基于GA-MVFOSM法的DSA250型受电弓运动可靠性分析

为分析运动副磨损与杆件尺寸不确定性2种因素对受电弓运动可靠性的影响，提出一种基于遗传一次二阶矩法(GA-MVFOSM)的受电弓运动可靠性计算方法。首先，构建受电弓运动学方程，应用Archard磨损理论建立其运动副磨损可靠性模型。在此基础上，考虑运动副磨损与杆件尺寸的不确定性，结合可靠性理论建立受电弓运动可靠性模型。其次，利用遗传算法优化一次二阶矩法，提出GA-MVFOSM算法，用以求解受电弓的运动可靠度。最后，以DSA250型受电弓为研究对象，利用所提方法分析其运动可靠性，并与传统方法进行对比。分析结果表明:各运动副磨损量分别在0.230 0 mm、0.136 6 mm、0.006 6 mm内时，运动副磨损可靠度处于较高水平，2种因素耦合情况下弓头运动可靠度最小值为0.964 7；基于遗传一次二阶矩的计算方法可以有效提高传统方法计算精度，为提高受电弓工作可靠性提供参考依据。     

Molecular Identification of Dendrobium Species (Orchidaceae) Based on the DNA Barcode ITS2 Region and Its Application for Phylogenetic Study

The over-collection and habitat destruction of natural Dendrobium populations for their commercial medicinal value has led to these plants being under severe threat of extinction. In addition, many Dendrobium plants are similarly shaped and easily confused during the absence of flowering stages. In the present study, we examined the application of the ITS2 region in barcoding and phylogenetic analyses of Dendrobium species (Orchidaceae). For barcoding, ITS2 regions of 43 samples in Dendrobium were amplified. In combination with sequences from GenBank, the sequences were aligned using Clustal W and genetic distances were computed using MEGA V5.1. The success rate of PCR amplification and sequencing was 100%. There was a significant divergence between the inter- and intra-specific genetic distances of ITS2 regions, while the presence of a barcoding gap was obvious. Based on the BLAST1, nearest distance and TaxonGAP methods, our results showed that the ITS2 regions could successfully identify the species of most Dendrobium samples examined; Second, we used ITS2 as a DNA marker to infer phylogenetic relationships of 64 Dendrobium species. The results showed that cluster analysis using the ITS2 region mainly supported the relationship between the species of Dendrobium established by traditional morphological methods and many previous molecular analyses. To sum up, the ITS2 region can not only be used as an efficient barcode to identify Dendrobium species, but also has the potential to contribute to the phylogenetic analysis of the genus Dendrobium.     

NNI-1型C_5/C_6烷烃异构化催化剂长周期运行分析及建议

中国石化海南炼油化工有限公司0.2 Mt/a C5/C6烷烃异构化装置以连续重整装置的拔头油为原料,使用NNI-1催化剂,采用一次通过流程,不设脱异戊烷塔和稳定塔,经设在连续重整装置内的脱丁烷塔稳定处理后作为汽油调合组分。该装置于2006年9月开工投产,截至2015年3月已连续运行3个周期。长周期运行分析结果表明:前两个周期中NNI-1催化剂具有较高的异构化活性及选择性,C5异构化率为60%左右,C6异构化率为80%左右,C6选择性为15%左右,产品辛烷值基本达到技术指标要求(RON≥78);而在第三周期运行中,催化剂积炭增加等原因导致其异构化活性及选择性降低,异构化产品辛烷值提升能力呈现逐步衰减的趋势,提高反应苛刻度已不能弥补催化剂活性下降造成的产品辛烷值降低。为保证装置长周期运行,建议择机停工对催化剂进行再生,或是直接换用与装置原料性质匹配的异构化催化剂。     

大型球磨机订购（制造）设计联络中零部件结构优化的探讨

针对大型球磨机使用中存在的问题，对球磨机主要零部件结构缺陷进行分析并提出解决方案。通过设计联络，提前对球磨机主要零部件结构进行优化，消除设备缺陷。大型球磨机设计联络中对主要零部件结构进行优化，对提高球磨机的运转率有着事半功倍的作用。     

产融结合对上市公司经营绩效和企业价值的影响

以我国上市公司为研究样本,从金融机构参股钢铁上市公司的视角,分析不同参股比例的产融结合行为对经营绩效、企业价值的影响。经分析发现,金融机构参股超过一定比例后,产融结合对企业经营绩效和企业价值呈显著非线性相关关系。     

A bi-objective integrated procurement,production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA

Efficient management of supply chain (SC) requires systematic considerations of miscellaneous issues in its comprehensive version. In this paper, a multi-periodic structure is developed for a supply chain network design (SCND) involving suppliers, factories, distribution centers (DCs), and retailers. The nature of the logistic decisions is tactical that encompasses procurement of raw materials from suppliers, production of finished product at factories, distribution of finished product to retailers via DCs, and the storage of raw materials and end product at factories and DCs. Besides, to make the structure more comprehensive, a flow-shop scheduling model in manufacturing part of the SC is integrated in order to obtain optimal delivery time of the product that consists of the makespan and the ship time of the product to DCs via factories. Moreover, to make the model more realistic, shortage in the form of backorder can occur in each period. The two objectives are minimizing the total SC costs as well as minimizing the average tardiness of product to DCs. The obtained model is a bi-objective mixed-integer non-linear programming (MINLP) model that is shown to belong to NP-Hard class of the optimization problems. Thus, a novel algorithm, called multi-objective biogeography based optimization (MOBBO) with tuned parameters is presented to find a near-optimum solution. As there is no benchmark available in the literature, the parameter-tuned multi-objective simulated annealing algorithm (MOSA) and the popular non-dominated sorting genetic algorithm (NSGA-II) are developed to validate the results obtained and to evaluate the performance of MOBBO using randomly generated test instances.     

环己酮废碱焚烧运行成本模拟方法及应用

通过反平衡法计算废碱焚烧炉热效率、产汽量及可变成本,建立了废碱焚烧运行成本模型,并计算分析了可变成本与燃料类型、组成、投碱量、尾气含氧量等因素的关联性。结果表明:随着混合燃料中干气比例提高,可变成本下降;仅使用辅助燃料渣油时,随着渣油量增加,可变成本不断增加,并出现加速拐点,急速增加;仅使用干气作辅助燃料时,随着干气量增加,投碱量减少,可变成本不断降低,并出现加速拐点,急速下降;随着尾气含氧量增加,锅炉的燃烧效率不断下降,可变成本不断增高;针对干气充足、干气不充足以及全部使用燃料油时,提出了相应的经济运行模式,并将其应用于指导生产,经济效益明显。     

Large eddy simulation of a 660 MW utility boiler under variable load conditions

Large eddy simulation (LES) has become a promising tool for pulverized coal combustion with the development of computational fluid dynamics (CFD) technologies in recent years. LES can better capture the unsteady features and turbulent structures of coal jet flame than Reynolds averaged Navier Stokes (RANS). The coal-fired power plants in China are now required to be operated in a wide load range and quickly respond to the electric grid. The boiler performance of variable loads should be evaluated in terms of flow, heat transfer, and combustion processes. In this paper, LES was applied to simulate a 660 MW ultra-supercritical boiler under BMCR (boiler maximum continue rate), 75%THA-100, and 50%THA-100 conditions. The predicted gas velocities agree well with the thermal calculation and the temperature error is less than 130 K. The simulation results show that the operation load has significant effects on the boiler performance. It is also proved that LES can provide guidance for the design and operation of advanced coal-fired boilers.     

Multi-modal approach to evaluate adaptive visual stimuli of remote operation system using gaze behavior

A multi-modal approach is proposed to evaluate the usability of Adaptive Visual Stimuli for User Interface (AVS4UI) of remote operation systems. This study focuses on the evaluation of AVS4UI for forklift work because the operation complexity includes driving and cargo handling, which typically requires multiple salient attention. Presenting this amount of information simultaneously on a User Interface (UI) tends to cause confusions to operators and reduces operation efficiency. AVS4UI can therefore be one of the promising solutions where the optimal visual stimuli are autonomously presented for different work conditions. However, evaluation of AVS4UI is challenging because operators may be disoriented by adaptive information and worked without safety considerations. Therefore, novel gaze metrics are proposed to evaluate responses of forklift operators to AVS4UI so that undesired behavior can be evaluated. The proposed metrics implicitly represent gaze pattern in terms of transition and distribution between UI elements, operation safety, and familiarity with the adaptive system. The ideal AVS4UI is expected to minimize the proposed gaze metrics and outperform the non-adaptive UI. More importantly, the results of these metrics are consistent with those of perceived workload defined by NASA-Task Load Index. We also propose a correlation model using stepwise linear regression that provides reasonable estimation of perceived workload. Such novel metrics and correlation model enable objective and online evaluation to minimize biases of subjective response. Therefore, online work support system can be developed to support workers.     

A review on modeling of solar photovoltaic systems using artificial neural networks,fuzzy logic,genetic algorithm and hybrid models

The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.