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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

Abstract: In this context, several approaches for superstructure optimization based on different surrogate modelsThe results indicate that even though surrogate-based optimization approaches alleviate the underlyingThe development of appropriate surrogate models, comprising the selection of surrogate type, samplingThese findings invite for a critical assessment of surrogate-based optimization approaches and point

Keywords： biotechnology     surrogate modelling     superstructure optimization     simulation-based optimization     process    

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Method for solving the nonlinear inverse problem in gas face seal diagnosis based on surrogate models

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0689-z

Abstract: The presented work develops a surrogate-model-assisted method for solving the nonlinear inverse problemLatin hypercube design and then performs an iterative routine that benefits from the rapidity of the surrogate

Keywords： surrogate model     gas face seal     fault diagnosis     nonlinear dynamics     tribology    

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Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 7,   Pages 1086-1099 doi: 10.1007/s11709-023-0976-8

Abstract: Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate

Keywords： RBF     surrogate model     turbine support structures    

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An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 277-291 doi: 10.1007/s11708-021-0731-6

Abstract: Based on the database, a novel predicting model of YSI values for surrogate fuels was proposed with theThe BMKL model provides an accurate and low-cost approach to assess surrogate performances of diesel,Particularly, this model is one of the first attempts to predict the sooting tendencies of surrogateDuring surrogate formulation, the BMKL model can be used to shrink the surrogate candidate list in termsof sooting tendency and ensure the optimal surrogate has a satisfying matching level of soot behaviors

Keywords： sooting tendency     yield sooting index     Bayesian multiple kernel learning     surrogate assessment     surrogate    

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A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 12,   Pages 1813-1829 doi: 10.1007/s11709-023-0007-9

Abstract: To reduce the heavy computational burden, a surrogate model of a dome structure was constructed to solvequantification framework using fully quantitative variance- and distribution-based methods through the surrogateFinally, the effects of the sample size and correlation function on the accuracy of the surrogate modelas well as the effects of the surrogate accuracy and failure probability on the sensitivity index valuesThe results show that surrogate modeling has high computational efficiency and acceptable accuracy in

Keywords： large-scale dome structure     surrogate model     global sensitivity analysis     uncertainty quantification    

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double-layer barrel vaults using genetic and pattern search algorithms and optimized neural network as surrogate

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 3,   Pages 378-395 doi: 10.1007/s11709-022-0899-9

Abstract: The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce

Keywords： optimization     surrogate models     artificial neural network     SAP2000     genetic algorithm    

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Understanding coupled factors that affect the modelling accuracy of typical planar compliant mechanisms

Guangbo HAO,Haiyang LI,Suzen KEMALCAN,Guimin CHEN,Jingjun YU

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 2,   Pages 129-134 doi: 10.1007/s11465-016-0392-z

Abstract: equivalent modulus using nonlinear finite element analysis (FEA) to reflect coupled factors in affecting the modelling

Keywords： coupling factors     modelling accuracy     compliant mechanisms     equivalent modulus    

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approach for structural damage detection using meta-heuristic algorithms and group method of data handling surrogate

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

Abstract: performance of an efficient two-stage methodology which is applied in a damage detection system using a surrogatemodal property change vector is evaluated using the group method of data handling (GMDH) network as a surrogateFinally, in order to achieve the most generalized neural network as a surrogate model, GMDH performance

Keywords： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 3,   Pages 393-410 doi: 10.1007/s11709-024-1060-8

Abstract: The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogateThe surrogate models are trained using response data obtained from the monitored structure through aThe proposed approach involves training a single surrogate model that can quickly predict the locationTo achieve the most generalized surrogate model, the study explores different types of layers and hyperparameters

Keywords： vibration-based damage detection     deep neural network     full-scale structures     finite element model updating     noisy incomplete modal data    

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3D fracture modelling and limit state analysis of prestressed composite concrete pipes

Pengfei HE, Yang SHEN, Yun GU, Pangyong SHEN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 165-175 doi: 10.1007/s11709-018-0484-4

Abstract: In this manuscript, we study fracture of prestressed cylindrical concrete pipes. Such concrete pipes play a major role in tunneling and underground engineering. The structure is modelled fully in 3D using three-dimensional continuum elements for the concrete structure which beam elements are employed to model the reinforcement. This allows the method to capture important phenomena compared to a pure shell model of concrete. A continuous approach to fracture is chosen when concrete is subjected to compressive loading while a combined continuous-discrete fracture method is employed in tension. The model is validated through comparisons with experimental data.

Keywords： cylindrical concrete structures     limit state analysis     3D fracture modelling     prestressed composite pipes    

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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

Abstract: We adopt a surrogate-based optimization (SBO) framework to solve three featured categories of NDPs (continuous

Keywords： Network design problem     Surrogate-based optimization     Transportation planning     Heuristics    

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ANN-based empirical modelling of pile behaviour under static compressive loading

Abdussamad ISMAIL

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 4,   Pages 594-608 doi: 10.1007/s11709-017-0446-2

Abstract: Artificial neural networks have been widely used over the past two decades to successfully develop empirical models for a variety of geotechnical problems. In this paper, an empirical model based on the product-unit neural network (PUNN) is developed to predict the load-deformation behaviour of piles based SPT values of the supporting soil. Other parameters used as inputs include particle grading, pile geometry, method of installation as well as the elastic modulus of the pile material. The model is trained using full-scale pile loading tests data retrieved from FHWA deep foundations database. From the results obtained, it is observed that the proposed model gives a better simulation of pile load-deformation curves compared to the Fleming’s hyperbolic model and t-z approach.

Keywords： piles in compression     load-deformation behaviour     product-unit neural network    

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Joint slip investigation based on finite element modelling verified by experimental results on wind turbine

Saleh YAGHOOBI, Ahmad SHOOSHTARI

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 3,   Pages 341-351 doi: 10.1007/s11709-017-0393-y

Abstract:

Slippage corresponds to the relative displacement of a bolted joint subjected to shear loads since the construction clearance between the bolt shank and the bolthole at assembly can cause joint slip. Deflections of towers with joint slippage effects is up to 1.9 times greater than the displacements obtained by linear analytical methods. In this study, 8 different types of joints are modelled and studied in the finite element program, and the results are verified by the experimental results which have been done in the laboratory. Moreover, several types of joints have been modelled and studied and load-deformation curves have also been presented. Finally, joint slip data for different types of angles, bolt diameter and bolt arrangements are generated. Thereupon, damping ratios (z) for different types of connections are reported. The study can be useful to help in designing of wind turbine towers with a higher level of accuracy and safety.

Keywords： Joint slip     cyclic loading     Finite element modelling     Experimental joint behavior     damping ratios (   

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Kinetic-compartmental modelling of potassium-containing cellulose feedstock gasification

Attila Egedy, Lívia Gyurik, Tamás Varga, Jun Zou, Norbert Miskolczi, Haiping Yang

Frontiers of Chemical Science and Engineering 2018, Volume 12, Issue 4,   Pages 708-717 doi: 10.1007/s11705-018-1767-y

Abstract:

Biomass is of growing interest as a secondary energy source and can be converted to fuels with higher energy density especially by pyrolysis or gasification. Understanding the mechanism and the kinetics of biomass pyrolysis (thermal decomposition) and gasification (conversion of organic material to gases) could be the key to the design of industrial devices capable of processing vast amounts of biomass feedstock. In our work real product components obtained in pyrolysis were took into consideration as well as char and oil as lumped components, and the kinetic constants for a biomass model compound (cellulose) pyrolysis and gasification were identified based on a proposed simplified reaction mechanism within a compartment model structure. A laboratory scale reactor was used for the physical experiments containing consecutive fast pyrolysis and gasification stages using alkali metal (K) containing feedstock, which has a significant effect on the cellulose pyrolysis and gasification. The detailed model was implemented in MATLAB/Simulink environment, and the unknown kinetic parameters were identified based on experimental data. The model was validated based on measurement data, and a good agreement was found. Based on the validated first principle model the optimal parameters were determined as 0.15 mL/min steam flow rate, and 4% K content.

Keywords： biomass pyrolysis     kinetic parameter identification     compartment modelling     optimisation    

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Numerical modelling of reinforced concrete flexural members strengthened using textile reinforced mortars

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 4,   Pages 649-668 doi: 10.1007/s11709-023-0919-4

Abstract: Externally bonded (EB) and near-surface mounted (NSM) bonding are two widely adopted and researched strengthening methods for reinforced-concrete structures. EB composite substrates are easy to reach and repair using appropriate surface treatments, whereas NSM techniques can be easily applied to the soffit and concrete member sides. The EB bonded fiber-reinforced polymer (FRP) technique has a significant drawback: combustibility, which calls for external protective agents, and textile reinforced mortar (TRM), a class of EB composites that is non-combustible and provides a similar functionality to any EB FRP-strengthened substrate. This study employs a finite element analysis technique to investigate the failing failure of carbon textile reinforced mortar (CTRM)-strengthened reinforced concrete beams. The principal objective of this numerical study was to develop a finite element model and validate a set of experimental data in existing literature. A set of seven beams was modelled and calibrated to obtain concrete damage plasticity (CDP) parameters. The predicted results, which were in the form of load versus deflection, load versus rebar strain, tensile damage, and compressive damage patterns, were in good agreement with the experimental data. Moreover, a parametric study was conducted to verify the applicability of the numerical model and study various influencing factors such as the concrete strength, internal reinforcement, textile roving spacing, and externally-applied load span. The ultimate load and deflection of the predicted finite element results had a coefficient of variation (COV) of 6.02% and 5.7%, respectively. A strain-based numerical comparison with known methods was then conducted to investigate the debonding mechanism. The developed finite element model can be applied and tailored further to explore similar TRM-strengthened beams undergoing debonding, and the preventive measures can be sought to avoid premature debonding.

Keywords： fiber reinforced polymer     textile reinforced mortar     finite element analysis     concrete damage plasticity     calibration and validation     parametric study    

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Title Author Date Type Operation

Synergistic optimization framework for the process synthesis and design of biorefineries

Journal Article

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

A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale

Journal Article

double-layer barrel vaults using genetic and pattern search algorithms and optimized neural network as surrogate

Journal Article

Understanding coupled factors that affect the modelling accuracy of typical planar compliant mechanisms

Guangbo HAO,Haiyang LI,Suzen KEMALCAN,Guimin CHEN,Jingjun YU

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

A deep neural network based surrogate model for damage identification in full-scale structures with incomplete

Journal Article

3D fracture modelling and limit state analysis of prestressed composite concrete pipes

Pengfei HE, Yang SHEN, Yun GU, Pangyong SHEN

Journal Article

A surrogate-based optimization algorithm for network design problems

Meng LI, Xi LIN, Xi-qun CHEN

Journal Article

ANN-based empirical modelling of pile behaviour under static compressive loading

Abdussamad ISMAIL

Journal Article

Joint slip investigation based on finite element modelling verified by experimental results on wind turbine

Saleh YAGHOOBI, Ahmad SHOOSHTARI

Journal Article

Kinetic-compartmental modelling of potassium-containing cellulose feedstock gasification

Attila Egedy, Lívia Gyurik, Tamás Varga, Jun Zou, Norbert Miskolczi, Haiping Yang

Journal Article

Numerical modelling of reinforced concrete flexural members strengthened using textile reinforced mortars

Journal Article