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Reaction-diffusion-advection media on semi-infinite domains are important in chemical, biological and ecological applications, yet remain a challenge for pattern formation theory. To demonstrate the rich emergence of nonlinear traveling…

Pattern Formation and Solitons · Physics 2018-08-16 Arik Yochelis

We shall construct a class of nonlinear reaction-diffusion equations starting from an infinitesimal algebraic skeleton. Our aim is to explore the possibility of an algebraic foundation of integrability properties and of stability of…

Adaptation and Self-Organizing Systems · Physics 2016-09-30 Marcella Palese

The presence of a dispersed phase substantially modifies small-scale turbulence. However, there has not been a comprehensive mechanistically-based understanding to predict turbulence modulation. Based on the energy flux balance, we propose…

Fluid Dynamics · Physics 2023-11-23 S. Balachandar , C. Peng , L. -P. Wang

An adaptive funnel control method is considered for the regulation of the output for a class of nonlinear infinite-dimensional systems on real Hilbert spaces. After a decomposition of the state space and some change of variables related to…

Optimization and Control · Mathematics 2022-04-06 Anthony Hastir , Joseph J. Winkin , Denis Dochain

We develop a mathematical model for dynamic simulation of an alkaline electrolyzer plant. The plant includes the stack, a water recirculation system and hydrogen storage with compressor. We model each component of the system with mass and…

Systems and Control · Electrical Eng. & Systems 2024-07-30 Nicola Cantisani , Josefine Dovits , John Bagterp Jørgensen

This study introduces a liquid-fueled reactor network (LFRN) framework for reduced-order modeling of gas turbine combustors. The proposed LFRN extends conventional gaseous-fueled reactor network methods by incorporating specialized reactors…

Fluid Dynamics · Physics 2025-10-16 Philip John , Sourav Saha , Opeoluwa Owoyele

Synchronous generators and inverter-based resources are complex systems with dynamics that cut across multiple intertwined physical domains and control loops. Modeling individual generators and inverters is, in itself, a very involved…

Systems and Control · Electrical Eng. & Systems 2022-07-26 D. Venkatramanan , Manish K. Singh , Olaolu Ajala , Alejandro Dominguez-Garcia , Sairaj Dhople

Machine learning has emerged recently as a powerful tool for predicting properties of quantum many-body systems. For many ground states of gapped Hamiltonians, generative models can learn from measurements of a single quantum state to…

Quantum Physics · Physics 2024-03-05 Haoxiang Wang , Maurice Weber , Josh Izaac , Cedric Yen-Yu Lin

In this manuscript, the performance of an ultracapacitor fuel cell in grid connected mode is investigated. Voltage regulation to the ultracapacitor was achieved with a three level bidirectional DC-DC converter while also achieving power…

Systems and Control · Electrical Eng. & Systems 2022-10-11 Webster Adepoju , Indranil Bhattacharya , 0lufunke Mary Sanyaolu

Starting from a Huxley-type model for an agitated vibrational mode, we propose an embedding of standard active particle models in terms of two-temperature processes. One temperature refers to an ambient thermal bath, and the other…

Statistical Mechanics · Physics 2024-07-02 Faezeh Khodabandehlou , Christian Maes

We prove some existence and uniqueness results and some qualitative properties for the solution of a system modelling the catalytic conversion in a cylinder. This model couples parabolic partial differential equations posed in a cylindrical…

Analysis of PDEs · Mathematics 2007-05-23 J. -D. Hoernel

Reservoir computing is a popular approach to design recurrent neural networks, due to its training simplicity and approximation performance. The recurrent part of these networks is not trained (e.g., via gradient descent), making them…

Neural and Evolutionary Computing · Computer Science 2021-02-15 Pietro Verzelli , Cesare Alippi , Lorenzo Livi , Peter Tino

With electric power systems becoming more compact and increasingly powerful, the relevance of thermal stress especially during overload operation is expected to increase ceaselessly. Whenever critical temperatures cannot be measured…

Machine Learning · Computer Science 2022-11-03 Wilhelm Kirchgässner , Oliver Wallscheid , Joachim Böcker

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two…

Machine Learning · Computer Science 2022-02-22 Amol Salunkhe , Dwyer Deighan , Paul DesJardin , Varun Chandola

Temperature control is a complex task due to its often unknown dynamics and disturbances. This paper explores the use of Neural Nonlinear AutoRegressive eXogenous (NNARX) models for nonlinear system identification and model predictive…

Systems and Control · Electrical Eng. & Systems 2024-02-09 Jing Xie , Léo Simpson , Jonas Asprion , Riccardo Scattolini

The simulation of open molecular systems requires explicit or implicit reservoirs of energy and particles. Whereas full atomistic resolution is desired in the region of interest, there is some freedom in the implementation of the…

Computational Physics · Physics 2019-04-26 Luigi Delle Site , Christian Krekeler , John Whittaker , Animesh Agarwal , Rupert Klein , Felix Höfling

We present a data-driven, differentiable neural network model designed to learn the temperature field, its gradient, and the cooling rate, while implicitly representing the melt pool boundary as a level set in laser powder bed fusion. The…

We derive the nonequilibrium conductance matrix for open stationary Chemical Reaction Networks (CRNs) described by a deterministic mass action kinetic equation. As an illustration, we determine the nonequilibrium conductance matrix of a CRN…

Statistical Mechanics · Physics 2025-06-27 Paul Raux , Christophe Goupil , Gatien Verley

We present a coupled cluster and linear response theory to compute properties of many-electron systems at non-zero temperatures. For this purpose, we make use of the thermofield dynamics, which allows for a compact wavefunction…

Chemical Physics · Physics 2020-05-14 Gaurav Harsha , Thomas M. Henderson , Gustavo E. Scuseria

Modularization is a cornerstone of computer science, abstracting complex functions into atomic building blocks. In this paper, we introduce a new level of modularization by abstracting generative models into atomic generative modules.…

Machine Learning · Computer Science 2025-02-26 Tianhong Li , Qinyi Sun , Lijie Fan , Kaiming He