Publications associées à Microstructure formation in micron-scale thin-walled Hastelloy X samples fabricated with laser powder bed fusion

Publications associées (19)

Self-locking Fe-based shape memory couplers: Insights into SME and interface contact mechanics

Fe-based Shape memory alloys (Fe-SMAs) have been extensively utilized in a variety of innovative engineering applications. Notably, Fe-based shape memory couplers present an alternative to welded and machined mechanical joints, offering advantages such as ...

Elsevier BV2025

Raising the temperature on electrodes for anion exchange membrane electrolysis-activity and stability aspects

Jan Van Herle

The membrane electrode assembly is the powerhouse of the anion exchange membrane water electrolyser (AEMWE), thereby placing a great importance on the associated preparation conditions. This paper investigated how annealing temperature and time impacted ac ...

ELSEVIER2023

Decentralized coordination between active distribution network and multi-microgrids through a fast decentralized adjustable robust operation framework

Yuning Jiang

Due to the autonomous characteristic and heterogeneity of the individual agents in active distribution network (ADN) with multi-microgrids (MMG), this paper proposes a fully decentralized adjustable robust operation framework achieving the coordinated oper ...

ELSEVIER2023

Validating Automatic Speech Recognition and Understanding for Pre-Filling Radar Labels-Increasing Safety While Reducing Air Traffic Controllers' Workload

Juan Pablo Zuluaga Gomez

Automatic speech recognition and understanding (ASRU) for air traffic control (ATC) has been investigated in different ATC environments and applications. The objective of this study was to quantify the effect of ASRU support for air traffic controllers (AT ...

2023

Bayesian Error-in-Variables Models for the Identification of Distribution Grids

Giancarlo Ferrari Trecate, Pulkit Nahata, Jean-Sébastien Hubert Brouillon

The increasing integration of renewable energy requires a good model of the existing power distribution infrastructure, represented by its admittance matrix. However, a reliable estimate may either be missing or quickly become obsolete, as distribution gri ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Machine Learning Security in Industry: A Quantitative Survey

Kathrin Grosse

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Microstructure et usinabilité d'alliages de titane béta-métastable

Loïc Favre

Titanium has become in recent years an interesting material in many applications that require a combination of high mechanical properties and low density. It has the peculiarity of undergoing an allotropic transformation at 882°C. Below this temperature, ...

EPFL2023

Auto-tuning deep forest for shear stiffness prediction of headed stud connectors

Xianlin Wang

The shear stiffness of headed stud connector is a critical parameter for the calculation of deflection and inter-facial shear force for steel-concrete composite structure. Thus, this study presented a promising data-driven model auto-tuning Deep Forest (AT ...

2022

Natural-Looking Adversarial Examples From Freehand Sketches

Davide Nanni, Hakgu Kim

Deep neural networks (DNNs) have achieved great success in image classification and recognition compared to previous methods. However, recent works have reported that DNNs are very vulnerable to adversarial examples that are intentionally generated to misl ...

IEEE2022

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Yinlin Hu, Yunpeng Li

Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring system. However, the covariate shift between RSI datasets under different capture conditions cannot be alleviated by directly using the unsupervised domain adaptatio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Adaptive Diffusion With Compressed Communication

Ali H. Sayed

We consider multi-agent networks that aim at solving, cooperatively and online, distributed optimization problems under communication constraints. We propose the ACTC (Adapt-Compress-Then-Combine) diffusion strategy, which leverages differential randomized ...

IEEE2022

An active charge balancing method suitable for integration in the output-stage of electrical neural stimulators

Alexandre Schmid

This paper presents a charge controlling circuit technique to integrate a charge balancer circuitry in the output-stage of electrical neural stimulators with the aim to reduce the area and the power consumption of the charge balancing circuitry. The propos ...

SPRINGER2022

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Entropic Compressibility of Levy Processes

Julien René Fageot

In contrast to their seemingly simple and shared structure of independence and stationarity, Levy processes exhibit a wide variety of behaviors, from the self-similar Wiener process to piecewise-constant compound Poisson processes. Inspired by the recent p ...

2022

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen dagger

Iurii Timrov, Matteo Cococcioni

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approa ...

ROYAL SOC CHEMISTRY2021

Time-Dependent Deep Image Prior for Dynamic MRI

Michaël Unser, Harshit Gupta, Kyong Hwan Jin, Jaejun Yoo

We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. We introduce a generalized version of t ...

Institute of Electrical and Electronics Engineers2021

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Lucas Cesar Eduardo Cassano

This article develops a fully decentralized multiagent algorithm for policy evaluation. The proposed scheme can be applied to two distinct scenarios. In the first scenario, a collection of agents have distinct datasets gathered by following different behav ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Unraveling the Influence of Thermal Drawing Parameters on the Microstructure and Thermo-Mechanical Properties of Multimaterial Fibers

Fabien Sorin, Inès Richard, Shahrzad Shadman Yazdi

Multimaterial thermally drawn fibers are becoming important building blocks in several foreseen applications in surgical probes, protective gears, or medical textiles. Here, the influence of the thermal drawing parameters on the degree of polymer chain ori ...

WILEY-V C H VERLAG GMBH2021