60 research outputs found

    Water–Phosphorus Nexus for Wet-Process Phosphoric Acid Production

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    The water–phosphorus nexus problem for wet-process phosphoric acid production is first addressed in this article. A systematic methodology for water system optimization and water–phosphorus nexus analysis is proposed. On the basis of the preliminary process flowsheet and water flow rate balance, the potential water sources and sinks as well as the key component can be extracted. The mathematical model for the water system optimization integrated with water flow rate balance is presented. The process flowsheet can be improved according to the optimized water system. The flow rate of fresh water is reduced from 1803.98 t/h (preliminary design) to 160.98 t/h (improved design). The utilization efficiencies of the phosphorus element (calculated as P<sub>2</sub>O<sub>5</sub>) are calculated for the preliminary and improved designs. Because the process for wet-process phosphoric acid production is mostly in the aqueous phase, the utilization efficiency of the phosphorus element is increased from 94.22% (preliminary design) to 98.76% (improved design) due to the reuse and recycling of water stream with the phosphorus element. Water minimization and phosphorus recovery can be achieved simultaneously. The additional annualized profit for the improved design reaches 248.8 × 10<sup>6</sup> CNY/a, which is a great benefit for the production plant

    Deciphering Refinery Water System Design and Optimization: Superstructure and Generalized Mathematical Model

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    The up-to-date approaches to optimizing water systems only include fresh water, regenerated water and wastewater and ignore other types of water in refinery, i.e., desalted water, deaerated water, circulated cooling water, steam with different pressure levels and condensate water. Therefore, the existing mathematical model for water system optimizaiton is not directly applicable for the optimization of practical refinery water systems. To overcome the limitation and bridge the theory and application, we first presented a generalized model of water-using processes including multiple types of water and a general superstructure for the optimization of refinery water system. The superstructure consists of water-using processes including multiple types of water in the main production units (i.e., crude oil distillation, fluid catalytic cracking), water pretreatment systems (i.e., fresh water station, desalted water station, steam power station) and wastewater treatment system. The flow rate balance equations for those components of a refinery water system and the correlation for all types of water are formulated. The replacement ratio of altered type of water is introduced in the flow rate balance equations for water reuse/recycling and it avoids the imprecise data extraction of limiting water quality for the inlets of water-using processes. We presented two mathematical models with different objective functions (minimum flow rate of water resource (Scenario 1) and minimum partial annualized cost (Scenario 2)). The proposed models are applied for the optimization of the water system of a large-scale refinery in China. Results show that the water system with a minimum flow rate of water source can be obtained in Scenario 1. In Scenario 2, the profit of water conversation for five strategies cannot offset the investment cost of added pipelines, and their actual replacement ratios are zero. It leads to an economic and simpler water system with slightly higher flow rate of water resources

    Algebraic Approach for the Integration of the Hydrogen Network with a Single Impurity

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    Fresh hydrogen is an expensive utility in refineries. The integration of hydrogen networks can make full use of hydrogen and reduce the fresh hydrogen consumption. In this work, a rigorous algebraic approach is proposed on the basis of the pinch conception to identify the minimum fresh hydrogen consumptions and pinch locations of hydrogen networks. This algebraic approach is derived from an existing graphical method by transforming the moving procedure of the source composite curve into an algebraic calculation according to the geometrical transformations. The conception of relative flow rate is introduced to describe each hydrogen source and sink. On this basis, a noniterative algebraic procedure is developed to figure out the surplus fresh hydrogen in each interval. Finally, the minimum fresh hydrogen consumption and pinch location can be identified. Furthermore, the proposed approach can be enlarged by considering the hydrogen purification process, and the purification process can be further analyzed to minimize its feed flow rate. This approach has a clear conception and an easy procedure and is valid for the hydrogen network with fresh hydrogen of any hydrogen concentration. A conventional hydrogen network is analyzed to test the applicability of the proposed approach

    Coefficients of the polynomial fit for <i>n</i>, <i>Q</i>, <i>α</i>, and ln <i>A</i>.

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    <p>Coefficients of the polynomial fit for <i>n</i>, <i>Q</i>, <i>α</i>, and ln <i>A</i>.</p

    4th order polynomial fit of the material constants.

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    <p>(a) <i>α</i>, (b) <i>n</i>, (c) <i>Q</i>, and (d) ln <i>A</i>.</p

    Chemical composition of the 316LN steel used in this study (wt.%).

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    <p>Chemical composition of the 316LN steel used in this study (wt.%).</p

    The relative error between the predicted curve and experimental curve at 900°C and 10 s<sup>−1</sup> and the given strain.

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    <p>The relative error between the predicted curve and experimental curve at 900°C and 10 s<sup>−1</sup> and the given strain.</p

    Comparison of experimental curves and predicted curves at various strain rates.

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    <p>(a) 10<sup>−3</sup> s<sup>−1</sup>, (b) 10<sup>−2</sup> s<sup>−1</sup>, (b) 10<sup>−1</sup> s<sup>−1</sup>, (b) 1 s<sup>−1</sup> and (b) 10 s<sup>−1</sup>.</p

    Flow stress curves of 316LN steels compressed at different temperatures and strain rates.

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    <p>(a) 10<sup>−3</sup> s<sup>−1</sup>, (b) 10<sup>−2</sup> s<sup>−1</sup>, (b) 10<sup>−1</sup> s<sup>−1</sup>, (b) 1 s<sup>−1</sup> and (b) 10 s<sup>−1</sup>.</p
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