《陶人心语》中唐英心境浅析

唐英,清代沈阳人,隶属汉军正白旗。《陶人心语》是清代督陶官唐英撰写的诗集。该诗集内容丰富,表达了唐英对皇帝的感恩之情,以及他的赤城之心;对制陶事业的热爱之情;对亲人的思念关爱之情,体恤百姓的疾苦,关心百姓等。此书具有丰富的文学价值和历史价值。     

炼油废白土在水泥厂燃煤自备电厂中再利用的实践

本项目主要研究和实现了工业废白土在BAYAH燃煤自备电厂中的再利用,实现变废为宝,减少了环境污染,同时为企业创造了一定的经济效益。针对废白土的特性,对燃料输送系统给煤机、皮带机、煤仓、下料溜子和排渣系统进行了改造。通过修改操作规程消除废白土对锅炉运行的影响。     

Increasing Volumetric CO2 Uptake of Hypercrosslinked Polymers through Composite Formation

To overcome the drawbacks of solid microporous materials for CO₂ capture, this proof‐of‐concept study demonstrates a low‐cost and rapid method for producing composites consisting of hypercrosslinked polymers (HCP) with a polyethyleneimine (PEI) binder. The resulting materials capture CO₂ through physical and chemical absorption simultaneously. Compared with HCP, the composites exhibit higher CO₂ uptake, higher volumetric density, and improved tolerance to water which is attributed to the PEI binder.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.