Open-wheeled race car aerodynamics is unquestionably challenging insofar as it involves many physical phenomena,such as slender and blunt body aerodynamics,ground effect,vortex management and interaction between diffe...Open-wheeled race car aerodynamics is unquestionably challenging insofar as it involves many physical phenomena,such as slender and blunt body aerodynamics,ground effect,vortex management and interaction between different sophisticated aero devices.In the current work,a 2017 F1 car aerodynamics has been investigated from a numerical point of view by using an open-source code.The vehicle project was developed by PERRINN(Copyright.2011—Present PERRINN),an engineering community founded by Nicolas Perrin in 2011.The racing car performance is quantitatively evaluated in terms of drag,downforce,efficiency and front balance.The goals of the present CFD(computational fluid dynamics)-based research are the following:analyzing the capabilities of the open-source software OpenFOAM in dealing with complex meshes and external aerodynamics calculation,and developing a reliable workflow from CAD(computer aided design)model to the post-processing of the results,in order to meet production demands.展开更多
This paper presents an OCPA （operant conditioning probabilistic automaton） bionic autonomous learning system based on Skinner＇s operant conditioning theory for solving the balance control problem of a two-wheeled f...This paper presents an OCPA （operant conditioning probabilistic automaton） bionic autonomous learning system based on Skinner＇s operant conditioning theory for solving the balance control problem of a two-wheeled flexible robot. The OCPA learning system consists of two stages： in the first stage, an operant action is selected stochastically from a set of operant actions and then used as the input of the control system; in the second stage, the learning system gathers the orientation information of the system and uses it for optimization until achieves control target. At the same time, the size of the operant action set can be automatically reduced during the learning process for avoiding little probability event. Theory analysis is made for the designed OCPA learning system in the paper, which theoretically proves the convergence of operant conditioning learning mechanism in OCPA learning system, namely the operant action entropy will converge to minimum with the learning process. And then OCPA learning system is applied to posture balanced control of two-wheeled flexible self-balanced robots. Robot does not have posutre balanced skill in initial state and the selecting probability of each operant in operant sets is equal. With the learning proceeding, the selected probabilities of optimal operant gradually tend to one and the operant action entropy gradually tends to minimum, and so robot gradually learned the posture balanced skill.展开更多
文摘Open-wheeled race car aerodynamics is unquestionably challenging insofar as it involves many physical phenomena,such as slender and blunt body aerodynamics,ground effect,vortex management and interaction between different sophisticated aero devices.In the current work,a 2017 F1 car aerodynamics has been investigated from a numerical point of view by using an open-source code.The vehicle project was developed by PERRINN(Copyright.2011—Present PERRINN),an engineering community founded by Nicolas Perrin in 2011.The racing car performance is quantitatively evaluated in terms of drag,downforce,efficiency and front balance.The goals of the present CFD(computational fluid dynamics)-based research are the following:analyzing the capabilities of the open-source software OpenFOAM in dealing with complex meshes and external aerodynamics calculation,and developing a reliable workflow from CAD(computer aided design)model to the post-processing of the results,in order to meet production demands.
基金supported by the National Natural Science Foundation of China (No. 60774077)the National High Technology Development Plan(863) of China (No. 2007AA04Z226)+1 种基金the Beijing Municipal Education Commission Key Project (No. KZ200810005002)the Beijing Natural Science Foundation Project (No. 4102011)
文摘This paper presents an OCPA （operant conditioning probabilistic automaton） bionic autonomous learning system based on Skinner＇s operant conditioning theory for solving the balance control problem of a two-wheeled flexible robot. The OCPA learning system consists of two stages： in the first stage, an operant action is selected stochastically from a set of operant actions and then used as the input of the control system; in the second stage, the learning system gathers the orientation information of the system and uses it for optimization until achieves control target. At the same time, the size of the operant action set can be automatically reduced during the learning process for avoiding little probability event. Theory analysis is made for the designed OCPA learning system in the paper, which theoretically proves the convergence of operant conditioning learning mechanism in OCPA learning system, namely the operant action entropy will converge to minimum with the learning process. And then OCPA learning system is applied to posture balanced control of two-wheeled flexible self-balanced robots. Robot does not have posutre balanced skill in initial state and the selecting probability of each operant in operant sets is equal. With the learning proceeding, the selected probabilities of optimal operant gradually tend to one and the operant action entropy gradually tends to minimum, and so robot gradually learned the posture balanced skill.
