Application of machine learning to viscoplastic flow modeling
نویسندگان
چکیده
منابع مشابه
Application of machine learning algorithms to flow modeling and optimization
1. Motivation and objectives We develop flow modeling and optimization techniques using biologically inspired algorithms such as neural networks and evolution strategies. The applications presented herein encompass a variety of problems such as cylinder drag minimization, neural net modeling of the near wall structures, enhanced jet mixing, and parameter optimization in turbine blade film cooli...
متن کاملApplication of Learning Machine Methods to 3D Object Modeling
Three different machine learning algorithms applied to 3D object modeling are compared. The methods considered, (Support Vector Machine, Growing Grid and Kohonen feature Map) were compared in their capacity of modeling the surface of several synthetic and experimental 3D objects. The preliminary experimental results show that with slight modifications these learning algorithms can be very well ...
متن کاملApplication of Machine Learning Approaches in Rainfall-Runoff Modeling (Case Study: Zayandeh_Rood Basin in Iran)
Run off resulted from rainfall is the main way of receiving water in most parts of the World. Therefore, prediction of runoff volume resulted from rainfall is getting more and more important in control, harvesting and management of surface water. In this research a number of machine learning and data mining methods including support vector machines, regression trees (CART algorithm), model tree...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملApplication of the Extreme Learning Machine for Modeling the Bead Geometry in Gas Metal Arc Welding Process
Rapid prototyping (RP) methods are used for production easily and quickly of a scale model of a physical part or assembly. Gas metal arc welding (GMAW) is a widespread process used for rapid prototyping of metallic parts. In this process, in order to obtain a desired welding geometry, it is very important to predict the weld bead geometry based on the input process parameters, which are voltage...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physics of Fluids
سال: 2018
ISSN: 1070-6631,1089-7666
DOI: 10.1063/1.5058127