Publications related to Real-Time Optimization Based on Adaptation of Surrogate Models

Related publications (38)

Context-Specific Selection of Poisson cluster rainfall models for accurate urban hydrological simulations

The Poisson cluster rainfall generation model has been underutilized in urban hydrological simulations due to challenges in reproducing fine-scale extreme precipitation. This study addresses this issue by comprehensively validating four variants of Poisson ...

Elsevier BV2025

Bike sharing systems: The impact of precise trip demand forecasting on operational efficiency in different city structures

Michel Bierlaire, Selin Ataç

Increasing environmental concerns drive interest in sustainable solutions across various fields. Vehicle sharing systems such as one-way station-based bike sharing systems (BSSs) offer one such solution in transportation, although they pose operational cha ...

2025

A Streamline Upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations Under Optimal Control

Gianluigi Rozza, Fabio Zoccolan

In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing with Advection-Diffusion PDEs for high values of the Peclet number. In this situation, computational instabilities occur, both for steady and unsteady cases. A Str ...

Walter De Gruyter Gmbh2024

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Adam Robert Swietek

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

EPFL2024

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

Denis Gillet, Juan Carlos Farah, Jérémy Alain La Scala-Jayet

Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

2024

On the difficulty of determining Kármán "constants" from direct numerical simulations

Peter Monkewitz

The difficulty of determining the slope of the famed logarithmic law in the mean velocity profile of wall-bounded turbulent flows, the inverse of the K & aacute;rm & aacute;n "constant" kappa, from direct numerical simulations (DNS) is discussed for channe ...

Melville2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

Alexis Berne, Athanasios Nenes, Satoshi Takahama, Anne-Claire Marie Billault--Roux, Georgia Sotiropoulou, Paraskevi Georgakaki, Kunfeng Gao, Romanos Foskinis

This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the pa ...

Zenodo2024

Computational Homogenization for Inverse Design of Surface-based Inflatables

Mark Pauly, Florin Isvoranu, Francis Julian Panetta, Yingying Ren, Seiichi Eduardo Suzuki Erazo, Uday Kusupati

Surface-based inflatables are composed of two thin layers of nearly inextensible sheet material joined together along carefully selected fusing curves. During inflation, pressure forces separate the two sheets to maximize the enclosed volume. The fusing c ...

Association for Computing Machinery (ACM)2024

Cross-layer Exploration of 2.5D Energy-Efficient Heterogeneous Chiplets Integration: From System Simulation to Open Hardware

Anna Burdina, David Atienza Alonso, Giovanni Ansaloni, Miguel Peon Quiros, Pasquale Davide Schiavone

In the past decade, computing systems have significantly increased in complexity and power consumption. Nowadays, heterogeneous multi-processor systems-on-chip (MPSoCs) integrate many computing cores. Heterogeneous MPSoCs often comprise general-purpose pro ...

Association for Computing Machinery, Inc2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Integrative structural design methods for bamboo woven deployable structures: The BamX! Research Pavilion

Seiichi Eduardo Suzuki Erazo

Bamboo deployable structures take advantage of the high elasticity of the naturally grown material to achieve substantial shape change beyond mechanical deployment. The deployability maximizes prefabrication while maintaining transportation compactness. Th ...

International Association for Shell and Spatial Structures (IASS)2024

The effect of smooth parametrizations on nonconvex optimization landscapes

Nicolas Boumal

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good g ...

Springer Heidelberg2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

2024

Mesh-based topology, shape and sizing optimization of ribbed plates

Ahmad Abdulrahman Ahmad Majdouba

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Springer2024

NBI optimization on SMART and implications for scenario development

Mario Ludovico Podesta, Francesca Maria Poli

The SMall Aspect Ratio Tokamak (SMART) under commissioning at the University of Seville, Spain, aims to explore confinement properties and possible advantages in confinement for compact/spherical tokamaks operating at negative vs. positive triangularity. T ...

Iop Publishing Ltd2024

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Elsevier Sci Ltd2024

Collimation simulations for the FCC-ee

Milica Rakic, Tatiana Pieloni, Guillaume Clément Broggi, Giovanni Iadarola, Félix Simon Carlier

The collimation system of the Future Circular Collider, operating with leptons (FCC-ee), must protect not only the experiments against backgrounds, but also the machine itself from beam losses. With a 17.8 MJ stored energy of the electron and positron beam ...

Iop Publishing Ltd2024

Towards practical reinforcement learning for tokamak magnetic control

Federico Alberto Alfredo Felici, Jonas Buchli, Cristian Galperti

Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbacks compared to traditional feedback control approaches for magnetic confinem ...

Elsevier Science Sa2024