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Large-scale constrained optimization is pivotal in modern scientific, engineering, and industrial computation, often involving complex systems with numerous variables and constraints. This paper provides a unified and comprehensive…

Optimization and Control · Mathematics 2025-10-21 Kangkang Deng , Rui Wang , Zhenyuan Zhu , Junyu Zhang , Zaiwen Wen

We introduce a class of first-order methods for smooth constrained optimization that are based on an analogy to non-smooth dynamical systems. Two distinctive features of our approach are that (i) projections or optimizations over the entire…

Optimization and Control · Mathematics 2025-04-15 Michael Muehlebach , Michael I. Jordan

We introduce MORPH, a method for co-optimization of hardware design parameters and control policies in simulation using reinforcement learning. Like most co-optimization methods, MORPH relies on a model of the hardware being optimized,…

Robotics · Computer Science 2023-10-02 Zhanpeng He , Matei Ciocarlie

Asymptotic efficiency of targeted maximum likelihood estimators (TMLE) of target features of the data distribution relies on a a second order remainder being asymptotically negligible. In previous work we proposed a nonparametric MLE termed…

Statistics Theory · Mathematics 2021-07-02 Mark van der Laan , Zeyi Wang , Lars van der Laan

Finite element based simulation of phenomena governed by partial differential equations is a standard tool in many engineering workflows today. However, the simulation of complex geometries is computationally expensive. Many engineering…

Numerical Analysis · Mathematics 2019-08-07 Andreas Buhr

We present a new polynomial-free prolongation scheme for Adaptive Mesh Refinement (AMR) simulations of compressible and incompressible computational fluid dynamics. The new method is constructed using a multi-dimensional kernel-based…

Numerical Analysis · Mathematics 2022-10-12 Steven I. Reeves , Dongwook Lee , Adam Reyes , Carlo Graziani , Petros Tzeferacos

Numerical simulations for flow and transport in subsurface porous media often prove computationally prohibitive due to property data availability at multiple spatial scales that can vary by orders of magnitude. A number of model order…

Numerical Analysis · Mathematics 2018-03-13 Gurpreet Singh , Wingtat Leung , Mary F. Wheeler

In this article, we investigate the artificial viscosity and hourglass control algorithms for high-order staggered Lagrangian hydrodynamics(SGH), as proposed in~\cite[Sun et al., 2025]{Sun2025High}. Inspired by the subzonal pressure method…

Numerical Analysis · Mathematics 2025-09-10 Zhiyuan Sun , Jun Liu , Pei Wang

This paper proposes an adaptive hyper-reduction method to reduce the computational cost associated with the simulation of parametric particle-based kinetic plasma models, specifically focusing on the Vlasov-Poisson equation. Conventional…

Numerical Analysis · Mathematics 2026-02-05 Cecilia Pagliantini , Federico Vismara

A cell-centered implicit-explicit updated Lagrangian finite volume scheme on unstructured grids is proposed for a unified first order hyperbolic formulation of continuum fluid and solid mechanics. The scheme provably respects the stiff…

Numerical Analysis · Mathematics 2022-01-26 Walter Boscheri , Simone Chiocchetti , Ilya Peshkov

In this work, we present a high-order finite volume framework for the numerical simulation of shallow water flows. The method is designed to accurately capture complex dynamics inherent in shallow water systems, particularly suited for…

Numerical Analysis · Mathematics 2025-05-14 Mirco Ciallella , Lorenzo Micalizzi , Victor Michel-Dansac , Philipp Öffner , Davide Torlo

The multiscale nature of turbulent combustion necessitates accurate and computationally efficient methods for direct numerical simulations (DNS). The field has long been dominated by high-order finite differences, which lack the flexibility…

Fluid Dynamics · Physics 2024-01-24 Jack R. C. King

Some methods based on simple regularizing geometric element transformations have heuristically been shown to give runtime efficient and quality effective smoothing algorithms for meshes. We describe the mathematical framework and a…

Computational Geometry · Computer Science 2013-07-09 Dimitris Vartziotis , Benjamin Himpel

In this paper we propose local approximation spaces for localized model order reduction procedures such as domain decomposition and multiscale methods. Those spaces are constructed from local solutions of the partial differential equation…

Numerical Analysis · Mathematics 2018-07-31 Andreas Buhr , Kathrin Smetana

This paper presents a methodological framework for training, self-optimising, and self-organising surrogate models to approximate and speed up multiobjective optimisation of technical systems based on multiphysics simulations. At the hand…

Machine Learning · Computer Science 2024-04-04 Diego Botache , Jens Decke , Winfried Ripken , Abhinay Dornipati , Franz Götz-Hahn , Mohamed Ayeb , Bernhard Sick

We design, analyse and implement an arbitrary order scheme applicable to generic meshes for a coupled elliptic-parabolic PDE system describing miscible displacement in porous media. The discretisation is based on several adaptations of the…

Computational Engineering, Finance, and Science · Computer Science 2019-01-16 Daniel Anderson , Jerome Droniou

We report the first high-order eddy-resolving simulation of flow over a marine propeller using a recently developed high-order sliding-mesh method. This method employs the flux reconstruction framework and a new dynamic curved mortar…

Fluid Dynamics · Physics 2021-06-07 Bin Zhang , Chi Ding , Chunlei Liang

An arbitrary Lagrangian--Eulerian (ALE) finite element method for arbitrarily curved and deforming two-dimensional materials and interfaces is presented here. An ALE theory is developed by endowing the surface with a mesh whose in-plane…

Computational Physics · Physics 2020-03-24 Amaresh Sahu , Yannick A. D. Omar , Roger A. Sauer , Kranthi K. Mandadapu

This paper deals with the identification of linear stochastic dynamical systems, where the unknowns include system coefficients and noise variances. Conventional approaches that rely on the maximum likelihood estimation (MLE) require…

Machine Learning · Statistics 2025-08-18 Jinwen Xu , Qin Lu , Yaakov Bar-Shalom

Over the past decades, the performance design of closed-chain legged mechanisms (CLMs) has not been adequately addressed. Most existing design methodologies have predominantly relied on trajectory synthesis, which inadvertently prioritizes…

Computational Engineering, Finance, and Science · Computer Science 2025-03-11 Long Guo , Ying Zhang , Qi Qin , Guanjun Liu , Hanyu Chen , Yan-an Yao