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In this paper, we present a data-driven model for forecasting the production increase after hydraulic fracturing (HF). We use data from fracturing jobs performed at one of the Siberian oilfields. The data includes features, characterizing…

Machine Learning · Statistics 2019-05-28 Ivan Makhotin , Dmitry Koroteev , Evgeny Burnaev

Harmonic drive systems (HDS) are high-precision robotic transmissions featuring compact size and high gear ratios. However, issues like kinematic transmission errors hamper their precision performance. This article focuses on data-driven…

Robotics · Computer Science 2023-12-14 Ju Wu

This paper deals with the problem of cost-optimal operation of smart buildings that integrate a centralized HVAC system, photovoltaic generation and both thermal and electrical storage devices. Building participation in a Demand-Response…

Systems and Control · Computer Science 2019-02-19 Gianni Bianchini , Marco Casini , Daniele Pepe , Antonio Vicino , Giovanni Gino Zanvettor

We investigate a stochastic heat engine based on an over-damped particle diffusing on the positive real axis in an externally driven time-periodic log-harmonic potential. The periodic driving is composed of two isothermal and two adiabatic…

Statistical Mechanics · Physics 2014-05-28 Viktor Holubec

The local equilibrium thermodynamics is a basic assumption of macroscopic descriptions of the out of equilibrium dynamics for Hamiltonian systems. We numerically analyze the Hamiltonian Potts model in two dimensions to study the violation…

Statistical Mechanics · Physics 2023-06-21 Michikazu Kobayashi , Naoko Nakagawa , Shin-ichi Sasa

Calibration of dynamic models to data is an important step in building building digital twins of HVAC equipment, thermal loads and control systems. Sometimes, when a model fails to calibrate to data, a possible cause is that the model has…

Computational Engineering, Finance, and Science · Computer Science 2026-03-18 Sebastian Micluta-Campeanu , Avinash Subramanian , Anas Abdelrehim , Ranjan Anantharaman , Rohit Dhumane , Brad Carman , Chris Rackauckas

We consider dynamical systems evolving near an equilibrium statistical state where the interest is in modelling long term behavior that is consistent with thermodynamic constraints. We adjust the distribution using an entropy-optimizing…

Fluid Dynamics · Physics 2014-11-25 Keith Myerscough , Jason Frank , Benedict Leimkuhler

The objective of this paper is to improve the accuracy and robustness of optimal power flow (OPF) formulations for distribution systems modeled down to the low-voltage point of connection of individual buildings. An approach for addressing…

Systems and Control · Electrical Eng. & Systems 2023-10-11 Dakota Hamilton , Loraine Navarro , Dionysios Aliprantis

Variational data assimilation optimizes for an initial state of a dynamical system such that its evolution fits observational data. The physical model can subsequently be evolved into the future to make predictions. This principle is a…

Machine Learning · Computer Science 2021-05-21 Thomas Frerix , Dmitrii Kochkov , Jamie A. Smith , Daniel Cremers , Michael P. Brenner , Stephan Hoyer

In this work we consider a flow network for which the goal is to solve a practical optimal regulation problem in the presence of input saturation. Based on Lyapunov arguments we propose distributed controllers which guarantee global…

Optimization and Control · Mathematics 2016-06-28 Tjardo Scholten , Claudio De Persis , Pietro Tesi

Hydraulic systems are widely utilized in industrial applications due to their high force generation, precise control, and ability to function in harsh environments. Hydraulic cylinders, as actuators in these systems, apply force and…

Machine Learning · Computer Science 2026-02-06 Mohamad Amin Jamshidi , Mehrbod Zarifi , Zolfa Anvari , Hamed Ghafarirad , Mohammad Zareinejad

Data-driven methods for computer simulations are blooming in many scientific areas. The traditional approach to simulating physical behaviors relies on solving partial differential equations (PDE). Since calculating these iterative…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-01 Sergio Iserte , Alejandro González-Barberá , Paloma Barreda , Krzysztof Rojek

We develop a flow renormalization approach for periodically-driven quantum systems, which reveals prethermal dynamical regimes and associated timescales via direct correspondence between real time and flow time behavior. In this formalism,…

Quantum Physics · Physics 2021-03-16 Martin Claassen

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

Numerical study has been conducted for the chaotic flow in a multi-turn closed-loop pulsating heat pipe (PHP). Heat flux and constant temperature boundary conditions have been applied for heating and cooling sections respectively. Water was…

Fluid Dynamics · Physics 2017-03-08 S. M. Pouryoussefi , Yuwen Zhang

The stochastic dynamics of the damped harmonic oscillator in a heat bath is simulated with an algorithm that is exact for time steps of arbitrary size. Exact analytical results are given for correlation functions and power spectra in the…

Data Analysis, Statistics and Probability · Physics 2011-04-06 Simon F. Norrelykke , Henrik Flyvbjerg

Current system thermal-hydraulic codes have limited credibility in simulating real plant conditions, especially when the geometry and boundary conditions are extrapolated beyond the range of test facilities. This paper proposes a…

Machine Learning · Computer Science 2020-01-14 Han Bao , Nam Dinh , Linyu Lin , Robert Youngblood , Jeffrey Lane , Hongbin Zhang

Predictions of hydrologic variables across the entire water cycle have significant value for water resource management as well as downstream applications such as ecosystem and water quality modeling. Recently, purely data-driven deep…

Machine Learning · Computer Science 2023-01-11 Dapeng Feng , Jiangtao Liu , Kathryn Lawson , Chaopeng Shen

Hydropower plants are one of the most convenient option for power generation, as they generate energy exploiting a renewable source, they have relatively low operating and maintenance costs, and they may be used to provide ancillary…

Signal Processing · Electrical Eng. & Systems 2019-11-15 Alessandro Betti , Emanuele Crisostomi , Gianluca Paolinelli , Antonio Piazzi , Fabrizio Ruffini , Mauro Tucci

Accurate and computationally-viable representations of clouds and turbulence are a long-standing challenge for climate model development. Traditional parameterizations that crudely but efficiently approximate these processes are a leading…

Atmospheric and Oceanic Physics · Physics 2024-01-05 Jerry Lin , Mohamed Aziz Bhouri , Tom Beucler , Sungduk Yu , Michael Pritchard