Results 91 to 100 of about 136,664 (227)

Experimental and numerical studies of the flow structure generated by a submerged sluice gate [PDF]

, 2010
Sluice gates are commonly used to control discharge and levels, and to monitor discharge. However discharge formulas perform poorly at large opening and large submergence.
Belaud, Gilles, Cassan, Ludovic
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Theory of one-element pumps for propulsion [PDF]

A basic theory for one-element propulsion pumps is developed. A limit to the obtainable efficiency is established and relationships among pump-performance parameters that result in the greatest efficiency are indicated.
Levy, J.
core   +1 more source

System Identification of Robotic Fish Swimming Reveals Roles of Reactive and Resistive Fluid Force in Two Distinct Swimming Gaits

Advanced Intelligent Systems, EarlyView.
System identification and particle image velocimetry reveal how a modular robotic fish changes thrust physics across gaits. A traveling‐wave, fish‐like motion draws thrust from resistive drag, while a resonant standing‐wave motion is driven by reactive pressure.
Donghao Li, Hankun Deng, Kundan Panta, Azar Panah, Bo Cheng   +4 more
wiley   +1 more source

A Soft Robotic Jellyfish with Decoupled Actuators for Agile 3D Locomotion

Advanced Intelligent Systems, EarlyView.
This study presents a soft robotic jellyfish featuring a functionally decoupled actuation architecture. By separating propulsion, steering, and vertical regulation into independent modules, the robot overcomes conventional coupled‐motion limitations. Utilizing a passive‐valve‐based differential drag strategy and lateral water jets, it achieves agile 3D
Zhuoheng Li, Ze Huang, Salvador Pané, Josep Puigmartí‐Luis, Jiwan Kim, Ji‐Hun Bae, Bumjin Jang   +6 more
wiley   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source

Multimodal Image Guidance in Subthalamic Deep Brain Stimulation for Parkinson's Disease

Annals of Neurology, EarlyView.
Objective Accurate electrode placement and individual stimulation parameters influence the outcomes of subthalamic deep brain stimulation in Parkinson's disease. Neuroimaging‐based models can help evaluate how electrode placement impacts improvement, aiming to reduce the burden of programming.
Patricia Zvarova, Christina van der Linden, Ningfei Li, Konstantin Butenko, Thea Berger, Garance M. Meyer, Ilkem Aysu Sahin, Lukas L. Goede, Bahne H. Bahners, Barbara Hollunder, Till A. Dembek, Andrew R. Pines, Martin Reich, Jens Volkmann, Vincent J. J. Odekerken, Rob M. A. de Bie, Xin Xu, Zhipei Ling, Chen Yao, Andrea A. Kühn, Surjo R. Soekadar, Kerstin Ritter, Michael T. Barbe, Veerle Visser‐Vandewalle, Michael D. Fox, Jan Niklas Petry‐Schmelzer, Nanditha Rajamani, Andreas Horn   +27 more
wiley   +1 more source

Potassium Migration of Chestnut Shell Ashes Under Oxidizing Atmosphere and Its Modification Mechanism by Additives

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Biomass energy plays a critical role in alleviating environmental pressures. However, its relatively high content of alkali metals (especially for potassium) would cause ash‐related issues during combustion. To mitigate these issues, the potassium migration behaviors during chestnut shell (CS) conversion and the modification mechanisms of ...
Meijie Zhou, Weijie Guo, Fenghai Li, Xuefei Liu, Ziqiang Yang, Mingjie Ma, Yitian Fang   +6 more
wiley   +1 more source