SEARCH · Search NASA
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.
An overview is presented of a candidate National Launch System (NLS) passive cryogenic propellant prestart conditioning system that offers a stable propellant thermal environment and minimum system complexity. A 2D, multinode model utilizing real fluid properties was developed. This model predicts flow recirculation due to thermal gradients by assuming vertical cold and warm opposing flow streams produced by density differential.
The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.
We describe the population, optomechanical alignment, and alignment verification of near-infrared gratings on the grating wheel mechanism (GWM) for the Infrared Multi- Object Spectrometer (IRMOS). IRMOS is a cryogenic (80 K) facility instrument for the Mayall Telescope (3.8 m) at Kitt Peak National Observatory and a MEMS spectrometer concept demonstrator for NASA's James Webb Space Telescope. The IRMOS optics, bench, and mechanisms are predominantly made of Al 6061 -T651. The GWM consists of 13 planar diffraction gratings and one flat imaging mirror (58 x 57 mm), each mounted at a unique compound angle on a 31.8 cm diameter gear. The Al 6061 grating substrates are stress relieved for enhanced cryogenic performance and the optical surface is replicated from an off-the-shelf master. The imaging mirror is diamond turned and post-polished. The grating mechanism spans a projected diameter of approximately 48cm when fully assembled, utilizes several flexure designs throughout the system to accommodate thermal gradient situations, and is controlled using custom software with an off-the-shelf controller. Each optic is aligned in six degrees of freedom relative to the GWM coordinate system, which is defined relative to an optical alignment cube mounted at the center of the gear. The tip/tilt (Rx, Ry) orientation of a given grating is measured using the zero-order return from an autocollimating theodolite. Each optic's mount includes a one-piece shim located between the optic and the gear. The shim is machined to fine align each optic. We also describe alignment verification, where grating diffractive properties are compared to model predictions.
Using ultraviolet photon pulses, we have probed the internal behavior of a molybdenum-gold Magnetic Penetration Thermometer (MPT) that we designed for x-ray microcalorimetry. In this low-temperature detector, the diamagnetic response of a superconducting MoAu bilayer is used to sense temperature changes in response to absorbed photons. We have previously described an approximate model that explains the high responsivity of the detector to temperature changes as a consequence of a Meissner transition of the molybdenum-gold film in the magnetic field applied by the superconducting circuit used to bias the detector. We compare measurements of MPT heat capacity and thermal conductance, derived from UV photon pulse data, to our model predictions for the thermodynamic properties of the sensor and for the electron cooling obtained by quasiparticle recombination. Our data on electron cooling power is also relevant to the operation of other superconducting detectors, such as Microwave Kinetic Inductance Detectors.
Output from numerical weather models is often used to simulate observations from remote sensing instruments, for purposes ranging from data assimilation, synthetic retrievals of geophysical quantities, and optimization of observing systems. However, when hydrometeors are present, the level of detail provided by the weather model is generally insufficient to fully constrain the input to the radiative transfer model (RTM), and further assumptions must be made by the RTM user in order to produce synthetic observations. Using a hierarchy of models including cloud-resolving, double-moment, bin microphysical, and ice-habit predicting models, along with scattering properties from the OpenSSP, Atmospheric Radiative Transfer Simulator (ARTS) databases, as well as relatively simple geometries (e.g., cylindrical plates and columns), we demonstrate the spread in synthetic observation output and the extent to which it is reduced when microphysics is more strongly constrained by the model. As an intermediate step, an error budget for the RTM simulations was derived and from that we developed and will describe best practices for observation simulation (e.g., optimal number of hydrometeor size bins, truncation of the particle size distribution, angular resolution of scattering phase function). Some statistical comparisons with observations will also be presented.
Agriculture in the Midwest is dominated by monoculture systems that strip the soil of nutrients, decrease yields, and worsen water quality. Crop diversification and cultivating small grains is economically and ecologically advantageous, but limited in practice due to a lack of data about small-grain crop performance as well as monoculture-favoring insurance coverage, economic incentives, and sociocultural traditions. Practical Farmers of Iowa (PFI) strives to create more sustainable agriculture and supports Midwestern farmers in adding small grains into their crop rotations. The DEVELOP team partnered with the USDA Agricultural Research Service and the USA National Phenology Network to assist PFI in applying NASA Earth observation data to track small-grain crop performance. This project developed a Google Earth Engine user interface that enables PFI farmers to compare satellite-assessed vegetation production and climatic conditions of their farm with other PFI farmers. The team assessed the crop performance through Normalized Difference Vegetation Index (NDVI) values derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI). Additionally, the team created a regression model to analyze the predictive properties of vegetation indices and crop yield, ultimately establishing a relationship with mean NDVI from the early growing season. PFI farmers can utilize these products to make informed decisions about their crop production as well as advocate for more expansive insurance policies to protect small-grain crops.
The Meteoroid Input Function (MIF) model has been developed with the purpose of understanding the temporal and spatial variability of the meteoroid impact in the atmosphere. This model includes the assessment of potential observational biases, namely through the use of empirical measurements to characterize the minimum detectable radar cross-section (RCS) for the particular High Power Large Aperture (HPLA) radar utilized. This RCS sensitivity threshold allows for the characterization of the radar system s ability to detect particles at a given mass and velocity. The MIF has been shown to accurately predict the meteor detection rate of several HPLA radar systems, including the Arecibo Observatory (AO) and the Poker Flat Incoherent Scatter Radar (PFISR), as well as the seasonal and diurnal variations of the meteor flux at various geographic locations. In this paper, the MIF model is used to predict several properties of the meteors observed by the Middle and Upper atmosphere (MU) radar, including the distributions of meteor areal density, speed, and radiant location. This study offers new insight into the accuracy of the MIF, as it addresses the ability of the model to predict meteor observations at middle geographic latitudes and for a radar operating frequency in the low VHF band. Furthermore, the interferometry capability of the MU radar allows for the assessment of the model s ability to capture information about the fundamental input parameters of meteoroid source and speed. This paper demonstrates that the MIF is applicable to a wide range of HPLA radar instruments and increases the confidence of using the MIF as a global model, and it shows that the model accurately considers the speed and sporadic source distributions for the portion of the meteoroid population observable by MU.
While the mechanisms responsible for the solar corona and the high-speed solar wind streams are still unknown, model computations offer means of predicting the properties of such mechanisms in light of the empirical constraints currently available. Modeling and data analysis efforts were aimed at understanding the plasma properties of the acceleration of the solar wind, its filamentary nature, and the conditions needed to account for a rapidly accelerating solar wind, reaching its terminal speed within 10 R(sub s). A sequence of models ranging from steady one-fluid descriptions of the solar wind to multi-fluid time-dependent models were developed. Plasma diagnostics evolved from the analysis of data acquired from Skylab to SOHO, and complemented by ground-based observations.
A numerical model for the prediction of local properties of statistically stationary spray-combusting flows is evaluated by comparison with experimental data. To appraise the relative performance of turbulence models, computations were carried out by the k-epsilon model and the algebraic stress model. The present numerical results show the qualitative agreement with experimental data. In terms of overall local flow properties, the algebraic stress model improves a degree of conformity to the experimental data due to its ability to introduce the nonisotropic turbulence effects. Two swirl numbers are considered to investigate the influence of swirl on the droplet evaporation and trajectories, and the effects of droplet/turbulence interactions in flow properties. It is found that the large swirl produces a higher evaporationn rate, and more intensive turbulent mixing and burning. The discrepancies observed in the results are attributed mainly to uncertainties in the initial spray size and velocity distributions, the droplet/wall impingement interaction, the combustion model with the fast chemistry and the turbulence models dealing with the strong streamline curvature and complex interactions between the dispersed droplets and the continuous gas-phase flows.
Traditionally, advanced aerospace composites have been manufactured using thermoset resins. However, recently, thermoplastics have been investigated for use in the manufacturing of composite materials due to their unique manufacturing characteristics. Thermoplastic resins can be reshaped and formed, along with the added benefit of being recyclable, which thermoset resin cannot. Thermoplastic materials undergo a crystallization process during manufacturing which affects the percent crystallinity of the material. The crystallization needs to be understood better to maximize the potential of thermoplastic resins. PEKK is a thermoplastic material with good chemical, thermal, and mechanical loading resistance. PEKK is also a material NASA is interested in for developing new bonded joint technology. The crystalline microstructure of PEKK is at the micrometer length scale, and it is of interest to model the effects of the crystallinity structure on PEKK’s bulk properties. Molecular dynamics (MD) is a simulation tool that allows for property-structure relationships between atomistic structure and nanometer-length portions of a material. This makes MD a useful tool for developing the structure-property relationship of PEKK. However, the micrometer length scale of PEKK’s crystal structure is too large for MD. Thus, a hybrid approach to modeling PEKK’s microstructure is proposed in this work where MD models are built of both the amorphous and crystalline phases of PEKK. The engineering material properties can be obtained using MD at the nanometer length scale. A micromechanics approach can then generate the micrometer length scale of the crystallinity and the effective properties can be homogenized. The objective of this paper is to show the MD model workflow and the MD-predicted properties of PEKK. The properties can then be homogenized with different crystalline percentages to build design graphs that can be used to tailor PEKK for specific composite applications.
Potential users of radar imagery need a better fundamental understanding of the capabilities of radar systems for vegetation studies than past studies provide. One approach is the use of theoretical models to predict observable active microwave properties of vegetation. This in turn requires accurate observations of backscattering coefficients and other active microwave properties in field research studies. The background document for the SRAEC program emphasizes the need to relate electromagnetic parameters to classical biophysical descriptors and to understand the role of polarization, especially cross-polarization. The broad goal of this study is to increase the understanding of the effects of canopy structure on the active microwave properties of vegetation canopies, with particular attention to polarization.
Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.
NASA and its contractors have completed a program to develop a basic mechanics underpinning for textile composites. Three major deliverables were produced by the program: 1. A set of test methods for measuring material properties and design allowables; 2. Mechanics models to predict the effects of the fiber preform architecture and constituent properties on engineering moduli, strength, damage resistance, and fatigue life; and 3. An electronic data base of coupon type test data. This report describes these three deliverables.
A research program has investigated the use of the von Schlippe string-type tire model for predicting the dynamic behavior of aircraft tires. The transfer-function method was used for theory evaluation. A more flexible two-constant modification to the string theory tire model is presented. Experiments were conducted on four types of scale model aircraft tires. Two types were of conventional bias construction, one type was an isotropic toroid, and one type was of unbelted radial construction. The conventional string theory and model gave predictions that were in good agreement with experimental data for bias constructed tires. The two-constant modification to string theory provided better agreement between predictions and experiment for the unconventional tires. The results indicate that the string theory tire model using static and slow-rolling tire properties predicts dynamic aircraft tire properties that have the same trends as the measured dynamic properties and, in most cases, provides good quantitative agreement.
To understand the scattering properties of a deciduous and a coniferous type vegetation scattering models were developed assuming either a disc type leaf or a needle type leaf. The major effort is to calculate the corresponding scattering phase functions and then each of the functions is used in a radiative transfer formulation to compute the scattering intensity and consequently the scattering coefficient. The radiative transfer formulation takes into account the irregular ground surface by including the rough soil surface in the boundary condition. Thus, the scattering model accounts for volume scattering inside the vegetation layer, the surface scattering from the ground and the interaction between scattering from the soil surface and the vegetation volume. The contribution to backscattering by each of the three scattering mechanisms is illustrated along with the effects of each layer or surface parameter. The major difference between the two types of vegetation is that when the incident wavelength is comparable to the size of the leaf there is a peak appearing in the mid angular region of the backscattering curve for the disc type leaf whereas it is a dip in the same region for a needle type leaf.
A constitutive model has been developed for predicting the dynamic properties of composite beams which accounts for the influence of microstructural damage. The model assumes the damage state to be fixed. The model can account for both the damping increase and stiffness loss due to microstructural damage. Damage dependent material constants obtained from a baseline data set can be used to predict damping changes for several composite layups. The validity of the model has been verified by comparing the experimental results to model predictions for crossply laminates with a variety of stacking sequences.
A mathematical model which can predict solid material properties from known melt properties and solidification environment is being developed to aid in selecting materials systems which could benefit scientifically or commercially from experimentation in space. In its present, preliminary form, the model calculates grain size and dendrite morphology from the undercooling parameter and the parameter which characterizes heterogeneous nucleation. Calculations with the present model are compared to experimental data, and needed improvements in the model are described. Some theoretical problems relating to undercooling and environmentally-induced solute segregation are also discussed.
The number of Extra-Vehicular Activities (EVAs) performed will increase dramatically with the upcoming Space Station assembly missions. It is estimated that up to 900 EVA hours may be required to assemble the Space Station with an additional 200 hours per year for maintenance requirements. Efficient modeling tools will be essential to assist in planning these EVAS. Important components include strength and fatigue parameters, multi-body dynamics and kinematics. This project is focused on building a model of the EVA crew member encompassing all these capabilities. Phase 1, which is currently underway, involves collecting EMU suited and unsuited fatigue, strength and range of motion data, for all major joints of the body. Phase 2 involves processing the data for model input, formulating comparisons between the EMU suits and deriving generalized relationships between suited and unsuited data. Phase 3 will be formulation of a multi-body dynamics model of the EMU capable of predicting mass handling properties and integration of empirical data into the model. Phase 4 will be validation of the model with collected EMU data from the Neutral Buoyancy Laboratory at NASA/JSC. Engineers and designers will use tie EVA suit database to better understand the capabilities of the suited individuals. This knowledge will lead to better design of tools and planned operations. Mission planners can use the modeling system and view the animations and the visualizations of the various parameters, such as overall fatigue, motion, timelines, reach, and strength to streamline the timing, duration, task arrangement, personnel and overall efficiency of the EVA tasks. Suit designers can use quantifiable data at common biomechanical structure points to better analyze and compare suit performance.