SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A model of Univac 1108 work flow has been developed to assist in performance evaluation studies and configuration planning. Workload profiles and system configurations are parameterized for ease of experimental modification. Outputs include capacity estimates and performance evaluation functions. The U1108 system is conceptualized as a service network; classical queueing theory is used to evaluate network dynamics.
The Navigation Campaign of the OSIRIS-REx mission began when the first image of Bennu was recorded by the PolyCam high-resolution imager on Au-gust 17, 2018. In the ensuing months, two teams began building shape models based on imagery taken during the Approach and Preliminary survey phases to be used for the transition to landmark navigation in the Orbital A phase. The orbit determination team began analyzing and characterizing the performance and errors associated with each shape model delivery working closely to iterate on the next shape model delivery. By the end of Orbital A, shape models produced by the Altimetry Working Group and JPL exceeded pre-launch performance re-quirements. This paper provides a summary of the analysis performed during operations.
As it has for the past few years, numerical modeling is being used to predict the on-orbit, high-contrast imaging performance of the WFIRST coronagraph, which was recently defined to be solely a technology demonstrator. A consequence has been a realignment of modeling priorities and revised applications of modeling uncertainty factors and margins, which apply to multiple factors such as pointing and wavefront jitter, thermally-induced deformations, polarization, and aberration sensitivities. At the same time, the models have increased in fidelity as additional parameters have been added, such as time-dependent pupil shear and mid-spatial-frequency deformations of the primary and secondary mirrors, detector effects, and reaction-wheel-speed-dependent pointing and wavefront jitter.
The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.
An integrated computational model of a generic hypersonic vehicle was developed for the purpose of determining the vehicle's performance characteristics, which include the lift, drag, thrust, and moment acting on the vehicle at specified altitude, flight condition, and vehicular configuration. The lift, drag, thrust, and moment are developed for the body fixed coordinate system. These forces and moments arise from both aerodynamic and propulsive sources. SCRAMjet engine performance characteristics, such as fuel flow rate, can also be determined. The vehicle is assumed to be a lifting body with a single aerodynamic control surface. The body shape and control surface location are arbitrary and must be defined. The aerodynamics are calculated using either 2-dimensional Newtonian or modified Newtonian theory and approximate high-Mach-number Prandtl-Meyer expansion theory. Skin-friction drag was also accounted for. The skin-friction drag coefficient is a function of the freestream Mach number. The data for the skin-friction drag coefficient values were taken from NASA Technical Memorandum 102610. The modeling of the vehicle's SCRAMjet engine is based on quasi 1-dimensional gas dynamics for the engine diffuser, nozzle, and the combustor with heat addition. The engine has three variable inputs for control: the engine inlet diffuser area ratio, the total temperature rise through the combustor due to combustion of the fuel, and the engine internal expansion nozzle area ratio. The pressure distribution over the vehicle's lower aft body surface, which acts as an external nozzle, is calculated using a combination of quasi 1-dimensional gas dynamic theory and Newtonian or modified Newtonian theory. The exhaust plume shape is determined by matching the pressure inside the plume, calculated from the gas dynamic equations, with the freestream pressure, calculated from Newtonian or Modified Newtonian theory. In this manner, the pressure distribution along the vehicle after body expansion surface is then determined. The aerodynamic modeling, the engine modeling, and the exhaust plume analysis are described in more detail. A description of the computer code used to perform the above calculations is given and an input/output example is then given. The computer code is available on a Macintosh floppy disk.
Single event upsets in digital flight control hardware induced by atmospheric neutrons can reduce system performance and possibly introduce a safety hazard. One method currently under investigation to help mitigate the effects of these upsets is NASA Langley s Recoverable Computer System. In this paper, a Markov jump-linear model is developed for a recoverable flight control system, which will be validated using data from future experiments with simulated and real neutron environments. The method of tracking error analysis and the plan for the experiments are also described.
The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a software system to simulate human performance in support of human reliability analysis (HRA) in nuclear power plants. This paper summarizes recent work to integrate HUNTER with a plant simulator, namely the Rancor Microworld Simulator. Rancor is an offshoot of earlier work at Idaho National Laboratory (INL) to support plant modernization. The graphical software tools used to mimic digital human-system interface upgrades at INL’s Human Systems Simulation Laboratory were linked to the Rancor Microworld Simulator, an INL-developed simplified plant model. HUNTER becomes a “virtual operator” coupled to the Rancor simulator, thereby allowing a tight coupling between a digital human twin and a digital twin of the plant. Rancor-HUNTER may be run through Monte Carlo iterations across a dynamic range of performance shaping factors, thereby producing distributions of human performance in terms of procedure paths, errors instantiations, and task durations. This paper overviews the various unique features of Rancor-HUNTER and presents an example run of Rancor-HUNTER for a startup scenario.
We describe the Metrology Data Processor (METDAT), the Optical Surface Analysis Code (OSAC), and their application to the image evaluation of the Far Ultraviolet Spectroscopic Explorer (FUSE) mirrors. The FUSE instrument - designed and developed by the Johns Hopkins University and launched in June 1999 is an astrophysics satellite which provides high resolution spectra (lambda/Delta(lambda) = 20,000 - 25,000) in the wavelength region from 90.5 to 118.7 nm The FUSE instrument is comprised of four co-aligned, normal incidence, off-axis parabolic mirrors, four Rowland circle spectrograph channels with holographic gratings, and delay line microchannel plate detectors. The OSAC code provides a comprehensive analysis of optical system performance, including the effects of optical surface misalignments, low spatial frequency deformations described by discrete polynomial terms, mid- and high-spatial frequency deformations (surface roughness), and diffraction due to the finite size of the aperture. Both normal incidence (traditionally infrared, visible, and near ultraviolet mirror systems) and grazing incidence (x-ray mirror systems) systems can be analyzed. The code also properly accounts for reflectance losses on the mirror surfaces. Low frequency surface errors are described in OSAC by using Zernike polynomials for normal incidence mirrors and Legendre-Fourier polynomials for grazing incidence mirrors. The scatter analysis of the mirror is based on scalar scatter theory. The program accepts simple autocovariance (ACV) function models or power spectral density (PSD) models derived from mirror surface metrology data as input to the scatter calculation. The end product of the program is a user-defined pixel array containing the system Point Spread Function (PSF). The METDAT routine is used in conjunction with the OSAC program. This code reads in laboratory metrology data in a normalized format. The code then fits the data using Zernike polynomials for normal incidence systems or Legendre-Fourier polynomials for grazing incidence systems. It removes low order terms from the metrology data, calculates statistical ACV or PSD functions, and fits these data to OSAC models for the scatter analysis. In this paper we briefly describe the laboratory image testing of FUSE spare mirror performed in the near and vacuum ultraviolet at John Hopkins University and OSAC modeling of the test setup performed at NASA/GSFC. The test setup is a double-pass configuration consisting of a Hg discharge source, the FUSE off-axis parabolic mirror under test, an autocollimating flat mirror, and a tomographic imaging detector. Two additional, small fold flats are used in the optical train to accommodate the light source and the detector. The modeling is based on Zernike fitting and PSD analysis of surface metrology data measured by both the mirror vendor (Tinsley) and JHU. The results of our models agree well with the laboratory imaging data, thus validating our theoretical model. Finally, we predict the imaging performance of FUSE mirrors in their flight configuration at far-ultraviolet wavelengths.
The development of a model to predict cell/battery behavior given databases of temperature is described. The model accommodates batteries of various structural as well as thermal designs. Cell internal design modifications can be accommodated as long as the databases reflect the cell's performance characteristics. Operational parameters can be varied to simulate any number of charge or discharge methods under any orbital regime. The flexibility of the model stems from the broad scope of input variables and allows the prediction of battery performance under simulated mission or test conditions.
Uranium mononitride (UN) is a nuclear fuel candidate for advanced reactor designs and an alternative being considered for light water reactors due to its higher thermal conductivity and uranium density than UO 2 . As with any nuclear fuel, swelling and fission gas release are important factors for safety, while also being some of the hardest phenomena to predict with a high degree of confidence. Getting a grasp on the gas swelling behavior and release is crucial to lower the barrier for UN utilization. An accelerated swelling rate at high temperatures observed experimentally, sometimes referred to as “breakaway swelling,” further complicates the prediction of fuel performance of UN. A mechanistic model has been developed using a multiscale approach to describe the intragranular and intergranular fission gas behavior. Lower-length-scale calculations have been employed to inform models of the gas and self-diffusion behavior, resolution rate, and bubble shape. Leveraging previous work on high burnup UO 2 , two populations of intragranular bubbles are considered; small bulk bubbles and larger bubbles located along dislocations. The dislocation bubbles were found to be crucial to the overall swelling behavior, and the breakaway swelling transition was associated with the transition in the gas atom diffusion mechanism from an irradiation-induced athermal diffusion regime at lower temperatures to an intrinsic thermal equilibrium regime at higher temperatures, accelerating the growth of the dislocation bubbles. Similarly, the threshold for fission gas release was associated with the grain boundary vacancy diffusivity surpassing the gas atom diffusivity at sufficiently high temperatures, allowing the over-pressurized grain boundary bubble to grow in size and interconnect. Using thermo-mechanical models with the fission gas model, two integral fuel pin assessment cases were simulated. Finally, this work demonstrates the ability of a multiscale approach to accelerate the understanding of advanced fuel forms when experimental data is limited.
We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3) with simplified chemistry and the Data Assimilation Research Testbed (DART) assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO) by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument. We verify the system performance using independent CO observations taken on board the NSFINCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B). Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence). The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (-140 ppbv). Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China) and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements. The work described above also brought to light several short-comings of the data assimilation approach for CO profiles. Because of the limited vertical resolution of the measurement, the retrievals at different altitudes are correlated which can lead to problems with numerical error and overall efficiency. This has resulted in a manuscript that is about to be submitted to JGR:
Data obtained from the boundary of a test section provides information on the model contained within it. A method for extracting some of this data in two dimensional testing is described. Examples of model data are included on lift, pitching moment and wake displacement thickness. A FORTRAN listing is also described, having a form suitable for incorporation into the software package used in the running of such a test section.
In 1988 computer codes from NASA and DLR were combined to analyze and optimize rocket engines for advance launch vehicles. Further effort has addressed performance propulsion parameters such as chamber pressure, cycle selection (including mixed and tripropellant cycles), nozzle extension, and new technologies. Results of the study indicate that lower dry masses can be reached with the staged combustion cycle than with the gas-generator cycle, using oxygen/hydrogen at relatively high mixture ratio (7:1) and modest chamber pressure (220 bar). For low dry masses the staged combustion cycle is only excelled by the dual-expander cycle using hydrogen and propane as fuels. The emphasis here is to explain the procedure and boundary conditions used for the analysis and the variety of configurations treated, as well as to demonstrate the methods used by presenting some of the major results.
With the recent need to qualify new reactor designs such as the Versatile Test Reactor (VTR), fuel performance calculations need to be performed to determine safety criteria of the proposed designs. In order to validate the fuel performance results obtained by a fuel performance code, BISON, for new reactor designs, legacy fuel from EBR-II and FFTF MFF with Post -Irradiation Examination (PIE) data need to be used as validation cases to benchmark models. Here in this work, BISON has been paired with the Fuels Irradiation & Physics Database (FIPD) and IFR Materials Information System (IMIS) to supply PIE data for comparison with simulations of EBR-II experiments X447/X447A. X447/X447A were assessed by implementing models for Fuel Cladding Chemical Interaction (FCCI) within BISON and optimizing the friction coefficient between the fuel surface and the cladding, the anisotropic swelling factor, and the HT9 first thermal creep scalar (which scales the first term in the HT9 creep equation) to best match the PIE axial fuel swelling height and cladding profilometry for all pins in X447/X447A. The optimal values were found using a generic algorithm developed to select different values for the three parameters until end criteria was met and error couldn’t be reduced further. The BISON-simulated cladding profilometry was evaluated using Standard Error of the Estimate (SEE) to account for the profile shape of the cladding profilometry. Optimal values for the friction coefficient, anisotropic fuel swelling factor, and HT9 first thermal creep scalar were found to best fit the BISON simulation results to the PIE measurements found in IMIS and FIPD. Improvements to current models are suggested to account for the underprediction of fuel swelling at low burnups and the overprediction of fuel swelling at higher burnups observed for the axial fuel swelling height. Although two pins in EBR-II X447/X447A (DP70 and DP75) were known to fail due to FCCI, none of the pins simulated in BISON reached a cumulative damage fraction (CDF) above 0.008 with FCCI correlations coupled in the BISON simulations. The error estimate generated for all pins in X447/X447A using optimal values was 209 µm, which is deemed acceptable.
Current artificial intelligence (AI) applications in geothermal exploration are tailored to specific geothermal sites, limiting their transferability and broader applicability. This study aims to develop a globally applicable and transferable geothermal AI model to empower the exploration of geothermal resources. This study presents a methodology for adopting geothermal AI that utilizes known indicators of geothermal areas, including mineral markers, land surface temperature (LST), and faults. The proposed methodology involves a comparative analysis of three distinct geothermal sites—Brady, Desert Peak, and Coso. The research plan includes self-testing to understand the unique characteristics of each site, followed by dependent and independent tests to assess cross-compatibility and model transferability. The results indicate that Desert Peak and Coso geothermal sites are cross-compatible due to their similar geothermal characteristics, allowing the AI model to be transferable between these sites. However, Brady is found to be incompatible with both Desert Peak and Coso. The geothermal AI model developed in this study demonstrates the potential for transferability and applicability to other geothermal sites with similar characteristics, enhancing the efficiency and effectiveness of geothermal resource exploration. This advancement in geothermal AI modeling can significantly contribute to the global expansion of geothermal energy, supporting sustainable energy goals.
The importance of reducing jet noise in both commercial and military aircraft applications has made jet acoustics a significant area of research. A technique for jet noise prediction commonly employed in practice is the MGB approach, based on the Lighthill acoustic analogy. This technique requires as aerodynamic input mean flow quantities and turbulence quantities like the kinetic energy and the dissipation. The purpose of the present paper is to assess existing capabilities for predicting these aerodynamic inputs. Two modern Navier-Stokes flow solvers, coupled with several modern turbulence models, are evaluated by comparison with experiment for their ability to predict mean flow properties in a supersonic jet plume. Potential weaknesses are identified for further investigation. Another comparison with similar intent is discussed by Barber et al. The ultimate goal of this research is to develop a reliable flow solver applicable to the low-noise, propulsion-efficient, nozzle exhaust systems being developed in NASA focused programs. These programs address a broad range of complex nozzle geometries operating in high temperature, compressible, flows. Seiner et al. previously discussed the jet configuration examined here. This convergent-divergent nozzle with an exit diameter of 3.6 inches was designed for an exhaust Mach number of 2.0 and a total temperature of 1680 F. The acoustic and aerodynamic data reported by Seiner et al. covered a range of jet total temperatures from 104 F to 2200 F at the fully-expanded nozzle pressure ratio. The aerodynamic data included centerline mean velocity and total temperature profiles. Computations were performed independently with two computational fluid dynamics (CFD) codes, ISAAC and PAB3D. Turbulence models employed include the k-epsilon model, the Gatski-Speziale algebraic-stress model and the Girimaji model, with and without the Sarkar compressibility correction. Centerline values of mean velocity and mean temperature are compared with experimental data.
Using measured device parameters from a monolithic three-terminal In/GaInAs (0.75 eV) tandem concentrator solar cell, a numerical model is constructed that calculates efficiency as a function of temperature and concentration ratio. The device measurements indicate that the series resistance in the InP top cell severely limits the maximum efficiency at high concentration ratios. Results from the model in which a single-junction InP concentrator solar cell that has a lower resistance by a factor of six was substituted for the top cell show that peak 20 C air-mass-zero (AM0) efficiencies should approach 30 percent at concentration ratios greater than 100. At 80 C, this tandem cell should exceed 24 percent AM0 efficiency.
An account is given of a Visibility Modeling Tool (VMT) which furnishes a crew-station designer with the means to assess configurational tradeoffs, with a view to the impact of various options on the unambiguous access of information to the pilot. The interactive interface of the VMT allows the manipulation of cockpit geometry, ambient lighting, pilot ergonomics, and the displayed symbology. Performance data can be displayed in the form of 3D contours into the crewstation graphic model, thereby yielding an indication of the operator's visual capabilities.