In this work a computational framework is proposed for the synthesis of flexible and controllable Heat Exchanger Networks. The synthesis is projected to operate over a specified range of expected variations in the inlet temperatures and flowrates of the process streams using a decentralized control system, such that the Total Annual Cost involving the utility consumption and the investment are optimized simultaneously. The framework is based on a two-stage strategy. A design stage is performed prior to the operability analysis where the design variables are chosen. In the second stage, the control variables are adjusted during operation on the realizations of the uncertain parameters. The framework yields a HEN design, which is guaranteed to operate with the designed control system under varying conditions ensuring stream temperature targets and optimal energy integration. The application of the proposed framework and its computational efficiency are illustrated with some numerical examples.
-In biotechnological processes, the productivity and costs depend strongly on the control of the operating conditions. For this reason, sensors that allow the monitoring of variables of interest become quite important. 2D fluorescence spectroscopy is one promising option among those that are being applied for this purpose. In the present work, three methods were evaluated to select the best excitation/emission wavelength pairs of 2D fluorescence spectra to infer product, substrate and cellular concentrations throughout a fermentation using a multiple linear chemometric model: Exhaustive Search (ES), Stepwise Regression and Genetic Algorithm (GA). The Stepwise Regression presented unsatisfying results, while GA always led to good R 2 values in short computational times. However, for the proposed problem, the ES showed the best performance, finding the global optimum in a few minutes.
The demand for hydrogen in refineries is growing due to its importance as a sulfur capture element. Therefore, hydrogen management is critical for fulfilling demands as efficiently as possible. Through mathematical modeling, hydrogen network management can be better performed. Cost-efficient Mixed-Integer Linear Programming (MILP) and Mixed-Integer Nonlinear Programming (MINLP) optimization models for (re)designing were proposed and implemented in GAMS with two case studies. Linear programming has the limitation of no stream mixing allowed; therefore, to overcome this limitation, an algorithm-based procedure called the Virtual Compressor Approach was proposed. Based on the MILP optimal solution obtained, the streams and compressors were merged. As a result, the number of compressors was reduced, along with the inherent investment costs. An operational cost reduction of more than 28% (example 1) and 26% (example 2) was obtained with a linear model. The optimal MILP solution after rearranging compressors was then provided as a good starting point to the MINLP. The operating costs were decreased by more than 31% (example 1) and 32% (example 2). Most of the cost reduction was obtained only with the usage of the MILP model. Besides, a higher level of cost reduction was only obtained when the linear model was used as the starting point.
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