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Synergistic optimization framework for the process synthesis and design of biorefineries

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 251-273 doi: 10.1007/s11705-021-2071-9

摘要： The conceptual process design of novel bioprocesses in biorefinery setups is an important task, which remains yet challenging due to several limitations. We propose a novel framework incorporating superstructure optimization and simulation-based optimization synergistically. In this context, several approaches for superstructure optimization based on different surrogate models can be deployed. By means of a case study, the framework is introduced and validated, and the different superstructure optimization approaches are benchmarked. The results indicate that even though surrogate-based optimization approaches alleviate the underlying computational issues, there remains a potential issue regarding their validation. The development of appropriate surrogate models, comprising the selection of surrogate type, sampling type, and size for training and cross-validation sets, are essential factors. Regarding this aspect, satisfactory validation metrics do not ensure a successful outcome from its embedded use in an optimization problem. Furthermore, the framework’s synergistic effects by sequentially performing superstructure optimization to determine candidate process topologies and simulation-based optimization to consolidate the process design under uncertainty offer an alternative and promising approach. These findings invite for a critical assessment of surrogate-based optimization approaches and point out the necessity of benchmarking to ensure consistency and quality of optimized solutions.

关键词： biotechnology     surrogate modelling     superstructure optimization     simulation-based optimization     process design    

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

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-022-0689-z

摘要： Physical models carry quantitative and explainable expert knowledge. However, they have not been introduced into gas face seal diagnosis tasks because of the unacceptable computational cost of inferring the input fault parameters for the observed output or solving the inverse problem of the physical model. The presented work develops a surrogate-model-assisted method for solving the nonlinear inverse problem in limited physical model evaluations. The method prepares a small initial database on sites generated with a Latin hypercube design and then performs an iterative routine that benefits from the rapidity of the surrogate models and the reliability of the physical model. The method is validated on simulated and experimental cases. Results demonstrate that the method can effectively identify the parameters that induce the abnormal signal output with limited physical model evaluations. The presented work provides a quantitative, explainable, and feasible approach for identifying the cause of gas face seal contact. It is also applicable to mechanical devices that face similar difficulties.

关键词： 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

《结构与土木工程前沿（英文）》   页码 1086-1099 doi: 10.1007/s11709-023-0976-8

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

关键词： 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

《能源前沿（英文）》 2022年 第16卷 第2期   页码 277-291 doi: 10.1007/s11708-021-0731-6

摘要： An integrated and systematic database of sooting tendency with more than 190 kinds of fuels was obtained through a series of experimental investigations. The laser-induced incandescence (LII) method was used to acquire the 2D distribution of soot volume fraction, and an apparatus-independent yield sooting index (YSI) was experimentally obtained. Based on the database, a novel predicting model of YSI values for surrogate fuels was proposed with the application of a machine learning method, named the Bayesian multiple kernel learning (BMKL) model. A high correlation coefficient (0.986) between measured YSIs and predicted values with the BMKL model was obtained, indicating that the BMKL model had a reliable and accurate predictive capacity for YSI values of surrogate fuels. The BMKL model provides an accurate and low-cost approach to assess surrogate performances of diesel, jet fuel, and biodiesel in terms of sooting tendency. Particularly, this model is one of the first attempts to predict the sooting tendencies of surrogate fuels that concurrently contain hydrocarbon and oxygenated components and shows a satisfying matching level. During surrogate formulation, the BMKL model can be used to shrink the surrogate candidate list in terms of sooting tendency and ensure the optimal surrogate has a satisfying matching level of soot behaviors. Due to the high accuracy and resolution of YSI prediction, the BMKL model is also capable of providing distinguishing information of sooting tendency for surrogate design.

关键词： sooting tendency     yield sooting index     Bayesian multiple kernel learning     surrogate assessment     surrogate formulation    

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

《结构与土木工程前沿（英文）》 2023年 第17卷 第3期   页码 378-395 doi: 10.1007/s11709-022-0899-9

摘要： This paper presents a combined method based on optimized neural networks and optimization algorithms to solve structural optimization problems. The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce the number of computations for structural analysis. First, the OANN is trained appropriately. Subsequently, the main optimization problem is solved using the OANN and a population-based algorithm. The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithm (GA). Finally, the abovementioned problem is solved using the optimal point obtained from the previous step and the pattern search (PS) algorithm. To evaluate the performance of the proposed method, two numerical examples are considered. In the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigated. Using the GA reduces the elapsed time by approximately 50% compared with using the AOA. Results show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural optimization problems and achieve the same optimal design. However, the OANN + GA + PS algorithm requires significantly fewer function evaluations to achieve the same accuracy as the OANN + AOA + PS algorithm.

关键词： 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

《机械工程前沿（英文）》 2016年 第11卷 第2期   页码 129-134 doi: 10.1007/s11465-016-0392-z

摘要：

In order to accurately model compliant mechanism utilizing plate flexures, qualitative planar stress (Young’s modulus) and planar strain (plate modulus) assumptions are not feasible. This paper investigates a quantitative equivalent modulus using nonlinear finite element analysis (FEA) to reflect coupled factors in affecting the modelling accuracy of two typical distributed-compliance mechanisms. It has been shown that all parameters have influences on the equivalent modulus with different degrees; that the presence of large load-stiffening effect makes the equivalent modulus significantly deviate from the planar assumptions in two ideal scenarios; and that a plate modulus assumption is more reasonable for a very large out-of-plane thickness if the beam length is large.

关键词： 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

《结构与土木工程前沿（英文）》 2020年 第14卷 第4期   页码 907-929 doi: 10.1007/s11709-020-0628-1

摘要： In this study, the performance of an efficient two-stage methodology which is applied in a damage detection system using a surrogate model of the structure has been investigated. In the first stage, in order to locate the damage accurately, the performance of the modal strain energy based index for using different numbers of natural mode shapes has been evaluated using the confusion matrix. In the second stage, to estimate the damage extent, the sensitivity of most used modal properties due to damage, such as natural frequency and flexibility matrix is compared with the mean normalized modal strain energy (MNMSE) of suspected damaged elements. Moreover, a modal property change vector is evaluated using the group method of data handling (GMDH) network as a surrogate model during damage extent estimation by optimization algorithm; in this part of methodology, the performance of the three popular optimization algorithms including particle swarm optimization (PSO), bat algorithm (BA), and colliding bodies optimization (CBO) is examined and in this regard, root mean square deviation ( ) based on the modal property change vector has been proposed as an objective function. Furthermore, the effect of noise in the measurement of structural responses by the sensors has also been studied. Finally, in order to achieve the most generalized neural network as a surrogate model, GMDH performance is compared with a properly trained cascade feed-forward neural network (CFNN) with log-sigmoid hidden layer transfer function. The results indicate that the accuracy of damage extent estimation is acceptable in the case of integration of PSO and MNMSE. Moreover, the GMDH model is also more efficient and mimics the behavior of the structure slightly better than CFNN model.

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

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

Pengfei HE, Yang SHEN, Yun GU, Pangyong SHEN

《结构与土木工程前沿（英文）》 2019年 第13卷 第1期   页码 165-175 doi: 10.1007/s11709-018-0484-4

摘要： 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.

关键词： cylindrical concrete structures     limit state analysis     3D fracture modelling     prestressed composite pipes     reinforced concrete     three-point bending test    

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网络设计问题的一种代理模型优化算法 Article

Meng LI, Xi LIN, Xi-qun CHEN

《信息与电子工程前沿（英文）》 2017年 第18卷 第11期   页码 1693-1704 doi: 10.1631/FITEE.1601403

摘要： 由于其双层规划结构本质上的非凸性，交通网络设计问题一直以来都是交通规划领域中最为困难的问题之一。尤其在考虑混合了连续变量与离散变量的决策变量时，得到的混合网络设计形式进一步增加了问题的难度。本文引入了一种代理模型优化算法，用以解决三种不同种类的网络设计问题，包括连续、离散与混合的情形。我们证明了提出的算法在解决连续网络设计问题时，能够确保“渐进完全收敛”的性质，即在给定足够长的计算时间时，算法能够以概率1收敛到全局最优解。为了展示本文提出的框架在实际问题中的表现，我们用大量的算例对比了代理模型算法与大量用于解决网络设计问题的经典算法、启发式算法的效果。结果表明，以效率与精确度而论，代理模型算法是其中最优秀之一，同时它还能够有效地解决超过20个变量的较大规模的问题。本文提出的代理模型优化框架也能够用于解决交通领域的其他优化问题。

关键词： 网络设计问题；代理模型优化；交通规划；启发式算法    

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

Abdussamad ISMAIL

《结构与土木工程前沿（英文）》 2018年 第12卷 第4期   页码 594-608 doi: 10.1007/s11709-017-0446-2

摘要： 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.

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

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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

《化学科学与工程前沿（英文）》 2018年 第12卷 第4期   页码 708-717 doi: 10.1007/s11705-018-1767-y

摘要：

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.

关键词： biomass pyrolysis     kinetic parameter identification     compartment modelling     optimisation    

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

Saleh YAGHOOBI, Ahmad SHOOSHTARI

《结构与土木工程前沿（英文）》 2018年 第12卷 第3期   页码 341-351 doi: 10.1007/s11709-017-0393-y

摘要：

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.

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

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

《结构与土木工程前沿（英文）》 2023年 第17卷 第4期   页码 649-668 doi: 10.1007/s11709-023-0919-4

摘要： 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.

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

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Dynamic modelling and simulation of a post-combustion CO capture process for coal-fired power plants

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 198-209 doi: 10.1007/s11705-021-2057-7

摘要： Solvent-based post-combustion capture technologies have great potential for CO2 mitigation in traditional coal-fired power plants. Modelling and simulation provide a low-cost opportunity to evaluate performances and guide flexible operation. Composed by a series of partial differential equations, first-principle post-combustion capture models are computationally expensive, which limits their use in real time process simulation and control. In this study, we propose a first-principle approach to develop the basic structure of a reduced-order model and then the dominant factor is used to fit properties and simplify the chemical and physical process, based on which a universal and hybrid post-combustion capture model is established. Model output at steady state and trend at dynamic state are validated using experimental data obtained from the literature. Then, impacts of liquid-to-gas ratio, reboiler power, desorber pressure, tower height and their combination on the absorption and desorption effects are analyzed. Results indicate that tower height should be designed in conjunction with the flue gas flow, and the gas-liquid ratio can be optimized to reduce the reboiler power under a certain capture target.

关键词： CO2 capture     post-combustion capture     simulation     dominant factor    

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Modeling of shear walls using finite shear connector elements based on continuum plasticity

Ulf Arne GIRHAMMAR, Per Johan GUSTAFSSON, Bo KÄLLSNER

《结构与土木工程前沿（英文）》 2017年 第11卷 第2期   页码 143-157 doi: 10.1007/s11709-016-0377-3

摘要： Light-frame timber buildings are often stabilized against lateral loads by using diaphragm action of roofs, floors and walls. The mechanical behavior of the sheathing-to-framing joints has a significant impact on the structural performance of shear walls. Most sheathing-to-framing joints show nonlinear load-displacement characteristics with plastic behavior. This paper is focused on the finite element modeling of shear walls. The purpose is to present a new shear connector element based on the theory of continuum plasticity. The incremental load-displacement relationship is derived based on the elastic-plastic stiffness tensor including the elastic stiffness tensor, the plastic modulus, a function representing the yield criterion and a hardening rule, and function representing the plastic potential. The plastic properties are determined from experimental results obtained from testing actual connections. Load-displacement curves for shear walls are calculated using the shear connector model and they are compared with experimental and other computational results. Also, the ultimate horizontal load-carrying capacity is compared to results obtained by an analytical plastic design method. Good agreements are found.

关键词： shear walls     wall diaphragms     finite element modelling     plastic shear connector     analytical modelling     experimental comparison    

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标题 作者 时间 类型 操作

Synergistic optimization framework for the process synthesis and design of biorefineries

期刊论文

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

期刊论文

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

期刊论文

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

期刊论文

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

期刊论文

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

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

期刊论文

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

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

期刊论文

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

Pengfei HE, Yang SHEN, Yun GU, Pangyong SHEN

期刊论文

网络设计问题的一种代理模型优化算法

Meng LI, Xi LIN, Xi-qun CHEN

期刊论文

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

Abdussamad ISMAIL

期刊论文

Kinetic-compartmental modelling of potassium-containing cellulose feedstock gasification

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

期刊论文

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

Saleh YAGHOOBI, Ahmad SHOOSHTARI

期刊论文

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

期刊论文

Dynamic modelling and simulation of a post-combustion CO capture process for coal-fired power plants

期刊论文

Modeling of shear walls using finite shear connector elements based on continuum plasticity

Ulf Arne GIRHAMMAR, Per Johan GUSTAFSSON, Bo KÄLLSNER

期刊论文