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Solving the non-convex optimal power flow (OPF) problem for large-scale power distribution systems is computationally expensive. An alternative is to solve the relaxed convex problem or linear approximated problem, but these methods lead to…

Systems and Control · Electrical Eng. & Systems 2022-11-09 Rabayet Sadnan , Anamika Dubey

Dynamic constrained optimization problems (DCOPs) have gained researchers attention in recent years because a vast majority of real world problems change over time. There are studies about the effect of constrained handling techniques in…

Neural and Evolutionary Computing · Computer Science 2018-02-19 Maria-Yaneli Ameca-Alducin , Maryam Hasani-Shoreh , Wilson Blaikie , Frank Neumann , Efren Mezura-Montes

A recently proposed generalised continuum theory of curved dislocations describes the spatial and temporal evolution of statistically stored and geometrically necessary dislocation densities as well as the curvature. The dynamics follow…

Materials Science · Physics 2026-01-13 István Groma , Dénes Berta , Lóránt Sándli , Péter Dusán Ispánovity

Dislocations are topological defects known to be crucial in the onset of plasticity and in many properties of crystals. Classical Elasticity still fails to fully explain their dynamics under extreme conditions of high strain gradients and…

Soft Condensed Matter · Physics 2021-01-05 P. C. N. Pereira , S. W. S. Apolinario

This paper presents a new monolithic free-surface formulation that exhibits correct kinetic and potential energy behavior. We focus in particular on the temporal energy behavior of two-fluids flow with varying densities. Correct energy…

Numerical Analysis · Mathematics 2019-01-11 I. Akkerman , M. ten Eikelder

Discrete mechanics is presented as an alternative to the equations of fluid mechanics, in particular to the Navier-Stokes equation. The derivation of the discrete equation of motion is built from the intuitions of Galileo, the principles of…

Fluid Dynamics · Physics 2021-01-26 Jean-Paul Caltagirone

This work presents a novel approach for the optimization of dynamic systems on finite-dimensional Lie groups. We rephrase dynamic systems as so-called neural ordinary differential equations (neural ODEs), and formulate the optimization…

Optimization and Control · Mathematics 2024-09-18 Yannik P. Wotte , Federico Califano , Stefano Stramigioli

To simulate the dynamics of fluid with polydisperse particles on macroscale level, one has to solve hydrodynamic equations with several relaxation terms, representing momentum transfer from fluid to particles and vice versa. For small…

The computational method of discrete dislocation dynamics (DDD), used as a coarse-grained model of true atomistic dynamics of lattice dislocations, has become of powerful tool to study metal plasticity arising from the collective behavior…

Materials Science · Physics 2023-09-27 Nicolas Bertin , Vasily V. Bulatov , Fei Zhou

This paper deals with the numerical resolution of kinetic models for systems of self-propelled particles subject to alignment interaction and attraction-repulsion. We focus on the kinetic model considered in [18, 17] where alignment is…

Numerical Analysis · Mathematics 2017-05-24 Francis Filbet , Chi-Wang Shu

The paper studies the distributed stochastic compositional optimization problems over networks, where all the agents' inner-level function is the sum of each agent's private expectation function. Focusing on the aggregative structure of the…

Optimization and Control · Mathematics 2022-11-10 Shengchao Zhao , Yongchao Liu

A variety of shooting methods for computing fully discrete time-periodic solutions of partial differential equations, including Newton-Krylov and optimization-based methods, are discussed and used to determine the periodic, compressible,…

Optimization and Control · Mathematics 2016-08-16 Matthew J. Zahr , Per-Olof Persson , Jon Wilkening

We consider a new class of problems in elasticity, referred to as Data-Driven problems, defined on the space of strain-stress field pairs, or phase space. The problem consists of minimizing the distance between a given material data set and…

Analysis of PDEs · Mathematics 2019-12-13 Sergio Conti , Stefan Müller , Michael Ortiz

This article introduces, and reviews recent work using, a simple optimisation technique for analysing the nonlinear stability of a state in a dynamical system. The technique can be used to identify the most efficient way to disturb a system…

Fluid Dynamics · Physics 2014-08-18 R. R. Kerswell , C. C. T. Pringle , A. P. Willis

In this paper we consider a distributed optimization scenario in which a set of agents has to solve a convex optimization problem with separable cost function, local constraint sets and a coupling inequality constraint. We propose a novel…

Systems and Control · Computer Science 2018-04-25 Ivano Notarnicola , Giuseppe Notarstefano

In this paper, we are concerned with the global pressure formulation of immiscible incompressible two-phase flow between different rock types. We develop for this problem two robust schemes based on domain decomposition (DD) methods and…

Analysis of PDEs · Mathematics 2020-01-08 Elyes Ahmed

This article presents a new numerical scheme for the discretization of dissipative particle dynamics with conserved energy. The key idea is to reduce elementary pairwise stochastic dynamics (either fluctuation/dissipation or thermal…

Statistical Mechanics · Physics 2017-04-26 Gabriel Stoltz

How systems transit between different stable states under external perturbation is an important practical issue. We discuss here how a recently-developed energy optimization method for identifying the minimal disturbance necessary to reach…

Pattern Formation and Solitons · Physics 2018-05-02 Daniel Lecoanet , Rich R. Kerswell

The energy-based dual-phase dynamics identification (EDDI) method is a new data-driven technique for the discovery of equations of motion (EOMs) of strongly nonlinear single-degree-of-freedom (SDOF) oscillators. This research uses the EDDI…

Dynamical Systems · Mathematics 2024-12-04 Cristian López , Keegan J. Moore

Gain-dissipative platforms consisting of lasers, optical parametric oscillators and nonequilibrium condensates operating at the condensation/coherence threshold have been recently proposed as efficient analog simulators of 2-local spin…

Disordered Systems and Neural Networks · Physics 2021-02-10 Nikita Stroev , Natalia G. Berloff