Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.

Implementation of the conjugate heat transfer code in KIVA-4

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.

Automatic Labeling of Software Components and their Evolution using Log-Likelihood Ratio of Word Frequencies in Source Code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.