Modeling and Optimization of a Large-Scale Ethylene Plant Energy System with Energy Structure Analysis and Management

The energy system of industrial process, particularly in the petrochemical industry, consumes most of the utility cost. In this paper, a superstructure of a large-scale industrial ethylene plant energy system including fuel, steam, electricity and water was studied. In this system, multitype energy is transferred by water, as the working medium, which makes it feasible for the multitype energy to be synthesized according to the heating, cooling, and phase changes of water. The unit models were developed by hybrid modeling method combining thermodynamics and least-square method (LSM). The seasonal energy system optimization based on typical day method was formulated as an mixed-integer nonlinear programming (MINLP) problem. Then, an efficient decomposition-based model solving strategy was proposed for solving this difficult problem, in which the fuel, steam, electricity, and water consumption were simultaneously optimized. The optimal operational solution was obtained by the following strategies: (1) regulating the steam flow rate in letdown valves, the condensing steam flow rate extracted from turbines, and selections of power sources for low demand mechanical users synergistically; (2) determining the cooling water temperature to balance the turbine efficiency and the electricity and water consumption; and (3) employing different numbers of cooling towers according to the seasons. The flow rate-related decisions are sensitive to uncertainty in the measurement, while the temperature-related and pressure-related ones are relatively more stable. The results showed that the total energy consumption was reduced by 14.42% in spring–autumn and 13.92% in summer, which were 1.44 and 0.89% better than these using the two-type energy optimization method in literature, respectively. Further energy structure analysis exhibiting consumption proportion of different types of energy showed that part of the fuel consumption was replaced by cheaper steam and electricity to reduce total energy cost. Finally, energy management strategies were formed on the basis of the above results

DataSheet_1_Serum levels of IL-6 and CRP can predict the efficacy of mFOLFIRINOX in patients with advanced pancreatic cancer.docx

ObjectivesThere is an urgent need for biomarkers that predict the survival outcome of patients diagnosed with metastatic pancreatic cancer, undergoing systemic chemotherapy. This study aimed to identify biomarkers associated with the survival of mPC patients treated with modified FOLFIRINOX (mFOLFIRINOX) as first-line chemotherapy.MethodsThis was a retrospective study of 30 patients with mPC who received mFOLFIRINOX between October 2018 and March 2021. Data on carcinoembryonic antigen (CEA), cancer antigen (CA)199, interleukin (IL)-6, C-reactive protein (CRP), neutrophils, platelets, lymphocytes, and albumin were collected and dichotomized using the upper or lower limit, as appropriate. These markers were examined for their association with progression-free survival (PFS). A receiver operating characteristic (ROC) curve analysis was used to explore a suitable model to predict mFOLFIRINOX effectiveness.ResultsIL-6 and CRP levels were associated with poor progression (P = 0.004 and P = ConclusionsThe serum levels of IL-6 and CRP might be considered as valuable biomarkers in predicting the outcomes of patients with mPC who received the mFOLFIRINOX regimen.</p