CFD applications in chemical propulsion engines

The present research is aimed at developing analytical procedures for predicting the performance and stability characteristics of chemical propulsion engines. Specific emphasis is being placed on understanding the physical and chemical processes in the small engines that are used for applications such as spacecraft attitude control and drag make-up. The small thrust sizes of these engines lead to low nozzle Reynolds numbers with thick boundary layers which may even meet at the nozzle centerline. For this reason, the classical high Reynolds number procedures that are commonly used in the industry are inaccurate and of questionable utility for design. A complete analysis capability for the combined viscous and inviscid regions as well as for the subsonic, transonic, and supersonic portions of the flowfield is necessary to estimate performance levels and to enable tradeoff studies during design procedures

Derivative Computations and Robust Standard Errors for Linear Mixed Effects Models in lme4

While robust standard errors and related facilities are available in R for many types of statistical models, the facilities are notably lacking for models estimated via lme4. This is because the necessary statistical output, including the Hessian and casewise gradient of random effect parameters, is not immediately available from lme4 and is not trivial to obtain. In this article, we supply and describe two new functions to obtain this output from Gaussian mixed models: estfun.lmerMod() and vcov.full.lmerMod(). We discuss the theoretical results implemented in the code, focusing on calculation of robust standard errors via package sandwich. We also use the Sleepstudy data to illustrate the code and compare it to a benchmark from package lavaan.Comment: Accepted at Journal of Statistical Softwar

An overview of the Penn State Propulsion Engineering Research Center

An overview of the Penn State Propulsion Engineering Research Center is presented. The following subject areas are covered: research objectives and long term perspective of the Center; current status and operational philosophy; and brief description of Center projects (combustion, fluid mechanics and heat transfer, materials compatibility, turbomachinery, and advanced propulsion concepts)

A Generic Framework for Engineering Graph Canonization Algorithms

The state-of-the-art tools for practical graph canonization are all based on the individualization-refinement paradigm, and their difference is primarily in the choice of heuristics they include and in the actual tool implementation. It is thus not possible to make a direct comparison of how individual algorithmic ideas affect the performance on different graph classes. We present an algorithmic software framework that facilitates implementation of heuristics as independent extensions to a common core algorithm. It therefore becomes easy to perform a detailed comparison of the performance and behaviour of different algorithmic ideas. Implementations are provided of a range of algorithms for tree traversal, target cell selection, and node invariant, including choices from the literature and new variations. The framework readily supports extraction and visualization of detailed data from separate algorithm executions for subsequent analysis and development of new heuristics. Using collections of different graph classes we investigate the effect of varying the selections of heuristics, often revealing exactly which individual algorithmic choice is responsible for particularly good or bad performance. On several benchmark collections, including a newly proposed class of difficult instances, we additionally find that our implementation performs better than the current state-of-the-art tools