Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and...Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.展开更多
This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using c...This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.展开更多
The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap co...The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.展开更多
数据复制技术广泛用于数据网格,如何合理地放置复制时产生的数据副本来更有效地提高数据访问性能成为一个值得研究的重要问题。本文针对无向连通图表示的数据网格模型,提出了一种满足各用户服务质量(quality of service,QoS)需求的副本...数据复制技术广泛用于数据网格,如何合理地放置复制时产生的数据副本来更有效地提高数据访问性能成为一个值得研究的重要问题。本文针对无向连通图表示的数据网格模型,提出了一种满足各用户服务质量(quality of service,QoS)需求的副本放置算法(replica placement algorithm,RPA),通过该QoS感知的副本放置算法能够获得k个副本放置位置,并且使得整个数据网格系统的通信代价最小。最后,文章通过相应的仿真实验证明了该算法的可靠性和有效性。展开更多
220 k V电网的站、线数量较多,电网拓扑复杂,如何经济、合理地配置220 k V线路的故障行波测距装置,实现故障测距功能的全覆盖,具有重要意义。该文分析线路故障电流行波可测性,采用扩展邻接矩阵对输电网各回线路和站际间的连接关系进行...220 k V电网的站、线数量较多,电网拓扑复杂,如何经济、合理地配置220 k V线路的故障行波测距装置,实现故障测距功能的全覆盖,具有重要意义。该文分析线路故障电流行波可测性,采用扩展邻接矩阵对输电网各回线路和站际间的连接关系进行抽象。以工程实际条件与可测性分析结果相结合作为必要的附加条件,将电流行波测距装置在电网的优化布置抽象为含不等式和等式约束的线性0-1规划模型,进而确定模型参数与电网拓扑参数的关系及模型求解方法,获得行波测距装置的全网最优静态布置方案。在此基础上,以每退出一套行波测距装置导致单、双端测距原理所减少的直接与间接可测线路的加权长度最小为依据,确定行波测距装置的动态装设顺序。并以某220 k V实际电网为例,验证所提算法的可行性及有效性。展开更多
基金Supported by the National Natural Science Foundation of China(51474184)the Natural Science Foundation of the State Administration of Work Safety in China(2012-387,Sichuan-0021-2016AQ)
文摘Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.
文摘This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.
文摘The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.
文摘数据复制技术广泛用于数据网格,如何合理地放置复制时产生的数据副本来更有效地提高数据访问性能成为一个值得研究的重要问题。本文针对无向连通图表示的数据网格模型,提出了一种满足各用户服务质量(quality of service,QoS)需求的副本放置算法(replica placement algorithm,RPA),通过该QoS感知的副本放置算法能够获得k个副本放置位置,并且使得整个数据网格系统的通信代价最小。最后,文章通过相应的仿真实验证明了该算法的可靠性和有效性。
文摘220 k V电网的站、线数量较多,电网拓扑复杂,如何经济、合理地配置220 k V线路的故障行波测距装置,实现故障测距功能的全覆盖,具有重要意义。该文分析线路故障电流行波可测性,采用扩展邻接矩阵对输电网各回线路和站际间的连接关系进行抽象。以工程实际条件与可测性分析结果相结合作为必要的附加条件,将电流行波测距装置在电网的优化布置抽象为含不等式和等式约束的线性0-1规划模型,进而确定模型参数与电网拓扑参数的关系及模型求解方法,获得行波测距装置的全网最优静态布置方案。在此基础上,以每退出一套行波测距装置导致单、双端测距原理所减少的直接与间接可测线路的加权长度最小为依据,确定行波测距装置的动态装设顺序。并以某220 k V实际电网为例,验证所提算法的可行性及有效性。
