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Fluidized beds with the liquid spray have been widely applied due to efficient heat transfer ability. In this work, the liquid-containing particles and the liquid dispersion pathway are visualized by a unique reversible thermochromic material (RTM) tracking method. The effects of evaporative liquid considering different nozzle modes on bubble density, particle motion and heat transfer are investigated combining PIV and DIA. The results indicate that the liquid injection decreases particle fluctuation and promotes bubble generation. A stable liquid-containing zone is observed under the top spray mode, whereas liquid disperses rapidly under the side-wall spray mode. A multi-zone heat transfer model (MHTM) is then developed based on the bubble growth and inter-layer exchange models. Experimental and calculated temperature profiles indicate that the side-wall spray mode leads to larger temperature differences. The methods proposed can be applied for the analysis of the complex multiphase system and optimization of the nozzle configuration. This work is supported by the National Natural Science Foundation of China for Young (No. 21808198), the Major Research Project of National Natural Science Foundation of China (91834303), the Natural Science Foundation of Zhejiang Province for Young (No. LQ18B060001), the National Science Fund for Distinguished Young (No. 21525627).

This paper presents a novel method for process heat exchanger network integration and decomposition: Clustering Approach. The objective of this new approach is to reduce the complexity of the integrated structure, construction and maintenance cost simultaneously. The main idea of this approach is to divide the original system into two or more clusters (subsystems) under several optimisation constrains such as piping and other investment cost, hot and cold stream matches. The results of utilities and investment cost for both original and clustered system are compared. The outcome of this study indicates effectiveness, potential and further application of the novel method. © 2012 Elsevier B.V.

This paper presents an approach to water system retrofitting by estimating both the economic and environmental impacts of the water network design using bi-objective optimization. The environmental impact is evaluated via benchmarking. By using benchmarking, the decision maker could obtain insight not only into the environmental impact of a certain design belonging to the Pareto optimal solutions, but also into the competitiveness of the design within a particular production sector. The economic criterion used is the total cost of the water network and involves the freshwater cost, annual investment costs of the storage tank, piping and local treatment unit installation, and wastewater treatment cost. This approach uses a mixed-integer nonlinear programming (MINLP) model that enables water re-use and regeneration re-use in batch and semi-continuous processes. The Pareto front is generated using the Normal-Boundary Intersection (NBI) method. The proposed approach can be used for the separate integration of production sections, but also for joint integration of the sections via temporal decomposition. The proposed approach was applied to an industrial case study in a brewery.

In refineries, hydrogen purification techniques include hydrocarbon removal units and hydrogen sulfide (H2S) removal units. Hydrocarbon removal units such as membrane separation and pressure swing adsorption (PSA) are frequently employed in the hydrogen network integration (HNI) study. However, the possibility of integrating H2S removal units into HNI study has been overlooked until recently. In the present work, an improved modeling and optimization approach has been developed to integrate H2S removal units into HNI. By introducing a desulfurization ratio, RdSpl j, simplified mass exchange network (MEN) is incorporated into hydrogen distribution network. Total annual cost (TAC) is employed as the optimizing object to investigate the tradeoffs between hydrogen distribution network cost and MEN cost. A practical case study is used to illustrate the application and effectiveness of the proposed method.

This paper presents two multilevel strategies for retrofitting a large-scale water system, which integrates water-using operations and wastewater treatment units in different production sections within the same network. The proposed strategies are based on temporal decomposition. They can be applied to production processes with repeating batch/semi-continuous operations, and daily changes in production schedules over a working week. This approach uses a mixed-integer nonlinear programming (MINLP) model for water re-use and regeneration re-use in batch and semi-continuous processes (Tokos and Novak Pintaric, 2009). In the first step, both strategies perform simultaneous retrofit of an integrated water system for each working day, by identifying daily re-use and regeneration re-use connections among water consumers in all sections. At the second level, within the first strategy, the design of an integrated water system is performed over the entire working week for each section by fixing the identified daily matches between sections. In the second strategy, the freshwater upper and wastewater lower bounds of the integrated processes are modified, and retrofit is performed for each production section over the entire working week. The proposed strategies are applied to an industrial case study within a Brewery. © 2011 Elsevier B.V.

The aim of this paper is to present a multi-objective genetic algorithm approach to optimize production planning in circumstance of uncertain price. The characteristic feature of this approach proposed is that various objectives are synthetically considered in the solving process. According to multi-objective programming, uncertain parameters in a mathematical model are considered triangular possibility distributions. Thus the uncertain optimizing problem can be transfer to a three objectives optimizing problem. An example was used to show the feasibility of the approach.

In order to achieve the cost-effective targets and reduce the passive environmental influence of chemical processes, mass exchanger network synthesis (MENs) is proposed to reduce the waste to an acceptable level at the cheapest cost. Now pinch analysis is the primary method to synthesize mass exchanger networks. But the capital cost could not be considered in the network analysis or it is difficult to be considered in the synthesizing process. Pointed to the deficiency of pinch analysis method, the genetic-alopex (algorithm of pattern extraction) algorithm is brought forward to synthesize the mass exchanger networks by solving a superstructure mathematical model. The model considers not only operating cost but also capital cost. By solving the mathematical model using genetic-alopex algorithm, we can get the optimal network with the least total cost. The examples computed by genetic-alopex algorithm show that the method is effective.