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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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All sources NASA NTRS DOE OSTI

DOE OSTI2021

X-composer: enabling cross-environments in-situ workflows between HPC and cloud

As large-scale scientific simulations and big data analyses become more popular, it is increasingly more expensive to store huge amounts of raw simulation results to perform post-analysis. To minimize the expensive data I/O, "in-situ" analysis is a promising approach, where data analysis applications analyze the simulation generated data on the fly without storing it first. However, it is challenging to organize, transform, and transport data at scales between two semantically different ecosystems due to the distinct software and hardware difference. To tackle these challenges, we design and implement the X-Composer framework. X-Composer connects cross-ecosystem applications to form an "in-situ" scientific workflow, and provides a unified approach and recipe for supporting such hybrid in-situ workflows on distributed heterogeneous resources. X-Composer reorganizes simulation data as continuous data streams and feeds them seamlessly into the Cloud-based stream processing services to minimize I/O overheads. For evaluation, we use X-Composer to set up and execute a cross-ecosystem workflow, which consists of a parallel Computational Fluid Dynamics simulation running on HPC, and a distributed Dynamic Mode Decomposition analysis application running on Cloud. Our experimental results show that X-Composer can seamlessly couple HPC and Big Data jobs in their own native environments, achieve good scalability, and provide high-fidelity analytics for ongoing simulations in real-time.

Wang, Dali↗

DOE OSTI2021

Hybrid electric buses fuel consumption prediction based on real-world driving data

Estimating fuel consumption by hybrid diesel buses is challenging due to its diversified operations and driving cycles. Here, long-term transit bus monitoring data were utilized to empirically compare fuel consumption of diesel and hybrid buses under various driving conditions. Artificial neural network (ANN) based high-fidelity microscopic (1 Hz) and mesoscopic (5–60 min) fuel consumption models were developed for hybrid buses. The microscopic model contained 1 Hz driving, grade, and environment variables. The mesoscopic model aggregated 1 Hz data into 5 to 60-minute traffic pattern factors and predicted average fuel consumption over its duration. The prediction results show mean absolute percentage errors of 1–2% for microscopic models and 5–8% for mesoscopic models. The data were partitioned by different driving speeds, vehicle engine demand, and road grade to investigate their impacts on prediction performance.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗

NASA NTRS1993

An investigation of fighter aircraft agility

This report attempts to unify in a single document the results of a series of studies on fighter aircraft agility funded by the NASA Ames Research Center, Dryden Flight Research Facility and conducted at the University of Kansas Flight Research Laboratory during the period January 1989 through December 1993. New metrics proposed by pilots and the research community to assess fighter aircraft agility are collected and analyzed. The report develops a framework for understanding the context into which the various proposed fighter agility metrics fit in terms of application and testing. Since new metrics continue to be proposed, this report does not claim to contain every proposed fighter agility metric. Flight test procedures, test constraints, and related criteria are developed. Instrumentation required to quantify agility via flight test is considered, as is the sensitivity of the candidate metrics to deviations from nominal pilot command inputs, which is studied in detail. Instead of supplying specific, detailed conclusions about the relevance or utility of one candidate metric versus another, the authors have attempted to provide sufficient data and analyses for readers to formulate their own conclusions. Readers are therefore ultimately responsible for judging exactly which metrics are 'best' for their particular needs. Additionally, it is not the intent of the authors to suggest combat tactics or other actual operational uses of the results and data in this report. This has been left up to the user community. Twenty of the candidate agility metrics were selected for evaluation with high fidelity, nonlinear, non real-time flight simulation computer programs of the F-5A Freedom Fighter, F-16A Fighting Falcon, F-18A Hornet, and X-29A. The information and data presented on the 20 candidate metrics which were evaluated will assist interested readers in conducting their own extensive investigations. The report provides a definition and analysis of each metric; details of how to test and measure the metric, including any special data reduction requirements; typical values for the metric obtained using one or more aircraft types; and a sensitivity analysis if applicable. The report is organized as follows. The first chapter in the report presents a historical review of air combat trends which demonstrate the need for agility metrics in assessing the combat performance of fighter aircraft in a modern, all-aspect missile environment. The second chapter presents a framework for classifying each candidate metric according to time scale (transient, functional, instantaneous), further subdivided by axis (pitch, lateral, axial). The report is then broadly divided into two parts, with the transient agility metrics (pitch lateral, axial) covered in chapters three, four, and five, and the functional agility metrics covered in chapter six. Conclusions, recommendations, and an extensive reference list and biography are also included. Five appendices contain a comprehensive list of the definitions of all the candidate metrics; a description of the aircraft models and flight simulation programs used for testing the metrics; several relations and concepts which are fundamental to the study of lateral agility; an in-depth analysis of the axial agility metrics; and a derivation of the relations for the instantaneous agility and their approximations.

Valasek, John↗

DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2016

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.

ISRU↗

NASA NTRS1992

Calibration and Change Detection of [Alaska Satellite Facility] ASF/ERS-1 SAR Image Data

The results of a calibration analysis performed on ERS-1 synthetic aperture radar (SAR) images produced by the Alaska SAR facility (ASF) are presented, together with some preliminary results on change detection on the Alaskan north slope derived from the same images. Image quality, geometric and radiometric fidelity, and repeat pass radiometric stability have all been determined to be satisfactory. A calibration workstation has been designed and implemented for use in operational data quality analysis of ASF data products. Higher-level data analysis programs have been developed for interferometry, texture analysis, and change detection.

Fatland, Rob↗

NASA NTRSDate not supplied

Evaluation of Preliminary Buffet Forcing Function Development based on Wind-Tunnel Tests of Geometrically-similar Models

The current state-of-the-art for launch vehicle buffet load estimation involves wind tunnel testing of highly instrumented rigid models and data processing of experimental unsteady pressure measurements to estimate the fluctuating aerodynamic loads. The model and instrumentation requirements to accomplish this type of testing are significant. The rigid model, in particular, must be built with relatively high geometric fidelity to approximate similar aerodynamic phenomena that will occur during the full-scale vehicle flight. Due to this requirement, several iterative wind tunnel tests are often required during the design maturation of the vehicle. For preliminary buffet load estimation, however, data from previous launch vehicle wind tunnel tests of geometrically similar models can be used to provide initial buffet environment estimates before a high geometric fidelity wind tunnel test has been conducted. In this paper, two components of this preliminary buffet estimation process are described: (1) assembly of buffet forcing functions from multiple data sources and (2) scaling of these buffet forcing functions to geometrically-similar components of a target vehicle configuration. The impacts of these estimation methods on the full-vehicle buffet forcing functions, including their longitudinal distribution along the vehicle, frequency-content at individual stations, and station-to-station coherence, are investigated. Considerations for using these methods to extrapolate wind tunnel data to geometrically similar models are also discussed.

Patrick S Heaney↗

NASA NTRS2010

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

In this paper, we will assess the performance of a data-driven anomaly detection algorithm, the Inductive Monitoring System (IMS), which can be used to detect simulated Thrust Vector Control (TVC) system failures. However, the ability of IMS to detect these failures in a true operational setting may be related to the realistic nature of how they are simulated. As such, we will investigate both a low fidelity and high fidelity approach to simulating such failures, with the latter based upon the underlying physics. Furthermore, the ability of IMS to detect anomalies that were previously unknown and not previously simulated will be studied in earnest, as well as apparent deficiencies or misapplications that result from using the data-driven paradigm. Our conclusions indicate that robust detection performance of simulated failures using IMS is not appreciably affected by the use of a high fidelity simulation. However, we have found that the inclusion of a data-driven algorithm such as IMS into a suite of deployable health management technologies does add significant value.

Martin, Rodney A.↗

NASA NTRS2013

Orion MPCV Touchdown Detection Threshold Development and Testing

A robust method of detecting Orion Multi-Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post-landing segment of the Flight Software (FSW). An in-depth trade study was completed to determine optimal characteristics of the touchdown detection method resulting in an algorithm monitoring filtered, lever-arm corrected, 200 Hz Inertial Measurement Unit (IMU) vehicle acceleration magnitude data against a tunable threshold using persistence counter logic. Following the design of the algorithm, high fidelity environment and vehicle simulations, coupled with the actual vehicle FSW, were used to tune the acceleration threshold and persistence counter value to result in adequate performance in detecting touchdown and sufficient safety margin against early detection while descending under parachutes. An analytical approach including Kriging and adaptive sampling allowed for a sufficient number of finite element analysis (FEA) impact simulations to be completed using minimal computation time. The combination of a persistence counter of 10 and an acceleration threshold of approximately 57.3 ft/s2 resulted in an impact performance factor of safety (FOS) of 1.0 and a safety FOS of approximately 2.6 for touchdown declaration. An RCS termination acceleration threshold of approximately 53.1 ft/s(exp)2 with a persistence counter of 10 resulted in an increased impact performance FOS of 1.2 at the expense of a lowered under-parachutes safety factor of 2.2. The resulting tuned algorithm was then tested on data from eight Capsule Parachute Assembly System (CPAS) flight tests, showing an experimental minimum safety FOS of 6.1. The formulated touchdown detection algorithm will be flown on the Orion MPCV FSW during the Exploration Flight Test 1 (EFT-1) mission in the second half of 2014.

Daum, Jared↗

DOE OSTI2020

Using Machine Learning to Predict Future Temperature Outputs in Geothermal Systems

Optimizing the power output, and economic value, of geothermal power plants over decades of operation is a major challenge in renewable energy. Optimizing the output requires the ability to predict the mass flow rates and the output temperatures of production wells based on the inputs of injection wells, as well as the time history of the system. Machine Learning (ML) that incorporates the known physics of geothermal systems is one possible solution to this challenge. In this work, we explore the ability of ML algorithms to predict future temperature outputs based on historical data. Considering the challenges with obtaining an empirical dataset from field data that is large enough to enable reliable ML, we propose an alternate approach: developing a high-fidelity reservoir model and using computational resources to build a dataset that enables ML. As a first step towards achieving this goal, we present preliminary results from applying ML to predict the temperature timeseries of simple modeled geothermal systems. We describe the application of relevant state-of-the-art ML approaches, such as the Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to extract temporal structures in the model data. We assess the accuracy of the forecasts we obtain, compare the selected approaches, and share the lessons learned that would inform the process of training and utilizing ML algorithms for larger and more complex geothermal systems.

GEOTHERMAL ENERGY↗

NASA NTRSDate not supplied

System Identification for eVTOL Aircraft Using Simulated Flight Data

This paper describes a system identification method for electric vertical takeoff and landing (eVTOL) aircraft. The approach merges fixed-wing and rotary-wing modeling techniques with new strategies to develop a modeling method for eVTOL vehicles using flight test data. The eVTOL aircraft system identification approach is demonstrated through application to the NASA LA-8 tandem tilt-wing, distributed electric propulsion aircraft using a high-fidelity flight dynamics simulation. Orthogonal phase-optimized multisine inputs are applied to each control surface and propulsor at numerous flight conditions throughout the flight envelope to collect informative flight data. An aero-propulsive model is identified at each flight condition using the equation-error method in the frequency domain. The local model parameters are then blended to create a global model across the nominal flight envelope. Parameter estimation results are shown to provide a good fit to modeling data and have good prediction capability. The methodology is developed with a discussion of unique eVTOL vehicle aerodynamic characteristics and practical strategies intended to inform future flight-based system identification efforts for eVTOL aircraft.

system identification↗

NASA NTRS2019

Immersive Simulations and Engineering Environment (iSEE): Improving Fidelity of Virtual Reality Simulations

The Immersive Simulation and Engineering Environment (iSEE) provides Kennedy Space Center (KSC) with accurate Human Systems Integration (HSI) analysis of the stresses on a human body incurred from physical work, along with accessibility and reach factors. Human Factors engineers can observe the simulations conducted by iSEE and work with the gathered data to help make the working environment at KSC safer. The software that runs the HSI analysis, however, provides users with a low fidelity virtual environment. Previously, this led to the addition and implementation of other iSEE programs that were capable of higher-fidelity simulations. The difficulties of streamlining the workflow in the lab with these new programs is currently being addressed.

Sein, Alexandr↗

DOE OSTI2021

Analysis of ZPPR-15 experimental data for VTR software validation

As part of the Versatile Test Reactor (VTR) program, extensive validation work is being performed to demonstrate the fidelity of the Argonne Reactor Code (ARC) software package presently used for the core design studies. It is anticipated that this software will be also used for initial operations although additional software may be introduced at a later time to supplement or replace some components. The validation work was focused on accumulating reactor models that are consistent with the VTR and thus can be used to validate the accuracy of predictions made by the software used to design and operate the VTR. The U.S. does not have any active experimental facilities that can neutronically mockup the VTR core design. However, in the past, the U.S. had extensive experimental facilities for fast reactor neutronics. In that regard, the ZPPR-15 experiments carried out at ANL during the 1980s work best because the fuel form is closest to the VTR design, there is a considerable amount of processed data available for use, and existing staff are already familiar with the experimental machine and measurements. Because of previous collaborative work, many of the ZPPR-15 loadings of interest have already been processed into MCNP and preliminary ARC models, and a full uncertainty quantification has already been completed for many of the ZPPR-15 measurements. This manuscript covers the recent analysis work on the ZPPR-15 experiments and compares it with the experimental results. With respect to the ARC software components, this manuscript focuses on validation of the MC 2 , DIF3D and GAMSOR using the ZPPR-15 experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1986

Vestibular models for design and evaluation of flight simulator motion

The use of spatial orientation models in the design and evaluation of control systems for motion-base flight simulators is investigated experimentally. The development of a high-fidelity motion drive controller using an optimal control approach based on human vestibular models is described. The formulation and implementation of the optimal washout system are discussed. The effectiveness of the motion washout system was evaluated by studying the response of six motion washout systems to the NASA/AMES Vertical Motion Simulator for a single dash-quick-stop maneuver. The effects of the motion washout system on pilot performance and simulator acceptability are examined. The data reveal that human spatial orientation models are useful for the design and evaluation of flight simulator motion fidelity.

Bussolari, S. R.↗

NASA NTRS2011

Determination of Barometric Altimeter Errors for the Orion Exploration Flight Test-1 Entry

The EFT-1 mission is the unmanned flight test for the upcoming Multi-Purpose Crew Vehicle (MPCV). During entry, the EFT-1 vehicle will trigger several Landing and Recovery System (LRS) events, such as parachute deployment, based on onboard altitude information. The primary altitude source is the filtered navigation solution updated with GPS measurement data. The vehicle also has three barometric altimeters that will be used to measure atmospheric pressure during entry. In the event that GPS data is not available during entry, the altitude derived from the barometric altimeter pressure will be used to trigger chute deployment for the drogues and main parachutes. Therefore it is important to understand the impact of error sources on the pressure measured by the barometric altimeters and on the altitude derived from that pressure. There are four primary error sources impacting the sensed pressure: sensor errors, Analog to Digital conversion errors, aerodynamic errors, and atmosphere modeling errors. This last error source is induced by the conversion from pressure to altitude in the vehicle flight software, which requires an atmosphere model such as the US Standard 1976 Atmosphere model. There are several secondary error sources as well, such as waves, tides, and latencies in data transmission. Typically, for error budget calculations it is assumed that all error sources are independent, normally distributed variables. Thus, the initial approach to developing the EFT-1 barometric altimeter altitude error budget was to create an itemized error budget under these assumptions. This budget was to be verified by simulation using high fidelity models of the vehicle hardware and software. The simulation barometric altimeter model includes hardware error sources and a data-driven model of the aerodynamic errors expected to impact the pressure in the midbay compartment in which the sensors are located. The aerodynamic model includes the pressure difference between the midbay compartment and the free stream pressure as a function of altitude, oscillations in sensed pressure due to wake effects, and an acoustics model capturing fluctuations in pressure due to motion of the passive vents separating the barometric altimeters from the outside of the vehicle.

Brown, Denise L.↗

DOE OSTI2022

Development of an Enhanced Radiation Physics Toolset for Modeling Spectral and Imaging Signatures in the Warm Dense Matter Experiments

Radiative and atomic processes in plasmas play a critical role in a wide variety of high energy density laboratory plasma (HEDLP) experiments. The emission, absorption, and transport of radiation can strongly affect the overall energetics and evolution of such plasmas. In addition, radiation-based diagnostics – including imaging, spectroscopy, and absolute flux measurements – are widely used to determine key features of HEDLPs. To advance our understanding of HEDLP science, it is vital to have high-fidelity computational physics tools that have well-tested radiation physics modeling, and that are readily accessible to researchers in the HEDLP community. Simulations play an extremely important role for planning and designing the experiments, as well as for post-experiment data analysis. Prism Computational Sciences develops software that is used by National Laboratories and universities (including five members of LaserNetUS network). Prominent examples of such research efforts include z-pinch and short-pulse laser experiments designed to study the basic physics of photoionized plasmas and photoionization fronts, as well as their application to astrophysical plasmas. The main effort was dedicated to the development of non-equilibrium equation-of-state (EOS) models within the HELIOS-CR code, a hydrodynamics code with inline collisional-radiative atomic kinetics. Gas cell experiments on Z and Omega demonstrated the importance of non-equilibrium effects on atomic kinetics in photoionized plasmas. Recent proof-of-principle experiments on Omega EP confirmed the advantages of using a short-pulse laser to create an intense radiation drive, leading to additional experiments being proposed. Photoionization front experiments at LLE also emphasizes the importance of radiation and atomic physics. In both studies, HELIOS-CR simulations played a crucial role in computing non-equilibrium opacities and ionization distributions. A newly developed non-LTE EOS model will help addressing possible non-equilibrium effects, on for example specific heat, and their influence in plasma evolution. Prism also implemented support for open-source atomic data generated by the Flexible Atomic Code. This allows researchers to generate custom atomic tables and use them within the complex framework of simulation tools developed by Prism. The ability to use open-source atomic data would be extremely valuable for hydrodynamics and spectroscopic simulations that include high-Z materials, e.g., picosecond x-ray pulse generation experiments. Support for new atomic structures was fully implemented, and the data can be used by all simulation tools developed at Prism: radiation-hydrodynamics, imaging and spectroscopy, EOS and opacity. The development resulted in a significant fidelity enhancement to the simulations tools developed by Prism that are currently used in other cutting-edge experiments including: opacity measurement experiments performed to both understand the basic radiative and atomic properties of plasmas as well as provide data for more accurately modeling the internal structure of the Sun and other stars, high-intensity short-pulse laser experiments performed to develop short-wavelength light sources for use as backlighters and to investigate fast ignition concepts for inertial fusion energy; capsule implosion experiments designed to develop inertial fusion as an energy source, etc.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2000

SSME Bearing and Seal Tester Data Compilation, Analysis and Reporting; and Refinement of the Cryogenic Bearing Analysis Mathematical Model

SRS and NASA/MSFC have developed software with unique capabilities to couple bearing kinematic modeling with high fidelity thermal modeling. The core thermomechanical modeling software was developed by SRS and others in the late 1980's and early 1990's under various different contractual efforts. SRS originally developed software that enabled SHABERTH (Shaft Bearing Thermal Model) and SINDA (Systems Improved Numerical Differencing Analyzer) to exchange data and autonomously allowing bearing component temperature effects to propagate into the steady state bearing mechanical model. A separate contract was issued in 1990 to create a personal computer version of the software. At that time SRS performed major improvements to the code. Both SHABERTH and SINDA were independently ported to the PC and compiled. SRS them integrated the two programs into a single program that was named SINSHA. This was a major code improvement.

Moore, James↗