Results 81 to 90 of about 4,709,515 (265)

Data-driven online SOH estimation of a grid-connected BESS: Accuracy improvements and lifetime prediction

Measurement: Energy
This analysis develops a Coulomb-counting-based online state-of-health (SOH) estimator using detected partial discharge segments for an existing operational battery energy storage system (BESS).
Mirko Ledro, Jon Goiburu, Jan Martin Zepter, Mattia Marinelli, Mikel Arrinda   +4 more
doaj   +1 more source

Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam

Advanced Engineering Materials, EarlyView.
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva, Joseph Lavoie, Afsaneh Rabiei   +2 more
wiley   +1 more source

Integration of Expert Judgment into Remaining Useful Lifetime Prediction of Components [PDF]

, 2014
Accurate estimates of renewal instances are necessary to avoid both machine breakdowns as well as unnecessary replacements. These instances are based upon a prognosis of the remaining useful lifetime of the components investigated but their usability is ...
Kirsten Tracht, Hendrik Stern, Schuh, Peter, Peter Schuh, Stern, Hendrik, Tracht, Kirsten   +5 more
core   +1 more source

State-of-charge estimation of IoT devices using genetic algorithm-optimized long short-term memory networks under real-world conditions

Energy Reports
Accurate State of Charge (SOC) estimation is crucial for remaining energy estimation and remaining useful life prediction. While in application scenarios such as Electric Vehicles (EVs), accurate SOC estimation can help to plan journeys, reducing range ...
Omer Ali, Mohamad Khairi Ishak, Khalid Ammar, Chia Ai Ooi, Ashraf Bani Ahmad   +4 more
doaj   +1 more source

Estimating the Remaining Lifetime of Power Transformers Using Paper Insulation Degradation

, 2018
Transformadores de potência são equipamentos essenciais para o bom funcionamento de uma rede eléctrica. Devido ao seu elevado custo e a todos os inconvenientes que a paragem de funcionamento de um transformador pode causar, é importante que as empresas que possuem este tipo de equipamentos possam prever qual o tempo de vida restante dos mesmos.
openaire   +2 more sources

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Conformal Prediction Intervals for Remaining Useful Lifetime Estimation

, 2022
The main objective of Prognostics and Health Management is to estimate the Remaining Useful Lifetime (RUL), namely, the time that a system or a piece of equipment is still in working order before starting to function incorrectly.
Hüllermeier, Eyke, Javanmardi, Alireza
core  

Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions

Advanced Functional Materials, EarlyView.
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian, Jingkai Lin, Zhihao Tian, Selusiwe Ncube, Huayang Zhang, Emiliano Cortés, Hongqi Sun, Shaobin Wang   +7 more
wiley   +1 more source