Magnetic Field Simulation With Data-Driven Material Modeling

Data-driven modeling and simulation framework for material handling systems in coal mines

In coal mining industry, discrete-event simulation has been widely used to support decisions in material handling system (MHS) to achieve premiums on revenues. However, the conventional simulation modeling approach requires extensive expertise of simulation during the modeling phase and lacks flexibility when the MHS structure changes. In this paper, a data-driven modeling and simulation framew...

Magnetic Material with Large Magnetic-Field-Induced Deformation

Dynamic data driven simulation with soft data

Dynamic data driven simulation dynamically assimilates observation data at runtime to improve the simulation results. Typically, the observations are “hard data” that are data collected from sensors. In this paper we consider dynamic data driven simulation with soft data, which are data coming from human reports. Compared with the quantified hard data, soft data are qualitative, fuzzy and subje...

modeling loss data by phase-type distribution

بیمه گران همیشه بابت خسارات بیمه نامه های تحت پوشش خود نگران بوده و روش هایی را جستجو می کنند که بتوانند داده های خسارات گذشته را با هدف اتخاذ یک تصمیم بهینه مدل بندی نمایند. در این پژوهش توزیع های فیزتایپ در مدل بندی داده های خسارات معرفی شده که شامل استنباط آماری مربوطه و استفاده از الگوریتم em در برآورد پارامترهای توزیع است. در پایان امکان استفاده از این توزیع در مدل بندی داده های گروه بندی ...

Dynamic Data Driven Methodologies for Multiphysics System Modeling and Simulation

We are presenting a progress overview associated with our work on a data-driven environment for multiphysics applications (DDEMA). In this paper, we emphasize the dynamic-data-driven adaptive modeling and simulation aspects. Adaptive simulation examples of sensororiginating data-driven precomputed solution synthesis are given for two applications. Finally, some of the computational implementati...