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Zamarripa, Miguel

Publications and source records attributed to Zamarripa, Miguel.

21 records · Page 2

Techno-Economic Optimization of Fixed Bed and Moving Bed Contactors for CO2 Capture from NGCC Plants Using a Functionalized Metal-Organic Framework

Amine-appended metal–organic frameworks (MOFs) have strong potential for post-combustion CO2 capture from NGCC plants. In this work, a specific tetramine-appended MOF, Mg2(dobpdc)(3-4-3) (dobpdc4− = 4,4′-dioxidobiphenyl-3,3′dicarboxylate; 3-4-3 = N,N′bis(3-aminopropyl)-1,4-diaminobutane), is evaluated due to its superior performance compared to other candidate diamine-appended and tetraamine-appended MOFs. Techno-economic optimization is performed to minimize the cost of capture by using the Framework for Optimization, Quantification of Uncertainty, and Surrogates (FOQUS), which is capable of optimizing systems by using derivative-free optimization solvers where process models are built using numerous modeling platforms. The technical and economic performances of both fixed bed and moving bed processes are compared with state-of-the-art amine-based solvent systems.

Hughes, Ryan

Scale-Bridging Optimization Framework for Desalination Integrated Produced Water Networks

In this work, we develop a Pyomo-based non-linear optimization strategy that includes rigorous MVR models. The detailed desalination unit is integrated into the multiperiod produced water network problem using the trust region filter (TRF) method. TRF decomposes the integrated problem into a master problem consisting of the network variables and a simplified surrogate model for the detailed desalination unit. The surrogate is updated using zero and first-order corrections from the optimal solution of the detailed models at every iteration. This framework allows us to co-optimize the design of the desalination units and operating policy for the multiperiod network. A common design is ensured across all periods using global capacity constraints. We validate the solution obtained using the TRF method by solving the full integrated problem for small network instances and show our results on real case studies on produced water networks from the Permian and Appalachian basins. In this work, we describe our TRF formulation, give details on our implementation in Pyomo, and analyze the results obtained by solving the optimization problem using IPOPT. We also present a discussion on the computational efficiency and scaling using the TRF approach against a full-scale integration of the rigorous models within the water network.

Naik, Sakshi

Optimization strategies for produced water networks with integrated desalination facilities

Optimal management and desalination of produced water is a major challenge for U.S. oil and gas development. Integrating rigorous desalination models into multi-period produced water network optimization problems presents several hurdles, which need to be tackled using advanced optimization strategies. Here, in this work, a novel multi-period produced water network formulation with separate solid and liquid flows is introduced to avoid singularities at zero flows. Rigorous steady state desalination models based on mechanical vapor recompression are embedded at the desalination sites in the network model. An integrated optimization formulation is developed to co-optimize the design of desalination units along with the operation of the network. Furthermore, a more robust approach based on the trust region filter method is developed to efficiently integrate complex desalination models into the multi-period planning problem. Both optimization approaches are demonstrated on a produced water network from the PARETO library (Drouven et al., 2022) using thermal desalination units. Our results show that while the TRF and integrated approaches have comparable solve times, the TRF approach has better performance reliability in terms of solver convergence. Furthermore, the optimal solution obtained by embedding rigorous models into the network is significantly different than when desalination costs are approximated using simple cost models, which motivates further research in this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH