Results 51 to 60 of about 30,371 (174)

Seismic Design of Concrete Dams: An Integrated Risk‐Informed Performance‐Based (RIPB) Framework

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT This paper advances the integration of risk‐informed principles into the seismic design of dams—a domain long guided by standards‐based, largely deterministic approaches. While performance‐based earthquake engineering is well established for buildings and bridges, its systematic adoption in dam engineering remains limited. We first address two
M. Amin Hariri‐Ardebili, Larry K. Nuss
wiley   +1 more source

Seasonal Predictions and Their Applications in the Mediterranean Region: Part I—Sources of Predictability and Prediction Skill

International Journal of Climatology, EarlyView.
The ability to predict climate fluctuations at seasonal timescales offers significant socio‐economic benefits. However, limited understanding of predictability mechanisms and model errors hinders forecast quality. Recent research has improved forecasting systems and data quality.
Gualdi Silvio, Javier García‐Serrano, Constantin Ardilouze, Silvia Terzago, Veronica Torralba, Wafae Badi, Lauriane Batté, Fatima Driouech, Kristina Fröhlich, Ernesto Rodriguez Camino, Esteban Rodriguez Guisado, Massimiliano Pasqui, Andrea Toreti   +12 more
wiley   +1 more source

On the Mean‐Field Limit of Consensus‐Based Methods

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT Consensus‐based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivative free sampling method referred to as consensus‐based sampling (CBS). In this paper, we investigate the “mean‐field limit” of a class of consensus methods, including
Marvin Koß, Simon Weissmann, Jakob Zech
wiley   +1 more source

Spectral Representation of Neurochemicals With Phase, Frequency Offset, and Lineshape Invariance: Application to JPRESS for In Vivo Concentration and T2 Mapping by Deep Learning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Using artificial intelligence neural networks to generate a representation that maps the input directly to neurochemical concentrations and metabolite‐level average transverse relaxation times (T2). Methods The proposed model used time‐domain JPRESS data as input and was trained to be invariant to phase shifts, frequency offsets, and ...
Yan Zhang, Jun Shen
wiley   +1 more source

Experimental Modal Analysis‐Driven Gaussian Process Regression Modeling of Rectangular Steel Beams With Various Hole Geometries

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Understanding the dynamic behavior of structural components is crucial for optimizing performance and ensuring structural integrity. This study presents a new method that combines a systematic experimental investigation of four distinct hole geometries (circular, square, compact rectangular, and long rectangular) with varying hole counts, all ...
Amir Hossein Rabiee, Majid Rajaei, Mohammad Hossein Mahdavi Nasab, Parsa Shafiei   +3 more
wiley   +1 more source

Forecast verification using information and noise

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Verification of weather forecasts is usually expressed in terms of total error metrics. This is useful for end users of the forecasts but does not allow evaluation of the intrinsic information content of the forecasts. To overcome this limitation, we propose a new total error decomposition into information and noise error measures, connect it to ...
Massimo Bonavita, Alan J. Geer
wiley   +1 more source

Simulating Quantum State Transfer Between Distributed Devices Using Noisy Interconnects

Advanced Quantum Technologies, EarlyView.
Noisy connections challenge future networked quantum computers. This work presents a practical method to address this by simulating an ideal state transfer over noisy interconnects. The approach reduces the high sampling cost of previous methods, an advantage that improves as interconnect quality gets better.
Marvin Bechtold, Johanna Barzen, Frank Leymann, Alexander Mandl   +3 more
wiley   +1 more source

Methodological Frameworks for Computational Electrocatalysis: From Theory to Practice

Small Methods, EarlyView.
Computational modeling is widely used to investigate electrocatalytic reactions, yet accurately describing electrochemical interfaces remains challenging. This review outlines theoretical and computational strategies, based on density functional theory, to model reaction thermodynamics, solvation effects, applied bias, and kinetics.
Michele Re Fiorentin, Michele G. Bianchi, Magnus A. H. Christiansen, Anna Ciotti, Francesca Risplendi, Wei Wang, Elvar Ö. Jónsson, Hannes Jónsson, Giancarlo Cicero   +8 more
wiley   +1 more source

Novel Bio‐Based Polyurethane Elastomers Customizable for Orthopedic Devices: Toughness, Rapid Degradability, and Safety

SusMat, EarlyView.
ABSTRACT Given the increasing global demand for sustainable materials and growing concerns over the depletion of petrochemical resources, we report the synthesis of an amorphous bio‐derived polyester diol, and this diol was polymerized with various isocyanates and butanediol, yielding a novel series of bio‐based polyurethane elastomers (BPUEs). Notably,
Chenxin Xu, Yushu Tian, Hengheng Zhao, Jiadong Wang, Qingjun Wang, Xiang Lin, Jun Liu, Zhao Wang, Xuan Qin, Liqun Zhang   +9 more
wiley   +1 more source

Quantifying Structural Complexity, Effort, and Performance: An Early Experiment Using Network Design Tasks

Systems Engineering, EarlyView.
ABSTRACT Structural Complexity is perceived as driving cost in system development, yet managing it effectively requires empirical understanding. This study investigates human decision‐making using a toy transportation‐style network design task, focusing on how Structural Complexity, Effort, and Performance interact. Seventy‐four participants (primarily
Alfonso Lanza, Joshua Sutherland, Marc‐Andre Chavy‐Macdonald, Olivier L. de Weck   +3 more
wiley   +1 more source