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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 1,747 records · Page 97

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NASA NTRS1999

Spares Management : Optimizing Hardware Usage for the Space Shuttle Main Engine

The complexity of the Space Shuttle Main Engine (SSME), combined with mounting requirements to reduce operations costs have increased demands for accurate tracking, maintenance, and projections of SSME assets. The SSME Logistics Team is developing an integrated asset management process. This PC-based tool provides a user-friendly asset database for daily decision making, plus a variable-input hardware usage simulation with complex logic yielding output that addresses essential asset management issues. Cycle times on critical tasks are significantly reduced. Associated costs have decreased as asset data quality and decision-making capability has increased.

Gulbrandsen, K. A.↗

NASA NTRS2001

Rotary Wing Flight Test Methods Used for the Evaluation of Night Vision Devices

A number of rotary wing flight tests have been conducted by the Army Aeroflightdynamics Directorate in cooperation with NASA which involved the use of night vision devices and simulated devices. The test set up and data analysis have been taken from two perspectives. Some of the flight tests were structured to look at aircraft handling qualities when the pilot's image quality was reduced from normal daylight levels. In this case, aircraft flight path information was given to the pilot as one input into the Handling Qualities Ratings. Other flight tests were structured to look at pilot and workload directly. In this second case, aircraft position was accurately measured and used as pilot performance data. This paper provides an overview of the test methods used, lessons learned, and recommendations for future tam of night vision devices.

Haworth, Loran↗

NASA NTRS2001

Robust Strategy for Rocket Engine Health Monitoring

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

Santi, L. Michael↗

NASA NTRS2011

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Lewandowski, Beth↗

NASA NTRS2014

Acoustics Research of Propulsion Systems

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests to generate 1/3 octave band Sound Pressure Level (SPL) spectra. In an effort to update the accuracy and quality of liftoff acoustic loading predictions, non-stationary flight data from the Ares I-X were processed in PC-Signal in two flight phases: simulated hold-down and liftoff. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semi-empirical methods. This consisted of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares I-X flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Gao, Ximing↗

NASA NTRS2015

Evaluation of Brine Processing Technologies for Spacecraft Wastewater

Brine drying systems may be used in spaceflight. There are several advantages to using brine processing technologies for long-duration human missions including a reduction in resupply requirements and achieving high water recovery ratios. The objective of this project was to evaluate four technologies for the drying of spacecraft water recycling system brine byproducts. The technologies tested were NASA's Forward Osmosis Brine Drying (FOBD), Paragon's Ionomer Water Processor (IWP), NASA's Brine Evaporation Bag (BEB) System, and UMPQUA's Ultrasonic Brine Dewatering System (UBDS). The purpose of this work was to evaluate the hardware using feed streams composed of brines similar to those generated on board the International Space Station (ISS) and future exploration missions. The brine formulations used for testing were the ISS Alternate Pretreatment and Solution 2 (Alt Pretreat). The brines were generated using the Wiped-film Rotating-disk (WFRD) evaporator, which is a vapor compression distillation system that is used to simulate the function of the ISS Urine Processor Assembly (UPA). Each system was evaluated based on the results from testing and Equivalent System Mass (ESM) calculations. A Quality Function Deployment (QFD) matrix was also developed as a method to compare the different technologies based on customer and engineering requirements.

recycling↗

NASA NTRS2017

Digital Cellular Solid Pressure Vessels: A Novel Approach for Human Habitation in Space

It is widely assumed that human exploration beyond Earth's orbit will require vehicles capable of providing long duration habitats that simulate an Earth-like environment - consistent artificial gravity, breathable atmosphere, and sufficient living space- while requiring the minimum possible launch mass. This paper examines how the qualities of digital cellular solids - high-performance, repairability, reconfigurability, tunable mechanical response - allow the accomplishment of long-duration habitat objectives at a fraction of the mass required for traditional structural technologies. To illustrate the impact digital cellular solids could make as a replacement to conventional habitat subsystems, we compare recent proposed deep space habitat structural systems with a digital cellular solids pressure vessel design that consists of a carbon fiber reinforced polymer (CFRP) digital cellular solid cylindrical framework that is lined with an ultra-high molecular weight polyethylene (UHMWPE) skin. We use the analytical treatment of a linear specific modulus scaling cellular solid to find the minimum mass pressure vessel for a structure and find that, for equivalent habitable volume and appropriate safety factors, the use of digital cellular solids provides clear methods for producing structures that are not only repairable and reconfigurable, but also higher performance than their conventionally manufactured counterparts.

Robotics↗

NASA NTRS2019

Atmospheric Chemistry Modeling Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2019

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O (sup 1) D (Deuterium) to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRSDate not supplied

Updated assessment of TROPOMI NO2 and HCHO columns using airborne spectrometers during the MOOSE and TRACER-AQ field campaigns

Airborne spectrometer data offers the opportunity to evaluate satellite product performance without the impact of subpixel heterogeneity between the different satellite and ground-based measurement footprints. Previous measurements during the Long Island Sound Tropospheric Ozone Study were used to evaluate TROPOMI’s v1.3 NO2 product and found very strong relationships (r2=0.96) between the airborne spectrometer and TROPOMI with a systematic low bias mostly attributed to the coarse a priori profile assumption within the standard TROPOMI retrieval. This presentation will update that analysis using the most up-to-date version 2 TROPOMI NO2 product as well as expand analysis to the HCHO product. In summer 2021, NASA GeoCAPE Airborne Simulator (GCAS) collected measurements over southeast Michigan/western Ontario for the Michigan-Ontario Ozone Source Experiment (MOOSE) and Houston, Texas during the TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ). Flight strategies for both deployments included repeated systematic sampling over common areas of interest coinciding with TROPOMI. During these flights, GCAS NO2 tropospheric columns are available at 250 m x 560 m resolution. Preliminary evaluation of GCAS NO2 retrievals with Pandora spectrometer data in Houston, Texas (3 sites) shows a median percent difference of 1.4% with an interquartile range of -15.5-14.9% (r2=0.72). Column HCHO was also retrieved at a slightly coarser resolution in Houston, Texas (750 m x 1680 m) showing distinct spatial patterns associated with secondary production through the oxidation of VOCs downwind of industrial facilities. Comparison to Pandora HCHO showed a low bias of ~25% (r2=0.29) with further investigation needed to identify the cause for this bias. This presentation will share how the GCAS/Pandora/TROPOMI NO2 and HCHO intercompare and will also extend analysis toward thinking about how these assets will contribute to the validation of future geostationary observations.

Laura Judd↗

NASA NTRS2023

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

Auralization of the sound fields within flight vehicle interiors is of interest to aircraft designers considering crew and passenger ride quality. Computer models can be used to predict the filtering effects that the fuselage structure and interior volume have on the exterior sound field in order to simulate the resulting cabin interior noise. However, this can become expensive when a wide frequency range of analysis suitable for passenger auralization is desired. This is particularly the case when using deterministic modeling methods such as finite element analysis (FEA) wherein prohibitively high levels of detail and finite element discretizations are required to resolve the wavelengths at high frequencies. On the contrary, Statistical Energy Analysis (SEA), while not capturing important modal behaviors at low frequencies, is better suited for higher frequency analyses where structural and interior dynamics exhibit high modal overlap and spatially averaged physical quantities suffice. For this reason, a hybrid procedure is considered here that utilizes FE modal solutions at lower frequencies and SEA results at higher frequencies. A transfer function dataset containing the exterior to interior vibroacoustic filtering effect is calculated accordingly and subsequently stored to be used for a variety of exterior dynamic load cases. At low frequencies, the transfer function dataset detail is related to the level of FE model refinement whereas at high frequencies it functions as an equalizer array with a level of detail corresponding to the SEA subsystem partitioning scheme. The above procedure is described herein and demonstrated on a six passenger flight vehicle with eight propulsors in a hover flight condition.

auralization↗

NASA NTRS2023

A Hybrid Transfer Function Procedure for Broadband Auralization Within Small Flight Vehicle Interiors

auralization↗

DOE OSTI2026

Collider-quality electron bunches from an all-optical plasma photoinjector

We present an approach for generating collider-quality electron bunches using a plasma photoinjector. The approach leverages recently developed techniques for the spatiotemporal control of laser pulses to produce a moving ionization front in a nonlinear plasma wave. The moving ionization front generates an electron bunch with a current profile that balances the longitudinal electric field of an electron beam-driven plasma wave, creating a uniform accelerating field across the bunch. Particle-in-cell (PIC) simulations of the ionization stage show the formation of an electron bunch with 220 pC charge and low emittance (ɛ 𝑥 = 171 nm rad, ɛ 𝑦 = 76 nm rad). Quasistatic PIC simulations of the acceleration stage show that the bunch is efficiently accelerated to 24 GeV over 2 m with a final energy spread of less than 1% and emittances of ɛ 𝑥 = 189 nm rad and ɛ 𝑦 = 80 nm rad. This high-quality electron bunch meets the requirements outlined by the Snowmass process for intermediate-energy colliders and compares favorably to the beam quality of proposed and existing accelerator facilities. The results establish the feasibility of plasma photoinjectors for future collider applications making a significant step toward the realization of high-luminosity, compact accelerators for particle physics research.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Behavioral simulations and experimental evaluations of stress induced spatial nonuniformity of dynamic bulk modulus in additive friction stir deposited AA 6061

Additive friction stir deposition (AFSD) is a rapidly developing solid-state additive manufacturing (AM) technology that enables the fabrication of customized products on a relatively large scale. The unique forge-liked process offers high quality products with refined equiaxed microstructure and exceptional mechanical performance. However, in AFSD, the spatially distributed mechanical properties within a deposited layer have not been established so far, due to the lack of a suitable large-scale mapping method. In the present work, an ultrasonic dynamic-elasticity mapping method was employed to map the distribution of physical properties in a AFSD 6061 Al. Strong spatial asymmetries in elastographies were mainly due to the residual stresses. The origin of the asymmetries was investigated through thermo-mechanical simulations of the AFSD process. It was observed that majority of the asymmetries were associated with the mechanical residual stresses instead of the symmetric thermal residual stresses during linear deposition of the AFSD process. However, the thermal residual stresses can be manipulated to become asymmetric with a 90° turn in the linear deposition path, due to the difference between the levels of cooling along the edges of the inner and outer corners. Hence, the mechanical and thermo-mechanical residual stresses can be additive or subtractive depending on the direction of the turns. Here, such numerically predicted behaviors were also experimentally observed on the AFSD fabricated samples by ultrasonic elastography. Furthermore, additional preliminary studies on multi-layer AFSD fabrications show the asymmetric mechanical stresses generated during the deposition process on different layers generate constructive or destructive interference which results to spatially variable dynamic bulk modulus depending on the deposition orientations of layers.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗

DOE OSTI2024

Attribute-Aware RBFs: Interactive Visualization of Time Series Particle Volumes Using RT Core Range Queries

Smoothed-particle hydrodynamics (SPH) is a mesh-free method used to simulate volumetric media in fluids, astrophysics, and solid mechanics. Visualizing these simulations is problematic because these datasets often contain millions, if not billions of particles carrying physical attributes and moving over time. Radial basis functions (RBFs) are used to model particles, and overlapping particles are interpolated to reconstruct a high-quality volumetric field; however, this interpolation process is expensive and makes interactive visualization difficult. Existing RBF interpolation schemes do not account for color-mapped attributes and are instead constrained to visualizing just the density field. To address these challenges, we exploit ray tracing cores in modern GPU architectures to accelerate scalar field reconstruction. We use a novel RBF interpolation scheme to integrate per-particle colors and densities, and leverage GPU-parallel tree construction and refitting to quickly update the tree as the simulation animates over time or when the user manipulates particle radii. We also propose a Hilbert reordering scheme to cluster particles together at the leaves of the tree to reduce tree memory consumption. Finally, we reduce the noise of volumetric shadows by adopting a spatially temporal blue noise sampling scheme. Our method can provide a more detailed and interactive view of these large, volumetric, time-series particle datasets than traditional methods, leading to new insights into these physics simulations.

Particle Volumes↗

DOE OSTI2023

Effects of Cr/Zircaloy-4 coating qualities for enhanced accident tolerant fuel cladding

Cr-coated zirconium alloys represent a modern approach to enhance cladding safety during accident scenarios. Two high-power impulse magnetron sputtered Cr-coated Zry-4 systems were subjected to simulated loss-of-coolant accident conditions to investigate cladding performance. The first Cr-coating (4.8 µm thick) was deposited onto Zry-4 cladding and exhibited through-thickness cracking while the second Cr-coating (6.8 µm thick) was deposited with improved deposition parameters onto polished Zry-4 and exhibited no cracking. During burst testing, the coating with a higher density of defects failed to consistently reduce oxidation and exhibited similar burst behavior as Zry-4. In contrast, the second Cr-coating reduced ZrO 2 formation through formation of Cr 2 O 3 and displayed enhanced burst temperatures by ~80 °C compared to Zry-4. Utilizing an empirical relation for burst behavior of zirconium alloys, the 6.8 µm Cr/Zry-4 system displayed enhanced burst temperatures equivalent to an effective 0.464 mm increase in Zry-4 wall thickness, highlighting the value of continuous Cr coatings for accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1978

Ground-based and in-flight simulator studies of low-speed handling characteristics of two supersonic cruise transport concepts

Conventional and powered lift concepts for supersonic approach and landing tasks are considered. Results indicated that the transport concepts had unacceptable low-speed handling qualities with no augmentation, and that in order to achieve satisfactory handling qualities, considerable augmentation was required. The available roll-control power was acceptable for the powered-lift concept.

Grantham, W. D.↗