Search scope:
排序: Display mode:
Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0689-z
Keywords: surrogate model gas face seal fault diagnosis nonlinear dynamics tribology
Frontiers of Structural and Civil Engineering Pages 1086-1099 doi: 10.1007/s11709-023-0976-8
Keywords: RBF surrogate model turbine support structures
Frontiers in Energy 2022, Volume 16, Issue 2, Pages 277-291 doi: 10.1007/s11708-021-0731-6
Keywords: sooting tendency yield sooting index Bayesian multiple kernel learning surrogate assessment surrogate
Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 3, Pages 378-395 doi: 10.1007/s11709-022-0899-9
Keywords: optimization surrogate models artificial neural network SAP2000 genetic algorithm
Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN
Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4, Pages 907-929 doi: 10.1007/s11709-020-0628-1
Keywords: two-stage method modal strain energy surrogate model GMDH optimization damage detection
Synergistic optimization framework for the process synthesis and design of biorefineries
Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 251-273 doi: 10.1007/s11705-021-2071-9
Keywords: biotechnology surrogate modelling superstructure optimization simulation-based optimization process
A surrogate-based optimization algorithm for network design problems Article
Meng LI, Xi LIN, Xi-qun CHEN
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11, Pages 1693-1704 doi: 10.1631/FITEE.1601403
Keywords: Network design problem Surrogate-based optimization Transportation planning Heuristics
Frontiers of Mechanical Engineering 2022, Volume 17, Issue 4, doi: 10.1007/s11465-022-0708-0
Keywords: shape−performance integrated digital twin (SPI-DT) multi-level fusion modeling (M-LFM) surrogate model
Tall Buildings with Dynamic Facade Under Winds Article
Fei Ding, Ahsan Kareem
Engineering 2020, Volume 6, Issue 12, Pages 1443-1453 doi: 10.1016/j.eng.2020.07.020
Burgeoning growth of tall buildings in urban areas around the world is placing new demands on their performance under winds. This involves selection of the building form that minimizes wind loads and structural topologies that efficiently transfer loads. Current practice is to search for optimal shapes, but this limits buildings with static or fixed form. Aerodynamic shape tailoring that consists of modifying the external form of the building has shown great promise in reducing wind loads and associated structural motions as reflected in the design of Taipei 101 and Burj Khalifa. In these buildings, corner modifications of the cross-section and tapering along the height are introduced. An appealing alternative is to design a building that can adapt its form to the changing complex wind environment in urban areas with clusters of tall buildings, i.e., by implementing a dynamic facade. To leap beyond the static shape optimization, autonomous dynamic morphing of the building shape is advanced in this study, which is implemented through a cyber–physical system that fuses together sensing, computing, actuating and engineering informatics. This approach will permit a building to intelligently morph its profile to minimize the source of dynamic wind load excitation, and holds the promise of revolutionizing tall buildings from conventional static to dynamic facades by taking advantage of the burgeoning advances in computational design.
Keywords: buildings Aerodynamic shape tailoring Autonomous morphing Cyber–physical system Computational design Surrogate
An experimental study on spray auto-ignition of RP-3 jet fuel and its surrogates
Yaozong DUAN, Wang LIU, Zhen HUANG, Dong HAN
Frontiers in Energy 2021, Volume 15, Issue 2, Pages 396-404 doi: 10.1007/s11708-020-0715-y
Keywords: RP-3 jet fuel surrogate spray auto-ignition constant volume combustion chamber
Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design Perspective
Teng Zhou, Rafiqul Gani, Kai Sundmacher
Engineering 2021, Volume 7, Issue 9, Pages 1231-1238 doi: 10.1016/j.eng.2020.12.022
The world’s increasing population requires the process industry to produce food, fuels, chemicals, and consumer products in a more efficient and sustainable way. Functional process materials lie at the heart of this challenge. Traditionally, new advanced materials are found empirically or through trial-and-error approaches. As theoretical methods and associated tools are being continuously improved and computer power has reached a high level, it is now efficient and popular to use computational methods to guide material selection and design. Due to the strong interaction between material selection and the operation of the process in which the material is used, it is essential to perform material and process design simultaneously. Despite this significant connection, the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required. Hybrid modeling provides a promising option to tackle such complex design problems. In hybrid modeling, the material properties, which are computationally expensive to obtain, are described by data-driven models, while the well-known process-related principles are represented by mechanistic models. This article highlights the significance of hybrid modeling in multiscale material and process design. The generic design methodology is first introduced. Six important application areas are then selected: four from the chemical engineering field and two from the energy systems engineering domain. For each selected area, state-ofthe- art work using hybrid modeling for multiscale material and process design is discussed. Concluding remarks are provided at the end, and current limitations and future opportunities are pointed out.
Keywords: Data-driven Surrogate model Machine learning Hybrid modeling Material design Process optimization
Title Author Date Type Operation
Method for solving the nonlinear inverse problem in gas face seal diagnosis based on surrogate models
Journal Article
Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate
Journal Article
An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency
Journal Article
double-layer barrel vaults using genetic and pattern search algorithms and optimized neural network as surrogate
Journal Article
approach for structural damage detection using meta-heuristic algorithms and group method of data handling surrogate
Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN
Journal Article
Synergistic optimization framework for the process synthesis and design of biorefineries
Journal Article
A surrogate-based optimization algorithm for network design problems
Meng LI, Xi LIN, Xi-qun CHEN
Journal Article
M-LFM: a multi-level fusion modeling method for shape−performance integrated digital twin of complex structure
Journal Article
An experimental study on spray auto-ignition of RP-3 jet fuel and its surrogates
Yaozong DUAN, Wang LIU, Zhen HUANG, Dong HAN
Journal Article