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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 541 records · Page 30
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NASA NTRS2014

Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site

The objective of this paper is to report the improvements in an empirical absolute calibration model developed at South Dakota State University using Libya 4 (+28.55 deg, +23.39 deg) pseudo invariant calibration site (PICS). The approach was based on use of the Terra MODIS as the radiometer to develop an absolute calibration model for the spectral channels covered by this instrument from visible to shortwave infrared. Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm, was used to extend the model to cover visible and near-infrared regions. A simple Bidirectional Reflectance Distribution function (BRDF) model was generated using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Libya 4 and the resulting model was validated with nadir data acquired from satellite sensors such as Aqua MODIS and Landsat 7 (L7) Enhanced Thematic Mapper (ETM+). The improvements in the absolute calibration model to account for the BRDF due to off-nadir measurements and annual variations in the atmosphere are summarized. BRDF models due to off-nadir viewing angles have been derived using the measurements from EO-1 Hyperion. In addition to L7 ETM+, measurements from other sensors such as Aqua MODIS, UK-2 Disaster Monitoring Constellation (DMC), ENVISAT Medium Resolution Imaging Spectrometer (MERIS) and Operational Land Imager (OLI) onboard Landsat 8 (L8), which was launched in February 2013, were employed to validate the model. These satellite sensors differ in terms of the width of their spectral bandpasses, overpass time, off-nadir-viewing capabilities, spatial resolution and temporal revisit time, etc. The results demonstrate that the proposed empirical calibration model has accuracy of the order of 3% with an uncertainty of about 2% for the sensors used in the study.

radiometric calibration↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Cascade↗
NASA NTRS2015

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

MODIS VIIRS↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Turbine↗
NASA NTRS2015

A Decade of Change in NO2 and SO2 over the Canadian Oil Sands As Seen from Space

A decade (20052014) of observations from the Ozone Monitoring Instrument (OMI) were used to examine trends in nitrogen dioxide(NO2) and sulfur dioxide (SO2) over a large region of western Canada and the northern United States, with a focus on the Canadian oil sands. In the oil sands, primarily over an area of intensive surface mining, NO2 tropospheric vertical column densities (VCDs) are seen to be increasing by as much as 10year, with the location of the largest trends in a newly developing NO2 lobe well removed from surface monitoring stations. SO2 VCDs in the oil sands have remained approximately constant. The only other significant increase in the region was seen in NO2 over Bakken gas fields in North Dakota which showed increases of up to5yr. By contrast, other locations in the region show substantial declines in both pollutants, providing strong evidence to the efficacy of environmental pollution control measures implemented by both nations. The OMI-derived trends were found to be consistent with those from the Canadian surface monitoring network, although in the case of SO2, it was necessary to apply a correction in order to remove the residual signal from volcanic eruptions present in the OMI data.

NO2↗
NASA NTRS2016

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon,−40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., N2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10 +/- 0.88 t/ha, and the total biomass for the country, given a total forest area of 688,096 sq km, is 3.65 +/- 0.06 Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152 Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06 Gt) by 19%.

Hybrid 3-Phase sampling↗
NASA NTRS2017

Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S􀂱3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn􀂶s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds􀂲all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan institutions as well as one in South Dakota and one in Alabama, this effort was able to provide next-day georeferenced estimates of cyanobacteria and scum concentrations. Very prompt processing and analysis of the hyperspectral imagery is necessary for the information to be acted upon. For example, a next-day report of an overflight over the Ohio River indicated that a bloom could be present as far downstream as the Cincinnati intake, but the Ohio EPA had not received visual reports of a bloom that far downstream. Water samples were obtained at the Cincinnati water intake, based on the flight data, and detected microcystins in the source water. The flight data helped State and municipal authorities realize the potential extent of that bloom, and triggered response sampling, before the visual river-wide scums started forming. The present document describes the process that was utilized to take raw remote sensing data and create information products; this includes system calibration and validation, efforts to correct atmospheric effects, and algorithms that produce the data products. Furthermore, successful research into improved algorithms for expanding the capability to delineate in water constituents is included. Finally, comparisons that show expected relationships between ground-based measurements and hyperspectral imager version 2 (HSI2) data results are presented, giving confidence in the remote sensing products.

Hyperspectral Imaging↗
NASA NTRS2017

3D Material Response Analysis of PICA Pyrolysis Experiments

The PICA decomposition experiments of Bessire and Minton are investigated using 3D material response analysis. The steady thermoelectric equations have been added to the CHAR code to enable analysis of the Joule-heated experiments and the DAKOTA optimization code is used to define the voltage boundary condition that yields the experimentally observed temperature response. This analysis has identified a potential spatial non-uniformity in the PICA sample temperature driven by the cooled copper electrodes and thermal radiation from the surface of the test article (Figure 1). The non-uniformity leads to a variable heating rate throughout the sample volume that has an effect on the quantitative results of the experiment. Averaging the results of integrating a kinetic reaction mechanism with the heating rates seen across the sample volume yield a shift of peak species production to lower temperatures that is more significant for higher heating rates (Figure 2) when compared to integrating the same mechanism at the reported heating rate. The analysis supporting these conclusions will be presented along with a proposed analysis procedure that permits quantitative use of the existing data. Time permitting, a status on the in-development kinetic decomposition mechanism based on this data will be presented as well.

Oliver, A. Brandon↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) National Campaign II

The Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA aims to enable access to low-altitude airspace for small UAS. This goal is being pursued partly through partnerships that NASA has developed with the UAS stakeholder community, the FAA, other government agencies, and the designated FAA UAS Test Sites. By partnering with the FAA UAS Test Sites, NASA's UTM project has performed a geographically diverse, simultaneous set of UAS operations at locations in six states. The demonstrations used an architecture that was developed by NASA in partnership with the FAA to safely coordinate such operations. These demonstrations-the second or 'Technical Capability Level (TCL 2)' National Campaign of UTM testing-was performed from May 15 through June 9, 2017. Multiple UAS operations occurred during the testing at sites located in Alaska, Nevada, Texas, North Dakota, Virginia, and New York with multiple organizations serving as UAS Service Suppliers and/or UAS Operators per the specifications provided by NASA. By engaging various members of the UAS community in development and operational roles, this campaign provided initial validation of different aspects of the UTM concept including: UAS Service Supplier technologies and procedures; geofencing technologies/conformance monitoring; ground-based surveillance/sense and avoid; airborne sense and avoid; communication, navigation, surveillance; and human factors related to UTM data creation and display. Additionally, measures of performance were defined and calculated from the flight data to establish quantitative bases for comparing flight test activities and to provide potential metrics that might be routinely monitored in future operational UTM systems.

Aweiss, Arwa S.↗
NASA NTRS2018

Mission Status for Earth Science Constellation MOWG Meeting @ Sioux Falls SD EOS Aura

This presentation provides mission operations status for the Earth Observing System (EOS) Aura satellite for the past six-months (December 2017 through May 2018). It only contains information that is of interest to the International Earth Science Constellation (ESC) Mission Operations Working Group (MOWG) member missions. It will be presented at the bi-annual MOWG Meeting at the USGS EROS Data Center in Sioux Falls, South Dakota on Wednesday, June 12, 2018. These meetings have been occurring twice a year since the MOWG was formed in 2003. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager Technical.

Aura satellite↗
NASA NTRS2018

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics.

PuMA↗
NASA NTRS2018

Ground Based Detect and Avoid

This presentation documents the results of an industry survey performed to help inform future research and requirements development regarding ground-based detect and avoid (GBDAA) systems. The author evaluated and summarized the current-state of existing GBDAA systems with a focus on system capabilities, current use cases, and concepts of operations. The survey included vendors such as Echodyne, Seamatica, and Raytheon, government organizations, including the Air Force and FAA, as well as members from the FAA's UAS Test Sites in New York, Alaska, Nevada, Virginia and North Dakota. High-level findings are provided as well as quotes from individuals involved in building and testing GBDAA systems. Conclusions include a lack of coordination between test sites, manufacturers and standards organizations. There is also a wide range of performance capabilities between test sites and systems. More work is required to define minimum operational performance standards for these systems, which are in a relatively immature state at the moment.

ground-based radar↗
NASA NTRS2018

Unmanned Aircraft Systems (UAS) Traffic Management (UTM) National Campaign II

The Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA aims to enable access to low-altitude airspace for small UAS. This goal is being pursued partly through partnerships that NASA has developed with the UAS stakeholder community, the FAA, other government agencies, and the designated FAA UAS Test Sites. By partnering with the FAA UAS Test Sites, NASA's UTM project has performed a geographically diverse, simultaneous set of UAS operations at locations in six states. The demonstrations used an architecture that was developed by NASA in partnership with the FAA to safely coordinate such operations. These demonstrations—the second or "Technical Capability Level (TCL 2)" National Campaign of UTM testing—was performed from May 15 through June 9, 2017. Multiple UAS operations occurred during the testing at sites located in Alaska, Nevada, Texas, North Dakota, Virginia, and New York with multiple organizations serving as UAS Service Suppliers and/or UAS Operators per the specifications provided by NASA. By engaging various members of the UAS community in development and operational roles, this campaign provided initial validation of different aspects of the UTM concept including: UAS Service Supplier technologies and procedures; geofencing technologies/conformance monitoring; ground-based surveillance/sense and avoid; airborne sense and avoid; communication, navigation, surveillance; and human factors related to UTM data creation and display. Additionally, measures of performance were defined and calculated from the flight data to establish quantitative bases for comparing flight test activities and to provide potential metrics that might be routinely monitored in future operational UTM systems.

Aweiss, Arwa↗
NASA NTRS2019

Flight Demonstration of Unmanned Aircraft System (UAS) Traffic Management (UTM) at Technical Capability Level 3

The goal of the Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA is to enable access to low-altitude airspace for small UAS. This goal is being achieved partly through partnerships that NASA has developed with the FAA, other government agencies, the UAS stakeholder community, and the designated FAA UAS Test Sites. This paper reports the technical and operational capabilities demonstrated during the UTM flight demonstration, March 6 through May 30, 2018. The demonstration featured geographically diverse operations, involving FAA UAS Test Sites in Alaska, Nevada, New York, North Dakota, Texas and Virginia. The demonstration leveraged the contributions of 30 partner organizations serving as UAS service suppliers, UAS operators, and/or providers of sensors, surveillance, connectivity, and management roles. Utilizing the UTM architecture developed at NASA, the demonstration explored 11 use cases for small UAS operations to highlight UTM capabilities at what NASA calls “Technical Capability Level (TCL) 3.” TCL 3 is characterized by multiple small UAS safely operating in moderately populated areas and beyond the visual line of sight of their operators. The TCL 3 flights demonstrated the basic feasibility of such operations in the UTM environment, including USS exchanges; communication, navigation and surveillance functions; sense and avoid capabilities; and technologies and procedures to enable them.

Aweiss, Arwa↗
NASA NTRS2019

Determination of Aerothermal Environment and Ablator Material Response Using Inverse Methods

The Mars Science Laboratory (MSL) was protected during entry into the Martian atmosphere by a thermal protection system that used NASA’s Phenolic Impregnated Carbon Ablator (PICA). The heat shield of the probe was instrumented with the Mars Entry Descent and Landing Instrument (MEDLI) suite of sensors. MEDLI Integrated Sensor Plugs (MISP) included thermocouples that measured in-depth temperatures at various locations on the heatshield. The flight data has been used as a benchmark for validating ablation codes within NASA. This work seeks to refine the estimate of the material properties for the MSL heat shield and the aerothermal environment during Mars entry using estimation methods in DAKOTA on the temperature data obtained from MEDLI.

Thornton, John M.↗
NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗
NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗
NASA NTRSDate not supplied

Predictive Modeling of Carbon Ablators Using Micro and Macro-Scale Modeling

Efforts to build a Predictive Material Modeling (PMM) framework from the micro-scale to the macro-scale are presented in this abstract. To reduce the need for extensive testing, accelerate the design cycle process, and reduce uncertainty margins applied to final designs, NASA is developing simulation and modeling tools that enable characterization of material properties and response to high-enthalpy environments. The Porous Microstructure Analysis (PuMA) code has been developed for computing macroscale (volume averaged) properties of porous materials using microscale images from micro-computed tomography (micro-CT). Microscale modeling requires a realistic representation of a material microstructure; these are obtained either synthetically during the design of the material or through X-ray micro-CT. Volume averaged properties are then used to inform macroscale material response models, such as those implemented in the Porous-material Analysis Toolbox based on OpenFOAM (PATO) software, also actively developed by NASA. The computational model in PATO is a generic heat and mass transfer model for porous reactive materials containing several solid phases and a single gas phase. The detailed chemical interactions occurring between the solid phases and the gas phase are modeled at the pore scale assuming local thermal equilibrium. These tools were developed to efficiently interface with other pre-existing codes such as SPARTA (direct simulation Monte Carlo), DPLR (hypersonic CFD), NEQAIR (radiative transport) and DAKOTA (uncertainty quantification and optimization). Detailed flight data (Mars Science Laboratory [MSL] Entry Descent and Landing Instrument [MEDLI]) is critical for validating these computational tools for NASA applications. Examples of modeling ablative material response using these codes will be presented including 3D simulations of the full-scale heatshield of the MSL capsule. The simulations demonstrate the ability of the modern material response code, PATO, to handle the material response of geometrically complex and large domains, through the use of massively parallel computations.

Thermal Protection Systems↗