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Related papers: Data-Driven, Parameterized Reduced-order Models fo…

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POD-DL-ROMs have been recently proposed as an extremely versatile strategy to build accurate and reliable reduced order models (ROMs) for nonlinear parametrized partial differential equations, combining (i) a preliminary dimensionality…

Numerical Analysis · Mathematics 2023-05-09 Simone Brivio , Stefania Fresca , Nicola Rares Franco , Andrea Manzoni

Laser Powder Bed Fusion (L-PBF) is a widely adopted additive manufacturing process for fabricating complex metallic parts layer by layer. Effective thermal management is essential to ensure part quality and structural integrity, as thermal…

Systems and Control · Electrical Eng. & Systems 2025-09-22 Yukta Pareek , Abdul Malik Al Mardhouf Al Saadi , Amrita Basak , Satadru Dey

In course of this work, we examine the process of plastic profile extrusion, where a polymer melt is shaped inside the so-called extrusion die and fixed in its shape by solidification in the downstream calibration unit. More precise, we…

Numerical Analysis · Mathematics 2022-09-08 Daniel Hilger , Norbert Hosters

Laser powder bed fusion (L-PBF) is a widely recognized additive manufacturing technology for producing intricate metal components with exceptional accuracy. A key challenge in L-PBF is the formation of complex microstructures affecting…

Computational Engineering, Finance, and Science · Computer Science 2025-06-30 Augustine Twumasi , Prokash Chandra Roy , Zixun Li , Soumya Shouvik Bhattacharjee , Zhengtao Gan

Traditional reduced order modeling techniques such as the reduced basis (RB) method (relying, e.g., on proper orthogonal decomposition (POD)) suffer from severe limitations when dealing with nonlinear time-dependent parametrized PDEs,…

Numerical Analysis · Mathematics 2020-01-14 Stefania Fresca , Luca Dede , Andrea Manzoni

Deep learning-based reduced order models (DL-ROMs) have been recently proposed to overcome common limitations shared by conventional ROMs - built, e.g., exclusively through proper orthogonal decomposition (POD) - when applied to nonlinear…

Numerical Analysis · Mathematics 2022-01-26 Federico Fatone , Stefania Fresca , Andrea Manzoni

Projection-based model reduction is among the most widely adopted methods for constructing parametric Reduced-Order Models (ROM). Utilizing the snapshot data from solving full-order governing equations, the Proper Orthogonal Decomposition…

Machine Learning · Statistics 2025-09-16 Xiao Liu , Jingyi Feng , Xinchao Liu

Directed energy deposition (DED) is a promising metal additive manufacturing technology capable of 3D printing metal parts with complex geometries at lower cost compared to traditional manufacturing. The technology is most effective when…

Numerical Analysis · Mathematics 2023-12-01 Aaron L. Brown , Eric B. Chin , Youngsoo Choi , Saad A. Khairallah , Joseph T. McKeown

We apply reduced-order modeling (ROM) techniques to single-phase flow in faulted porous media, accounting for changing rock properties and fault geometry variations using a radial basis function mesh deformation method. This approach…

Numerical Analysis · Mathematics 2024-03-07 Enrico Ballini , Luca Formaggia , Alessio Fumagalli , Anna Scotti , Paolo Zunino

Additive manufacturing is a free-form manufacturing technique in which parts are built in a layer-by-layer manner. Laser powder bed fusion is one of the popular techniques used to fabricate metal parts. However, it induces residual stress…

Computational Engineering, Finance, and Science · Computer Science 2021-05-07 Takao Miki , Takayuki Yamada

Cardio-mechanical models can be used to support clinical decision-making. Unfortunately, the substantial computational effort involved in many cardiac models hinders their application in the clinic, despite the fact that they may provide…

Computational Engineering, Finance, and Science · Computer Science 2026-05-19 Robin Willems , Peter Förster , Sebastian Schöps , Olaf van der Sluis , Clemens V. Verhoosel

This paper presents a physics-based data-driven method to learn predictive reduced-order models (ROMs) from high-fidelity simulations, and illustrates it in the challenging context of a single-injector combustion process. The method…

Computational Physics · Physics 2020-07-14 Renee Swischuk , Boris Kramer , Cheng Huang , Karen Willcox

Qualification of high-performance metal components produced by laser powder bed fusion (LPBF) must identify process-induced porous defects that reduce ductility and nucleate fatigue cracking. Detecting such defects via optical monitoring of…

Optics · Physics 2024-11-22 Ryan W. Penny , Zachery Kutschke , A. John Hart

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and…

Computational Engineering, Finance, and Science · Computer Science 2025-07-18 Nicholas Kirschbaum , Nathaniel Wood , Chang-Eun Kim , Thejaswi U. Tumkur , Chinedum Okwudire

Reduced-order models (ROMs) are widely used in fluid engineering to enable rapid prediction of flow fields for parametric analysis, design optimization, and control applications. Proper orthogonal decomposition (POD) is commonly employed to…

Fluid Dynamics · Physics 2026-02-25 Yuto Nakamura , Shintaro Sato , Naofumi Ohnishi

This contribution proposes novel data-driven surrogate modeling approaches for parameterized parabolic PDEs, where the parameter dependence can be split into two parts with different decay behavior of the Kolmogorov $N$-width. Such problems…

Numerical Analysis · Mathematics 2026-04-27 Dawid Kotowski , Mario Ohlberger

In this paper, we propose an equation-based parametric Reduced Order Model (ROM), whose accuracy is improved with data-driven terms added into the reduced equations. These additions have the aim of reintroducing contributions that in…

Numerical Analysis · Mathematics 2025-05-26 Anna Ivagnes , Giovanni Stabile , Gianluigi Rozza

Pore formation during Laser Powder Bed Fusion (LPBF) has long posed challenges in metal 3D printing, significantly affecting the mechanical properties of the final product. Porosity frequently occurs because of an unstable keyhole…

Computational Engineering, Finance, and Science · Computer Science 2024-10-29 Chuxiao Meng , Conor Porter , Sina Malakpour , Garrett Mathesen , Seongyeon Yang

The stochastic formation of defects during Laser Powder Bed Fusion (L-PBF) negatively impacts its adoption for high-precision use cases. Optical monitoring techniques can be used to identify defects based on layer-wise imaging, but these…

Image and Video Processing · Electrical Eng. & Systems 2024-09-23 Francis Ogoke , Sumesh Kalambettu Suresh , Jesse Adamczyk , Dan Bolintineanu , Anthony Garland , Michael Heiden , Amir Barati Farimani

The goal of this paper is to assess the utility of Reduced-Order Models (ROMs) developed from 3D physics-based models for predicting transient thermal power output for an enhanced geothermal reservoir while explicitly accounting for…

Computational Engineering, Finance, and Science · Computer Science 2018-06-18 M. K. Mudunuru , S. Karra , D. R. Harp , G. D. Guthrie , H. S. Viswanathan
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