Kazunori Shinohara

Modelling Adopter Behaviour Based on the Navier Stokes Equation

Aiming to improve the current models describing the diffusion of innovation, a method based on an analogy with a physical system is presented. In particular, we model the movement of adopters of a particular innovation as a flow and the diffusion of the innovation as heat diffusion, thus making use of mathematical tools such as the Navier-Stokes equation. Building on our previous work, in this study we focus on the movement of adopters in the simulation domain, which we refer to as convection. As an application to modeling the convection phenomenon, we simulate the flow of people in a real building floor, the Tokyo Aquarium. Besides being a necessary part when simulating diffusion of innovations, such a modeling approach may also prove useful in different fields, such as deciding layout of public spaces or evacuation policies.

Shape Optimization Using an Adjoint Variable Method in ITBL Grid Environment

To decrease the fluid drag force on the surface of a specified object subjected to an unsteady flow, under a constant volume condition, the adjoint variable method is formulated by using FEM. Based on the Lagrange multiplier method (a conditional variational principle), this method consists of the state equation, the adjoint equation and the sensitivity equation. To solve the equations effectively using the steepest descent method, a parallel algorithm that finds the Armijos line-search step size is constructed. The shape optimization code for solving a large scale 3D problem using a parallel algorithm was implemented on ITBL using the HPC-MW library. Results show that, by using shape optimization, the fluid drag force on the object can be reduced by about 17.5%. (authors)