a b s t r a c tWe present a multi-scale framework for the optimal design of CO 2 capture, utilization, and sequestration (CCUS) supply chain network to minimize the cost while reducing stationary CO 2 emissions in the United States. We also design a novel CO 2 capture and utilization (CCU) network for economic benefit through utilizing CO 2 for enhanced oil recovery. Both the designs of CCUS and CCU supply chain networks are multi-scale problems which require decision making at material, process and supply chain levels. We present a hierarchical and multi-scale framework to design CCUS and CCU supply chain networks with minimum investment, operating and material costs. While doing so, we take into consideration the selection of source plants, capture processes, capture materials, CO 2 pipelines, locations of utilization and sequestration sites, and amounts of CO 2 storage. Each CO 2 capture process is optimized, and the best materials are screened from large pool of candidate materials. Our optimized CCUS supply chain network can reduce 50% of the total stationary CO 2 emission in the U.S. at a cost of $35.63 per ton of CO 2 captured and managed. The optimum CCU supply chain network can capture and utilize CO 2 to make a total profit of more than 555 million dollars per year ($9.23 per ton). We have also shown that more than 3% of the total stationary CO 2 emissions in the United States can be eliminated through CCU networks at zero net cost. These results highlight both the environmental and economic benefits which can be gained through CCUS and CCU networks. We have designed the CCUS and CCU networks through (i) selecting novel materials and optimized process configurations for CO 2 capture, (ii) simultaneous selection of materials and capture technologies, (iii) CO 2 capture from diverse emission sources, and (iv) CO 2 utilization for enhanced oil recovery. While we demonstrate the CCUS and CCU networks to reduce stationary CO 2 emissions and generate profits in the United States, the proposed framework can be applied to other countries and regions as well.

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in Wiley InterScience (www.interscience.wiley.com).Multistream heat exchangers (MSHE) enable the simultaneous exchange of heat among multiple streams, and are preferred in cryogenic processes such as air separation and LNG. Most MSHEs are complex; proprietary and involve phase changes of mixtures. Although modeling MSHE is crucial for process optimization, no such work exists to our knowledge. We present a novel approach for deriving an approximate operational (vs. design) model from historic data for an MSHE. Using a superstructure of simple 2-stream exchangers, we propose a mixed-integer nonlinear programming (MINLP) formulation to obtain a HE network that best represents the MSHE operation. We also develop an iterative algorithm to solve the large and nonconvex MINLP model in reasonable time, as existing commercial solvers fail to do so. Finally, we demonstrate the application of our work on an MSHE from an existing LNG plant, and successfully predict its performance over a variety of seasons and feed conditions.

Many chemical plants produce a variety of hydrocarbon gases with fuel value. A fuel gas network (FGN) integrates and uses these fuel gases appropriately to make best use of them. FGNs are critical components of many chemical plants including liquefied natural gas (LNG) plants and refineries. However, a systematic approach to design and operate realistic FGNs is not currently available in the literature. We address the optimal synthesis of an FGN with many practical features such as auxiliary equipment (valves, pipelines, compressors, heaters/coolers, etc.), nonisobaric and nonisothermal operation, nonisothermal mixing, nonlinear fuel-quality specifications, fuel/utility costs, disposal and treatment costs, and emission standards. We develop a nonlinear program (NLP) based on a novel superstructure that embeds plausible alternatives for heating/cooling, moving, mixing, and splitting. We successfully apply our model to three real-life case studies from the LNG and refinery industries to demonstrate that an FGN can save 40À50% of the total energy costs of a plant and reduce the fuel-from-feed or fuel-from-product consumptions by similar amounts. This work represents an important contribution toward conserving energy, preserving the environment, and improving plant economics using advanced techniques of process systems optimization.