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Saving energy is an important issue for cloud providers to reduce energy cost in a data center. With the increasing popularity of cloud computing, it is time to examine various energy reduction methods for which energy consumption could be…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-12-21 Nasrin Akhter , Mohamed Othman , Ranesh Kumar Naha

Today's intelligent applications can achieve high performance accuracy using machine learning (ML) techniques, such as deep neural networks (DNNs). Traditionally, in a remote DNN inference problem, an edge device transmits raw data to a…

Machine Learning · Computer Science 2021-06-03 Mounssif Krouka , Anis Elgabli , Chaouki Ben Issaid , Mehdi Bennis

This paper presents a multiscale methodology for efficient unsteady conjugate heat transfer simulations. The solid domain is modelled by coupling a global representation of the temperature field, based on the eigenfunctions of the unsteady…

Computational Physics · Physics 2025-07-31 Yann Dreze , Muting Hao , Luca di Mare

Surrogate modeling has emerged as a powerful tool to accelerate Computational Fluid Dynamics (CFD) simulations. Existing 3D geometric learning models based on point clouds, voxels, meshes, or graphs depend on explicit geometric…

Fluid Dynamics · Physics 2025-05-26 Qian Chen , Mohamed Elrefaie , Angela Dai , Faez Ahmed

The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…

Simulations of optical quantum systems are essential for the development of quantum technologies. However, these simulations are often computationally intensive, especially when repeated evaluations are required for data fitting, parameter…

Environmentally-powered computer systems operate on renewable energy harvested from their environment, such as solar or wind, and stored in batteries. While harvesting environmental energy has long been necessary for small-scale embedded…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-02 Noman Bashir , Yasra Chandio , David Irwin , Fatima M. Anwar , Jeremy Gummeson , Prashant Shenoy

We present a novel 3D adaptive observer framework for use in the determination of subsurface organic tissue temperatures in electrosurgery. The observer structure leverages pointwise 2D surface temperature readings obtained from a real-time…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Hamza El-Kebir , Junren Ran , Martin Ostoja-Starzewski , Richard Berlin , Joseph Bentsman , Leonardo P. Chamorro

The rapid cloud computing growth has turned data center energy consumption into a global problem. At the same time, modern cloud providers operate multiple geographically-distributed data centers. Distributed data center infrastructure…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-18 Dražen Lučanin , Ivona Brandic

With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as…

Machine Learning · Computer Science 2025-12-30 Liping Sun , Yucheng Guo , Siliang Lu , Zhenzhen Li

Advanced control strategies for delivering heat to users in a district heating network have the potential to improve performance and reduce wasted energy. To enable the design of such controllers, this paper proposes an automated plant…

Systems and Control · Electrical Eng. & Systems 2024-04-15 Audrey Blizard , Stephanie Stockar

Energy-efficient ventilation control plays a vital role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate…

Systems and Control · Electrical Eng. & Systems 2025-11-20 Yuexin Bian , Oliver Schmidt , Yuanyuan Shi

Computationally expensive, high-accuracy detector simulations are a major bottleneck for many particle physics experiments such as those at the Large Hadron Collider (LHC) as well as those planned for future colliders. This challenge has…

Instrumentation and Detectors · Physics 2026-03-17 P. Alex May , Qibin Liu , Julia Gonski , Benjamin Nachman

An initial study of surrogate-assisted evolutionary algorithms used to design vertical-axis wind turbines wherein candidate prototypes are evaluated under fan generated wind conditions after being physically instantiated by a 3D printer has…

Neural and Evolutionary Computing · Computer Science 2016-03-14 Richard J. Preen , Larry Bull

Model predictive control (MPC) has been shown to significantly improve the energy efficiency of buildings while maintaining thermal comfort. Data-driven approaches based on neural networks have been proposed to facilitate system modelling.…

Systems and Control · Electrical Eng. & Systems 2024-08-19 Marie-Christine Paré , Vasken Dermardiros , Antoine Lesage-Landry

Hybrid modeling combining data-driven techniques and numerical methods is an emerging and promising research direction for efficient climate simulation. However, previous works lack practical platforms, making developing hybrid modeling a…

Atmospheric and Oceanic Physics · Physics 2022-09-20 Xin Wang , Wei Xue , Yilun Han , Guangwen Yang

We introduce a method for real-time navigation and tracking with differentiably rendered world models. Learning models for control has led to impressive results in robotics and computer games, but this success has yet to be extended to…

Machine Learning · Computer Science 2022-01-26 Baris Kayalibay , Atanas Mirchev , Patrick van der Smagt , Justin Bayer

Generative design has been growing across the design community as a viable method for design space exploration. Thermal design is more complex than mechanical or aerodynamic design because of the additional convection-diffusion equation and…

Machine Learning · Computer Science 2022-08-18 Hadi Keramati , Feridun Hamdullahpur

Surrogate strategies are used widely for uncertainty quantification of groundwater models in order to improve computational efficiency. However, their application to dynamic multiphase flow problems is hindered by the curse of…

Machine Learning · Statistics 2019-05-02 Shaoxing Mo , Yinhao Zhu , Nicholas Zabaras , Xiaoqing Shi , Jichun Wu

Accurately predicting the temperature field in metal additive manufacturing (AM) processes is critical to preventing overheating, adjusting process parameters, and ensuring process stability. While physics-based computational models offer…

Machine Learning · Computer Science 2024-01-05 Pouyan Sajadi , Mostafa Rahmani Dehaghani , Yifan Tang , G. Gary Wang
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