Zobrazeno 1 - 10
of 1 790
pro vyhledávání: '"multi-fidelity"'
Publikováno v:
气体物理, Vol 9, Iss 4, Pp 1-8 (2024)
Data-driven deep learning modeling has been applied in different disciplines such as mechanics and materials. The computational accuracy of deep learning modeling requires a large amount of high-fidelity data. In many real-world applications, only a
Externí odkaz:
https://doaj.org/article/c8c674988e944079a90cef499762e846
Publikováno v:
International Journal of Numerical Methods for Heat & Fluid Flow, 2024, Vol. 34, Issue 9, pp. 3615-3634.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/HFF-12-2023-0745
Publikováno v:
Heliyon, Vol 10, Iss 18, Pp e38103- (2024)
Accurate numerical modeling of multiphase flow in subsurface oil and gas reservoirs is critical for optimizing hydrocarbon recovery. However, traditional physics-based algorithms face substantial computational hurdles due to the need for fine grid re
Externí odkaz:
https://doaj.org/article/5aa8e10f734a4d17bf532e3813140035
Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion
Autor:
Francis Ogoke, Quanliang Liu, Olabode Ajenifujah, Alexander Myers, Guadalupe Quirarte, Jonathan Malen, Jack Beuth, Amir Barati Farimani
Publikováno v:
Materials & Design, Vol 245, Iss , Pp 113181- (2024)
Defects in Laser Powder Bed Fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. Experimental in-situ monitoring of the three-dimensional melt pool physical fields is challenging,
Externí odkaz:
https://doaj.org/article/56cf0785913446acb480dbad30cd3441
Autor:
Andrea Serani, Matteo Diez
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 11, p 1979 (2024)
This paper explores the integration of advanced machine learning (ML) techniques within simulation-based design optimization (SBDO) processes for naval applications, focusing on the hydrodynamic shape optimization of the DTMB 5415 destroyer model. Th
Externí odkaz:
https://doaj.org/article/f08d2a59586d4a538c84c92af687bb2f
Autor:
Fuad Hasan, Abderrachid Hamrani, Md Munim Rayhan, Tyler Dolmetsch, Dwayne McDaniel, Arvind Agarwal
Publikováno v:
Journal of Manufacturing and Materials Processing, Vol 8, Iss 5, p 222 (2024)
Thermal simulation is essential in wire-arc-directed energy deposition (W-DED) to accurately estimate temperature distributions, impacting residual stress and distortion in components. Proper calibration of simulation models minimizes inaccuracies ca
Externí odkaz:
https://doaj.org/article/8c95684ccdfc46a09b8b8aca28c2b8a7
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 3576-3592 (2023)
In this work, metamodeling was performed to conduct efficiency-based design optimization (EBDO) of an H-rotor VAWT coupled with fixed guiding-walls surrounding its rotor. A design of experiments (DoE) created sampling points from the desired design s
Externí odkaz:
https://doaj.org/article/93ca81c846b448be972f3904273435e8
Autor:
Tharathep Phiboon, Auraluck Pichitkul, Suradet Tantrairatn, Sujin Bureerat, Masahiro Kanazaki, Atthaphon Ariyarit
Publikováno v:
Symmetry, Vol 16, Iss 8, p 1094 (2024)
The multiple additional sampling point method has become popular for use in Efficient Global Optimization (EGO) to obtain aerodynamically shaped designs in recent years. It is a challenging task to study the influence of adding multi-sampling points,
Externí odkaz:
https://doaj.org/article/947f6e30985b4ed8b42a688174ca88b3
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 10, Iss 1, Pp 1-21 (2023)
Abstract In the present work, we introduce a novel approach to enhance the precision of reduced order models by exploiting a multi-fidelity perspective and DeepONets. Reduced models provide a real-time numerical approximation by simplifying the origi
Externí odkaz:
https://doaj.org/article/c02ce668480c4d2d9e1e52a62c37228b
Publikováno v:
Japan Architectural Review, Vol 7, Iss 1, Pp n/a-n/a (2024)
Abstract This study introduces an approach for probabilistic seismic performance estimation, which focuses on the probability of intensity measures exceeding a specified value based on engineering demand parameters. Conventional methods face challeng
Externí odkaz:
https://doaj.org/article/86ccfeee7cf94a2faffb79b13794f064