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A review on different theoretical models of electrocaloric effect for refrigeration

《能源前沿（英文）》 2023年 第17卷 第4期   页码 478-503 doi: 10.1007/s11708-023-0884-6

摘要： The performance parameters for characterizing the electrocaloric effect are isothermal entropy change and the adiabatic temperature change, respectively. This paper reviews the electrocaloric effect of ferroelectric materials based on different theoretical models. First, it provides four different calculation scales (the first-principle-based effective Hamiltonian, the Landau-Devonshire thermodynamic theory, phase-field simulation, and finite element analysis) to explain the basic theory of calculating the electrocaloric effect. Then, it comprehensively reviews the recent progress of these methods in regulating the electrocaloric effect and the generation mechanism of the electrocaloric effect. Finally, it summarizes and anticipates the exploration of more novel electrocaloric materials based on the framework constructed by the different computational methods.

关键词： electrocaloric effect     effective Hamiltonian     phase-field modeling     different theoretical models    

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Predictive models on photolysis and photoinduced toxicity of persistent organic chemicals

Qing ZHANG

《环境科学与工程前沿（英文）》 2013年 第7卷 第6期   页码 803-814 doi: 10.1007/s11783-013-0547-7

摘要： Photodegradation is a major abiotic transformation pathway of toxic chemicals in the environment, which in some cases might lead to photoinduced toxicities. The data on photodegradation kinetics and photoinduced toxicities of organic chemicals are essential for their risk assessment. However, the relevant data are only available for a limited number of chemicals, due to the difficulty and high cost of experimental determination. Quantitative structure-activity relationship (QSAR) models that relate photodegradation kinetics or photoinduced toxicity of organic chemicals with their physicochemical properties or molecular structural descriptors may enable simple and fast estimation of their photochemical behaviors. This paper reviews the QSAR models on photodegradation quantum yields and rate constants for toxic organic chemicals in different media including liquid phase, gaseous phase, surfaces of plant leaves, and QSAR models on photoinduced toxicity of organic chemicals to plants, bacteria, and aquatic invertebrates. Further prospects for QSAR model development on photodegradation kinetics and photoinduced toxicity of refractory organic chemicals are proposed.

关键词： quantitative structure-activity relationship (QSAR) models     photodegradation     persistent organic pollutants     environmental media     mechanisms    

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Empirical models and design codes in prediction of modulus of elasticity of concrete

Behnam VAKHSHOURI, Shami NEJADI

《结构与土木工程前沿（英文）》 2019年 第13卷 第1期   页码 38-48 doi: 10.1007/s11709-018-0479-1

摘要： Modulus of Elasticity (MOE) is a key parameter in reinforced concrete design. It represents the stress-strain relationship in the elastic range and is used in the prediction of concrete structures. Out of range estimation of MOE in the existing codes of practice strongly affect the design and performance of the concrete structures. This study includes: (a) evaluation and comparison of the existing analytical models to estimating the MOE in normal strength concrete, and (b) proposing and verifying a new model. In addition, a wide range of experimental databases and empirical models to estimate the MOE from compressive strength and density of concrete are evaluated to verification of the proposed model. The results show underestimation of MOE of conventional concrete in majority of the existing models. Also, considering the consistency between density and mechanical properties of concrete, the predicted MOE in the models including density effect, are more compatible with the experimental results.

关键词： modulus of elasticity     normal strength normal weight concrete     empirical models     design codes     compressive strength     density    

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Machine learning based models for predicting compressive strength of geopolymer concrete

《结构与土木工程前沿（英文）》 2024年 第18卷 第7期   页码 1028-1049 doi: 10.1007/s11709-024-1039-5

摘要： Machine learning based models for predicting compressive strength of geopolymer concrete

关键词： strength geopolymer concrete    

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enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models

《农业科学与工程前沿（英文）》 doi: 10.15302/J-FASE-2024572

摘要：

● Sustainable approach to minimize pesticide usage and enhance crop productivity was developed.

关键词： Disease management     site-specific sprayer     spectral sensor     machine learning models     cauliflower crop     black-rot disease    

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Managing economic and social profit of cooperative models in three-echelon reverse supply chain for waste

Jian Li, Zhen Wang, Bao Jiang

《环境科学与工程前沿（英文）》 2017年 第11卷 第5期 doi: 10.1007/s11783-017-0999-2

摘要： In addition to maximizing economic benefits, reverse supply chains should further seek to maximize social benefits by increasing the quantity of waste electrical and electronic equipment (WEEE). The paper investigates cooperative models with different parties in a three-echelon reverse supply chain for WEEE consisting of a single collector, a single remanufacturer, and two retailers based on complete information. In addition, the optimal decisions of four cooperative models and the effect of the market demand of remanufactured WEEE products and the market share of two retailers on the optimal decisions are discussed. The results indicate that optimal total channel profit and recycle quantity in a reverse supply chain are maximized in a centralized model. The optimal total channel profit and recycle quantity increase with an increase in the market demand of remanufactured WEEE products. The three-echelon reverse supply chain consisting of duopolistic retailers maximizes total channel profit and recycle quantity in a reverse supply chain for WEEE.

关键词： Waste electrical and electronic equipment (WEEE)     Reverse supply chains     Recycle quantity     Social benefit     Cooperative models     Duopolistic retailers    

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Impact analytical models for earthquake-induced pounding simulation

Kun YE, Li LI

《结构与土木工程前沿（英文）》 2009年 第3卷 第2期   页码 142-147 doi: 10.1007/s11709-009-0029-y

摘要： Structural pounding under earthquake has been recently extensively investigated using various impact analytical models. In this paper, a brief review on the commonly used impact analytical models is conducted. Based on this review, the formula used to determine the damping constant related to the impact spring stiffness, coefficient of restitution, and relative approaching velocity in the Hertz model with nonlinear damping is found to be incorrect. To correct this error, a more accurate approximating formula for the damping constant is theoretically derived and numerically verified. At the same time, a modified Kelvin impact model, which can reasonably account for the physical nature of pounding and conveniently implemented in the earthquake-induced pounding simulation of structural engineering is proposed.

关键词： structural pounding     Hertz model     Kelvin model     nonlinear damping     coefficient of restitution    

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扩散模型在时间序列的应用综述 Review Article

林乐荃1,李正坤2,李瑞昆1,李旭亮1,高俊斌1

《信息与电子工程前沿（英文）》 2024年 第25卷 第1期   页码 19-41 doi: 10.1631/FITEE.2300310

摘要： 扩散模型，一类基于深度学习的生成模型家族，在前沿机器学习研究中变得日益重要。扩散模型以在生成与观察数据相似样本方面的卓越性能而著称，如今广泛用于图像、视频和文本合成。近年来，扩散的概念已扩展到时间序列应用领域，涌现出许多强大的模型。鉴于这些模型缺乏系统性总结和讨论，我们提供此综述作为此领域新研究人员的基础资源，并为激发未来研究提供灵感。为更好理解，引入了有关扩散模型基础知识的介绍。除此之外，主要关注基于扩散的时间序列预测、插补和生成方法，并将它们分别在三个独立章节中呈现。还比较了同一应用的不同方法，并强调它们之间的关联（若适用）。最后，总结了扩散方法的共同局限性，并突出强调潜在的未来研究方向。

关键词： 扩散模型，时间序列预测，时间序列插补，去噪扩散概率模型，基于斯坦方法的生成模型，随机微分方程    

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Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 183-197 doi: 10.1007/s11705-021-2073-7

摘要： Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations, so that solvability becomes a practical issue. Additional constraints from technical, economic, environmental, and safety considerations may further limit the feasible solution space beyond the convergence requirement. A priori, the design variable domains for which a simulation converges and fulfills the imposed constraints are usually unknown and it can become very time-consuming to distinguish feasible from infeasible design variable choices by simply running the simulation for each choice. To support the exploration of the design variable space for such scenarios, an adaptive sampling technique based on machine learning models has recently been proposed. However, that approach only considers the exploration of the convergent domain and ignores additional constraints. In this paper, we present an improvement which particularly takes the fulfillment of constraints into account. We successfully apply the proposed algorithm to a toy example in up to 20 dimensions and to an industrially relevant flowsheet simulation.

关键词： machine learning     flowsheet simulations     constraints     exploration    

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Depth of cut models for multipass abrasive waterjet cutting of alumina ceramics with nozzle oscillation

Jun WANG

《机械工程前沿（英文）》 2010年 第5卷 第1期   页码 19-32 doi: 10.1007/s11465-009-0082-1

摘要： An experimental study of the depth of cut in multipass abrasive waterjet (AWJ) cutting of alumina ceramics with controlled nozzle oscillation is presented. It is found that this cutting technique can significantly increase the depth of cut by an average of 50.8% as compared to single pass cutting without nozzle oscillation under the corresponding cutting conditions and within the same cutting time. Predictive models for the depth of cut are then developed. The modelling process starts with single pass cutting using a dimensional analysis technique and the particle erosion theories applied to alumina ceramics, before progressing to the development of the models for multipass cutting. The models are finally assessed both qualitatively and quantitatively with experimental data. It is shown that the model predictions are in good agreement with the experimental data with the average deviations of about 1%.

关键词： abrasive waterjet     engineering ceramics     depth of cut     cutting performance     nozzle oscillation     machining    

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Availability growth models and verification of power equipment

Jinyuan SHI, Jiamin XU

《能源前沿（英文）》 2021年 第15卷 第2期   页码 529-538 doi: 10.1007/s11708-019-0624-0

摘要： The general availability growth models for large scale complicated repairable system such as electric generating units, power station auxiliaries, and transmission and distribution installations are presented. The calculation formulas for the maintenance coefficient, mathematical expressions for general availability growth models, ways for estimating, and fitting on checking the parameters of the model are introduced. Availability growth models for electric generating units, power station auxiliaries, and transmission and distribution installations are given together with verification examples for availability growth models of 320–1000 MW nuclear power units and 1000 MW thermal power units, 200–1000 MW power station auxiliaries, and 220–500 kV transmission and distribution installations. The verification results for operation availability data show that the maintenance coefficients for electric generating units, power station auxiliaries, transmission and distribution installations conform to the power function, and general availability growth models conform to rules of availability growth tendency of power equipment.

关键词： repairable system     power equipment     electric generating unit     power station auxiliary     transmission and distribution installation     reliability     availability     availability growth model    

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Assessment and validation of liquid breakup models for high-pressure dense diesel sprays

Yi REN,Xianguo LI

《能源前沿（英文）》 2016年 第10卷 第2期   页码 164-175 doi: 10.1007/s11708-016-0407-9

摘要： Liquid breakup in fuel spray and atomization significantly affects the consequent mixture formation, combustion behavior, and emission formation processes in a direct injection diesel engine. In this paper, different models for liquid breakup processes in high-pressure dense diesel sprays and its impact on multi-dimensional diesel engine simulation have been evaluated against experimental observations, along with the influence of the liquid breakup models and the sensitivity of model parameters on diesel sprays and diesel engine simulations. It is found that the modified Kelvin-Helmholtz (KH)–Rayleigh-Taylor (RT) breakup model gives the most reasonable predicted results in both engine simulation and high-pressure diesel spray simulation. For the standard KH-RT model, the model constant for the breakup length has a significant effect on the predictability of the model, and a fixed value of the constant cannot provide a satisfactory result for different operation conditions. The Taylor-analogy-breakup (TAB) based models and the RT model do not provide reasonable predictions for the characteristics of high-pressure sprays and simulated engine performance and emissions.

关键词： breakup model     diesel engine     high-pressure injection     simulations    

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

《结构与土木工程前沿（英文）》 2021年 第15卷 第3期   页码 665-681 doi: 10.1007/s11709-021-0713-0

摘要： The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

关键词： long contraction scour     prediction     uncertainty     ANFIS model     meta-heuristic algorithm    

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Predicting torsional capacity of reinforced concrete members by data-driven machine learning models

《结构与土木工程前沿（英文）》 2024年 第18卷 第3期   页码 444-460 doi: 10.1007/s11709-024-1050-x

摘要： Due to the complicated three-dimensional behaviors and testing limitations of reinforced concrete (RC) members in torsion, torsional mechanism exploration and torsional performance prediction have always been difficult. In the present paper, several machine learning models were applied to predict the torsional capacity of RC members. Experimental results of a total of 287 torsional specimens were collected through an overall literature review. Algorithms of extreme gradient boosting machine (XGBM), random forest regression, back propagation artificial neural network and support vector machine, were trained and tested by 10-fold cross-validation method. Predictive performances of proposed machine learning models were evaluated and compared, both with each other and with the calculated results of existing design codes, i.e., GB 50010, ACI 318-19, and Eurocode 2. The results demonstrated that better predictive performance was achieved by machine learning models, whereas GB 50010 slightly overestimated the torsional capacity, and ACI 318-19 and Eurocode 2 underestimated it, especially in the case of ACI 318-19. The XGBM model gave the most favorable predictions with R2 = 0.999, RMSE = 1.386, MAE = 0.86, and λ¯ = 0.976. Moreover, strength of concrete was the most sensitive input parameters affecting the reliability of the predictive model, followed by transverse-to-longitudinal reinforcement ratio and total reinforcement ratio.

关键词： RC members     torsional capacity     machine learning models     design codes    

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Thermodynamic models and energy distribution of single-phase heated surface in a boiler under unsteady

Xiyan GUO, Yongping YANG

《能源前沿（英文）》 2011年 第5卷 第1期   页码 69-74 doi: 10.1007/s11708-010-0117-7

摘要： A coal-fired power unit frequently operates under unsteady conditions; thus, in order to acquire scientific energy analysis of the unit, thermodynamic analysis of a single-phase heated surface in a boiler under such conditions requires investigation. Processes are analyzed, and distributions of energy and exergy are qualitatively revealed. Models for energy analysis, entropy analysis, and exergy analysis of control volumes and irreversible heat transfer processes are established. Taking the low-temperature superheater of a 610 t/h-boiler as an example, the distribution of energy, entropy production, and exergy is depicted quantitatively, and the results are analyzed.

关键词： thermodynamic model     energy distribution     boiler     unsteady conditions    

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标题 作者 时间 类型 操作

A review on different theoretical models of electrocaloric effect for refrigeration

期刊论文

Predictive models on photolysis and photoinduced toxicity of persistent organic chemicals

Qing ZHANG

期刊论文

Empirical models and design codes in prediction of modulus of elasticity of concrete

Behnam VAKHSHOURI, Shami NEJADI

期刊论文

Machine learning based models for predicting compressive strength of geopolymer concrete

期刊论文

enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models

期刊论文

Managing economic and social profit of cooperative models in three-echelon reverse supply chain for waste

Jian Li, Zhen Wang, Bao Jiang

期刊论文

Impact analytical models for earthquake-induced pounding simulation

Kun YE, Li LI

期刊论文

扩散模型在时间序列的应用综述

林乐荃1,李正坤2,李瑞昆1,李旭亮1,高俊斌1

期刊论文

Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

期刊论文

Depth of cut models for multipass abrasive waterjet cutting of alumina ceramics with nozzle oscillation

Jun WANG

期刊论文

Availability growth models and verification of power equipment

Jinyuan SHI, Jiamin XU

期刊论文

Assessment and validation of liquid breakup models for high-pressure dense diesel sprays

Yi REN,Xianguo LI

期刊论文

Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

期刊论文

Predicting torsional capacity of reinforced concrete members by data-driven machine learning models

期刊论文

Thermodynamic models and energy distribution of single-phase heated surface in a boiler under unsteady

Xiyan GUO, Yongping YANG

期刊论文