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In this work, we propose a joint collaboration-compression framework for sequential estimation of a random vector parameter in a resource constrained wireless sensor network (WSN). Specifically, we propose a framework where the local…

Signal Processing · Electrical Eng. & Systems 2021-09-08 Xiancheng Cheng , Prashant Khanduri , Boxiao Chen , Pramod K. Varshney

This article addresses the research question if and how the finite cell method, an embedded domain finite element method of high order, may be used in the simulation of metal deposition to harvest its computational efficiency. This…

Numerical Analysis · Mathematics 2018-09-26 Ali Özcan , Stefan Kollmannsberger , John N. Jomo , Ernst Rank

Thermomechanical stress induced by through-silicon vias (TSVs) plays an important role in the performance and reliability analysis of 2.5D/3D ICs. While the finite element method (FEM) adopted by commercial software can provide accurate…

Computational Engineering, Finance, and Science · Computer Science 2024-11-20 Tianxiang Zhu , Qipan Wang , Yibo Lin , Runsheng Wang , Ru Huang

We introduce a hyperreduced reduced basis element method for model reduction of parameterized, component-based systems in continuum mechanics governed by nonlinear partial differential equations. In the offline phase, the method constructs,…

Numerical Analysis · Mathematics 2025-01-06 Mehran Ebrahimi , Masayuki Yano

This paper presents a reduced order approach for transient modeling of multiple moving objects in nonlinear crossflows. The Proper Orthogonal Decomposition method and the Galerkin projection are used to construct a reduced version of the…

Fluid Dynamics · Physics 2021-06-07 My Ha Dao

Elastomeric mechanical metamaterials exhibit unconventional behaviour, emerging from their microstructures often deforming in a highly nonlinear and unstable manner. Such microstructural pattern transformations lead to non-local behaviour…

Soft Condensed Matter · Physics 2025-02-18 S. O. Sperling , T. Guo , R. H. J. Peerlings , V. G. Kouznetsova , M. G. D. Geers , O. Rokoš

Sampling is a fundamental aspect of any implementation of compressive sensing. Typically, the choice of sampling method is guided by the reconstruction basis. However, this approach can be problematic with respect to certain hardware…

Signal Processing · Electrical Eng. & Systems 2019-06-24 Elin Farnell , Henry Kvinge , John P. Dixon , Julia R. Dupuis , Michael Kirby , Chris Peterson , Elizabeth C. Schundler , Christian W. Smith

This paper introduces the concept of abstracted model reduction: a framework to improve the tractability of structure-preserving methods for the complexity reduction of interconnected system models. To effectively reduce high-order,…

Systems and Control · Electrical Eng. & Systems 2024-11-21 Luuk Poort , Lars A. L. Janssen , Bart Besselink , Rob H. B. Fey , Nathan van de Wouw

The authors have shown in previous contributions that reduced order modeling with optimal cubature applied to finite element square (FE2) techniques results in a reliable and affordable multiscale approach, the HPR-FE2 technique. Such…

Numerical Analysis · Mathematics 2021-07-20 Marcelo Raschi , Oriol Lloberas-Valls , Alfredo Huespe , Javier Oliver

This paper deals with the development of a Reduced-Order Model (ROM) to investigate haemodynamics in cardiovascular applications. It employs the use of Proper Orthogonal Decomposition (POD) for the computation of the basis functions and the…

Numerical Analysis · Mathematics 2025-01-24 Pierfrancesco Siena , Pasquale Claudio Africa , Michele Girfoglio , Gianluigi Rozza

Predictive high-fidelity finite element simulations of human cardiac mechanics co\-mmon\-ly require a large number of structural degrees of freedom. Additionally, these models are often coupled with lumped-parameter models of hemodynamics.…

Computational Engineering, Finance, and Science · Computer Science 2020-02-18 Martin R. Pfaller , Maria Cruz Varona , Johannes Lang , Cristóbal Bertoglio , Wolfgang A. Wall

Due to the substantial scale of Large Language Models (LLMs), the direct application of conventional compression methodologies proves impractical. The computational demands associated with even minimal gradient updates present challenges,…

Machine Learning · Computer Science 2023-12-13 Arnav Chavan , Nahush Lele , Deepak Gupta

A novel probabilistic approach for the design of mechanical structures with friction interfaces is proposed. The objective function is defined as the probability that a specified performance measure of the forced vibration response is…

Computational Engineering, Finance, and Science · Computer Science 2021-01-01 Malte Krack , Sebastian Tatzko , Lars Panning-von Scheidt , Jörg Wallaschek

Multiple model reduction techniques have been proposed to tackle linear and non linear problems. Intrusive model order reduction techniques exhibit high accuracy levels, however, they are rarely used as a standalone industrial tool, because…

Computational Engineering, Finance, and Science · Computer Science 2025-04-10 Mikhael Tannous , Chady Ghnatios , Eivind Fonn , Trond Kvamsdal , Francisco Chinesta

Tactile perception is key to dexterous manipulation, yet simulating high-resolution elastomer deformation remains computationally prohibitive. Finite element methods (FEM) deliver high fidelity but demand costly remeshing, while Material…

Robotics · Computer Science 2026-05-07 Yuhu Guo , Zhikai Shen , Jiasheng Qu , Chenghao Qian , Yuming Huang , Bin Chen , Guoxing Fang

Linear kinetic transport equations play a critical role in optical tomography, radiative transfer and neutron transport. The fundamental difficulty hampering their efficient and accurate numerical resolution lies in the high dimensionality…

Numerical Analysis · Mathematics 2021-12-07 Zhichao Peng , Yanlai Chen , Yingda Cheng , Fengyan Li

While reduced-order models (ROMs) have been popular for efficiently solving large systems of differential equations, the stability of reduced models over long-time integration is of present challenges. We present a greedy approach for ROM…

Numerical Analysis · Mathematics 2018-03-20 Babak Maboudi Afkham , Jan S. Hesthaven

This paper proposes a new approach for the calibration of material parameters in local elastoplastic constitutive models. The calibration is posed as a constrained optimization problem, where the constitutive model evolution equations for a…

Computational Engineering, Finance, and Science · Computer Science 2025-05-09 Ryan Yan , D. Thomas Seidl , Reese E. Jones , Panayiotis Papadopoulos

We consider the problem of jointly modeling and clustering populations of tensors by introducing a high-dimensional tensor mixture model with heterogeneous covariances. To effectively tackle the high dimensionality of tensor objects, we…

Methodology · Statistics 2024-11-21 Biao Cai , Jingfei Zhang , Will Wei Sun

In this paper we propose the first better than second order accurate method in space and time for the numerical solution of the resistive relativistic magnetohydrodynamics (RRMHD) equations on unstructured meshes in multiple space…

General Relativity and Quantum Cosmology · Physics 2015-05-13 Michael Dumbser , Olindo Zanotti
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