Fellowship - Turbulence simulations for design optimisation of products affected by fluid forces

Refernza Lavoro: 000085

Luogo: Japan

Data di Chiusura: 10/01/2020

Annuncio inserito il: 30/08/2019

Retribuzione: C10M JPY

Ruolo: Toshiba Fellowship

Categoria: Research & Development

  which complement the incomplete MBD, and achieve both the shortest design turn-around-time (TAT) and the best system performance. Also in the system operations, the aging performance deteriorations and their variations are difficult to predict in the design process are detected by IoT and AI. The results are not only reported to the system operator but also act as feedback to the next system design, and the system reliability is further improved. This research is in the cross research domain, and the chances that the applied researcher is familiar with all the related layers are slim. The Fellowship researcher will pursue research based-on his/her wide, deep knowledge, rich ideas and systematic thinking regardless of one’s major. This research area is likely to be one of the most important ones for the next generation of Toshiba with its wide variety of power electronics businesses. Moreover, Toshiba is the best environment for such research activity considering the existence of all the related layers of power electronics technologies and applications.Turbulence simulations for design optimisation of products affected by fluid forces

Toshiba has been working on producing various products with higher performance and developing technologies such as accurate fluid simulations, topology optimisation for optimal design, and Deep Learning. Topology optimisation, which is auseful strategy for optimal design, is widely used as of recently, especially the topology optimisation based on structural analyses with a variety of commercial software. However, the topology optimisation based on fluid analyses is comparatively new and has not yet been used in the engineering field. Toshiba is working on the topology optimisation based on fluid analyses and trying to apply it to shape optimisation of products affected by fluid forces such as turbo machineries (ex. Power generating turbines). Separately, research on a shape optimisation technology using Deep Learning has been carried out as another method for optimal design.

Description of Research
The aim of this research is to develop turbulence flow simulations with high accuracy for the optimal design of products affected by fluid forces. As mentioned above, Toshiba is trying to utilise topology optimisation based on fluid analyses;, however, turbulence flow simulations with high accuracy are still needed. Therefore, we envisage that  the research plan would be as follows:
STEP 1. To develop turbulence flow simulation with high accuracy around rotor blades by using an open source software OpenFOAM.
STEP 2. To develop a novel technique for design optimisation considering the turbulence simulations, for example, a topology optimisation based on a turbulence simulation, or Deep-Learning-based shape optimisation)

Required Knowledge and Skills
Candidates should possess expertise in turbulence flow simulations, especially unsteady turbulence flow simulations such as LES (Large Eddy Simulation) and DES (Detached Eddy Simulation).

Related papers
[1] M. Tanaka, et al., "Modification of the LSMPS method for the conservation of the thermal energy in laser irradiation processes", International Journal for Numerical Methods in Engineering, 117, 2, 161-187, 2019.
[2] M. Tanaka, et al., "Multi-resolution MPS method", Journal of Computational Physics, 359, 106-136, 2018.
[3] M. Tanaka and T. Masunaga, "Stabilization and smoothing of pressure in MPS method by Quasi-Compressibility", Journal of Computational Physics, 229, 11, 4279-4290, 2010.



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