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Uncertainty Quantification of Fiber Orientation and Epicardial Activation

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Uncertainty Quantification of Fiber Orientation and Epicardi...

Computers in Cardiology (CinC)

作者： Lindsay C Rupp Anna Busatto Jake A Bergquist Karli Gillette Akil Narayan Gernot Plank Rob S MacLeod Scientific Computing and Imaging Institute University of Utah SLC UT USA Nora Eccles Cardiovascular Research and Training Institute University of Utah SLC UT USA Department of Biomedical Engineering University of Utah SLC UT USA Institute of Biophysics Medical University of Graz Graz Austria Department of Mathematics University of Utah SLC UT USA

Predictive models and simulations of cardiac function require accurate representations of anatomy, often to the scale of local myocardial fiber structure. However, acquiring this information in a patient-specific manner is challenging. Moreover, the impact of physiological variability in fiber orientation on simulations of cardiac activation is poorly understood. To explore these effects, we implemented bi-ventricular activation simulations using rule-based fiber algorithms and robust uncertainty quantification techniques to generate detailed maps of model variability. Specifically, we utilized polynomial chaos expansion, enabling efficient exploration with reduced computational demand through an emulator function approximating the underlying forward model. Our study focused on examining the epicardial activation sequences of the heart in response to six stimuli locations and five metrics of activation. Our findings revealed that physiological variability in fiber orientation does not significantly affect the location of activation features, but it does impact the overall spread of activation. We observed low variability near the earliest activation sites, but high variability across the rest of the epicardial surface. We conclude that the level of accuracy of myocardial fiber orientation required for simulation depends on the specific goals of the model and the related research or clinical goals.

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Neural Networks for Fault diagnosis in Electrical Machine

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Neural Networks for Fault diagnosis in Electrical Machine

Intelligent Technologies (ACOIT), Asian Conference on

作者： R. Vinston Raja J. Raja Sreenivasulu Gogula Atul Katiyar T. Thilagam V. S. Bhagavan Department of Computational Intelligence Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering (Data Science) Vardhaman College of Engineering Hyderabad Telangana India Department of Electrical Engineering Mahatma Jyotiba Phule Rohilkhand University Bareilly Uttar Pradesh India Department of Science and Engineering S.A Engineering College Chennai Tamil Nadu India Department of Mathematics Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

Finding electrical equipment problems quickly is essential for minimising downtime and ensuring ongoing functioning. When it comes to early defect identification, traditional methods like human inspection or sensor-based surveillance might not cut it. Another alternative to employing machine learning algorithms to analyse complex patterns in sensor data is neural networks. With an emphasis on motor drives, this article lays forth a method for identifying electrical equipment issues using neural networks. The network has been trained to identify various issues, such as imbalanced rotors, broken stator windings, and failing bearings, by examining historical data. The trial findings prove that the suggested method may effectively find issues, make things more reliable, and cut down on maintenance expenses.

关键词： Fault diagnosis Motor drives Machine learning algorithms Surveillance Neural networks Stator windings Rotors Machine learning Maintenance Predictive maintenance

Amplitude Expansion Phase Field Crystal (APFC) Modeling based Efficient Dislocation Simulations using Fourier Pseudospectral Method

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arXiv 2024年

作者： Wei, Xinyi Wang, Yangshuai Jiang, Kai Zhang, Lei School of Mathematical Sciences Institute of Natural Sciences and MOE-LSC Shanghai Jiao Tong University Shanghai200240 China Department of Mathematics Faculty of Science National University of Singapore 10 Lower Kent Ridge Road Singapore Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Crystalline defects play a critical role in determining the properties of crystalline solids, underscoring the need for accurate computational methods to study them. Lattice deformation in dislocation simulations, which involves changes in atomic positions, can be described either microscopically by specific atomic configurations or macroscopically by continuum elasticity, each with inherent limitations. The complex amplitude expansion of the phase field crystal (APFC) model provides a mesoscopic approach that bridges these scales. In this paper, we introduce a Fourier pseudospectral method for efficiently solving the APFC model in the context of crystalline defect simulations. This study marks the first application of the Fourier pseudospectral method to the APFC model. The method fully exploits the system’s periodicity and facilitates the implementation of periodic boundary conditions, thanks to its high accuracy and computational efficiency. Numerical experiments conducted on two-dimensional triangular lattices and three-dimensional body-centered cubic lattices for edge dislocation geometry optimization have produced strain field images that align well with by continuum elasticity predictions. The findings demonstrate the potential of the APFC model to accurately capture the complex strain fields associated with dislocations at the mesoscopic scales, a key step toward modeling more intricate crystalline defect structures and dynamics. © 2024, CC BY.

关键词： Edge dislocations

MatterChat: A Multi-Modal LLM for Material Science

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arXiv 2025年

作者： Tang, Yingheng Xu, Wenbin Cao, Jie Gao, Weilu Farrell, Steven Erichson, Benjamin Mahoney, Michael W. Nonaka, Andy Yao, Zhi Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA United States National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory BerkeleyCA United States NSF National AI Institute for Student-AI Teaming University of Colorado at Boulder Boulder United States Department of Electrical and Computer Engineering The University of Utah Salt Lake CityUT United States Scientific Data Division Lawrence Berkeley National Laboratory BerkeleyCA United States International Computer Science Institute BerkeleyCA United States Department of Statistics University of California at Berkeley BerkeleyCA United States

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics, and beyond. Integrating material structure data with language-based information through multi-modal large language models (LLMs) offers great potential to support these efforts by enhancing human–AI interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multi-modal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat employs a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat significantly improves performance in material property prediction and human-AI interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis. © 2025, CC BY.

关键词： Structure (composition)

Multiple-distribution-function finite-difference lattice Boltzmann method for incompressible Navier-Stokes equation

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arXiv 2023年

作者： Chen, Xinmeng Chai, Zhenhua Zhao, Yong Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China School of Mathematics and Statistics Changsha University of Science and Technology Hunan Changsha410114 China

In this paper, a multiple-distribution-function finite-difference lattice Boltzmann method (MDF-FDLBM) is proposed for the convection-diffusion system based incompressible Navier-Stokes equations (NSEs). By Chapman Enskog analysis, the convection-diffusion system based incompressible NSEs can be recovered from MDF-FDLBM. Some quantities, including the velocity gradient, velocity divergence, strain rate tensor, shear stress and vorticity, can be computed locally by the first-order moment of the non-equilibrium distribution function. Through the von Neumann analysis, we conduct the stability analysis for the MDF-FDLBM and incompressible finite-difference lattice Boltzmann method (IFDLBM). It is found that the IFDLBM will be more stable than that of MDF-FDLBM with small kinematic viscosity, and the MDF-FDLBM will be more stable than that of IFDLBM with large Courant-Friedrichs-Lewy condition number. Finally, some simulations are conducted to validate the MDF-FDLBM. The results agree well with the analytical solutions and previous results. Through the numerical testing, we find that the MDF-FDLBM has a second-order convergence rate in space and time. The MDF-FDLBMcombined with non-uniform grid also works well. Meanwhile, compared with IFDLBM, it can be found that MDF-FDLBM offers higher accuracy and computational efficiency, reducing computation time by more than 36%. © 2023, CC BY.

关键词： Distribution functions

Numerical Simulation of Power-Law Fluid Flow in a Trapezoidal Cavity using the Incompressible Finite-Difference Lattice Boltzmann Method

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arXiv 2023年

In this paper, a numerical investigation of power-law fluid flow in the trapezoidal cavity has been conducted by incompressible finite-difference lattice Boltzmann method (IFDLBM). By designing the equilibrium distribution function, the Navier-Stokes equations (NSEs) can be recovered exactly. Through the coordinate transformation method, the body-fitted grid in physical region is transformed into a uniform grid in computational region. The effect of Reynolds (Re) number, the power-law index n and the vertical angle θ on the trapezoidal cavity are investigated. According to the numerical results, we come to some conclusions. For low Re number Re = 100, it can be found that the behavior of power-law fluid flow becomes more complicated with the increase of n. And as vertical angle θ decreases, the flow becomes smooth and the number of vortices decreases. For high Re numbers, the flow development becomes more complex, the number and strength of vortices increase. If the Reynolds number increases further, the power-law fluid will changes from steady flow to periodic flow and then to turbulent flow. For the steady flow, the lager the θ, the more complicated the vortices. And the critical Re number from steady to periodic state decreases with the decrease of power-law index n. © 2023, CC BY.

关键词： Reynolds number

A Robust Remote Client Password Authentication Technique for Smart Cities E-Governance Applications

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A Robust Remote Client Password Authentication Technique for...

2023 IEEE International Conference on Communications, computing, Cybersecurity and Informatics, CCCI 2023

作者： Obaidat, Mohammad S. Meshram, Chandrashekhar Kartikey, Deepak Hsiao, Kuei-Fang Imoize, Agbotiname Lucky Barve, Sharad Kumar Abdullah Ii School of Information Technology The University of Jordan Amman11942 Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China School of Computing Srm University Department of Computational Intelligence TN Kattankulathur603203 India School of Engineering The Amity University UP Noida201301 India Jayawanti Haksar Government Post Graduation College College of Barkatullah University Department of Post Graduation Studies and Research in Mathematics M.P. Betul460001 India S.S.P. Govt. College Waraseoni Department of Mathematics M.P. Balaghat India University of Texas-Permian Basin Computer Science Department OdessaTX79762 United States University of Lagos Faculty of Engineering Department of Electrical and Electronics Engineering Lagos100213 Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany Pandit S. N. Shukla University Shahdol Department of Mathematics Madhya Pradesh Shahdol484001 India

ISBN: (纸本)9798350302561

Smart cities are fast proliferating the global space in recent times. In order to achieve the envisioned next-generation cities, the smart city paradigm aspires to develop a completely integrated network-based infrastructure. With the development of innovative smart cities, ICT-based e-governance has made it possible for services to be delivered intelligently and interactively via online platforms. However, the communication between government agencies and other stakeholders in the smart city ecosystem is through open channels, which poses serious security concerns. In order to address this problem, this work proposes a robust remote client password authentication technique for e-governance applications in smart cities. The proposed authentication technique is lightweight, resistant to several attacks, and achieves low computational overhead. © 2023 IEEE.

关键词： Smart cards

Stability implies robust convergence of a class of preconditioned parallel-in-time iterative algorithms

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arXiv 2021年

作者： Wu, Shu-Lin Zhou, Tao Zhou, Zhi School of Mathematics and Statistics Northeast Normal University Changchun130024 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing AMSS Chinese Academy of Sciences Beijing100190 China Department of Applied Mathematics Hong Kong Polytechnic University Kowloon Hong Kong

Solving evolutionary equations in a parallel-in-time manner is an attractive topic and many algorithms are proposed in recent two decades. The algorithm based on the block α-circulant preconditioning technique has shown promising advantages, especially for wave propagation problems. By fast Fourier transform for factorizing the involved circulant matrices, the preconditioned iteration can be computed efficiently via the so-called diagonalization technique, which yields a direct parallel implementation across all time levels. In recent years, considerable efforts have been devoted to exploring the convergence of the preconditioned iteration by studying the spectral radius of the iteration matrix, and this leads to many case-by-case studies depending on the used time-integrator. In this paper, we propose a unified convergence analysis for the algorithm applied to u0 + Au = f, where σ(A) ⊂ C+ with σ(A) being the spectrum of A ∈ Cm×m. For any one-step method (such as the Runge-Kutta methods) with stability function R(z), we prove that the decay rate of the global error is bounded by α/(1 - α), provided the method is stable, i.e., maxλ∈σ(A) |R(∆tλ)| ≤ 1. For any linear multistep method, such a bound becomes cα/(1 - cα), where c ≥ 1 is a constant specified by the multistep method itself. Our proof only relies on the stability of the time-integrator and the estimate is independent of the step size ∆t and the spectrum σ(A). © 2021, CC0.

关键词： Stability

Efficacy of reduced order source terms for a coupled wave-circulation model in the Gulf of Mexico

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arXiv 2023年

作者： Loveland, Mark Meixner, Jessica Valseth, Eirik Dawson, Clint Oden Institute for Computational Engineering and Sciences University of Texas at Austin Oden Institute for Computational Engineering and Sciences The University of Texas at Austin 201 E. 24th St. AustinTX78712 United States College ParkMD United States The Department of Data Science The Norwegian University of Life Science Drøbakveien 31 Ås1433 Norway Department of Scientific Computing and Numerical Analysis Simula Research Laboratory Kristian Augusts gate 23 Oslo0164 Norway

During hurricanes, coupled wave-circulation models are critical tools for public safety. The standard approach is to use a high fidelity circulation model coupled with a wave model that uses the most advanced source terms. As a result, the models can be computationally expensive and so this study investigates the potential consequences of using simplified (reduced order) source terms within the wave model component of the coupled wave-circulation model. The trade-off between run time and accuracy with respect to observations is quantified for a set of two storms that impacted the Gulf of Mexico, Hurricane Ike and Hurricane Ida. Water surface elevations as well as wave statistics (significant wave height, peak period, and mean wave direction) are compared to observations. The usage of the reduced order source terms yielded significant savings in computational cost. Additionally, relatively low amounts of additional error with respect to observations during the simulations with reduced order source terms are observed in our computational experiments. However, large changes in global model outputs of the wave statistics were observed based on the choice of source terms particularly near the track of each hurricane. © 2023, CC BY.

关键词： Hurricanes