Compressor Driven Networks Flows

压缩机驱动的网络流

• 批准号: 9622106
• 负责人: Way Kuo
• 金额: $ 24.89万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-15 至 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9622106&HistoricalAwards=false
• 关键词: Compressor; Driven; Networks; Flows

9622106 Boyd This research focuses on models and solution methodologies for minimizing fuel consumption in compressor-driven flow networks. Recent advances in the fields of discrete optimization and large-scale integer programming will be employed, and solution algorithms will be developed on parallel computing platforms. The domain of feasible solutions prescribed by the models is mathematically complicated by virtue of the existence of both nonlinearities and discontinuities. Classical techniques are wholly inadequate for many of the large and growing pipeline networks in operation today. Necessary mathematical results will be developed for obtaining optimization algorithms, first, for the steady-state case, and then, for the transient case. Intelligent search procedures will be developed and mixed-integer linear programming models will be developed for the steady-state case. Based on the experience gained in the steady-state analysis, an algorithm for solving the transient case will be developed. Results of this research can be used to operate existing networks efficiently, to evaluate tradeoffs between safety and throughput, and to design safe and energy-efficient new networks. The direct impact of the research will be applicable methods for reducing operating costs and pollutants generated by the thousands of gas pipeline networks in operation throughout the world. A better understanding of a little-studied class of network flow problems with broad applicability in a variety of industries will also result.

9622106 Boyd 这项研究的重点是最大限度地减少压缩机驱动的流动网络中的燃料消耗的模型和解决方案方法。 将采用离散优化和大规模整数规划领域的最新进展，并在并行计算平台上开发求解算法。 由于非线性和不连续性的存在，模型规定的可行解的域在数学上是复杂的。 经典技术完全不足以满足当今运行中的许多大型且不断增长的管道网络的需要。 将开发必要的数学结果以获得优化算法，首先针对稳态情况，然后针对瞬态情况。 将开发智能搜索程序，并针对稳态情况开发混合整数线性规划模型。 根据稳态分析中获得的经验，将开发解决瞬态情况的算法。 这项研究的结果可用于有效运营现有网络，评估安全性和吞吐量之间的权衡，以及设计安全且节能的新网络。 该研究的直接影响将是减少世界各地运行的数千个天然气管网产生的运营成本和污染物的适用方法。 还将更好地理解一类鲜为人知的网络流问题，并在各个行业中具有广泛的适用性。