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 method is developed for estimating an error model for geopotential coefficients using satellite tracking data. A single station's apparent timing error for each pass is attributed to geopotential errors. The root sum of the residuals for each station also depends on the geopotential errors, and these are used to select an error model. The model chosen is 1/4 of the difference between the SAO M1 and the APL 3.5 geopotential.
Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a full-scale crash test of a Fokker F28 MK1000 aircraft to investigate the performance of transport aircraft under realistic crash conditions. This crash test was computationally recreated using finite element (FE) human body models (HBMs) to further explore potential injury risks to occupants and analyze the utilization of HBMs in the aerospace crash environment. The Global Human Body Model Consortium (GHBMC) male 50th percentile occupant detailed model (v6.0) and the Toyota Human Model for Safety (THUMS) male 50th percentile occupant model (v6.1) were selected to be used in the crash simulations. The HBMs were simulated in conditions matching those of anthropomorphic test device (ATD) experiments included within the aircraft cabin during the crash test. Seven occupant locations within the cabin were simulated utilizing each of the models. The models were positioned in a neutral upright posture with hands resting on the legs and the feet contacting the floor. Head, brain, neck, and lumbar vertebra injury metrics were calculated for all trials. Both HBM models required minor modifications to stabilize these simulations. The GHBMC model required added erosion for six parts while the THUMS model only required one in order to complete the full simulation. The THUMS model, however, required a much smaller timestep for stability and therefore took significantly more computational time. In addition the GHBMC model includes integrated instrumentation while the THUMS model requires development and implementation of instrumentation. Both models predicted 100% injury risk for lumbar vertebra fracture in all test conditions. This prediction was in family with high lumbar load values measured by the ATDs during the crash test. The THUMS model consistently predicted lower injury risks than the GHBMC model in all three other metrics varying depending on the crash pulse. Overall, the THUMS model required less modifications to allow for this study. However, the GHBMC models significantly faster run time and integrated instrumentation make it a more intuitive model for this research.
Large temperature and pressure fluctuations have a profound effect on turbulence development in transonic and supersonic jets. For high-speed, high-temperature jet flows, standard turbulence models lack the ability to predict the observed mixing rate of a shear layer. Several proposals to address this deficiency have been advanced in the literature to modify the turbulence transport equations in a variety of ways. In the present study, some of the most proven and simple modifications to two-equation turbulence models have been selected and implemented in NASA's USM3D tetrahedral Navier-Stokes flow solver. The modifications include the addition of compressibility correction and pressure dilatation terms in the turbulence transport equations for high-speed flows, and the addition of a simple modification to the Boussinesq's closure model coefficient for high-temperature jets. The efficacy of the extended models is demonstrated by comparison with experimental data for two supersonic axisymmetric jet test cases at design pressure ratio.
The bulk chemistries of 33 chondrules from the Allende meteorite were determined by electron microbeam analyses and the modal recombination model. Chondrules were selected on the basis of a petrographic study of 2755 inclusions, of which 997 are chondrules, classified as recrystallized olivine chondrules, euhedral olivine chondrules, anhedral olivine chondrules, glassy/skeletal olivine chondrules, barred olivine chondrules, and pyroxene type chondrules. The data indicate that nonequilibrium metastable paths of crystallization were followed, a model which is supported by olivine-liquid (glassy mesostases) relationships. Variations in olivine morphology are related to cooling rate, degree of supercooling, normative olivine, and calculated viscosities. The chondrules in Allende were derived from highly undersaturated ultramafic melts in which Fe-Ni-S-O immiscible liquids were produced. The chondrule suite exhibits systematic variations in volatile loss, and this relationship is used to support a melting event (however, neither the nature of this event nor the mechanism of melt formation is established).
The Anvil Tool GUI allows users to select a Data Type, toggle the map refresh on/off, place labels, and choose the Profiler Type (source of the KSC 50 MHz profiler data), the Date- Time of the data, the Center of Plot, and the Station (location of the RAOB or 50 MHz profiler). If the Data Type is Models, the user selects a Fcst Hour (forecast hour) instead of Station. There are menus for User Profiles, Circle Label Options, and Frame Label Options. Labels can be placed near the center circle of the plot and/or at a specified distance and direction from the center of the circle (Center of Plot). The default selection for the map refresh is "ON". When the user creates a new Anvil Tool map with Refresh Map "ON, the plot is automatically displayed in the AWIPS frame. If another Anvil Tool map is already displayed and the user does not change the existing map number shown at the bottom of the GUI, the new Anvil Tool map will overwrite the old one. If the user turns the Refresh Map "OFF", the new Anvil Tool map is created but not automatically displayed. The user can still display the Anvil Tool map through the Maps dropdown menu* as shown in Figure 4.
The current model for the polarized brightness (pB) spectrum has a decades-long history of progressively incorporating its dependence on electron density Ne, temperature Te, and flow velocity in the radial direction V e . The pB N e spectrum follows the exact shape of the photosphere spectrum, which is not smooth, which is expected from the thermal Doppler broadening of the photosphere spectrum due to the high coronal T e ; the pB N e T e spectrum is smooth, but the free coronal electrons remain static and unaffected by solar wind, and the pB N e T e V e spectrum is red-shifted by electrons seeing a red-shifted photosphere spectrum as they flow away from the Sun as solar wind, which takes a radial direction above 2.5 R ⨀ from Sun center. In this article, we review the progress of the above three model pB spectra in describing the observations and highlight the differences, first by comparing the three model pB spectra against wavelength using a model for Ne and constant values for T e and V e , and second by generating three model 2D pB maps by integrating over a selected wavelengthregion in the three model pB spectra along lines of sight passing through the 14 July 2000 (“Bastille Day”) coronal mass ejection (CME) model, which contains 3D information on N e , T e , and V e . In this regard, the COronal Diagnostic EXperiment (CODEX) on the International Space Station (ISS) in 2024 will measure N e , T e , and V e by matching the measured pB with modeled pB N e T e V e in selected wavelength regions using multiple filters.
The selection of inflow values at boundaries far upstream of an aircraft is considered, for one- and two-equation turbulence models. Inflow values are distinguished from the ambient values near the aircraft, which may be much smaller. Ambient values should be selected first, and inflow values that will lead to them after the decay second; this is not always possible, especially for the time scale. The two-equation decay during the approach to the aircraft is shown; often, the time scale has been set too short for this decay to be calculated accurately on typical grids. A simple remedy for both issues is to impose floor values for the turbulence variables, outside the viscous sublayer, and it is argued that overriding the equations in this manner is physically justified. Selecting laminar ambient values is easy, if the boundary layers are to be tripped, but a more common practice is to seek ambient values that will cause immediate transition in boundary layers. This opens up a wide range of values, and selection criteria are discussed. The turbulent Reynolds number, or ratio of eddy viscosity to laminar viscosity has a huge dynamic range that makes it unwieldy; it has been widely mis-used, particularly by codes that set upper limits on it. The value of turbulent kinetic energy in a wind tunnel or the atmosphere is also of dubious value as an input to the model. Concretely, the ambient eddy viscosity must be small enough to preserve potential cores in small geometry features, such as flap gaps. The ambient frequency scale should also be small enough, compared with shear rates in the boundary layer. Specific values are recommended and demonstrated for airfoil flows
In this presentation we report on our continuing effort in geomagnetic data assimilation, aiming at understanding and predicting geomagnetic secular variation on decadal time scales. In particular, we focus on the effect of the torque balances on the cylindrical surfaces in the core co-axial with the Earth's rotation axis (the Taylor cylinders) on the time evolution of assimilated solutions. We use our MoSST core dynamics,model and observed geomagnetic field at the Earth's surface derived via Comprehensive Field Model (CFM) for the geomagnetic data assimilation. In our earlier studies, a model solution is selected randomly from our numerical database. It is then assimilated with the observations such that the poloidal field possesses the same field tomography on the core-mantel boundary (CMB) continued downward from surface observations. This tomography change is assumed to be effective through out the outer core. While this approach allows rapid convergence between model solutions and the observations, it also generates sevee numerical instabilities: the delicate balance between weak fluid inertia and the magnetic torques on the Taylor cylinders are completely altered. Consequently, the assimilated solution diverges quickly (in approximately 10% of the magnetic free-decay time in the core). To improve the assimilation, we propose a partial penetration of the assimilation from the CMB: The full-scale modification at the CMB decreases linearly and vanish at an interior radius r(sub a). We shall examine from our assimilation tests possible relationships between the convergence rate of the model solutions to observations and the cut-off radius r(sub a). A better assimilation shall serve our nudging tests in near future.
The cost of quality vs cost of failure correction has been a long-running topic of discussion within the Aerospace community. It leads directly to concepts of “risk tolerance”, and risk-based decision-making. It would be valuable if there was a way to compute the optimal investment in customer-executed quality assurance activities using defect significance with respect to performance objectives, the activities’ defect detection effectiveness, and the cost-penalty for late discovery of impactful defects. This optimization is particularly of interest to projects whose budget constraints significantly limit their risk management options.The cost to fix defects (i.e., failure correction) escalates as the project matures. There have been studies attempting to determine the relative cost of fixing defects discovered during various phases of a project life cycle with important implications, all of which suggest growth factors are large. The commonly referred to 1:10:100 rule represents a cost multiplier for repair/rework across the Design to Fab to Test hardware development phases. Cost premiums for QA activities also accumulate when they are treated as mandatory (due to schedule drag) or are performed later than their assigned phase.This paper describes the modeling of development phase -dependencies in the conduct of typical customer-executed quality assurance activities. Our initial modeling encompasses:• Distinct phases of the production lifecycle• Multiple kinds of Defects, each with some a-priori likelihood of being present• Each defect’s impact on performance Objectives for a type of hardware• The cost and efficacy of assurance techniques at detecting such Defects• The costs of fixing those Defects detected in a given phase of the production lifecycleThe model captures assurance activities’ abilities to Detect defects. Upon detection it is assumed that the Defect is immediately fixed. Defects that “escape” detection by some activity may thereafter be detected by a later activity, but by then the cost of fixing the Defect may have escalated. Defects are related to the performance Objectives they would detract from, were those Defects to remain present in the operating system.We have constructed and are exploring, a model that relates the importance of hardware system elements to mission objectives, the impact of types of Defects on those hardware types, the cost of customer-executed assurance activities (i.e., supplier controls) and their effectiveness towards reducing an impactful quality escape, and the cost of Defect correction across production phase. We describe the approach taken to select the key model aspects, why they are relevant to our NASA mission, and our efforts to populate it with relevant and contemporary data. We use a notional example to illustrate model design and function.
This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between liquid and vapor phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures, temperatures, and pressurant requirements agree with experimental data, with pressurant mass predictions within 16\% of observed values. This study highlights the importance of selecting appropriate turbulence models to accurately simulate complex flow and heat transfer phenomena during tank pressurization and expulsion. By enhancing the accuracy and reliability of CFD models for liquid hydrogen under cryogenic conditions, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.
This paper is devoted to the concept of instability in dynamical systems with the main emphasis on orbital, Hadamard, and Reynolds instabilities. It demonstrates that the requirement about differentiability in dynamics in some cases is not consistent with the physical nature of motions, and may lead to unrealistic solutions. Special attention is paid to the fact that instability is not an invariant of motion: it depends upon frames of reference, the metric of configuration space, and classes of functions selected for mathematical models of physical phenomena. This leads to the possibility of elimination of certain types of instabilities (in particular, those which lead to chaos and turbulence) by enlarging the class of functions using the Reynolds-type transformation in combination with the stabilization principle: the additional terms (the so-called Reynolds stresses) are found from the conditions that they suppress the original instability. Based upon these ideas, a new approach to chaos and turbulence as well as a new mathematical formalism for nonlinear dynamics are discussed.
This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between vapor and liquid phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved autogenous pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures and temperatures agree well with experimental data, whereas the pressurant mass predictions are within 16% of observed values. This study emphasizes the importance of selecting appropriate turbulence models to accurately simulate the complex flow and heat transfer phenomena during tank autogenous pressurization and expulsion. By improving the accuracy and reliability of CFD models for these processes, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.
A software library has been developed to enable high-fidelity computational simulation of the dynamics of multiple spacecraft distributed over a region of outer space and acting with a common purpose. All of the modeling capabilities afforded by this software are available independently in other, separate software systems, but have not previously been brought together in a single system. A user can choose among several dynamical models, many high-fidelity environment models, and several numerical-integration schemes. The user can select whether to use models that assume weak coupling between spacecraft, or strong coupling in the case of feedback control or tethering of spacecraft to each other. For weak coupling, spacecraft orbits are propagated independently, and are synchronized in time by controlling the step size of the integration. For strong coupling, the orbits are integrated simultaneously. Among the integration schemes that the user can choose are Runge-Kutta Verner, Prince-Dormand, Adams-Bashforth-Moulton, and Bulirsh- Stoer. Comparisons of performance are included for both the weak- and strongcoupling dynamical models for all of the numerical integrators.
A flexible and computationally economical model of the internal combustion engine was developed for use on large digital computer systems. It is based on a system of ordinary differential equations for cylinder-averaged properties. The computer program is capable of multicycle calculations, with some parameters varying from cycle to cycle, and has restart capabilities. It can accommodate a broad spectrum of reactants, permits changes in physical properties, and offers a wide selection of alternative modeling functions without any reprogramming. It readily adapts to the amount of information available in a particular case because the model is in fact a hierarchy of five models. The models range from a simple model requiring only thermodynamic properties to a complex model demanding full combustion kinetics, transport properties, and poppet valve flow characteristics. Among its many features the model includes heat transfer, valve timing, supercharging, motoring, finite burning rates, cycle-to-cycle variations in air-fuel ratio, humid air, residual and recirculated exhaust gas, and full combustion kinetics.
Main issues to be considered in designing an air transport system are discussed, and a model for the selection of an optimal air network for a region is presented. It was desired to have the ability to consider a dense network of nodes and air routes and variations in schedules on routes, which in combination would represent virtually all conceivable alternatives. Linear and integer programming were chosen as the most promising analysis methodologies. Integer programming was found to be intractable, while linear programming provided efficient solutions. The model was applied to studying the feasibility of a STOL network in West Virginia. Based on allowable paths, an examination of intercity demands, and established growth points, desired levels of service expressed as minimum flights were determined for certain city pairs.
Human presence in space, whether permanent or temporary, is accompanied by the presence of microbes. However, the extent of microbial changes in response to spaceflight conditions and the corresponding changes to infectious disease risk is unclear. Previous studies have indicated that spaceflight weakens the immune system in humans and animals. In addition, preflight and in-flight monitoring of the International Space Station (ISS) and other spacecraft indicates the presence of opportunistic pathogens and the potential of obligate pathogens. Altered antibiotic resistance of microbes in flight has also been shown. As astronauts and cosmonauts live for longer periods in a closed environment, especially one using recycled water and air, there is an increased risk to crewmembers of infectious disease events occurring in-flight. Therefore, understanding how the space environment affects microorganisms and their disease potential is critically important for spaceflight missions and requires further study. The goal of this flight experiment, operationally called MICROBE, is to utilize three model microbial pathogens, Salmonella typhimurium, Pseudomonas aeruginosa, and Candida albicans to examine the global effects of spaceflight on microbial gene expression and virulence attributes. Specifically, the aims are (1) to perform microarray-mediated gene expression profiling of S. typhimurium, P. aeruginosa, and C. albicans, in response to spaceflight in comparison to ground controls and (2) to determine the effect of spaceflight on the virulence potential of these microorganisms immediately following their return from spaceflight using murine models. The model microorganisms were selected as they have been isolated from preflight or in-flight monitoring, represent different degrees of pathogenic behavior, are well characterized, and have sequenced genomes with available microarrays. In particular, extensive studies of S. typhimurium by the Principal Investigator, Dr. Nickerson, using ground-based analog systems demonstrate important changes in the genotypic, phenotypic, and virulence characteristics of this pathogen resulting from exposure to a flight-like environment (i.e. modeled microgravity).
Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.
The paradigm that gamma-ray bursts originate from Galactic sources is studied in detail using the angular and intensity distributions observed by the Burst and Transient Source Experiment (BATSE) on NASA's Compton Gamma Ray Observatory (CGRO). Monte Carlo models of gamma-ray burst spatial distributions and luminosity functions are used to simulate bursts, which are then folded through mathematical models of BATSE selection effects. The observed and computed angular intensity distributions are analyzed using modifications of standard statistical homogeneity and isotropy studies. Analysis of the BATSE angular and intensity distributions greatly constrains the origins and luminosities of burst sources. In particular, it appears that no single population of sources confined to a Galactic disk, halo, or localized spiral arm satisfactorily explains BATSE observations and that effects of the burst luminosity function are secondary when considering such models. One family of models that still satisfies BATSE observations comprises sources located in an extended spherical Galactic corona. Coronal models are limited to small ranges of burst luminosity and core radius, and the allowed parameter space for such models shrinks with each new burst BATSE observes. Multiple-population models of bursts are found to work only if (1) the primary population accounts for the general isotropy and inhomogeneity seen in the BATSE observations and (2) secondary populations either have characteristics similar to the primary population or contain numbers that are small relative to the primary population.