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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, fluid mechanics including fluid dynamics, acoustics, and combustion, aerodynamics, and computer science during the period 1 Apr. 1992 - 30 Sep. 1992 is summarized.
In this review we briefly summarize some current models of evaporation and the atmospheric boundary layer (ABL) and discuss new experimental and computational oppurtunities that may aid our understanding of evaporation at these larger scales. In particular, consideration is given to remote sensing of the atmosphere, computational fluid dynamics and the role numerical models can play in understanding land-atmosphere interactions. These powerful modeling and measurement tools are allowing us to visualize and study spatial and temporal scales previously untouched, thereby increasing the oppurtunities to improve our understanding of land-atmosphere interaction.
One of the major achievements in engineering science has been the development of computer algorithms for solving nonlinear differential equations such as the Navier-Stokes equations. These algorithms are now used in the practical engineering design of devices such as cars and airplanes as well as theoretical studies of complex phenomena such as fluid turbulence. In past years, limited computer resources have motivated the development of efficient numerical methods in computational fluid dynamics (CFD) utilizing structured meshes. These meshes are comprised of systematic arrays of quadrilateral or hexahedral cells. The use of structured meshes greatly simplifies the implementation of CFD algorithms on conventional computers. Structured meshes also permit the use of highly efficient solution techniques such as alternating direction implicit (ADI) iteration schemes or multigrid. Following the dramatic improvement in computing speed in recent years, emphasis has shifted towards the design of algorithms capable of treating complex geometries. The automatic generation of structured grids about complex geometries is problematic. Unstructured grids offer one promising alternative technique for treating these general geometries. Unstructured meshes have irregular connectivity and usually contain triangles and/or quadrilaterals in two dimensions and tetrahedra and/or hexahedra in three dimensions. The generation and use of unstructured grids poses new challenges in computational fluid dynamics. This is true for both grid generation as well as for the design of algorithms for flow solution. The purpose of these notes is to present recent developments in the unstructured grid generation and flow solution technology.
At low latitudes in the Earth's atmosphere, the observed zonal flow velocities are dominated by the semi-annual and quasi-biennial oscillations with periods of 6 months and 20 to 32 months respectively. These terrestrial oscillations, the SAO and QBO respectively, are driven by wave-mean flow interactions due to upward propagating planetary-scale waves (periods of days) and small-scale gravity waves (periods of hours). We are proposing (see also Mayr et al., GRL, 2001) that such a mechanism may drive long period oscillations (reversing flows) in stellar and planetary interiors, and we apply it to the Sun. The reversing flows would occur below the convective envelope where waves can propagate. We apply a simplified, one dimensional, analytical flow model that incorporates a gravity wave parameterization due to Hines (1997). Based on this analysis, our estimates show that relatively small wave amplitudes less than 10 m/s can produce zonal flow amplitudes of 20 m/s, which should be sufficient to generate the observed variations in the magnetic field. To produce the 22-year period of oscillation, a low buoyancy frequency must be chosen, and this places the proposed flow in a region that is close to (and below) the base of the convective envelope. Enhanced turbulence associated with this low stability should help to generate the dynamo currents. With larger stability at deeper levels in the solar interior, the model can readily produce also oscillations with much longer periods. To provide an understanding of the fluid dynamics involved, we present numerical results from a 2D model for the terrestrial atmosphere that exemplify the non-linear nature of the wave interaction for which a mechanical analog is the escapement mechanism of the clock.
Parallel Plate Plastometer (PPP) is a device commonly used for measuring the viscosity of high polymers at low rates of shear in the range 10 4 to 10 9 poises. This device is being validated for use in measuring the viscosity of liquid glasses at high temperatures having similar ranges for the viscosity values. PPP instrument consists of two similar parallel plates, both in the range of 1 inch in diameter with the upper plate being movable while the lower one is kept stationary. Load is applied to the upper plate by means of a beam connected to shaft attached to the upper plate. The viscosity of the fluid is deduced from measuring the variation of the plate separation, h, as a function of time when a specified fixed load is applied on the beam. Operating plate speeds measured with the PPP is usually in the range of 10 -3 cm/s or lower. The flow field within the PPP can be simulated using the equations of motion of fluid flow for this configuration. With flow speeds in the range quoted above the flow field between the two plates is certainly incompressible and laminar. Such flows can be easily simulated using numerical modeling with computational fluid dynamics (CFD) codes. We present below the mathematical model used to simulate this flow field and also the solutions obtained for the flow using a commercially available finite element CFD code.
DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.
The National Aeronautics and Space Administration (NASA) is sending a large (>850 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars in 2011. The rover's primary power source is a Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) that generates roughly 2000 W of heat, which is converted to approximately 110 W of electrical power for use by the rover electronics, science instruments, and mechanism-actuators. The large rover size and extreme thermal environments (cold and hot) for which the rover is designed for led to a sophisticated thermal control system to keep it within allowable temperature limits. The pre-existing Martian atmosphere of low thermal conductivity CO2 gas (8 Torr) is used to thermally protect the rover and its components from the extremely cold Martian environment (temperatures as low as -130 deg C). Conventional vacuum based insulation like Multi Layer Insulation (MLI) is not effective in a gaseous atmosphere, so engineered gaps between the warm rover internal components and the cold rover external structure were employed to implement this thermal isolation. Large gaps would lead to more thermal isolation, but would also require more of the precious volume available within the rover. Therefore, a balance of the degree of thermal isolation achieved vs. the volume of rover utilized is required to reach an acceptable design. The temperature differences between the controlled components and the rover structure vary from location to location so each gap has to be evaluated on a case-by-case basis to arrive at an optimal thickness. For every configuration and temperature difference, there is a critical thickness below which the heat transfer mechanism is dominated by simple gaseous thermal conduction. For larger gaps, the mechanism is dominated by natural convection. In general, convection leads to a poorer level of thermal isolation as compared to conduction. All these considerations play important roles in the optimization process. A three-step process was utilized to design this insulation. The first step is to come up with a simple, textbook based, closed-form equation assessment of gap thickness vs. resultant thermal isolation achieved. The second step is a more sophisticated numerical assessment using Computational Fluid Dynamics (CFD) software to investigate the effect of complicated geometries and temperature contours along them to arrive at the effective thermal isolation in a CO2 atmosphere. The third step is to test samples of representative geometries in a CO2 filled chamber to measure the thermal isolation achieved. The results of these assessments along with the consistency checks across these methods leads to the formulation of design-guidelines for gap implementation within the rover geometry. Finally, based on the geometric and functional constraints within the real rover system, a detailed design that accommodates all these factors is arrived at. This paper will describe in detail this entire process, the results of these assessments and the final design that was implemented.
A numerical, and experimental investigation to study the effects of flow distortion on a Mass Flow Plug (MFP) used to control and measure mass-flow during an inlet test has been conducted. The MFP was first calibrated using the WIND-US flow solver for uniform (undistorted) inflow conditions. These results are shown to compare favorably with an experimental calibration under similar conditions. The effects of distortion were investigated by imposing distorted flow conditions taken from an actual inlet test to the inflow plane of the numerical simulation. The computational fluid dynamic (CFD) based distortion study only showed the general trend in mass flow rate. The study used only total pressure as the upstream boundary condition, which was not enough to define the flow. A better simulation requires knowledge of the turbulence structure and a specific distortion pattern over a range of plug positions. It is recommended that future distortion studies utilize a rake with at least the same amount of pitot tubes as the AIP rake.
The space-time Conservation Element and Solution Element (CESE) method for solving conservation laws is examined for its development motivation and design requirements. The characteristics of the resulting scheme are discussed. The discretization of the Euler equations is presented to show readers how to construct a scheme based on the CESE method. The differences and similarities between the CESE method and other traditional methods are discussed. The strengths and weaknesses of the method are also addressed.
The block Jacobi symmetric successive overrelaxation (SSOR) algorithm has been reformulated as a parallelized algorithm for the OVERFLOWstructured, overset grid, computational fluid dynamics flow solver. Simple changes to the flow solver required to implement the algorithm are discussed. A series of test cases are presented that demonstrate how the addition of implicit overset boundaries has improved the robustness and nonlinear convergence characteristics of the flow solver.
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This paper describes and discusses the textbook, Fundamentals of Computational Fluid Dynamics by Lomax, Pulliam, and Zingg, which is intended for a graduate level first course in computational fluid dynamics. This textbook emphasizes fundamental concepts in developing, analyzing, and understanding numerical methods for the partial differential equations governing the physics of fluid flow. Its underlying philosophy is that the theory of linear algebra and the attendant eigenanalysis of linear systems provides a mathematical framework to describe and unify most numerical methods in common use in the field of fluid dynamics. Two linear model equations, the linear convection and diffusion equations, are used to illustrate concepts throughout. Emphasis is on the semi-discrete approach, in which the governing partial differential equations (PDE's) are reduced to systems of ordinary differential equations (ODE's) through a discretization of the spatial derivatives. The ordinary differential equations are then reduced to ordinary difference equations (O(Delta)E's) using a time-marching method. This methodology, using the progression from PDE through ODE's to O(Delta)E's, together with the use of the eigensystems of tridiagonal matrices and the theory of O(Delta)E's, gives the book its distinctiveness and provides a sound basis for a deep understanding of fundamental concepts in computational fluid dynamics.
Spurious behavior in underresolved grids and/or semi-implicit temporal discretizations for four computational fluid dynamics (CFD) simulations are studied. The numerical simulations consist of (a) a 1-D chemically relaxed nonequilibrium model, (b) the direct numerical simulation (DNS) of 2-D incompressible flow over a backward facing step, (c) a loosely-coupled approach for a 2-D fluid-structure interaction, and (d) a 3-D compressible unsteady flow simulation of vortex breakdown in delta wings. Using knowledge from dynamical systems theory, various types of spurious behaviors that are numerical artifacts were systematically identified. These studies revealed the various possible dangers of misinterpreting numerical simulation of realistic complex flows that are constrained by the available computing power. In large scale computations underresolved grids, semi-implicit procedures, loosely-coupled implicit procedures, and insufficiently long time integration in DNS are most often unavoidable. Consequently, care must be taken in both computation and in interpretation of the numerical data. The results presented confirm the important role that dynamical systems theory can play in the understanding of the nonlinear behavior of numerical algorithms and in aiding the identification of the sources of numerical uncertainties in CFD.
A comprehensive analytical, numerical and experimental study of convective flow in multilayer immiscible liquids has been performed. Studies include transparent high Prandtl number of liquid as well as opaque low Prandtl metallic melts. A new radioscopic flow visualization has been developed for the latter studies.
The purpose here is to assess the state of the art in the areas of numerical analysis that are particularly relevant to computational fluid dynamics (CFD), to identify promising new developments in various areas of numerical analysis that will impact CFD, and to establish a long-term perspective focusing on opportunities and needs. Overviews are given of discretization schemes, computational fluid dynamics, algorithmic trends in CFD for aerospace flow field calculations, simulation of compressible viscous flow, and massively parallel computation. Also discussed are accerelation methods, spectral and high-order methods, multi-resolution and subcell resolution schemes, and inherently multidimensional schemes.
Subscale test motors are often used for the evaluation of solid rocket motor component materials such as internal insulation. These motors are useful for characterizing insulation performance behavior, screening insulation material candidates and obtaining material thermal and ablative property design data. One of the primary challenges associated with using subscale motors however, is the uncertainty involved when extrapolating the results to full-scale motor conditions. These uncertainties are related to differences in such phenomena as turbulent flow behavior and boundary layer development, propellant particle interactions with the wall, insulation off-gas mixing and thermochemical reactions with the bulk flow, radiation levels, material response to the local environment, and other anomalous flow conditions. In addition to the need for better understanding of physical mechanisms, there is also a need to better understand how to best simulate these phenomena using numerical modeling approaches such as computational fluid dynamics (CFD). To better understand and model interactions between major phenomena in a subscale test motor, a numerical study of the internal flow environment of a representative motor was performed. Simulation of the environment included not only gas dynamics, but two-phase flow modeling of entrained alumina particles like those found in an aluminized propellant, and offgassing from wall surfaces similar to an ablating insulation material. This work represents a starting point for establishing the internal environment of a subscale test motor using comprehensive modeling techniques, and lays the groundwork for improving the understanding of the applicability of subscale test data to full-scale motors. It was found that grid resolution, and inclusion of phenomena in addition to gas dynamics, such as two-phase and multi-component gas composition are all important factors that can effect the overall flow field predictions.
The objective of this effort is to develop an efficient and accurate computational methodology to predict both detailed thermo-fluid environments and global characteristics of the internal ballistics for a hypothetical solid-core nuclear thermal thrust chamber assembly (NTTCA). Several numerical and multi-physics thermo-fluid models, such as real fluid, chemically reacting, turbulence, conjugate heat transfer, porosity, and power generation, were incorporated into an unstructured-grid, pressure-based computational fluid dynamics solver as the underlying computational methodology. The numerical simulations of detailed thermo-fluid environment of a single flow element provide a mechanism to estimate the thermal stress and possible occurrence of the mid-section corrosion of the solid core. In addition, the numerical results of the detailed simulation were employed to fine tune the porosity model mimic the pressure drop and thermal load of the coolant flow through a single flow element. The use of the tuned porosity model enables an efficient simulation of the entire NTTCA system, and evaluating its performance during the design cycle.
Many numerical methods used in computational fluid dynamics (CFD) incorporate an artificial dissipation term to suppress spurious oscillations and control nonlinear instabilities. The same effect can be accomplished by using upwind techniques, sometimes augmented with limiters to form Total Variation Diminishing (TVD) schemes. An analysis based on numerical satisfaction of the second law of thermodynamics allows many such methods to be compared and improved upon. A nonlinear stability proof is given for discrete scalar equations arising from a conservation law. Solutions to such equations are bounded in the L sub 2 norm if the second law of thermodynamics is satisfied in a global sense over a periodic domain. It is conjectured that an analogous statement is true for discrete equations arising from systems of conservation laws. Analysis and numerical experiments suggest that a more restrictive condition, a positive entropy production rate in each cell, is sufficient to exclude unphysical phenomena such as oscillations and expansion shocks. Construction of schemes which satisfy this condition is demonstrated for linear and nonlinear wave equations and for the one-dimensional Euler equations.