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Show prohibiting furnace designers and operators to optimize these design parameters. With the growth of CFD (Computational Fluid Dynamics) technology, a three dimensional numerical analysis has become one of the promising tools to facilitate the optimization of design parameters as well as operating conditions of a wide variety of industrial furnaces. C F D method is capable of predicting complex heat transfer phenomena generated by flow, combustion, thermal conduction and radiation. C F D method is believed to help encourage the design of innovative high performance furnaces. It also predicts emissions from furnaces by coupling with specific chemical reaction models. For all of its advantages, C F D still requires lots of know-how and expertise to model various furnaces. Furthermore, it requires relatively long period of time to obtain results. For those reasons, the use of C F D used to be out of reach for furnace designers and engineers. Three Japanese major gas companies (Tokyo Gas, Osaka Gas and Toho Gas) recognized the advantages of C F D methods as a powerful tool for providing engineering services. They also recognized problems associated with the practical use of C F D . To solve the problems, a joint collaboration was made to develop an intelligent pre-processor for C F D of industrial furnaces named if-Diss. Coupled with major C F D solvers such as C F X , F L U E N T / U N S and STAR-CD, if-Diss maximize the capabilities of C F D for the industrial furnaces. This paper describes development and results of test runs of the pre-processor if-Diss. 2. CONCEPTS OF if-Diss 2.1. Model Database The first objective of the development of if-Diss is to establish a model database that integrates developed mathematical models, knowledge and know-how related to the C F D analysis of industrial furnaces. The database is aimed to integrate mathematical models for natural gas flames which has been developed by the participating gas companies along with universities and institutions and a lot of experience that has been compiled for the C F D analysis of industrial furnaces. The database allows non-experts to easily conduct C F D analysis, which used to require deep understanding of physical phenomena as well as mathematical modeling. The database provides a variety of established mathematical models and technical know-how. Furthermore, the database incorporates newly developed technologies and know-how. 2.2. Pre-processor The second objective is to reduce user's workload for pre-processing. Figure 1 shows typical work processes for C F D of industrial furnaces. Part of the preparation for calculation, such as specifying furnace configuration, choosing calculation models, generating numerical grid and so on, is called "pre-processing." The workload of pre-processing is generally quite high. Wide and specialized knowledge on both C F D methods and industrial furnaces are required, consuming very long period of time and often evoking frustration. Furthermore, the whole process including the pre-processing needs to be iterated whenever input conditions are to be changed in for parametric study. A n intelligent pre-processing tools are required to reduce workload and to utilize C F D effectively. 2 |
