1,678 research outputs found
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
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
Time-derivative preconditioning for viscous flows
A time-derivative preconditioning algorithm that is effective over a wide range of flow conditions from inviscid to very diffusive flows and from low speed to supersonic flows was developed. This algorithm uses a viscous set of primary dependent variables to introduce well-conditioned eigenvalues and to avoid having a nonphysical time reversal for viscous flow. The resulting algorithm also provides a mechanism for controlling the inviscid and viscous time step parameters to be of order one for very diffusive flows, thereby ensuring rapid convergence at very viscous flows as well as for inviscid flows. Convergence capabilities are demonstrated through computation of a wide variety of problems
CFD Applications in Propulsion
An overview of various applications of Computational Fluid Dynamics (CFD) algorithms to propulsion problems is given. Topics of interest include incompressible, low speed compressible, transonic, and supersonic problems. A common family of algorithms is used for all applications and emphasis is placed on maintaining accuracy and convergence efficiency for all problems. Specific problems include pump hydrodynamics, simultaneous combustion and mixing in rocket engines, viscous nozzle flow, and CFD applications to combustion stability
Inferring Chemical Reaction Patterns Using Rule Composition in Graph Grammars
Modeling molecules as undirected graphs and chemical reactions as graph
rewriting operations is a natural and convenient approach tom odeling
chemistry. Graph grammar rules are most naturally employed to model elementary
reactions like merging, splitting, and isomerisation of molecules. It is often
convenient, in particular in the analysis of larger systems, to summarize
several subsequent reactions into a single composite chemical reaction. We use
a generic approach for composing graph grammar rules to define a chemically
useful rule compositions. We iteratively apply these rule compositions to
elementary transformations in order to automatically infer complex
transformation patterns. This is useful for instance to understand the net
effect of complex catalytic cycles such as the Formose reaction. The
automatically inferred graph grammar rule is a generic representative that also
covers the overall reaction pattern of the Formose cycle, namely two carbonyl
groups that can react with a bound glycolaldehyde to a second glycolaldehyde.
Rule composition also can be used to study polymerization reactions as well as
more complicated iterative reaction schemes. Terpenes and the polyketides, for
instance, form two naturally occurring classes of compounds of utmost
pharmaceutical interest that can be understood as "generalized polymers"
consisting of five-carbon (isoprene) and two-carbon units, respectively
Generic Strategies for Chemical Space Exploration
Computational approaches to exploring "chemical universes", i.e., very large
sets, potentially infinite sets of compounds that can be constructed by a
prescribed collection of reaction mechanisms, in practice suffer from a
combinatorial explosion. It quickly becomes impossible to test, for all pairs
of compounds in a rapidly growing network, whether they can react with each
other. More sophisticated and efficient strategies are therefore required to
construct very large chemical reaction networks.
Undirected labeled graphs and graph rewriting are natural models of chemical
compounds and chemical reactions. Borrowing the idea of partial evaluation from
functional programming, we introduce partial applications of rewrite rules.
Binding substrate to rules increases the number of rules but drastically prunes
the substrate sets to which it might match, resulting in dramatically reduced
resource requirements. At the same time, exploration strategies can be guided,
e.g. based on restrictions on the product molecules to avoid the explicit
enumeration of very unlikely compounds. To this end we introduce here a generic
framework for the specification of exploration strategies in graph-rewriting
systems. Using key examples of complex chemical networks from sugar chemistry
and the realm of metabolic networks we demonstrate the feasibility of a
high-level strategy framework.
The ideas presented here can not only be used for a strategy-based chemical
space exploration that has close correspondence of experimental results, but
are much more general. In particular, the framework can be used to emulate
higher-level transformation models such as illustrated in a small puzzle game
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