown parameters with global convergence, while the Barzilar-Borwein method and the BFGS Quasi-Newton Algorithm can improve the convergence speed.
NONLINEAR DYNAMICS
(2023)
Article
Physiology
Jan Lebert, Namita Ravi, Flavio H. Fenton, Jan Christoph
Summary: The analysis of electrical impulse phenomena in cardiac muscle tissue is crucial for diagnosing heart rhythm disorders and other cardiac pathophysiology. Cardiac mapping techniques visualize the spread of electrophysiological wave phenomena across the heart surface by acquiring local temporal measurements and combining them. However, challenges such as low spatial resolution, sparse measurement locations, noise, and other artifacts make it difficult to accurately visualize spatio-temporal activity.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Zexu Lin, Dmitry Kireev, Ning Liu, Shubham Gupta, Jessica LaPiano, Sofian N. N. Obaid, Zhiyuan Chen, Deji Akinwande, Igor R. R. Efimov
Summary: Heart rhythm disorders, known as arrhythmias, are a significant cause of illness and mortality. This study reports the first use of a graphene biointerface for cardiac electrophysiology, demonstrating its potential for in vivo and in vitro applications. The graphene arrays show effective electrochemical properties and have shown positive results in arrhythmia treatment.
ADVANCED MATERIALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Linhe Zhu, Yuxuan Tang, Shuling Shen
Summary: In this paper, a reaction-diffusion dynamic model with time delay is established to analyze the behavior of users in spreading rumors on the network. The Turing instability condition and different types of Turing patterns are studied. The effectiveness of the model is verified by numerical and Monte Carlo simulations, and the effects of different networks and time-delay conditions on pattern formation are studied. Furthermore, parameter identification and optimization control are carried out to make the model applicable to real situations.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Physiology
Girish S. Ramlugun, Kanchan Kulkarni, Nestor Pallares-Lupon, Bastiaan J. Boukens, Igor R. Efimov, Edward J. Vigmond, Olivier Bernus, Richard D. Walton
Summary: This study establishes an automated activation time-based analytical framework for optical mapping images of complex electrical behavior. The framework is able to accurately process high pacing frequency or irregular activity signals and provide detailed quantitative assessment and visualization.
FRONTIERS IN PHYSIOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Zhiyuan Chen, Nicolas Boyajian, Zexu Lin, Rose T. Yin, Sofian N. Obaid, Jinbi Tian, Jaclyn A. Brennan, Sheena W. Chen, Alana N. Miniovich, Leqi Lin, Yarong Qi, Xitong Liu, Igor R. Efimov, Luyao Lu
Summary: Transparent microelectrodes have emerged as a promising approach for crosstalk-free multifunctional electrical and optical biointerfacing, requiring high-performance flexible platforms for seamless integration with soft tissue systems. Silver nanowires (Ag NWs) based transparent microelectrode arrays (MEAs) and interconnects are designed to meet this demand, exhibiting high optical transparency, superior mechanical stability, low electrochemical impedance, and excellent sheet resistance. Studies demonstrate that Ag NWs MEAs enable real-time monitoring of heart rhythm during co-localized optogenetic pacing and optical mapping, showing potential for next-generation large-area multifunctional biointerfaces for interrogating complex biological systems.
ADVANCED MATERIALS TECHNOLOGIES
(2021)
Article
Physiology
Suran Galappaththige, Pras Pathmanathan, Richard A. Gray
Summary: There are challenges in evaluating clinical cardiac mapping systems due to the inability to record transmembrane potential throughout the entire heart during patient procedures. A computational modeling framework has been developed to evaluate system performance, including the localization and characterization of arrhythmogenic sources. This framework allows for performance evaluation under various conditions and involves blind comparison against computer simulations of known transmembrane potential patterns.
FRONTIERS IN PHYSIOLOGY
(2023)
Article
Cardiac & Cardiovascular Systems
Clara Herrero Martin, Alon Oved, Rasheda A. Chowdhury, Elisabeth Ullmann, Nicholas S. Peters, Anil A. Bharath, Marta Varela
Summary: EP-PINNs is a new tool that accurately estimates electrophysiological parameters and simulates action potentials. It is capable of reconstructing the spatio-temporal evolution of action potentials, predicting parameters related to action potential duration, excitability, and diffusion coefficients. It can also detect fibrosis and other pathologies associated with arrhythmias. In in vitro preparations, EP-PINNs are effective in studying the effects of anti-arrhythmic drugs on action potentials.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Mathematics
Lilly Maria Treml, Ezio Bartocci, Alessio Gizzi
Summary: The heart is made up of a complex network of billions of cells that propagate electrical signals in a synchronized manner to generate a heartbeat. Failure in synchronization can lead to life-threatening events. The modeling and analysis of electrophysiological properties in cardiac tissue remain a challenge due to the complexity of underlying nonlinear dynamics and numerous biological components involved.
Article
Engineering, Multidisciplinary
Alessio Gizzi, Maria Laura De Bellis, Marcello Vasta, Anna Pandolfi
Summary: This study describes a multiphysics model of collagen in the cornea, specifically focusing on the progressive reduction of stiffness leading to diseases such as keratoconus. By simulating a reaction-diffusion process of chemical bond degeneration, it illustrates how the mechanical weakening of intra-crosslink bonds in structural collagen can result in the typical bulging of keratoconus corneas.
JOURNAL OF ENGINEERING MATHEMATICS
(2021)
Article
Oncology
Rosalba Portuesi, Alessandro Loppini, Rosanna Mancari, Simonetta Filippi, Nicoletta Colombo
Summary: This study validates the value of inhibin B in detecting recurrences in adult-type granulosa cell tumors of the ovary and explores its role in guiding follow-up examinations and treatment strategies. Results showed that inhibin B is a sensitive and specific marker that may be used during follow-up for detection of recurrences, guiding clinicians in decision-making regarding imaging and avoiding unnecessary tests in the absence of clinical suspicion.
INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER
(2021)
Article
Astronomy & Astrophysics
R. Ruffini, R. Moradi, J. A. Rueda, L. Li, N. Sahakyan, Y-C Chen, Y. Wang, Y. Aimuratov, L. Becerra, C. L. Bianco, C. Cherubini, S. Filippi, M. Karlica, G. J. Mathews, M. Muccino, G. B. Pisani, S. S. Xue
Summary: The study suggests that long gamma-ray bursts (GRBs) have binary progenitors, with new examples showing a binary-driven hypernova consisting of a carbon-oxygen core and a neutron star companion. Spectral analysis of prototype GRBs provides insights into the characteristics and evolution of supernovae, GeV emissions, black hole masses, and their rotational energy extraction. The findings indicate the presence of GeV radiation emitted within a cone from the orbital plane and validate the BH mass-energy formula through time evolution analysis.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Materials Science, Multidisciplinary
Leonardo Molinari, Luca Gerardo-Giorda, Alessio Gizzi
Summary: A generalized, thermodynamically consistent, transverse isotropic thermo-hyperelastic constitutive model of the myocardium was proposed, filling the gap in constitutive modeling of cardiac RFCA. Numerical solutions showed better matching with current models and revealed the elliptical shape of the lesion.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS
(2022)
Review
Materials Science, Multidisciplinary
Bhavesh Patel, Alessio Gizzi, Javad Hashemi, Yousif Awakeem, Hans Gregersen, Ghassan Kassab
Summary: The gastrointestinal tract is a continuous channel in the body responsible for digestion and waste elimination. The mechanical behavior of GI tissues is crucial for proper GI function. This article provides a systematic review of biomechanical constitutive models for GI tissues and identifies the need for more advanced modeling techniques.
MATERIALS & DESIGN
(2022)
Article
Materials Science, Multidisciplinary
Anna Pandolfi, Maria Laura De Bellis, Alessio Gizzi, Marcello Vasta
Summary: This article proposes an enriched micromechanical model to study the role of collagen in eye stromal tissue. By using a more realistic chemical bond model and introducing a pseudo-chemical potential, the model provides a better understanding of conditions such as corneal bulging and tissue degradation.
MATHEMATICS AND MECHANICS OF SOLIDS
(2023)
Article
Physiology
Leonardo Molinari, Martina Zaltieri, Carlo Massaroni, Simonetta Filippi, Alessio Gizzi, Emiliano Schena
Summary: Radiofrequency catheter ablation (RFCA) is the main treatment for drug-refractory cardiac fibrillation. However, incorrect dosage of radiofrequency energy may lead to tissue damage or treatment failure. This study focuses on the effect of myocardial microstructure on thermo-electric behavior, and establishes a computational model to optimize RFCA settings.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Medicine, General & Internal
Daniele Bianchi, Cristina Falcinelli, Leonardo Molinari, Alessio Gizzi, Alberto Di Martino
Summary: Metastatic lesions in vertebrae can compromise mechanical integrity and increase fracture risk. A computational approach assessing the effect of lesion size, location, type, and shape on fracture load and patterns is critical for predicting overall mechanical response. Size, location, and type of metastasis significantly affect vertebral mechanical response, showing the importance of considering these parameters in estimating fracture risk.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Chemistry, Analytical
Daniela Lo Presti, Daniele Bianchi, Carlo Massaroni, Alessio Gizzi, Emiliano Schena
Summary: Wearables are valuable solutions for monitoring physiological parameters, especially in cardiorespiratory monitoring. A soft biosensor capable of simultaneously monitoring heart and respiratory rates addresses technical challenges in wearables and shows potential for real-time monitoring in various home settings.
Article
Biochemistry & Molecular Biology
Margherita A. G. Matarrese, Alessandro Loppini, Martina Nicoletti, Simonetta Filippi, Letizia Chiodo
Summary: The study of RNA structure is crucial in understanding RNA molecular functioning. With the flexibility of RNA, the large number of expressed RNAs, and the diverse functions they have, it is difficult to obtain structural information on the same scale as is available for proteins. In silico prediction of RNA 3D structures is particularly important to understand the relationship between structure and function, as the 3D structure plays a significant role in molecular interactions with DNA or protein complexes. The accuracy of RNA 3D structure prediction relies on a properly predicted or measured secondary structure. This paper comparatively evaluates computational tools for modeling RNA secondary structure, focusing on freely available web-server versions for more accessible use. The evaluation focuses on the performance for long sequences and aims to select the best methods for investigating long non-coding RNAs (lncRNAs), which are of special relevance due to their involvement in regulatory mechanisms.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Engineering, Biomedical
Alessandro Barone, Domenico Grieco, Alessio Gizzi, Leonardo Molinari, Martina Zaltieri, Carlo Massaroni, Alessandro Loppini, Emiliano Schena, Edoardo Bressi, Ermenegildo de Ruvo, Leonardo Calo, Simonetta Filippi
Summary: This study evaluated the optimal setup for His bundle pacing (HBP) therapy in terms of electrode placement and pacing protocol for achieving superior electrical synchrony in the case of complete His-Purkinje block and left bundle branch block. The results showed that perpendicular placement of the electrode was the most effective in restoring the physiological function of the His-Purkinje system, and increasing the electrode helix length could improve the resynchronization even with low-energy pacing protocols.
MEDICAL ENGINEERING & PHYSICS
(2022)
Article
Astronomy & Astrophysics
Y. Aimuratov, L. M. Becerra, C. L. Bianco, C. Cherubini, M. Della Valle, S. Filippi, Liang Li, R. Moradi, F. Rastegarnia, J. A. Rueda, R. Ruffini, N. Sahakyan, Y. Wang, S. R. Zhang
Summary: This article focuses on the observations of supernovae occurring after long gamma-ray bursts. The binary-driven hypernova model is used to explain the origin and evolution of these supernovae. Through multiwavelength observations and theoretical analysis, several new events related to supernovae and gamma-ray bursts have been discovered.
ASTROPHYSICAL JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
D. Lo Presti, A. Dimo, L. Zoboli, D. Bianchi, C. Massaroni, V. Altomare, A. Grasso, C. M. Oddo, A. Gizzi, E. Schena
Summary: This study introduces an innovative tactile probe for breast cancer identification, utilizing fiber Bragg grating (FBG) technology combined with 3D printing. The sensing unit design was optimized through analysis, fabrication, and characterization, leading to the development of a prototype integrating multiple sensing units. Promising results were obtained through tests on silicone samples with different hardness and a phantom mimicking early stage breast tumor, providing guidance for further optimization of the probe design.
IEEE SENSORS JOURNAL
(2023)
Proceedings Paper
Computer Science, Theory & Methods
Nicole Luchetti, Letizia Chiodo, Alessandro Loppini, Simonetta Filippi
Summary: Electrophysiological modeling is a fundamental tool to understand the behavior of excitable cells, but the determination of model parameters is crucial. This study demonstrates how multiscale simulation tools and molecular modeling can provide reliable estimation of ion channel conductance in cell modeling.
PROCEEDINGS OF 2022 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR INDUSTRY 4.0 & IOT (IEEE METROIND4.0&IOT)
(2022)
Article
Engineering, Multidisciplinary
Akshay J. Thomas, Mateusz Jaszczuk, Eduardo Barocio, Gourab Ghosh, Ilias Bilionis, R. Byron Pipes
Summary: We propose a physics-guided transfer learning approach to predict the thermal conductivity of additively manufactured short-fiber reinforced polymers using micro-structural characteristics obtained from tensile tests. A Bayesian framework is developed to transfer the thermal conductivity properties across different extrusion deposition additive manufacturing systems. The experimental results demonstrate the effectiveness and reliability of our method in accounting for epistemic and aleatory uncertainties.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis
Summary: In this study, deep learning and artificial intelligence were used to discover a mathematical model for the progression of Alzheimer's disease. By analyzing longitudinal tau positron emission tomography data, a reaction-diffusion type partial differential equation for tau protein misfolding and spreading was discovered. The results showed different misfolding models for Alzheimer's and healthy control groups, indicating faster misfolding in Alzheimer's group. The study provides a foundation for early diagnosis and treatment of Alzheimer's disease and other misfolding-protein based neurodegenerative disorders using image-based technologies.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jonghyuk Baek, Jiun-Shyan Chen
Summary: This paper introduces an improved neural network-enhanced reproducing kernel particle method for modeling the localization of brittle fractures. By adding a neural network approximation to the background reproducing kernel approximation, the method allows for the automatic location and insertion of discontinuities in the function space, enhancing the modeling effectiveness. The proposed method uses an energy-based loss function for optimization and regularizes the approximation results through constraints on the spatial gradient of the parametric coordinates, ensuring convergence.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Bodhinanda Chandra, Ryota Hashimoto, Shinnosuke Matsumi, Ken Kamrin, Kenichi Soga
Summary: This paper proposes new and robust stabilization strategies for accurately modeling incompressible fluid flow problems in the material point method (MPM). The proposed approach adopts a monolithic displacement-pressure formulation and integrates two stabilization strategies to ensure stability. The effectiveness of the proposed method is validated through benchmark cases and real-world scenarios involving violent free-surface fluid motion.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Chao Peng, Alessandro Tasora, Dario Fusai, Dario Mangoni
Summary: This article discusses the importance of the tangent stiffness matrix of constraints in multibody systems and provides a general formulation based on quaternion parametrization. The article also presents the analytical expression of the tangent stiffness matrix derived through linearization. Examples demonstrate the positive effect of this additional stiffness term on static and eigenvalue analyses.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Thibaut Vadcard, Fabrice Thouverez, Alain Batailly
Summary: This contribution presents a methodology for detecting isolated branches of periodic solutions to nonlinear mechanical equations. The method combines harmonic balance method-based solving procedure with the Melnikov energy principle. It is able to predict the location of isolated branches of solutions near families of autonomous periodic solutions. The relevance and accuracy of this methodology are demonstrated through academic and industrial applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Weisheng Zhang, Yue Wang, Sung-Kie Youn, Xu Guo
Summary: This study proposes a sketch-guided topology optimization approach based on machine learning, which incorporates computer sketches as constraint functions to improve the efficiency of computer-aided structural design models and meet the design intention and requirements of designers.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Leilei Chen, Zhongwang Wang, Haojie Lian, Yujing Ma, Zhuxuan Meng, Pei Li, Chensen Ding, Stephane P. A. Bordas
Summary: This paper presents a model order reduction method for electromagnetic boundary element analysis and extends it to computer-aided design integrated shape optimization of multi-frequency electromagnetic scattering problems. The proposed method utilizes a series expansion technique and the second-order Arnoldi procedure to reduce the order of original systems. It also employs the isogeometric boundary element method to ensure geometric exactness and avoid re-meshing during shape optimization. The Grey Wolf Optimization-Artificial Neural Network is used as a surrogate model for shape optimization, with radar cross section as the objective function.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
C. Pilloton, P. N. Sun, X. Zhang, A. Colagrossi
Summary: This paper investigates the smoothed particle hydrodynamics (SPH) simulations of violent sloshing flows and discusses the impact of volume conservation errors on the simulation results. Different techniques are used to directly measure the particles' volumes and stabilization terms are introduced to control the errors. Experimental comparisons demonstrate the effectiveness of the numerical techniques.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Ye Lu, Weidong Zhu
Summary: This work presents a novel global digital image correlation (DIC) method based on a convolution finite element (C-FE) approximation. The C-FE based DIC provides highly smooth and accurate displacement and strain results with the same element size as the usual finite element (FE) based DIC. The proposed method's formulation and implementation, as well as the controlling parameters, have been discussed in detail. The C-FE method outperformed the FE method in all tested examples, demonstrating its potential for highly smooth, accurate, and robust DIC analysis.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Mojtaba Ghasemi, Mohsen Zare, Amir Zahedi, Pavel Trojovsky, Laith Abualigah, Eva Trojovska
Summary: This paper introduces Lung performance-based optimization (LPO), a novel algorithm that draws inspiration from the efficient oxygen exchange in the lungs. Through experiments and comparisons with contemporary algorithms, LPO demonstrates its effectiveness in solving complex optimization problems and shows potential for a wide range of applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jingyu Hu, Yang Liu, Huixin Huang, Shutian Liu
Summary: In this study, a new topology optimization method is proposed for structures with embedded components, considering the tension/compression asymmetric interface stress constraint. The method optimizes the topology of the host structure and the layout of embedded components simultaneously, and a new interpolation model is developed to determine interface layers between the host structure and embedded components.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Qiang Liu, Wei Zhu, Xiyu Jia, Feng Ma, Jun Wen, Yixiong Wu, Kuangqi Chen, Zhenhai Zhang, Shuang Wang
Summary: In this study, a multiscale and nonlinear turbulence characteristic extraction model using a graph neural network was designed. This model can directly compute turbulence data without resorting to simplified formulas. Experimental results demonstrate that the model has high computational performance in turbulence calculation.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jacinto Ulloa, Geert Degrande, Jose E. Andrade, Stijn Francois
Summary: This paper presents a multi-temporal formulation for simulating elastoplastic solids under cyclic loading. The proper generalized decomposition (PGD) is leveraged to decompose the displacements into multiple time scales, separating the spatial and intra-cyclic dependence from the inter-cyclic variation, thereby reducing computational burden.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma, Tim Besard, Prakitr Srisuma, Tim Gymnich, Adam R. Gerlach, Alan Edelman, George Barbastathis, Richard D. Braatz, Christopher Rackauckas
Summary: This article presents a high-performance vendor-agnostic method for massively parallel solving of ordinary and stochastic differential equations on GPUs. The method integrates with a popular differential equation solver library and achieves state-of-the-art performance compared to hand-optimized kernels.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
