Flow Science Japan Inc.

Taitō-ku, Japan

Flow Science Japan Inc.

Taitō-ku, Japan

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Kanazawa K.,Mie University | Yano K.,Mie University | Kawatani R.,Yamaha | Ogura J.,Yamaha | Nemoto Y.,Flow Science Japan Inc.
72nd World Foundry Congress, WFC 2016 | Year: 2016

This study aimed to optimize a gating system design for high pressure die casting (HPDC) to minimize air entrapment defects using mold filling simulation. The optimized gating system design and another conventional design were applied to actual metal molds, and casting experiments using an HPDC machine with each of the gating system designs were conducted. Eventually, the results showed that the optimized gating system design can excellently decrease air entrapment defects in products. © 2016, The WFO (The World Foundry Organization Ltd). All rights reserved.


Kuriyama Y.,Gifu University | Yamada H.,Mie University | Yano K.,Mie University | Michioka Y.,Aisin Takaoka Co. | And 2 more authors.
ICINCO 2013 - Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics | Year: 2013

Tilting-type automatic pouring machines are used for gravity casting in manufacturing processes, and their pouring speed is set by workers through trial and error. Therefore, it is difficult to achieve pouring that results in high-quality casting and high process yield. On the other hand, in recent years, this control input has been derived by computer using a CFD simulator. However, the computation of a single condition currently requires a few hours, and the entire optimization requires hundreds of such computations. Thus, a considerable amount of time is required in order to perform an optimization using a CFD simulator. The purpose of this study was to design a calculation method for a pouring machine that would reduce the calculation time. The effectiveness of the proposed system is shown through CFD simulation.


Kanazawa K.,Mie University | Yano K.,Mie University | Ogura J.,Yamaha | Baba S.,Flow Science Japan Inc.
ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) | Year: 2013

We propose a nonparametric curve optimization method based on a genetic algorithm. With conventional curve optimization methods, since the shape of a curve is defined by a finite number of design variables of real numbers and also has only finite flexibility, such methods may not provide the proper optimum curves. In contrast, the method we propose directly treats curves as solutions in the form of functions, without design variables, and can effectively optimize the curves by numerically synthesizing several functions. We demonstrate the effectiveness of the curve optimization method by applying it to an optimum design problem for die casting using a computational fluid dynamics (CFD) simulation. Copyright © 2013 by ASME.


Kanazawa K.,Mie University | Yano K.,Mie University | Ogura J.,Yamaha | Nemoto Y.,Flow Science Japan Inc.
ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) | Year: 2014

This study aimed to optimize the design of a runner for high-pressure die casting (HPDC) using computational fluid dynamics (CFD) simulations, and to verify the effectiveness of the runner with water-model experiments. A runner is a part of the flow path through which molten metal enters a product part. As a design problem, we sought to optimize the shape of the runner to minimize air entrainment in the runner and align the flow of molten metal after it passed through the runner. The problem was solved using our proposed nonparametric shape optimization method. The method is based on a genetic algorithm (GA), and directly treats a geometric shape that is comprised of several curves as an individual of a GA in the form of a set of mathematical functions. In addition, the crossover, which is one of the genetic operations, is defined as a weighted summation of two parent curves. Thus, the optimization method can generate optimized shapes with a lot of flexibility. The effectiveness of the optimized shape of the runner was demonstrated with both CFD simulations and water-model experiments using a visualization device for HPDC. Copyright © 2014 by ASME.

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