3 resultados para Open-source code
em Digital Commons - Michigan Tech
Resumo:
KIVA is an open Computational Fluid Dynamics (CFD) source code that is capable to compute the transient two and three-dimensional chemically reactive fluid flows with spray. The latest version in the family of KIVA codes is the KIVA-4 which is capable of handling the unstructured mesh. This project focuses on the implementation of the Conjugate Heat Transfer code (CHT) in KIVA-4. The previous version of KIVA code with conjugate heat transfer code has been developed at Michigan Technological University by Egel Urip and is be used in this project. During the first phase of the project, the difference in the code structure between the previous version of KIVA and the KIVA-4 has been studied, which is the most challenging part of the project. The second phase involves the reverse engineering where the CHT code in previous version is extracted and implemented in KIVA-4 according to the new code structure. The validation of the implemented code is performed using a 4-valve Pentroof engine case. A solid cylinder wall has been developed using GRIDGEN which surrounds 3/4th of the engine cylinder and heat transfer to the solid wall during one engine cycle (0-720 Crank Angle Degree) is compared with that of the reference result. The reference results are nothing but the same engine case run in the previous version with the original code developed by Egel. The results of current code are very much comparable to that of the reference results which verifies that successful implementation of the CHT code in KIVA-4.
Resumo:
The main purpose of this project is to understand the process of engine simulation using the open source CFD code called KIVA. This report mainly discusses the simulation of the 4-valve Pentroof engine through KIVA 3VR2. KIVA is an open source FORTRAN code which is used to solve the fluid flow field in the engines with the transient 2D and 3D chemically reactive flow with spray. It also focuses on the complete procedure to simulate an engine cycle starting from pre- processing until the final results. This report will serve a handbook for the using the KIVA code.
Resumo:
In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.