Improving Prediction Accuracy of a Rate-Based Model of an MEA-BasedCarbon Capture Process for Large-Scale Commercial Deployment

Carbon capture and storage （CCS） technology will play a critical role in reducing anthropogenic carbondioxide （CO2） emission from fossil-fired power plants and other energy-intensive processes. However, theincrement of energy cost caused by equipping a carbon capture process is the main barrier to its commer-cial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been madeto achieve optimal design and operation through process modeling, simulation, and optimization. Accuratemodels form an essential foundation for this purpose. This paper presents a study on developing a moreaccurate rate-based model in Aspen Plus for the monoethanolamine （MEA）-based carbon capture processby multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamicmodel, physical properties calculations, and a process model at the pilot plant scale, covering a wide rangeof pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacialarea were updated by coding Fortran subroutines in Aspen Plus. The validation results show that the cor-relation combination for the thermodynamic model used in this study has higher accuracy than those ofthree other key publications and the model prediction of the process model has a good agreement with thepilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combinedcycle gas turbine （CCGT） power plant. Shorter packing height and lower specific duty were achieved usingthis accurate model.

STEADY-STATE OPERATION ANALYSIS OF AN IDEAL HEAT INTEGRATED DISTILLATION COLUMN

A systematic approach for the steady-state operation analysis of chemical processes is pro-posed.The method affords the possibility of taking operation resilience into consideration during thestage of process design.It may serve the designer as an efficient means for the initial screening ofalternative design schemes.An ideal heat integrated distillation column(HIDiC),without any reboileror condenser attached,is studied throughout this work.It has been found that among the various va-riables concerned with the ideal HIDiC,feed thermal condition appears to be the only factor exertingsignificant influences on the interaction between the top and the bottom control loops.Maximuminteraction is expected when the feed thermal condition approaches 0.5.Total number of stages andheat transfer rate are essential to the system ability of disturbance rejection.Therefore,more stagesand higher heat transfer rate ought to be preferred.But,too many stages and higher heat transfer ratemay increase the load of the

Traffic Modeling of a Finite-Source Power Line Communication Network

Power line communication (PLC) is a promising smart grid application for information transmission using existing power lines. We analytically model a finite-source PLC network subject to channel failure through a queueing theoretic framework. The proposed PLC network model consists of a base station (BS), which is located at a transformer station and connected to the backbone communication networks, and a number of subscriber stations that are interconnected with each other and with the BS via the power line transmission medium. An orthogonal frequency division multiplexing based technique is assumed for forming the transmission channels in a frequency spectrum. The channels are subject to failure during service due to noise. We determine the steady-state solution of the proposed model and derive a set of performance metrics of interest. Numerical and simulation results are presented to provide further insights into the analytical results. The proposed modeling method is expected to be used for evaluation and design of future PLC networks.

Efficiency of collective myosin Ⅱ motors studied with an elastic coupling power-stroke ratchet model

We proposed a modified ratchet model including power-stroke and elastic coupling to study the efficiency of collective non-processive motors such as myosin Ⅱ in muscle. Our theoretical results are in good agreement with the experimental data. Our study not only reveals that the maximum efficiency depends on elasticity and is independent of transition rates but also indicates that the parameters fitted to fast muscle are different from those fitted to a slow one. The latter may imply that the structure of the fast muscle is different from that of the slow one. The main reason that our model succeeds is that velocity in this model is an independent variable.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Ignition models and simulation of solid propellant of thermodynamic undersea vehicle

The starting characteristics of thermodynamic undersea vehicle systems are determined by the geometry, size and combustion area of solid propellants, which directly effect liquid propellant pipeline design. It is necessary to establish accurate burning models for solid propellants. Based on combustion models using powder rings and two different solid ignition grains, namely star-shaped ignition grains and stuffed ignition grains, a mathematic model of the ignition process of the propulsion system was built. With the help of Matlab, a series of calculations were made to determine the effects of different grains on ignition characteristics. The results show that stuffed ignition grain is best suited to be the ignition grain of a thermodynamic undersea vehicle system.

Lag compensation errors in active power filters based on DSP controllers

The growing problems of harmonic pollution on coal mine power lines caused by high-power DC drive systems has increased the use of active power filters.We analyzed compensation errors caused by the time lag in the detecting circuits of an active power filter based on DSP control.We derived a mathematical model for the compensation error starting from the error estimation when a single distortion frequency is present.This model was then extended to the case where multiple frequencies are present in the distortion.A formula for a general theory of compensation error with fixed load and fixed lag time is presented.The theoretical analysis and experimental results show that the delay time of an active power filter mainly arises from the sampling time.Lower sampling frequencies introduce larger compensation errors in the active power filter reference current.

Random process simulation of strong ground motion

The state-of-art of random process simulation model research of strong ground motion are analysed and theshortcomings of previous models is pointed out in this paper. Based on these, a random process model of groundmotion with color spectrum on bedrock is presented which can give expression to the recent results in engineeringseismology and near-field seismology and simulate the practical spectrum function of strong ground motion aswell. Moreover, the presented model can solve the incompatible problem between the horizontal model and therotational model, and it is easy to determine the model parameters and to set up a practical design criterion ofrandom seismic motion by use of the basic parameters used in the present aseismic design.

Nonlinear Mixed-Effects Models for Repairable Systems Reliability

Mixed-effects models,also called random-effects models,are a regression type of analysis which enables the analyst to not only describe the trend over time within each subject,but also to describe the variation among different subjects.Nonlinear mixed-effects models provide a powerful and flexible tool for handling the unbalanced count data.In this paper,nonlinear mixed-effects models are used to analyze the failure data from a repairable system with multiple copies.By using this type of models,statistical inferences about the population and all copies can be made when accounting for copy-to-copy variance.Results of fitting nonlinear mixed-effects models to nine failure-data sets show that the nonlinear mixed-effects models provide a useful tool for analyzing the failure data from multi-copy repairable systems.

Combining a Safety Management Process with a Safety Framework

A safety document management system, known as a Permit for Work (PFW) system is used commonly in the Power Industry to provide appropriate safety conditions for those working on the generating system. This paper investigates how a safety management process (+PFW) can be combined with a safety framework to enhance system effectiveness to ensure the requirements of users and suppliers can be met. While the paper makes some reference to the power industry, the concept is applicable to the management of systems in other domains.

A mathematical Model to Predict Transition-to-Fatigue During Isometric Exercise on Muscles of the Lower Extremities

Surface Electromyography (sEMG) activities of the four muscles were studied from twelve healthy subjects to analyze muscle fatigue. Data were recorded while subjects performed isometric exercises for a period of time until fatigue. The signal was segmented with 5000 samples to enable the evolutionary process. Based on the mean power spectrum and Median Frequency (MDF) of each segment, we developed a methodology that is able to detect the signal into a meaningful sequence of Non-Fatigue to Transition-to-Fatigue. By identifying this transitional fatigue stage, it is possible to predict when fatigue will occur, which provides the foundation of the automated system that has the potential to aid in many applications of our lives, including sports, rehabilitation and ergonomics.

基于组合赋权-云模型的抽蓄电站高质量发展评价体系

为科学评价生产期抽蓄电站高质量发展现状、把握电站发展的薄弱环节、明确建设期及新投运电站发展方向,根据抽蓄电站定位及高质量发展内涵,经过2轮筛选,构建了包含服务电力系统稳定运行、经济、绿色、创新、共享5个一级指标以及18个二级指标的评价指标体系;选用层次分析法–决策实验分析方法确定指标权重,运用云模型评价各电站高质量发展等级。最后,选取A抽蓄电站为算例验证评价体系适用性。评价结果显示,该电站服务电力系统稳定运行、绿色和共享3个指标表现均为良好,经济和创新指标表现为中等,与电站实际运行情况相符合。该验证结果表明,采用上述方法构建的评价指标体系有很好的适用性。

基于改进SVM的电力工程造价预测

针对支持向量机求解速度较慢且用于预测电力工程造价的性能不理想等问题,提出了一种基于改进SVM的电力工程造价预测模型。该模型全面考虑了电力工程成本的组成要素并进行参数归一化处理,利用最小二乘估计改进SVM模型,同时采用遗传算法求解LSSVM的参数最优值,并通过优化后的GA-LSSVM模型实现对电力工程成本的预测。基于MATLAB仿真平台的仿真实验结果表明,模型预测的工程成本与实际值较为接近,归一化均方误差与平均绝对百分比误差分别为18.34万元和3.58%,且预测时间仅为256 ms,证明了其整体性能优于其他对比模型。

基于SEM-AHP方法的核电厂定量人为因素评价研究

文章基于人为因素分析与分类系统,分析了115起核电厂执照运行事件报告(Licensed Operation Event Report,LOER),并对影响核电厂事件发生的人为因素进行分类,采用结构方程模型方法得出各影响因素的路径系数,两两比较得到层次分析模型的判断矩阵,进而确定各因素的权重。同时对核电厂人为因素的重要性做排序分析,找到核电厂运行过程中的安全管理薄弱环节,从而促进核电厂系统平稳运行。

电网企业标准数字化能力成熟度模型构建研究

标准数字化正日益成为国际与国内发展的核心趋势。为实现转型升级,企业需要科学分析和评估其标准数字化能力。现有研究多聚焦企业数字化转型成熟度模型和标准数字化能力等级通用模型两个领域,针对特定行业或公司实际业务层面的标准数字化能力成熟度评估模型研究尚显不足。借鉴能力成熟度模型(capability maturity model,CMM)思想,结合标准全生命周期管理和电网企业技术标准实施情况,开展专家访谈,构建了一个结构清晰的标准数字化能力成熟度模型,该模型包括5个标准数字化能力域和7个标准数字化过程域这两大维度。以国家电网某公司业扩报装场景为例,采用二维表评估方法,得到该公司在这一业务场景下的标准数字化能力达到L2探索级,验证了模型的实际应用效果。

基于FAHP-CM的舰船电力系统韧性评价研究

针对当前评价舰船电力系统韧性具有较大的不确定性和主观性问题,在建立舰船电力系统韧性评价指标体系的基础上,将云模型(cloud model,CM)和模糊层次分析法(fuzzy analytic hierarchy process,FAHP)相结合,提出FAHP-CM的舰船电力系统韧性评价方法。该方法利用FAHP-CM计算评价指标的权重,使权重更加客观准确,同时简化计算过程,提高评估效率。实例分析结果表明,所建立的评价方法能够很好地反映舰船电力系统的韧性,并能有效解决评价的不确定性和主观性问题,使评价结果更加科学合理。

基于改进OPA模型的配电网综合停电风险评估方法

配电网综合故障往往是由连锁故障导致,加大了配电网综合停电风险评估的难度,因此提出基于改进OPA模型的配电网综合停电风险评估方法。建立基于直流潮流的改进OPA模型,模拟配电网连锁故障,以提高配电网综合停电风险评估;以风险价值、条件风险价值、负荷损失期望值为综合风险评估指标,利用改进OPA模型模拟配电网连锁故障,计算评估指标值,根据评估指标值完成配电网综合停电风险评估。实验证明:该方法可有效评估配电网综合停电风险,风力会提升停电风险;在不同线路改造力度与初始负荷水平时,该方法均可有效评估配电网综合停电风险。

核电厂高压蒸汽管道焊缝切割装置的研制

为了修复某核电厂GPV高压缸排汽管膨胀节导流筒焊缝因热处理不当导致的开裂,研发了一款焊缝切割装置,用于将开裂的焊缝切除并加工坡口以进行下一步的自动焊接修复。首先利用SolidWorks对焊缝切割设备进行了机械设计并三维建模,对驱动电机进行了选型计算,设计了控制系统架构,随后制作了设备样机和膨胀节导流筒模拟体,最后在试验室利用模拟体对设备样机的性能进行了连续切削试验,验证了该装备能够高效完成膨胀节导流筒开裂焊缝的切除和坡口加工,且坡口加工质量优良,装置性能稳定。

基于模糊层次分析法的海上风电场航标效能评价

针对海上风电场航标效能评价,根据评价指标选择原则,创建包括27个三级指标的评价指标体系。采用层次分析法(Analytic Hierarchy Process, AHP)和模糊综合评价法(Fuzzy Comprehensive Evaluation, FCE)构建评价模型,采用模糊层次分析法(Fuzzy Analytic Hierarchy Process, FAHP)确定评价流程。以某海上风电场为例,进行海上风电场航行效能评价。结果表明,FAHP在海上风电场航标效能评价方面具有系统性、客观性和可操作性强的特点。

基于模糊综合评价法的热电厂设备安全风险评估

为定量评价热电厂生产过程中的安全隐患,对热电厂的储煤运煤、锅炉设备、除灰除渣和脱硫脱硝四个子系统中存在的主要危险源进行辨识,并采用模糊综合评价模型进行评估。通过层次分析法确定了热电厂一级主因素和二级子因素的权重并对各因素的危险性大小进行排序;通过计算隶属矩阵得出一级模糊评价矩阵和二级模糊评价矩阵,得出基于专家打分的四个子系统的危险性水平和热电厂的危险性水平,最后计算出该热电厂的安全评价分值为92.7分。所得结论对提高该热电厂的安全水平和后续安全管理具有理论指导作用。