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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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Getting a Grip on Grid Generation

GridPro is an automatic, object-oriented, multi-block grid generator that provides ease of use, high quality, rapid production, and parametric design. When paired with a 3-D graphic user interface called az- Manager, GridPro presents users with an extremely efficient, interactive capability to build topology, edit surfaces, set computational fluid dynamics (CFD) boundary conditions, and view multi-block grids. The origins of the GridPro technology date back to a 1989 SBIR contract with NASA's Glenn Research Center, in which Glenn was seeking a multi-block grid generation program that would run automatically upon identifying a pattern of grid blocks supplied by a user. The technology is currently used in many engineering fields, including aerospace, turbo- machinery, automotive, and chemical industries.

Source record↗

TIGER: A user-friendly interactive grid generation system for complicated turbomachinery and axis-symmetric configurations

The issue of time efficiency in grid generation is addressed by developing a user friendly graphical interface for interactive/automatic construction of structured grids around complex turbomachinery/axis-symmetric configurations. The accuracy of geometry modeling and its fidelity is accomplished by adapting the nonuniform rational b-spline (NURBS) representation. A customized interactive grid generation code, TIGER, has been developed to facilitate the grid generation process for complicated internal, external, and internal-external turbomachinery fields simulations. The FORMS Library is utilized to build user-friendly graphical interface. The algorithm allows a user to redistribute grid points interactively on curves/surfaces using NURBS formulation with accurate geometric definition. TIGER's features include multiblock, multiduct/shroud, multiblade row, uneven blade count, and patched/overlapping block interfaces. It has been applied to generate grids for various complicated turbomachinery geometries, as well as rocket and missile configurations.

Shih, Ming H.↗

Fluid-Structure Interaction Simulations of the ASPIRE SR01 Supersonic Parachute

High-fidelity computational fluid dynamics (CFD) simulations have so far only played exploratory and supporting roles in the study and qualification of parachutes for planetary entry. The last few years have seen the maturation of coupled computational methods that are capable of modeling the complex fluid-structure interactions between a parachute canopy and the supersonic flow in the wake of an entry vehicle in flight conditions. One of the primary goals of these methods is to predict the peak opening load experienced by the parachute during inflation. The Launch, Ascent, and Vehicle Aerodynamics (LAVA)team is developing efficient, high-fidelity numerical methods to perform such challenging fluid-structure interaction simulations. A loose coupling approach is used to advance the solutions of a Cartesian ghost cell immersed boundary method CFD solver and a finite element computational structural dynamics (CSD) solver in space and time. The coupled solver is employed to simulate the ASPIRE SR01 flight test, where a build-to-print version of the Mars Science Laboratory parachute was inflated in supersonic conditions in the upper terrestrial atmosphere. The simulations conducted in the current paper predict a peak opening load that is within 10% of that from the flight test. Grid convergence with respect to the volume and structural domains is demonstrated, and less than 1% variation in the peak opening load is predicted between all grid resolutions.

ARMD↗

Numerical Simulations of A Conceptual MSR-EES Shoulder Recession

The present study demonstrates our in-house material response solver, Icarus's capability to simulate the ablative conditions, including pyrolysis effects due to the interaction between hypersonic boundary layers and the thermal protection system (TPS). A conceptual aeroshell shoulder design, which undergoes mission-relevant flow and material conditions, is selected for the demonstration purpose. LAURA, a structured flow solver, is used to solve flow around the shoulder at several trajectory points of a flight path. The aerothermal dataset obtained from LAURA is used to enforce boundary conditions on the aeroshell wall to simulate ablation processes. The two-layered material system is stacked with HEEET (TPS) and Aluminum (actual material). A set of base parameters, such as the angle of material orientation with respect to the flow direction, convective heat-transfer co-efficient, and aerothermal boundary conditions on the rear end of the HEEET material layer, is selected to conduct a base-case simulation. A small amount of recession was observed, indicating that the design should be fine to go through the selected flow and material conditions. Furthermore, the parameters mentioned above are individually altered and are observed to affect the shoulder design's recession compared to the base case. Verification of our Icarus setup was also carried out using a one-dimensional grid and FIAT, a one-dimensional material-response solver, to build credibility for our results. As the current work is an uncoupled fluid-material-response simulation, a local sharp mesh deformation in the recessed surface near the shoulder corner is observed.

Prakash Shrestha↗

CAPRI: Using a Geometric Foundation for Computational Analysis and Design

CAPRI (Computational Analysis Programming Interface) is a software development tool intended to make computerized design, simulation and analysis faster and more efficient. The computational steps traditionally taken for most engineering analysis (Computational Fluid Dynamics (CFD), structural analysis, etc.) are: Surface Generation, usually by employing a Computer Aided Design (CAD) system; Grid Generation, preparing the volume for the simulation; Flow Solver, producing the results at the specified operational point; Post-processing Visualization, interactively attempting to understand the results. It should be noted that the structures problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go IGES files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D) data formats and the upcoming CGNS). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Instead of the serial approach to analysis, CAPRI takes a geometry centric approach. CAPRI is a software building tool-kit that refers to two ideas: (1) A simplified, object-oriented, hierarchical view of a solid part integrating both geometry and topology definitions, and (2) programming access to this part or assembly and any attached data. The connection to the geometry is made through an Application Programming Interface (API) and not a file system.

Haimes, Robert↗

Modeling and Analysis of Stirling Power Convertors

Modeling and Analysis of Stirling Power Convertors Luis A. Rodriguez1 Steven M. Geng, Terry V. Reid, Scott D. Wilson NASA Glenn Research Center, Cleveland, OH, 44135, USA NASA Glenn’s Thermal Energy Conversion Branch is supporting the development of the next generation free-piston Stirling power convertors. American Superconductor (AMSC) and Sunpower Inc. are the two firms under contract to develop the Flexure Isotope Stirling Convertor (FISC) and the Sunpower Robust Stirling Convertor (SRSC), respectively. To comprehend and forecast convertor performance, Sage, ANSYS® Maxwell, and ANSYS® Fluent were used to model the Stirling thermodynamic cycle, alternator electromagnetics, and piston and displacer dynamics. I. Introduction Stirling convertors are being developed by NASA as a potential steady source of electrical power for NASA’s future scientific space missions. Currently, NASA Glenn Research Center has two corporations under contract, American Superconductor (AMSC) and Sunpower Inc., for the development of the next generation of free-piston Stirling convertors for dynamic radioisotope power systems. AMSC is developing the Flexure Isotope Stirling Convertor (FISC), which uses flexures to prevent side motion and rubbing of the piston. Similarly, Sunpower Inc, is developing the Sunpower Robust Stirling Convertor (SRSC). The SRSC uses gas bearings to prevent radial contact of the moving piston. As convertor development continues, it is increasingly important to understand and predict the interactions of components in the system, how they respond to one another, and how they perform as a response to changes in operating conditions. A suitable and enlightening way to demonstrate and foresee these interactions is with the use of accurate modeling software. Sage, ANSYS® Maxwell, and ANSYS® Fluent are the current modeling tools used by NASA to analytically determine convertor performance. Sage is a one-dimensional object-oriented commercial software package used for modeling and optimizing Stirling convertors for Dynamic Radioisotope Power Systems (DRPS) and it is one of the most accurate Stirling convertor codes in use by NASA. This code is the successor to GLIMPS (Globally-Implicit Stirling Cycle Simulation) and GLOP (GLIMPS Optimization) software created by Gedeon Associates [1]. Model input parameters are typically material/gas type, component physical dimensions, temperatures, frequency, charge pressure, and number of time/space nodes. Sage is used to model both the FISC’s and SRSC’s Stirling cycle thermodynamics and piston/displacer dynamics. Performance maps were created and analyzed for both power systems to better understand the relationship between the following conditions: cold-end temperature, hot-end temperature, piston/displacer amplitudes, pressure drop, and thermal input power. The synergy between these conditions will help determine parameter sensitivity. ANSYS® Maxwell was used to create a three-dimensional (3-D) axisymmetric model for both FISC and SRSC alternators. The significant physical components included in each model are the magnets, magnet carrier, outer/inner laminations, and the coil. Inputs to the model are piston amplitude, piston frequency, alternator load, coil resistance, tuning capacitance, and specific material properties. The alternator models calculate terminal voltage, current, piston/current phase, voltage/current phase, coil inductance, terminal power and efficiency. The RI2 losses, core (hysteresis and eddy) losses, and magnet/can eddy losses are also a part of the final results. ANSYS® Fluent is used to build 3-D computational fluid dynamic (CFD) models to examine the Stirling cycle thermodynamics for both the FISC and SRSC systems. Three-dimensional Computer Aided Design (CAD) models were used to create the physical components of each convertor. Steady-state simulations were conducted for hardware testing, prediction of environmental losses during testing, and generation of radiation look-up tables. The model inputs to the aforementioned analysis are the material properties and boundary thermal conditions. The steady-state model calculates temperature and heat flow distributions. Transient 3-D calculations were also part of the CFD analysis. In this study a physically reduced version of the FISC is used to obtain a prediction of available engine power. For the gas bearing SRSC, the transient effort is used to obtain a prediction of bearing pad performance and its sensitivity to micro-channel geometric variation. The model inputs to the transient simulations are the piston amplitude, displacer amplitude, frequency, displacer/piston phase angle, dynamic deforming CFD grid, temperature boundary conditions, and user defined files describing motion profile of piston/displacer. The results of the model are temperature distributions, heat distributions, and PV power produced at pre-determined conditions.

Luis A Rodriguez↗