Control of TAME reactive distillation using Non-Dominated Sorting Genetic Algorithm-II

The control system performs poor in characteristics and even it becomes unstable, if improper values of the controller tuning constants are used. So it becomes necessary to tune the controller parameters to achieve good control performance with the proper choice of tuning constants. Many control problems involve simultaneous optimization of multiple variables that competing with each other. In this paper, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has been successfully applied to optimization of dynamic state of t-amyl-methyl-ether (TAME) reactive distillation process. This paper presents the tuning of Proportional-Integral-Derivative (PID) controllers by minimizing of two objective functions (overshoot and Integral of Absolute Error (IAE)) through the NSGA-II. Results show that genetic algorithm is more suitable method for optimal control of the TAME reactive distillation columns than traditional methods such as Tyreus-Luyben.     

改进的遗传算法在城市污水处理厂区间数优化设计模型中的应用

对于高度非线性的城市污水处理厂区间数优化设计模型(IPODM),若采用传统的方法求解,不仅计算繁琐,且难以有效地寻找全局最优解.本文通过引入遗传算法(GA),与传统的步长搜索法相结合,大大提高了问题的求解效率.本文给出了这种改进算法在某一城市污水处理厂优化设计中的应用实例.结果表明,不仅解的搜索效率有明显的提高,而且目标函数值在原有的基础上改进了20%,有着显著的经济效益;但是由于遗传算法自身的局限性,所求得的解只是一定条件下的最优区间解.     

考虑救援时效的化工园区应急物资储备站点选址模型研究

针对化工园区的应急物资储备站点选址问题,在同时考虑经济因素以及救援效果的基础上,建立了多目标覆盖选址模型,同时引入了应急救援时效函数,以反映物资运输时间对救援效果的影响。最后将模型应用于江苏省南部的化工园区应急物资储存站点的选址问题进行算例分析,使用NSGA-II算法对模型进行求解,并采用TODIM法对得到的帕累托最优解进行排序,为决策者选取最终方案做出了参考。     

Anhydrous ethanol production by extractive distillation: A solvent case study

Production of anhydrous ethanol in large scale has been made by extractive distillation using conventional solvents like ethylene-glycol. In the present paper, extractive distillation process is studied to obtain pure ethanol using ethylene-glycol and tetraethylene-glycol as solvents. Residue curve maps are used to analyse the proposed distillation processes in interpreting mixture behaviours and feasibility of distillation columns. The industrial process is simulated at steady state from residue curve map analysis. Simulation results for the ethanol/water mixture using ethylene-glycol, the conventional solvent, and tetraethylene-glycol, an alternative solvent, are presented. These results showed that the process using tetraethylene-glycol is reliable, although it requires more energy than the process with ethylene-glycol. However, ethylene-glycol has a considerable toxicity level while tetraethylene-glycol is non-toxic.     

Systematic incorporation of inherent safety in hazardous chemicals supply chain optimization

Increasing globalization has made many chemical supply chains large, interdependent and complex. Process incidents often affect the reliability of a supply chain and can cause large disruptions at different segments of the industry. We propose an optimization-based framework that systematically takes into account the trade-offs between process safety and supply chain economics for decision-making. We quantify the hazard at various supply chain echelons in the form of a safety index that takes both fire and toxic hazards into account. A mixed-integer nonlinear programming (MINLP)-based model is developed to either maximize profit for specified hazard limits, or to minimize hazard in a supply chain with multiple production plants, technological options, warehouses and distribution nodes. The MINLP model is used to generate trade-off optimal solutions for various toxic and fire hazard limits. The framework is demonstrated by applying it to an end-to-end ammonia supply chain case study which resulted in several non-intuitive observations regarding hazardous supply chain design and optimization.     

Optimizing safety-constrained solvent selection for process systems with economic uncertainties

Solvents are very commonly used in industrial facilities for a multitude of reasons. Traditionally, solvent selection has been based on minimizing the process operating cost while satisfying a set of operational requirements. Regrettably, safety considerations have typically been overlooked during the design phase. In this paper, a systematic approach is introduced to integrate safety issues into solvent selection and provides a computationally effective method for establishing tradeoffs between the economic and safety objectives. In order to quantify the risk associated with the solvent, we focus on the potential spillage of the solvent and introduce a risk index that is a function of the amount of solvent used and stored, as well as the Permissible Exposure Limit (PEL) dictated by regulatory directives. An optimization formulation is developed and the associated mathematical program solved to select optimal solvents and blends while incorporating economic, technical, and safety considerations. Tradeoff (Pareto) curves are developed to represent the multi-objective optimization results and tradeoffs. Furthermore, economic-data uncertainty and variability over expected ranges are included in the optimization formulation to conduct an insightful sensitivity analysis. Finally, an illustrative case study is considered via increasing levels of complexity in order to evaluate the proposed optimization method which considers both operating cost and safety risk implications in the presence of economic uncertainties.     

Ageing management and monitoring of critical equipment at Seveso sites: An ontological approach

A safe “ageing” of Seveso establishments is a challenge for both operators and regulators. To this scope, Seveso III Directive required to integrate the equipment integrity issue into the safety management system for the major accident prevention; at the same time, the Italian Authority adopted a short-cut method for a quick ageing evaluation, which awards the application of the best techniques to control integrity and prevent deterioration-related failures. In this paper, the use of the ontology has been proposed to support decision-making about the implementation of technical solutions to control equipment ageing and comply the requirements of the Seveso legislation. To contrast deterioration mechanisms, the rapid development of data intensive smart sensors should be exploited and, in this frame, the automated on-line direct monitoring of equipment conditions, based on innovative low-cost sensors, is a novelty and promising solution. The developed ontology-based system points towards the adoption, when possible, of on-line monitoring. This solution provides much more data than traditional measurements and it is essential for the operators to understand how to merge concurrent information and data and to adequately control equipment deterioration. The ontology-based approach appears a viable solution even for this purpose. To demonstrate its potentiality, a real use-case has been used, where the model has been tested in finding the best technical solutions to improve the ageing management of an atmospheric distillation unit of a refinery in order to comply with safety requirements. A further use-case is given to show how the model can be used to react, after real-time damage signals, to restore safety conditions by means of an adequate decision-making.     

The integration of Dow's fire and explosion index (F&EI) into process design and optimization to achieve inherently safer design

For the processing industries, it is critically to have an economically optimum and inherently safer design and operation. The basic concept is to achieve the best design based on technical and business performance criteria while performing within acceptable safety levels. Commonly, safety is examined and incorporated typically as an after-thought to design. Therefore, systematic and structured procedure for integrating safety into process design and optimization that is compatible with currently available optimization and safety analysis methodology must be available.The objective of this paper is to develop a systematic procedure for the incorporation of safety into the conceptual design and optimization stage. We propose the inclusion of the Dow fire and explosion index (F&EI) as the safety metric in the design and optimization framework by incorporating F&EI within the design and optimization framework. We first develop the F&EI computer program to calculate the F&EI value and to generate the mathematical expression of F&EI as a function of material inventory and operating pressure. The proposed procedure is applied to a case study involving reaction and separation. Then, the design and optimization of the system are compared for the cases with and without safety as the optimization constraint. The final result is the optimum economic and inherently safer design for the reactor and distillation column system.     

Advanced process control system with MPC as a new approach for layer of protection analysis

Layer of protection analysis (LOPA) is a widely used method to support process safety in the chemical industries. In the LOPA, the process is classified into many layers, one of such layers considers the basic process control system (BPCS) which commonly uses PID controllers. This kind of controllers cannot deal with constraints. For this reason, the main purpose of this work is to provide a framework to enhance the control layer in the LOPA, which consists of a model predictive control (MPC) with safety features. These features include: sublayers in the controller system (such as real time optimization, target calculation, and MPC), safety constraints, and guarantee of stability by adopting an Infinite Horizon MPC (IHMPC). Here, we propose an approach for control-inspired view to process safety, replacing the BPCS by an Advanced Process Control System (APCS). Moving forward with these concepts, first, a literature review emphasizes the content, showing two perspectives for the APCS. The APCS is designed for two varieties of controllers, a basic IHMPC and IHMPC with zone control to compare the performance. In this framework, the first sublayer consists of a real time optimization (RTO) structure, that calculates the optimal operating condition for the process controller, which computes the control action. Besides, RTO has an additional constraint called the safety index, based on the protection of process operational. RTO and basic IHMPC communicate directly, while for IHMPC with zone control there is an inner sublayer called Target Calculation, it computes a feasible target to the controller, working as another safety strategy in APCS. After that, we demonstrate both structures applied to a CSTR reactor. From the case study, we compared both controllers, and evaluated the effect that the safety index constraint causes in the setpoints, outputs, and control actions. The use of safety constraint in RTO proved to be a safe strategy for the control layer, as well as IHMPC with zone control presented a safer profile than basic IHMPC. Furthermore, the results show that safety constraint affect the economic goal, decreasing its value.     

先进控制软件(APC)在精馏装置的应用

为进一步提高甲醇精馏装置的综合自动化水平,稳定工艺指标,根据装置安全稳定运行的重要性,采用先进控制技术,应用预测控制、智能控制、软测量等先进控制技术,研究模型预测和反馈控制。结果表明:精馏装置相关工艺参数波动明显变小,工艺参与运行趋于更加平稳,产品质量也得到提升。     

PLS-based EWMA fault detection strategy for process monitoring

Fault detection (FD) and diagnosis in industrial processes is essential to ensure process safety and maintain product quality. Partial least squares (PLS) has been used successfully in process monitoring because it can effectively deal with highly correlated process variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T² and the Q statistics are ill suited to detect small faults because they only use information from the most recent observations. Other univariate statistical monitoring methods, such as the exponentially weighted moving average (EWMA) control scheme, has shown better abilities to detect small faults. However, EWMA can only be used to monitor single variables. Therefore, the main objective of this paper is to combine the advantages of the univariate EWMA and PLS methods to enhance their performances and widen their applicability in practice. The performance of the proposed PLS-based EWMA FD method was compared with that of the conventional PLS FD method through two simulated examples, one using synthetic data and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS, especially in the presence of faults with small magnitudes.     

最优指标法在环境监测优化布点中的应用

采用最优指标法对郑州市17个大气环境采样点的监测数据进行优选,得到的优化点位基本能反映城市空气质量的总体情况,可以达到环境监测优化布点的目的.     

基于Multi-class SVM的车辆换道行为识别模型研究

自动安全换道是车辆实现无人驾驶的关键,为精确识别行驶车辆换道状态,保证行车安全,设计了一种基于多分类支持向量机(Multi-class Support Vector Machine,Multiclass SVM)的车辆换道识别模型。从NGSIM数据集中选取美国101公路车辆轨迹数据进行分类处理,并将车辆换道过程划分为车辆跟驰阶段、车辆换道准备阶段和车辆换道执行阶段。采用网格搜索结合粒子群优化算法(Grid Search-PSO)对SVM模型中惩罚参数C和核参数g进行寻优标定,利用多分类支持向量机换道识别模型对样本数据进行训练和测试,模型测试精度达97.68%。研究表明,模型能够很好地识别车辆在换道过程中的行为状态,为车辆换道阶段的研究提供支持。     

Steady-state analyses for reactive distillation control: An MTBE case study

An approach, based purely on steady-state analyses, for synthesizing effective control structures for reactive distillation (RD) columns is presented. The main idea is to analyze the steady-state relationships between the manipulated (input) variables and the potential controlled (output) variables to identify input–output (IO) pairings that are sensitive and avoid steady-state multiplicities providing a large range of nearly linear operating region around the base case design. Traditional SISO control loops are then implemented using these IO pairings to obtain control structures that maintain the column near the design product purity and conversion for the anticipated primary disturbances. The Niederlinski Index is used to eliminate dynamically unstable pairings in control structures with multiple loops. The approach is demonstrated on an example MTBE RD column. The impact of steady-state multiplicities on control structure design is highlighted.     

基于GPR-TOPSIS方法的充填配比多目标多属性优化

为获得某金矿尾砂胶结充填材料最优配比,基于试验结果,以海水比例、灰砂比和料浆质量浓度为输入参数,以充填体强度、塌落度及泌水率为输出参数,建立了充填配比与其响应量的高斯过程回归模型,分析了不同因素对充填性能的影响程度;采用遗传算法对高斯过程回归模型进行多目标参数优化,获得了Pareto非劣解,在此基础上,引入多属性决策的TOPSIS法对Pareto非劣解进行方案优选,确定了充填最优配比。研究结果表明:高斯过程回归模型相对误差值均小于6%,可靠性高;灰砂比及料浆质量浓度对充填性能影响较为显著,采用海水作为充填水源将降低充填体的强度;经优化后的充填配比与试验结果相符。     

A formulation to optimize the risk reduction process based on LOPA

This paper presents a mixed integer nonlinear programming (MINLP) model to improve the computational use of the layer of protection analysis (LOPA). For a given set of independent protection layers to be implemented in a process, the proposed optimization model is solved to: a) Include costs associated with the different prevention, protection and mitigation devices, and b) Satisfy the risk level typically specified in the LOPA analysis through the occurrence probability. The underline purpose focuses on improving the analysis process and decision making to obtain the optimal solution in the safeguards selection that satisfies the requirements to be considered as IPL’s. The optimization is based on economic and risk tolerance criteria. As a first stage of this proposal, the safety instrumented system (SIS) design is optimized so that the selection of SIS components minimizes the risk and satisfies the safety integrity level (SIL) requirements. A case study is presented to validate the whole proposed approach.     

Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.     

The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): two novel evaluation methods for developing optimal training programs

Current methodologies in training evaluation studies largely employ a single method entitled random confirmatory trials, prompting several concerns. First, practitioners and researchers often analyze the effectiveness of their entire omnibus training, rather than the individual elements or identifiable components of the training program. This slows the testing of theory and development of optimal training programs. Second, a common training is typically administered to all employees within an organization or workgroup; however, certain factors may cause individualized training to be more effective. Given these concerns, the current paper presents two training evaluation methodologies to overcome these problems: the multiphase optimization strategy and sequential multiple assignment randomized trials. The multiphase optimization strategy is a method to evaluate a standard training, which emphasizes the importance of a multi‐stage training evaluation process to analyze individual training elements. In contrast, sequential multiple assignment randomized trial is used to evaluate an adaptive training that varies over time and/or trainees. These methodologies jointly overcome the problems noted earlier, and they can be integrated to address several of the key challenges facing training researchers and practitioners. Copyright © 2016 John Wiley & Sons, Ltd.     

Seismic response mitigation of chemical plant components by passive control techniques

This paper deals with the applicability of seismic passive control in major-hazard chemical installations. The objective is to show numerically and experimentally the applicability of Passive Control Techniques (PCT) in industrial plants. Consequently, the main components of a process plant are classified and collected into a limited number of classes; for each class, the main damages caused by past earthquakes are described and the most vulnerable components are identified. A synthesis of the effects of earthquakes on the different typologies of process components is also presented and the most suitable innovative seismic protection systems, in particular passive control techniques (PCT), are acknowledged. Finally, the effectiveness of PCT in reducing the seismic response of process plant components is proved by three representative case studies: a base isolated above-ground storage tank, a distillation column connected by elastoplastic dampers to the adjacent service frame and an application of non-conventional Tuned Mass Dampers to a support frame.     

溜井泡沫抑尘剂的研制及其抑尘性能实验研究

矿山溜井卸矿过程中产生的大量冲击性粉尘已成为矿井可呼吸性粉尘的主要来源,为了有效解决溜矿井卸矿时产生的大量冲击性粉尘,基于泡沫抑尘的机理,研究了发泡倍数和半衰期两个指标进行优选实验,通过正交法和单因素法优选出最佳的泡沫抑尘配方为十二烷基硫酸钠、月桂酸钠和聚丙乙酰胺,各成分的质量浓度分别为0.6%、0.8%与0.4%。结果表明,通过模拟溜井卸矿测得不同泡沫高度的抑尘效率在85%~95%之间,呼吸性粉尘的抑尘效率为87%左右,其时效性可达2h以上。