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For problems involving large deformations of thin structures, simulating fluid-structure interaction (FSI) remains challenging largely due to the need to balance computational feasibility, efficiency, and solution accuracy. Overlapping…

Computational Engineering, Finance, and Science · Computer Science 2020-03-18 Maximilian Balmus , Andre Massing , Johan Hoffman , Reza Razavi , David Nordsletten

Interface problems depict many fundamental physical phenomena and widely apply in the engineering. However, it is challenging to develop efficient fully decoupled numerical methods for solving degenerate interface problems in which the…

Numerical Analysis · Mathematics 2023-06-06 Chen Fan , Zhiyue Zhang

In this paper, a direct finite element method is proposed for solving interface problems on unfitted meshes. This new method treats the two interface conditions as an $H^{\frac12}(\Gamma)\times H^{-\frac12}(\Gamma)$ pair for the mutual…

Numerical Analysis · Mathematics 2025-08-19 Jun Hu , Limin Ma

Three-dimensional concrete printing (3DCP) has gained a lot of popularity in recent years. According to many, 3DCP is set to revolutionize the construction industry: yielding unparalleled aesthetics, better quality control, lower cost, and…

Computational Physics · Physics 2020-09-16 Gieljan Vantyghem , Ticho Ooms , Wouter De Corte

We propose and analyze a domain decomposition solver for the biharmonic problem. The problem is discretized in a conforming way using multi-patch Isogeometric Analysis. As first step, we discuss the setup of a sufficiently smooth…

Numerical Analysis · Mathematics 2025-11-10 Stefan Takacs

This work illustrates the possibility to apply the Fast Fourier Transformation to obtain the integrals of the Boundary Element Method (BEM) on arbitrary shapes. The procedure is inspired by the technique used with great success within the…

Computational Physics · Physics 2018-09-05 Justus Benad

A novel method for complex fluid-structure interaction (FSI) involving large structural deformation and motion is proposed. The new approach is based on a hybrid fluid formulation that combines the advantages of purely Eulerian (fixed-grid)…

Computational Engineering, Finance, and Science · Computer Science 2018-08-02 Benedikt Schott , Christoph Ager , Wolfgang A. Wall

Notched components are commonly used in engineering structures, where stress concentration may easily lead to crack initiation and development. The main goal of this work is to develop a simple numerical method to predict the structural…

Numerical Analysis · Mathematics 2021-12-14 Kailei Wang , Baoying Shen , Mingjing Li , Leiting Dong , Satya N. Atluri

One of the key aspects governing the mechanical performance of composite materials is debonding: the local separation of reinforcing constituents from matrix when the interfacial strength is exceeded. In this contribution, two strategies to…

Materials Science · Physics 2009-08-12 P. Gruber , J. Zeman , J. Kruis , M. Sejnoha

Boolean tensor has been broadly utilized in representing high dimensional logical data collected on spatial, temporal and/or other relational domains. Boolean Tensor Decomposition (BTD) factorizes a binary tensor into the Boolean sum of…

Machine Learning · Computer Science 2020-10-28 Changlin Wan , Wennan Chang , Tong Zhao , Sha Cao , Chi Zhang

The most popular methods for self-consistent simulation of fields interacting with charged species is using finite difference time domain (FDTD) methods together with Newton's laws of motion to evolve locations and velocities of particles.…

Computational Physics · Physics 2022-04-29 Zane D. Crawford , O. H. Ramachandran , Scott O'Connor , Daniel L. Dault , John Luginsland , B. Shanker

Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells,…

Numerical Analysis · Mathematics 2024-07-08 Adi Ditkowski , Anne Le Blanc , Chi-Wang Shu

Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells,…

Numerical Analysis · Mathematics 2024-05-21 Adi Ditkowski , Anne Le Blanc , Chi-Wang Shu

Signal decomposition is an effective tool to assist the identification of modal information in time-domain signals. Two signal decomposition methods, including the empirical wavelet transform (EWT) and Fourier decomposition method (FDM),…

Signal Processing · Electrical Eng. & Systems 2023-01-31 Wei Zhou , Zhongren Feng , Y. F. Xu , Xiongjiang Wang , Hao Lv

In the design of offshore jacket foundations, fatigue life is crucial. Post-weld treatment has been proposed to enhance the fatigue performance of welded joints, where particularly high-frequency mechanical impact (HFMI) treatment has been…

Computer Vision and Pattern Recognition · Computer Science 2023-07-31 Anders Faarbæk Mikkelstrup , Morten Kristiansen

Although FFT-based methods are renowned for their numerical efficiency and stability, traditional discretizations fail to capture material interfaces that are not aligned with the grid, resulting in suboptimal accuracy. To address this…

Computational Engineering, Finance, and Science · Computer Science 2026-05-21 Flavia Gehrig , Matti Schneider

We propose an energy-stable parametric finite element method (ES-PFEM) for simulating solid-state dewetting of thin films in two dimensions via a sharp-interface model, which is governed by surface diffusion and contact line (point)…

Numerical Analysis · Mathematics 2020-06-08 Quan Zhao , Wei Jiang , Weizhu Bao

Consciousness about power consumption at the appliance level can assist user in promoting energy efficiency in households. In this paper, a superior non-intrusive appliance recognition method that can provide particular consumption…

Computers and Society · Computer Science 2020-09-28 Yassine Himeur , Abdullah Alsalemi , Faycal Bensaali , Abbes Amira

Federated Learning (FL) presents significant potential for collaborative optimization without data sharing. Since synthetic data is sent to the server, leveraging the popular concept of dataset distillation, this FL framework protects real…

Machine Learning · Computer Science 2025-10-29 Haozhi Shi , Weiying Xie , Hangyu Ye , Daixun Li , Jitao Ma , Yunsong Li , Leyuan Fang

Federated Learning (FL) enables multiple resource-constrained edge devices with varying levels of heterogeneity to collaboratively train a global model. However, devices with limited capacity can create bottlenecks and slow down model…

Machine Learning · Computer Science 2025-04-08 Afsaneh Mahanipour , Hana Khamfroush