Abstract

Publisher Summary This chapter describes a mathematical model for a pipeline infrastructure for CO2 sequestration and utilizes various mathematical programming techniques to find minimum cost strategies for building and operating this pipeline network. The greenhouse gas emissions from direct combustion of fuels can be greatly reduced if they are replaced with hydrogen produced from fossil sources, and if hydrogen production is coupled with capture and secure sequestration of the resulting CO2 at storage sites such as aquifers and depleted hydrocarbon reservoirs. The transportation of CO2 from fossil hydrogen plants to sequestration sites can be accomplished via a pipeline network. The design of this pipeline is an important aspect of the overall energy network. It has been proposed that the CO2 produced at sources such as fossil energy conversion facilities and industrial process plants could be captured, compressed to supercritical pressures, transported via pipelines, and stored in underground geologic formations such as depleted oil and natural gas reservoirs and deep saline aquifers. A nonlinear model of the CO2 pipeline system is described, with appropriate constraints, and the lowest cost system is found using a state-of-the-art nonlinear optimization software called LOQO. The chapter also presents ways to model the behavior of the system over time, and to model the impact of uncertainties. Document type: Part of book or chapter of book

Abstract

International audience Air traffic management (ATM) represents a domain of emerging and challenging applications of mixed-integer nonlinear programming (MINLP). A number of problems arising in ATM lead naturally to optimization problems whose efficient and reliable solution constitutes a key ingredient of air traffic safety [576]. The air traffic level currently attained in Europe is on the order of tens of thousands of flights per day, and it is expected to grow further on the world scale during the next 20 years. Increasing levels of traffic raise the problem of increasing the capacity of air sectors by better managing the air traffic. This requires increasing the level of automation in ATM, as pointed out in the context of the major projects Single European Sky ATM Research (SESAR) [1667] in Europe and Next Generation Air Transportation System (NextGen) [906] in the United States, which are aimed at designing future ATM systems. Aircraft conflict detection and resolution in en route flights, and the related problem of conflict-free aircraft trajectory planning, are prominent examples of problems that urgently need to be addressed to ensure a higher level of automation in ATM, and consequently more efficiency and safety in air traffic. These problems still deserve investigation of both the identification of suitable mathematical models and the development of efficient and reliable solution methods and algorithms. Mixed-integer nonlinear optimization formulations appear particularly suitable, as they allow us to simultaneously consider continuous as well as discrete decision-making variables and model the complex nonlinear processes characterizing ATM systems. Document type: Part of book or chapter of book