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Optimization of a new type of ultrasonic linear motor

Publications associées (30)

Robust optimization of control parameters for WEC arrays using stochastic methods

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

Journal of Computational Physics2023

Increasing the Energy Efficiency of Gas Boosters for Hydrogen Storage and for Refueling Stations

Alfred Rufer

A new electrically driven gas booster is described as an alternative to the classical air-driven gas boosters known for their poor energetic efficiency. These boosters are used in small scale Hydrogen storage facilities and in refueling stations for Hydrog ...

MDPI2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system

François Maréchal, Yuxuan Li

The load tracking performance of combined cooling, heating, and power multi-energy system (CCHP-MES) greatly depends on the equipment capacity configuration. And the frequent fluctuations in the source-load uncertainty puts higher demands on the load track ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Acoustic Levitation apparatus (Robotics Practicals)

Lorenzo Francesco John Noseda, Mahmut Selman Sakar, Amit Yedidia Dolev, Bora Yalcin

The following data contain the information and files, which are required to recreate and build the experimental setup that is described in the Laboratory manual. Further details can be found in the associated publication “A graduate laboratory experiment t ...

Zenodo2023

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Jürg Alexander Schiffmann, Cyril Picard, Soheyl Massoudi

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

ASME Amer Soc Mechanical Engineers2023

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

2023

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Baiwei Guo, Giancarlo Ferrari Trecate, Yuning Jiang, Maryam Kamgarpour

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...

IEEE2023

Bayesian Optimization for Chemical Reactions

Philippe Schwaller, Bojana Rankovic, Jeff Guo

Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...

Swiss Chemical Soc2023