Results 21 to 30 of about 6,794 (215)

A consistent computational fluid dynamics surrogate model for wind turbine interaction including atmospheric stability [PDF]

Wind Energy Science
Wind turbine wake and blockage effects can reduce the energy yield in wind farms, and fast models are required to mitigate these effects by wind farm layout optimization.
M. P. van der Laan, A. Meyer Forsting, P.-E. Réthoré   +2 more
doaj   +1 more source

Universal Prediction Distribution for Surrogate Models [PDF]

SIAM/ASA Journal on Uncertainty Quantification, 2017
The use of surrogate models instead of computationally expensive simulation codes is very convenient in engineering. Roughly speaking, there are two kinds of surrogate models: the deterministic and the probabilistic ones. These last are generally based on Gaussian assumptions.
Ben Salem, Malek, Roustant, Olivier, Gamboa, Fabrice, Tomaso, Lionel   +3 more
openaire   +5 more sources

Comparison of a Response Surface Method and Artificial Neural Network in Predicting the Aerodynamic Performance of a Wind Turbine Airfoil and Its Optimization

Applied Sciences, 2020
To find the optimal design for an engineering object, thousands of (or even more) simulations should be implemented to obtain the outcome data for the variously designed objects.
Sahuck Oh
doaj   +1 more source

A general approach to risk modeling using partial surrogate markers with application to perioperative acute kidney injury

Diagnostic and Prognostic Research, 2017
Background Surrogate outcomes are often utilized when disease outcomes are difficult to directly measure. When a biological threshold effect exists, surrogate outcomes may only represent disease in specific subpopulations.
Derek K. Smith, Loren E. Smith, Frederic T. Billings, Jeffrey D. Blume   +3 more
doaj   +1 more source

Development of surrogate-optimization models for a novel transcritical power cycle integrated with a small modular reactor

Energy and AI
In recent years, various types of surrogate optimization models have been proposed to reduce the computational time and to improve the emulation accuracy.
Yili Zhang, Jacob Bryan, Geordie Richards, Hailei Wang   +3 more
doaj   +1 more source

A Kriging Surrogate Model for the Interference Reduction in the Settlement Surveillance Sensors of Steel Transmission Towers

Applied Sciences, 2019
The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers highly
Jiajia Shi, Liu Chu, Eduardo Souza de Cursi   +2 more
doaj   +1 more source

Development of a diesel surrogate for improved autoignition prediction: Methodology and detailed chemical kinetic modeling

Applications in Energy and Combustion Science, 2023
While the surrogate fuel approach has been successfully applied to the simulation of the combustion behaviors of complex gasoline and jet fuels, its application to diesel fuels has been challenging.
Goutham Kukkadapu, Russell Whitesides, Mengyuan Wang, Scott W. Wagnon, Marco Mehl, Charles K. Westbrook, Robert McCormick, Chih-Jen Sung, William J. Pitz   +8 more
doaj   +1 more source

A surrogate FRAX model for Nepal [PDF]

Archives of Osteoporosis
Abstract Summary A surrogate FRAX® model for Nepal has been constructed using age- and sex-specific hip fracture rates for Indians living in Singapore and age- and sex-specific mortality rates from Nepal. Introduction FRAX
Johansson, H., Pandey, D., Lorentzon, M., Harvey, N.C., McCloskey, E.V., Kanis, J.A.   +5 more
openaire   +5 more sources

COMPARATIVE STUDY OF XAI USING FORMAL CONCEPT LATTICE AND LIME

ICTACT Journal on Soft Computing, 2022
Local Interpretable Model Agnostic Explanation (LIME) is a technique to explain a black box machine learning model using a surrogate model approach.
Bhaskaran Venkatsubramaniam, Pallav Kumar Baruah   +1 more
doaj   +1 more source

Sensitivity analysis and optimization method of partition surrogate model based on physical knowledge driven

Hangkong gongcheng jinzhan
The problem of "dimensionality disaster" of design variable is a key technical problem that restricts the application of current agent-based optimization algorithms.
SHAO Mengying, XIA Lu, ZHANG Wei, ZHAO Ke   +3 more
doaj   +1 more source