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Damage model of fresh concrete in sulphate environment 被引量:4
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作者 张敬书 张银华 +3 位作者 冯立平 金德保 汪朝成 董庆友 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第3期1104-1113,共10页
A model of damage to fresh concrete in a corrosive sulphate environment was formulated to investigate how and why the strength of corroded concrete changes over time. First, a corroded concrete block was divided into ... A model of damage to fresh concrete in a corrosive sulphate environment was formulated to investigate how and why the strength of corroded concrete changes over time. First, a corroded concrete block was divided into three regions: an expanded and dense region; a crack-development region; and a noncorroded region. Second, based on the thickness of the surface corrosion layer and the rate of loss of compressive strength of the corroding region, a computational model of the concrete blocks' corrosion-resistance coefficient of compressive strength in a sulphate environment was generated. Third, experimental tests of the corrosion of concrete were conducted by immersing specimens in a corrosive medium for 270 d. A comparison of the experimental results with the computational formulae shows that the calculation results and test results are in good agreement. A parameter analysis reveals that the corrosion reaction plays a major role in the corrosion of fresh concrete containing ordinary Portland cement,but the diffusion of the corrosion medium plays a major role in the corrosion of concrete mixtures containing fly ash and sulphate-resistant cement. Fresh concrete with a high water-to-cement ratio shows high performance during the whole experiment process whereas fresh concrete with a low water-to-cement ratio shows poor performance during the late experiment period. 展开更多
关键词 fresh concrete sulphate corrosion corrosion coefficient computational model
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模型辅助的计算费时进化高维多目标优化 被引量:12
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作者 孙超利 李贞 金耀初 《自动化学报》 EI CAS CSCD 北大核心 2022年第4期1119-1128,共10页
代理模型能够辅助进化算法在计算资源有限的情况下加快找到问题的最优解集,因此建立高效的代理模型辅助多目标进化搜索逐渐受到了重视.然而随着目标数量的增加,对每个目标分别建立高斯过程模型时个体整体估值的不确定度会随之增加.因此... 代理模型能够辅助进化算法在计算资源有限的情况下加快找到问题的最优解集,因此建立高效的代理模型辅助多目标进化搜索逐渐受到了重视.然而随着目标数量的增加,对每个目标分别建立高斯过程模型时个体整体估值的不确定度会随之增加.因此通过对模型最优解集的搜索探索原问题潜在的非支配解集,并基于个体的收敛性,种群的多样性和估值的不确定度,提出了一种新的期望提高计算方法,用于辅助从潜在的非支配解集中选择使用真实目标函数计算的个体,从而更新代理模型,能够在有限的计算资源下更有效地辅助优化算法找到好的非支配解集.在7个DTLZ基准测试问题上的实验对比结果表明,该算法在求解计算费时高维多目标优化问题上是有效的,且具有较强的竞争力. 展开更多
关键词 高维多目标优化 代理模型 计算费时问题 填充准则
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Closed circle DNA algorithm of change positive-weighted Hamilton circuit problem 被引量:5
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作者 Zhou Kang Tong Xiaojun Xu Jin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第3期636-642,共7页
Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so clos... Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions are composed. Then, the feasible solutions are filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment are discussed. 展开更多
关键词 closed circle DNA computing model change positive-weighted Hamilton circuit problem group insert experiment group delete experiment.
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Design and optimization of exhaust gas aftertreatment system for a heavy-duty diesel engine 被引量:1
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作者 TAN Pi-qiang YAO Chao-jie +3 位作者 WANG De-yuan ZHU Lei HU Zhi-yuan LOU Di-ming 《Journal of Central South University》 SCIE EI CAS CSCD 2022年第7期2127-2141,共15页
Diesel engines meeting the latest emission regulations must be equipped with exhaust gas aftertreatment system,including diesel oxidation catalysts(DOC),diesel particulate filters(DPF),and selective catalytic reductio... Diesel engines meeting the latest emission regulations must be equipped with exhaust gas aftertreatment system,including diesel oxidation catalysts(DOC),diesel particulate filters(DPF),and selective catalytic reduction(SCR).However,before the final integration of the aftertreatment system(DOC+DPF+SCR)and the diesel engine,a reasonable structural optimization of the catalytic converters and a large number of bench calibration tests must be completed,involving large costs and long development cycles.The design and optimization of the exhaust gas aftertreatment system for a heavy-duty diesel engine was proposed in this paper.Firstly,one-dimensional(1D)and threedimensional(3D)computational models of the exhaust gas aftertreatment system accounting for the structural parameters of the catalytic converters were established.Then based on the calibrated models,the effects of the converter’s structural parameters on their main performance indicators,including the conversion of various exhaust pollutants and the temperatures and pressure drops of the converters,were studied.Finally,the optimal design scheme was obtained.The temperature distribution of the solid substrates and pressure distributions of the catalytic converters were studied based on the 3D model.The method proposed in this paper has guiding significance for the optimization of diesel engine aftertreatment systems. 展开更多
关键词 diesel engine EMISSION exhaust gas aftertreatment computational model optimal design
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全局与局部模型交替辅助的差分进化算法 被引量:5
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作者 于成龙 付国霞 +1 位作者 孙超利 张国晨 《计算机工程》 CAS CSCD 北大核心 2022年第3期115-123,共9页
为求解实际复杂工程应用中的高维计算费时优化问题,提出一种全局与局部代理模型交替辅助的差分进化算法。利用历史样本训练全局和局部代理模型,通过交替搜索全局和局部代理模型得到模型最优解并对其进行真实目标函数评价,实现探索和开... 为求解实际复杂工程应用中的高维计算费时优化问题,提出一种全局与局部代理模型交替辅助的差分进化算法。利用历史样本训练全局和局部代理模型,通过交替搜索全局和局部代理模型得到模型最优解并对其进行真实目标函数评价,实现探索和开采的平衡以减少真实目标函数的计算次数,同时通过针对性地选择个体进行真实目标函数计算,辅助算法快速找到目标函数的较优解。在15个低维测试问题和14个高维测试问题上的实验结果表明,在有限的计算资源情况下,该算法在12个低维测试问题上相较于最优重启策略代理辅助的社会学习粒子群优化算法、基于主动学习的代理模型辅助的粒子群优化算法等表现更好,在7个高维测试问题上相较于高斯过程辅助的进化算法、代理模型辅助的分层粒子群优化算法、求解高维费时问题的代理辅助的多种群优化算法等能找到目标函数的更优解。 展开更多
关键词 全局代理模型 局部代理模型 差分进化算法 计算费时优化问题 径向基函数网络
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