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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Application of Single Crystal Failure Criteria: Theory and Turbine Blade Case Study

The orientation of the single crystal material within a structural component is known to affect the strength and life of the part. The first stage blade of the High Pressure Fuel Turbopump (HPFTP)/ Alternative Turbopump Development (ATD), of the Space Shuttle Main Engine (SSME) was used to study the effects of secondary axis'orientation angles on the failure rate of the blade. A new failure criterion was developed based on normal and shear strains on the primary crystallographic planes. The criterion was verified using low cycle fatigue (LCF) specimen data and a finite element model of the test specimens. The criterion was then used to study ATD/HPFTP first stage blade failure events. A detailed ANSYS finite element model of the blade was used to calculate the failure parameter for the different crystallographic orientations. A total of 297 cases were run to cover a wide range of acceptable orientations within the blade. Those orientations are related to the base crystallographic coordinate system that was created in the ANSYS finite element model. Contour plots of the criterion as a function of orientation for the blade tip and attachment were obtained. Results of the analysis revealed a 40% increase in the failure parameter due to changing of the primary and secondary axes of material orientations. A comparison between failure criterion predictions and actual engine test data was then conducted. The engine test data comes from two ATD/HPFTP builds (units F3- 4B and F6-5D), which were ground tested on the SSME at the Stennis Space Center in Mississippi. Both units experienced cracking of the airfoil tips in multiple blades, but only a few cracks grew all the way across the wall of the hollow core airfoil.

Sayyah, Tarek↗
NASA NTRS2001

Adaptive Multi-Layer LMS Controller Design and Application to Active Vibration Suppression on a Truss and Proposed Impact Analysis Technique

This research develops an adaptive controller that actively suppresses a single frequency disturbance source at a remote position and tests the system on the NPS Space Truss. The experimental results are then compared to those predicted by an ANSYS finite element model. The NPS space truss is a 3.7-meter long truss that simulates a space-borne appendage with sensitive equipment mounted at its extremities. One of two installed piezoelectric actuators and an Adaptive Multi-Layer LMS control law were used to effectively eliminate an axial component of the vibrations induced by a linear proof mass actuator mounted at one end of the truss. Experimental and analytical results both demonstrate reductions to the level of system noise. Vibration reductions in excess of 50dB were obtained through experimentation and over 100dB using ANSYS, demonstrating the ability to model this system with a finite element model. This report also proposes a method to use distributed quartz accelerometers to evaluate the location, direction, and energy of impacts on the NPS space truss using the dSPACE data acquisition and processing system to capture the structural response and compare it to known reference Signals.

Barney, Timothy A.↗
NASA NTRS2003

Development of Probabilistic Life Prediction Methodologies and Testing Strategies for MEMS and CMC's

This effort is to investigate probabilistic life prediction methodologies for ceramic matrix composites and MicroElectroMechanical Systems (MEMS) and to analyze designs that determine stochastic properties of MEMS. For CMC's this includes a brief literature survey regarding lifing methodologies. Also of interest for MEMS is the design of a proper test for the Weibull size effect in thin film (bulge test) specimens. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. A main objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures/Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads. A second set of objectives is to determine the applicability/suitability of the CARES/Life methodology for CMC analysis, what changes would be needed to the methodology and software, and if feasible, run a demonstration problem. Also important is an evaluation of CARES/Life coupled to the ANSYS Probabilistic Design System (PDS) and the potential of coupling transient reliability analysis to the ANSYS PDS.

Jadaan, Osama↗
NASA NTRS2010

CFD Fuel Slosh Modeling of Fluid-Structure Interaction in Spacecraft Propellant Tanks with Diaphragms

Liquid sloshing within spacecraft propellant tanks causes rapid energy dissipation at resonant modes, which can result in attitude destabilization of the vehicle. Identifying resonant slosh modes currently requires experimental testing and mechanical pendulum analogs to characterize the slosh dynamics. Computational Fluid Dynamics (CFD) techniques have recently been validated as an effective tool for simulating fuel slosh within free-surface propellant tanks. Propellant tanks often incorporate an internal flexible diaphragm to separate ullage and propellant which increases modeling complexity. A coupled fluid-structure CFD model is required to capture the damping effects of a flexible diaphragm on the propellant. ANSYS multidisciplinary engineering software employs a coupled solver for analyzing two-way Fluid Structure Interaction (FSI) cases such as the diaphragm propellant tank system. Slosh models generated by ANSYS software are validated by experimental lateral slosh test results. Accurate data correlation would produce an innovative technique for modeling fuel slosh within diaphragm tanks and provide an accurate and efficient tool for identifying resonant modes and the slosh dynamic response.

Sances, Dillon J.↗
NASA NTRS2006

Probabilistic Prediction of Lifetimes of Ceramic Parts

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Nemeth, Noel N.↗
NASA NTRS2012

CFD Simulations for the Effect of Unsteady Wakes on the Boundary Layer of a Highly Loaded Low-Pressure Turbine Airfoil (L1A)

This report is the third part of a three-part final report of research performed under an NRA cooperative Agreement contract. The first part was published as NASA/CR-2012-217415. The second part was published as NASA/CR-2012-217416. The study of the very high lift low-pressure turbine airfoil L1A in the presence of unsteady wakes was performed computationally and compared against experimental results. The experiments were conducted in a low speed wind tunnel under high (4.9%) and then low (0.6%) freestream turbulence intensity for Reynolds number equal to 25,000 and 50,000. The experimental and computational data have shown that in cases without wakes, the boundary layer separated without reattachment. The CFD was done with LES and URANS utilizing the finite-volume code ANSYS Fluent (ANSYS, Inc.) under the same freestream turbulence and Reynolds number conditions as the experiment but only at a rod to blade spacing of 1. With wakes, separation was largely suppressed, particularly if the wake passing frequency was sufficiently high. This was validated in the 3D CFD efforts by comparing the experimental results for the pressure coefficients and velocity profiles, which were reasonable for all cases examined. The 2D CFD efforts failed to capture the three dimensionality effects of the wake and thus were less consistent with the experimental data. The effect of the freestream turbulence intensity levels also showed a little more consistency with the experimental data at higher intensities when compared with the low intensity cases. Additional cases with higher wake passing frequencies which were not run experimentally were simulated. The results showed that an initial 25% increase from the experimental wake passing greatly reduced the size of the separation bubble, nearly completely suppressing it.

Vinci, Samuel, J.↗
NASA NTRS2013

Application Program Interface for the Orion Aerodynamics Database

The Application Programming Interface (API) for the Crew Exploration Vehicle (CEV) Aerodynamic Database has been developed to provide the developers of software an easily implemented, fully self-contained method of accessing the CEV Aerodynamic Database for use in their analysis and simulation tools. The API is programmed in C and provides a series of functions to interact with the database, such as initialization, selecting various options, and calculating the aerodynamic data. No special functions (file read/write, table lookup) are required on the host system other than those included with a standard ANSI C installation. It reads one or more files of aero data tables. Previous releases of aerodynamic databases for space vehicles have only included data tables and a document of the algorithm and equations to combine them for the total aerodynamic forces and moments. This process required each software tool to have a unique implementation of the database code. Errors or omissions in the documentation, or errors in the implementation, led to a lengthy and burdensome process of having to debug each instance of the code. Additionally, input file formats differ for each space vehicle simulation tool, requiring the aero database tables to be reformatted to meet the tool s input file structure requirements. Finally, the capabilities for built-in table lookup routines vary for each simulation tool. Implementation of a new database may require an update to and verification of the table lookup routines. This may be required if the number of dimensions of a data table exceeds the capability of the simulation tools built-in lookup routines. A single software solution was created to provide an aerodynamics software model that could be integrated into other simulation and analysis tools. The highly complex Orion aerodynamics model can then be quickly included in a wide variety of tools. The API code is written in ANSI C for ease of portability to a wide variety of systems. The input data files are in standard formatted ASCII, also for improved portability. The API contains its own implementation of multidimensional table reading and lookup routines. The same aerodynamics input file can be used without modification on all implementations. The turnaround time from aerodynamics model release to a working implementation is significantly reduced

Robinson, Philip E.↗
NASA NTRS2013

Next Generation Lightweight Mirror Modeling Software

The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models possible.

Arnold, William↗
NASA NTRS2013

Next-Generation Lightweight Mirror Modeling Software

The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models possible

Arnold, William R., Sr.↗
NASA NTRS2013

Next Generation Lightweight Mirror Modeling Software

The advances in manufacturing techniques for lightweight mirrors, such as EXELSIS deep core low temperature fusion, Corning's continued improvements in the Frit bonding process and the ability to cast large complex designs, combined with water-jet and conventional diamond machining of glasses and ceramics has created the need for more efficient means of generating finite element models of these structures. Traditional methods of assembling 400,000 + element models can take weeks of effort, severely limiting the range of possible optimization variables. This paper will introduce model generation software developed under NASA sponsorship for the design of both terrestrial and space based mirrors. The software deals with any current mirror manufacturing technique, single substrates, multiple arrays of substrates, as well as the ability to merge submodels into a single large model. The modeler generates both mirror and suspension system elements, suspensions can be created either for each individual petal or the whole mirror. A typical model generation of 250,000 nodes and 450,000 elements only takes 5-10 minutes, much of that time being variable input time. The program can create input decks for ANSYS, ABAQUS and NASTRAN. An archive/retrieval system permits creation of complete trade studies, varying cell size, depth, and petal size, suspension geometry with the ability to recall a particular set of parameters and make small or large changes with ease. The input decks created by the modeler are text files which can be modified by any editor, all the key shell thickness parameters are accessible and comments in deck identify which groups of elements are associated with these parameters. This again makes optimization easier. With ANSYS decks, the nodes representing support attachments are grouped into components; in ABAQUS these are SETS and in NASTRAN as GRIDPOINT SETS, this make integration of these models into large telescope or satellite models easier.

Arnold, William R., Sr.↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRSDate not supplied

Pragmatic Stress Prediction on Additively Manufactured Coupons

Prediction of residual stresses from process parameters for additively manufactured large metal parts is computationally expensive. NASA is currently developing meter-scale parts with direct energy deposition. Practically, the predictive computational methods need to efficiently scale-up to meter-scale parts. Coupled thermal-mechanical multi-physics simulations have been developed with the pragmatic method using ABAQUS, COMSOL Multiphysics, ALE3D software. The residual stresses are a result of the manufacturing process which creates thermal cycling of the build layers. The pragmatic method uses lumped thermal layers for stress predictions to reduce computational costs. The stress predictions as well as deformations of the different codes are compared with each other and with ANSYS Additive using identical material models, boundary and initial conditions. The codes were used to simulate three different geometries: a thin wall, hollow cylinder and twin-cantilever part. The coupon parts were then manufactured with Inconel-625. The residual stresses in these parts were measured using X-ray diffraction as well as neutron beam diffraction at NIST. The stress measurements for the two technologies are compared. The pragmatic stress prediction method enabled predictions of the multi-centimeter scale parts using desktop computer workstations in only a few hours for each coupon. The results of the simulated stress predictions compared favorably with the measured stresses even though thermally lumped layers were employed. Finally, a two-meter scale nozzle was simulated using ANSYS Additive. The simulations were used to examine the build orientation trade-space with respect to resulting geometric deformation. The predicted deformations were compared to measurements of an actual subscale part manufactured with direct energy deposition.

Additive Manufacturing↗
NASA NTRSDate not supplied

Modeling and Analysis of Stirling Power Convertors

NASA Glenn’s Thermal Energy Conversion Branch is supporting the development of the next generation free-piston Stirling power convertors for Dynamic Radioisotope Power Systems (DRPS). American Superconductor (AMSC) and Sunpower Inc. are the two of the firms under contract to develop the Flexure Isotope Stirling Convertor (FISC) and the Sunpower Robust Stirling Convertor (SRSC), respectively, to meet DRPS requirements. 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.

Stirling↗
NASA NTRSDate not supplied

Modeling and Analysis of Stirling Power Convertors

NASA Glenn’s Thermal Energy Conversion Branch is supporting the development of the next generation free-piston Stirling power convertors for Dynamic Radioisotope Power Systems (DRPS). American Superconductor (AMSC) and Sunpower Inc. are the two of the firms under contract to develop the Flexure Isotope Stirling Convertor (FISC) and the Sunpower Robust Stirling Convertor (SRSC), respectively, to meet DRPS requirements. 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.

Stirling↗
NASA NTRSDate not supplied

Pragmatic Stress Prediction on Additively Manufactured Coupons

Prediction of residual stresses from process parameters for additively manufactured large metal parts is computationally expensive. NASA is currently developing meter-scale parts with direct energy deposition. Practically, the predictive computational methods need to efficiently scale-up to meter-scale parts. Coupled thermal-mechanical multi-physics simulations have been developed with the pragmatic method using ABAQUS, COMSOL Multiphysics, ALE3D software. The residual stresses are a result of the manufacturing process which creates thermal cycling of the build layers. The pragmatic method uses lumped thermal layers for stress predictions to reduce computational costs. The stress predictions as well as deformations of the different codes are compared with each other and with ANSYS Additive using identical material models, boundary and initial conditions. The codes were used to simulate three different geometries: a thin wall, hollow cylinder and twin-cantilever part. The coupon parts were then manufactured with Inconel-625. The residual stresses in these parts were measured using X-ray diffraction as well as neutron beam diffraction at NIST. The stress measurements for the two technologies are compared. The pragmatic stress prediction method enabled predictions of the multi-centimeter scale parts using desktop computer workstations in only a few hours for each coupon. The results of the simulated stress predictions compared favorably with the measured stresses even though thermally lumped layers were employed. Finally, a two-meter scale nozzle was simulated using ANSYS Additive. The simulations were used to examine the build orientation trade-space with respect to resulting geometric deformation. The predicted deformations were compared to measurements of an actual subscale part manufactured with direct energy deposition.

pragmatic method↗
NASA NTRS2024

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗
NASA NTRSDate not supplied

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗