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NASA NTRS2001

InP MMIC chip set for power sources covering 86-170 GHz

Ngo, Catherine↗

NASA NTRS2021

Improved Representation of the Global Dust Cycle Using Observational Constraints on Dust Properties and Abundance

Even though desert dust is the most abundant aerosol by mass in Earth’s atmosphere, atmospheric models 25 struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused byfundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, 30 extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global 35 basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current 40 model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

aerosols, dust↗

NASA NTRS1985

A Preliminary Comparison of the Information Content of Data from the LANDSAT 4 Thematic Mapper and Multispectral Scanner

The thematic mapper (TM) on LANDSAT 4, acquires 6 spectral channels at 30 meter resolution as well as a thermal IR channel at 120 meter resolution. Because both MSS and TM can acquire data simultaneously, the advantages and disadvantages of the two instruments can be directly compared. The information content of the two instruments is compared for areas in a representative agricultural region. Although the parameter information does not equate in an obvious way to the value or utility of the data, it provides a basis for physical interpretation. By focusing on the redundancy of the digital data, the estimation of information content suggests possibilities for algorithms dealing with subsets of the image data, as well as transformations which reduce the total volume of data to be analyzed. To the degree that a satisfactory description by a reduced data set is possible, there exist implications both for design of future satellite instruments and for analysis procedures.

Price, J. C.↗

NASA NTRS2005

A Thorium-rich Mare Basalt Rock Fragment from the Apollo 12 Regolith: A Sample from a Young Procellarum Flow?

In this abstract, we report on the composition, mineralogy and petrography of a basaltic rock fragment, 12032,366-18, found in the Apollo 12 regolith. Age data, collected as part of an investigation by Barra et al., will be presented in detail in. Here, only the age dating result is summarized. This rock fragment garnered our attention because it is significantly enriched in incompatible elements, e.g., 7 ppm thorium, compared to other known lunar basalts. Its mineral- and trace-element chemistry set it apart from other Apollo 12 basalts and indeed from all Apollo and Luna basalts. What makes it potentially very significant is the possibility that it is a sample of a relatively young, thorium-rich basalt flow similar to those inferred to occur in the Procellarum region, especially northwestern Procellarum, on the basis of Lunar Prospector orbital data. Exploiting the lunar regolith for the diversity of rock types that have been delivered to a landing site by impact processes and correlating them to their likely site of origin using remote sensing will be an important part of future missions to the Moon. One such mission is Moonrise, which would collect regolith samples from the South Pole-Aitken Basin, concentrating thousands of rock fragments of 3-20 mm size from the regolith, and returning the samples to Earth.

Jolliff, B. L.↗

NASA NTRS2005

Neural network post-processing of grayscale optical correlator

In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

grayscale optical correlator↗

NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

NASA NTRSDate not supplied

An Interim Set of TNT Curves for LOX/LNG Explosions

Space launch companies are actively developing, or in some cases have already developed, new vehicles that use large quantities of liquid oxygen (LOX) and liquid natural gas (LNG) propellants. This propellant mixture currently lacks sound/verified explosive safety standards for use in explosive siting and flight safety analysis. In the U.S., multiple government and commercial organizations have conducted limited testing, or are preparing to conduct tests, intended to provide a sound technical basis for LOX/LNG explosive standards applicable to space launch vehicle ground and flight operations. The limited testing and analysis conducted so far indicates the potential to produce extremely energetic explosions due to the miscibility of LOX/LNG (methane), a unique feature relative to previously used propellant mixtures such as hydrogen/oxygen or kerosene/oxygen. MOX is a homogenous mixture of methane and oxygen that is possible because of methane’s 100% miscibility in LOX. Preliminary testing by N2L, Inc. described in this paper shows that it is possible to form MOX with a variety of mixing methods, and that MOX is a sensitive high explosive capable of producing overpressures greater than comparable masses of C-4. The limited amount and quality of large-scale LOX/LNG explosive test data, and the potential formation of high-explosive MOX, create significant unknowns in the determination of hazard areas (cleared of the public) for ground operations (such as a static fire test) and flights of launch vehicles with LOX/LNG propellant. This paper will review the methods used by NASA to develop and validate the LOX/LH2 blast model using large-scale explosive test programs such as Project PYRO, the Hydrogen-Oxygen Vertical Impact (HOVI), and the Large-Scale Hydrogen-Oxygen Explosion (LSHOE) tests. This paper will describe how the same process was used to prepare an interim LOX/LNG blast model that applies to various LV failure scenarios and conservatively accounts for potential MOX formation. This paper also summarizes past and future testing and modeling efforts funded by a consortium of NASA, the US Federal Aviation Administration (FAA), and the US Space Force (USSF). These test programs should be concluded within the next 3 years and are intended to provide empirical data for model verification and validation.

Liquid Oxygen↗

NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or aerial wildfire operations reports to better understand the risks present. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement. These applications can benefit from the use of state-of-the-art natural language processing techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of adaptation of NLP tools to the aviation domain by fine-tuning transformer based models using aviation data sets. In 2018, a novel language model based on neural units (also called transformers) was created and became known as “Bidirectional Encoder Representations from Transformers” or BERT. This architecture combined with large amounts of English training data and innovative semi-supervised training tasks set the standard for what would later emerge as Large Language Models. The performance of these models was further improved by hyperparameter tuning and refinement of the semi-supervised training task and resulted in “Robustly Optimized BERT Pre-training Approach through hyperparameter tuning” or RoBERTa models. These pre-trained Large Language Models proved to be useful for a wide variety of natural language processing tasks such as text classification and question answering through a process called fine-tuning. The transformer architecture with pre-trained weights served as the basis with the last few layers replaced with layers fine-tuned to perform a new task e.g., a layer that provides a label for the entire input text. This process of fine-tuning can also be used to adapt the models to new domains; e.g., BioBERT started with the pre-trained BERT model and was completed by additional fine-tuning and training on biomedical documents. Transformer-based architectures can also be used to create rich representations of text called embeddings which can serve as the input to other machine learning models. This allows simpler algorithms such as logistic regression to use context-rich representations of the text while still remaining quick to train and evaluate. In the world of aviation, there is a growing demand for natural language processing and understanding but the domain presents unique challenges. Due to the technical content (and specialized language) of most aviation documents, fine-tuning pre-trained Large Language Models to specific tasks has not met the benchmark on natural language processing tasks set by simpler models trained from scratch on the data. To address this deficiency, this paper evaluates the improvements from fine-tuning a Large Language Model on a large set of aviation documents using the original semi-supervised training tasks before performing specific natural language tasks. In fine-tuning, a domain-specific dataset is used on the original training task but with the pre-trained Large Language Model instead of starting from a random initialization. This approach allows the model to be adapted to the specific domain language without discarding the information gained from training on general English data. This paper utilized two major dataset types to train and assess the RoBERTa fine-tuning performance. The first are 7,057 Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the semi-supervised fine-tuning. The second type is the 494 document classification labels to be used for evaluation. This down-stream evaluation aims to show the performance of the fine-tuned model, better understand how much data is needed for an effective fine-tuning, and how fine-tuning can be adapted for different applications in-the domain. After semi-supervised training, evaluation begins by encoding the documents for classification using the fine-tuned RoBERTa model. Then a logistic regression classifier is trained to label the document type and compared against our ground truth labels. This currently leads to a 82.8% accuracy on 10-fold cross validation showing improvement over baseline RoBERTa which achieved 81.0%. We plan to measure the improvements on additional tasks and it is expected that these improvements will lead to more robust models that can tackle the natural language processing challenges present in aviation datasets.

ATM↗

NASA NTRS1978

Models and techniques for evaluating the effectiveness of aircraft computing systems

The development of system models that can provide a basis for the formulation and evaluation of aircraft computer system effectiveness, the formulation of quantitative measures of system effectiveness, and the development of analytic and simulation techniques for evaluating the effectiveness of a proposed or existing aircraft computer are described. Specific topics covered include: system models; performability evaluation; capability and functional dependence; computation of trajectory set probabilities; and hierarchical modeling of an air transport mission.

Meyer, J. F.↗

NASA NTRS1988

Telepresence and telerobotics

The capability for a single operator to simultaneously control complex remote multi degree of freedom robotic arms and associated dextrous end effectors is being developed. An optimal solution within the realm of current technology, can be achieved by recognizing that: (1) machines/computer systems are more effective than humans when the task is routine and specified, and (2) humans process complex data sets and deal with the unpredictable better than machines. These observations lead naturally to a philosophy in which the human's role becomes a higher level function associated with planning, teaching, initiating, monitoring, and intervening when the machine gets into trouble, while the machine performs the codifiable tasks with deliberate efficiency. This concept forms the basis for the integration of man and telerobotics, i.e., robotics with the operator in the control loop. The concept of integration of the human in the loop and maximizing the feed-forward and feed-back data flow is referred to as telepresence.

Garin, John↗

NASA NTRS1994

An investigation of fluid flow during induction stroke of a water analog model of an IC engine using an innovative optical velocimetry concept: LIPA

Optical measurements on an axisymmetrical quartz component engine research model were made to evaluate the flow field encountered during induction. The measurement technique is LIPA (Laser Induced Photochemical Anemometry), a non-intrusive velocimetry concept that provides an investigator of fluid flow with a tool to attain planar information about three-dimensional velocity and vorticity vectors in a single measurement step. The goal of this investigation is to further develop this measurement technique and apply it to study the induction stroke of a water analog model of a four-stroke internal combustion engine. The research conducted in the water analog model is a fundamental scientific inquiry into the flow fields that develop in the induction stroke of an engine at idling engine speeds. As this is the first investigation of its kind using LIPA technique, our goal has been to quantify, in a preliminary manner, the flow field features that develop during the intake stroke. In the process a more comprehensive understanding of the flow field features was developed, and tied to the quantification. The study evaluated the flow field of the intake stroke by estimating fields of velocity and vorticity. On the basis of these data, information about fluid dynamics during induction at engine speeds of 10, 20, and 30 RPM (corresponding to 170, 340, and 510 RPM respectively, when air is the flowing medium) for three different valve lifts was obtained. The overall development of the flow field, its energy content (kinetic, fluctuation) for the different settings of the engine parameters, vorticity information, and cyclic variations have been quantified. These have been discussed in terms of mixing performance.

Stier, Bernd↗

NASA NTRS1994

Interacting galaxies resolved by IRAS

We discuss procedures, limitations and results of high resolution processing of interacting galaxies observed by the Infrared Astronomical Satellite (IRAS). Among 56 potentially resolvable interacting groups selected from the IRAS Bright Galaxy Sample, 22 systems have been resolved yielding fluxes for a total of 51 galaxies. In about 2/3 of the resolved pairs, both galaxies were detected in the far-infrared. A set of isolated non-interacting galaxies was chosen from the Bright Galaxy Sample for comparison with the interacting galaxies. For the current sample, which naturally excludes close pairs and ultraluminous merging systems, the primary conclusions are: (1) It is not possible to distinguish individual interacting galaxies from isolated galaxies of similar luminosity on the basis of infrared properties alone. (2) No direct correlation was found between measures of interaction strength and indicators of enhanced star formation within the resolved systems. (3) Comparison of the interacting and isolated samples indicates statistically significant differences between their distributions of far-infrared color ratios, luminosities, and surface brightnesses. Even during the early stages of interaction spanned by these systems, in a statistical sense, tidal perturbations substantially boost far-infrared indicators of star formation compared to non-interacting systems. We also briefly discuss future prospects for pushing the IRAS data to its limits for additional interacting systems.

Mazzarella, Joseph M.↗

NASA NTRS2001

InP MMIC Chip Set for Power Sources Covering 80-170 GHz

We will present a Monolithic Millimeter-wave Integrated Circuit (MMIC) chip set which provides high output-power sources for driving diode frequency multipliers into the terahertz range. The chip set was fabricated at HRL Laboratories using a 0.1-micrometer gate-length InAlAs/InGaAs/InP high electron mobility transistor (HEMT) process, and features transistors with an f(sub max) above 600 GHz. The HRL InP HEMT process has already demonstrated amplifiers in the 60-200 GHz range. In this paper, these high frequency HEMTs form the basis for power sources up to 170 GHz. A number of state-of-the-art InP HEMT MMICs will be presented. These include voltage-controlled and fixed-tuned oscillators, power amplifiers, and an active doubler. We will first discuss an 80 GHz voltage-controlled oscillator with 5 GHz of tunability and at least 17 mW of output power, as well as a 120 GHz oscillator providing 7 mW of output power. In addition, we will present results of a power amplifier which covers the full WRIO waveguide band (75-110 GHz), and provides 40-50 mW of output power. Furthermore, we will present an active doubler at 164 GHz providing 8% bandwidth, 3 mW of output power, and an unprecedented 2 dB of conversion loss for an InP HEMT MMIC at this frequency. Finally, we will demonstrate a power amplifier to cover 140-170 GHz with 15-25 mW of output power and 8 dB gain. These components can form a power source in the 155-165 GHz range by cascading the 80 GHz oscillator, W-band power amplifier, 164 GHz active doubler and final 140-170 GHz power amplifier for a stable, compact local oscillator subsystem, which could be used for atmospheric science or astrophysics radiometers.

Ngo, Catherine↗

NASA NTRS2004

Potential of Radar Imaging and Sounding Methods in Mapping Heavily Eroded Impact Craters: Mapping Some Structural Elements of the Hico Crater, TX

Shuttle Radar Topography Mission (SRTM) and Ground Penetrating Radar (GPR) data collected over an area north of the town of Hico, central Texas, have been used to map disturbances in the surface topography and subsurface stratigraphy. The Radar topography results confirm the presence of multiple rings suggestive of an impact crater. Correlation between the orbital SRTM and on-the-ground GPR field data are affected by different biases related to variations in terrain and vegetation cover. Nevertheless, the correspondence of the two data sets supports the earlier conclusions that a complex, multiple ring impact structure is reflected in the topography of this area. The SRTM data reveal three previously unrecognized rings; with the outermost ring some 5-6 km in diameter. The crater appears to be significantly larger than the size (2.5 km diameter) previously inferred on the basis of aerial images. In addition, the GPR data suggest the presence of subsurface faulting that spatially coincides with the two inner rings of the crater. This suggests that the topographic rings are structurally controlled by faulting.

Heggy, E.↗

NASA NTRS2006

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Markus, Thorsten↗

NASA NTRS2011

Establishing Approaches to Modeling the Ares I-X and Ares I Roll Control System with Free-stream Interaction

Approaches were established for modeling the roll control system and analyzing the jet interactions of the activated roll control system on Ares-type configurations using the USM3D Navier-Stokes solver. Components of the modeling approach for the roll control system include a choice of turbulence models, basis for computing a dynamic equivalence of the real gas rocket exhaust flow in terms of an ideal gas, and techniques to evaluate roll control system performance for wind tunnel and flight conditions. A simplified Ares I-X configuration was used during the development phase of the roll control system modeling approach. A limited set of Navier-Stokes solutions was obtained for the purposes of this investigation and highlights of the results are included in this paper. The USM3D solutions were compared to equivalent solutions at select flow conditions from a real gas Navier- Stokes solver (Loci-CHEM) and a structured overset grid Navier-Stokes solver (OVERFLOW).

Pao, S. Paul↗

NASA NTRS2013

Semi-Supervised Eigenbasis Novelty Detection

Recent discoveries in high-time-resolution radio astronomy data have focused attention on a new class of events. Fast transients are rare pulses of radio frequency energy lasting from microseconds to seconds that might be produced by a variety of exotic astrophysical phenomena. For example, X-ray bursts, neutron stars, and active galactic nuclei are all possible sources of short-duration, transient radio signals. It is difficult to anticipate where such signals might appear, and they are most commonly discovered through analysis of high-time- resolution data that had been collected for other purposes. Transients are often faint and difficult to detect, so improved detection algorithms can directly benefit the science yield of all such commensal monitoring. A new detection algorithm learns a low-dimensional linear manifold for describing the normal data. High reconstruction error indicates a novel signal that does not match the patterns of normal data. One unsupervised portion of the manifold model adapts its representation in response to recent data. A second supervised portion of the model is made of a basis trained in advance using labeled examples of RFI; this prevents false positives due to these events. For a linear model, an orthonormalization operation is used to combine these bases prior to the anomaly detection decision. Another novel aspect of the approach lies in combining basis vectors learned in an unsupervised, online fashion from the data stream with supervised basis vectors learned in advance from known examples of false alarms. Adaptive, data-driven detection is achieved that is also informed by existing domain knowledge about signals that may be statistically anomalous, but are not interesting and should therefore be ignored. The method was evaluated using data from the Parkes Multibeam Survey. This data set was originally collected to search for pulsars, which are astronomical sources that emit radio pulses at regular periods. However, several non-pulsar anomalies have recently been discovered in this dataset, making it a compelling test case. By explicitly filtering known false alarm patterns, the approach yields significantly better performance than current transient detection methods.

Wagstaff, Kiri L.↗

NASA NTRSDate not supplied

An Interim Set of TNT Curves for LOX/LNG Explosions

Space launch companies are actively developing, or in some cases have already developed, new vehicles that use large quantities of liquid oxygen (LOX) and liquid natural gas (LNG) propellants. This propellant mixture currently lacks sound/verified LOX/LNG explosive safety standards for use in explosive siting and flight safety analysis. In the U.S., multiple government and commercial organizations have conducted limited testing, or are preparing to conduct tests, intended to provide a sound technical basis for explosive standards applicable to space launch vehicle ground and flight operations. The limited testing and analysis conducted so far indicates the potential to produce extremely energetic explosions due to the miscibility of LOX/LNG (methane), a unique feature relative to previously used propellant mixtures such as hydrogen/oxygen or kerosene/oxygen. MOX is a homogenous mixture of methane and oxygen that is possible because of methane’s 100% miscibility in LOX. Preliminary testing by N2L, Inc. described in this paper shows that it is possible to form MOX with a variety of mixing methods, and that MOX is a sensitive high explosive capable of producing overpressures greater than comparable masses of C-4. The limited amount and quality of large-scale LOX/LNG explosive test data, and the potential formation of high-explosive MOX, create significant unknowns in the determination of hazard areas (cleared of the public) for ground operations (such as a static fire test) and flights of launch vehicles with LOX/LNG propellant. This paper will review the methods used by NASA to develop and validate the LOX/LH2 blast model using large-scale explosive test programs such as Project PYRO, the Hydrogen-Oxygen Vertical Impact (HOVI), and the Large-Scale Hydrogen-Oxygen Explosion (LSHOE) tests. This paper will describe how the same process was used to prepare an interim LOX/LNG blast model that applies to various LV failure scenarios and conservatively accounts for potential MOX formation. This paper also summarizes past and future testing and modeling efforts funded by a consortium of NASA, the US Federal Aviation Administration (FAA), and the US Space Force (USSF). These test programs should be concluded within the next 3 years and are intended to provide empirical data for model verification and validation.

Liquid Oxygen↗