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At least 379 records · Page 21

Beyond Coordination: Joint Planning and Program Execution. The IHPRPT Materials Working Group

"Partnership is more than just coordination," stated then-Commander of the Air Force Research Laboratory (AFRL), Major General Dick Paul (USAF-Ret), at this year's National Space and Missile Materials Symposium. His comment referred to the example of the joint planning and program execution provided by the Integrated High Payoff Rocket Propulsion Technology (IHPRPT) Materials Working Group (IMWG). Most people agree that fiscal pressures imposed by shrinking budgets have made it extremely difficult to build upon our existing technical capabilities. In times of sufficient budgets, building advanced systems poses no major difficulties. However, with today's budgets, realizing enhanced capabilities and developing advanced systems often comes at an unaffordable cost. Overcoming this problem represents both a challenge and an opportunity to develop new business practices that allow us to develop advanced technologies within the restrictions imposed by current funding levels. Coordination of technology developments between different government agencies and organizations is a valuable tool for technology transfer. However, rarely do the newly developed technologies have direct applicability to other ongoing programs. Technology requirements are typically determined up-front during the program planning stage so that schedule risk can be minimized. The problem with this process is that the costs associated with the technology development are often borne by a single program. Additionally, the potential exists for duplication of technical effort. Changing this paradigm is a difficult process but one that can be extremely worthwhile should the right opportunity arise. The IMWG is one such example where NASA, the DoD, and industry have developed joint requirements that are intended to satisfy multiple program needs. More than mere coordination, the organizations comprising the group come together as partners, sharing information and resources, proceeding from a joint roadmap.

Stropki, Michael A.↗

Solar Heating System installed at Belz Investment Company, Memphis, Tennessee

A hot air solar system which utilizes flat plate air collectors is discussed. Collector areas for each of four buildings cover 780 sq ft, with storage capacity of 390 cu ft per building. The air system has a special air handling unit to move air through the collectors and into and out of the rock storage, with connection to the air duct distribution system. The heat of the motor is added to the heat delivered to the system. The solar system also includes four motorized special low leakage dampers and two gravity fabric dampers. The system is automatically controlled by a solid state controller with three thermistors: one located in the collectors, one in the rock box to plenum, one in the return air duct from the heated space. A three stage heating thermostat, located in the conditioned space, controls the operation.

Source record↗

Acquisition of background and technical information and class trip planning

Instructors who are very familiar with a study area, as well as those who are not, find the field trip information acquisition and planning process speeded and made more effective by organizing it in stages. The stage follow a deductive progression: from the associated context region, to the study area, to the specific sample window sites, and from generalized background information on the study region to specific technical data on the environmental and human use systems to be interpreted at each site. On the class trip and in the follow up laboratory, the learning/interpretive process are at first deductive in applying previously learned information and skills to analysis of the study site, then inductive in reading and interpreting the landscape, imagery, and maps of the site, correlating them with information of other samples sites and building valid generalizations about the larger study area, its context region, and other (similar and/or contrasting) regions.

Mackinnon, R. M.↗

Perception for rugged terrain

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Kweon, In SO↗

NASA Ares I Launch Vehicle Roll and Reaction Control Systems Lessons Learned

On April 15, 2010 President Barak Obama made the official announcement that the Constellation Program, which included the Ares I launch vehicle, would be canceled. NASA s Ares I launch vehicle was being designed to launch the Orion Crew Exploration Vehicle, returning humans to the moon, Mars, and beyond. It consisted of a First Stage (FS) five segment solid rocket booster and a liquid J-2X Upper Stage (US) engine. Roll control for the FS was planned to be handled by a dedicated Roll Control System (RoCS), located on the connecting interstage. Induced yaw or pitch moments experienced during FS ascent would have been handled by vectoring of the booster nozzle. After FS booster separation, the US Reaction Control System (ReCS) would have provided the US Element with three degrees of freedom control as needed. The lessons learned documented in this paper will be focused on the technical designs and producibility of both systems along with the partnership between NASA and Boeing, who was on contract to build the Ares I US Element, which included the FS RoCS and US ReCS. In regards to partnership, focus will be placed on integration along with technical work accomplished by Boeing with special emphasis on each task order. In summary, this paper attempts to capture key lessons learned that should be helpful in the development of future launch vehicle RCS designs.

Butt, Adam↗

Best Practices from the Design and Development of the Ares I Launch Vehicle Roll and Reaction Control Systems

On April 15, 2010 President Barak Obama made the official announcement that the Constellation Program, which included the Ares I launch vehicle, would be canceled. NASA s Ares I launch vehicle was being designed to launch the Orion Crew Exploration Vehicle, returning humans to the moon, Mars, and beyond. It consisted of a First Stage (FS) five segment solid rocket booster and a liquid J-2X Upper Stage (US) engine. Roll control for the FS was planned to be handled by a dedicated Roll Control System (RoCS), located on the connecting interstage. Induced yaw or pitch moments experienced during FS ascent would have been handled by vectoring of the booster nozzle. After FS booster separation, the US Reaction Control System (ReCS) would have provided the US Element with three degrees of freedom control as needed. The best practices documented in this paper will be focused on the technical designs and producibility of both systems along with the partnership between NASA and Boeing, who was on contract to build the Ares I US Element, which included the FS RoCS and US ReCS. In regards to partnership, focus will be placed on integration along with technical work accomplished by Boeing. This will include detailed emphasis on task orders developed between NASA and Boeing that were used to direct specific work that needed to be accomplished. In summary, this paper attempts to capture key best practices that should be helpful in the development of future launch vehicle and spacecraft RCS designs.

Butt, Adam↗

Spatiotemporal Analysis of High-Resolution Pressure-Sensitive Paint Measurements on a Launch Vehicle Wind Tunnel Model

An accurate understanding of unsteady aerodynamic loads is critical for launch vehicle structural design and for development of the vibro-acoustic environment for payload components. Analysts commonly use point-wise surface pressure measurements from wind tunnel testing to build statistical models of the in-flight turbulent boundary layer flow structures, often extrapolating over large swaths of the surface due to measurement sparsity. We present novel results from a transonic wind tunnel test using fast-response pressure-sensitive paint (PSP) and show how it can be used to visualize and quantify localized turbulent boundary layer wall pressure statistics with unprecedented spatial resolution. The wind tunnel model is a scaled model of the Space Launch System (SLS) rocket Block 1B Crew configuration and analysis focused on the compression corner between the Service Module fairing and the Universal Stage Adapter.

Corcos Model↗

Ellicott City Disasters II - Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

Ellicott City Disasters III: Building a Real-Time Statistical Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Machine Learning Classification

During and after flooding events, mapping the extent of floodwaters aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. Complimentary optical and SAR images from domestic and foreign entities are brought together through activations of the International Charter: Space and Major Disasters to support response efforts, from true-color, near-infrared, and thermal remote sensing data obtained by NASA, NOAA, and international satellites to the collection of high-resolution true color aerial photography by NOAA and the National Geodetic Survey. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. In this study, true-color NOAA aerial and commercial satellite imagery are used in conjunction with four UAVSAR data swaths centered on the Lumberton and Cape Fear River basins in southeastern North Carolina to develop a Random Forest classification model focused on mapping open water and floodwater otherwise obscured by vegetation or lingering cloud cover. Ancillary building footprint, transportation route, and population data will also be incorporated into the classification scheme to estimate the societal impacts of flooding based on the proximity of features to detected inundation. Preliminary results from the Hurricane Florence case study will be discussed in addition to the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander M Melancon↗

HIAD on ULA (HULA) Orbital Reentry Flight Experiment Concept

This paper describes a proposed orbital velocity reentry flight test of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). The flight test builds upon ground development activities that continue to advance the materials, design, and manufacturing techniques for the inflatable structure and flexible thermal protection system (F-TPS) that comprise the inflatable heat shield. While certain aspects of material and system performance can be assessed using a variety of ground testing capabilities, only orbital velocity energy on a trajectory through the gradient density of the atmosphere can impart the combined aerodynamic and aeroheating design environments in real time. To achieve this at limited cost, the HIAD would be delivered to a spin-stabilized entry trajectory as a secondary payload on the Centaur stage of a United Launch Alliance (ULA) Atlas V launch vehicle. Initial trajectory studies indicate that the combination of launch vehicle capability and achievable reentry vehicle ballistic numbers make this a strategic opportunity for technology development. This 4 to 6 meter diameter scale aeroshell flight, referred to as HIAD on ULA (HULA), would also contribute to ULA asset recovery development. ULA has proposed that a HIAD be utilized as part of the Sensible, Modular, Autonomous Return Technology (SMART) initiative to enable recovery of the Vulcan launch vehicle booster main engines [1], including a Mid-Air Recovery (MAR) to gently return these assets for reuse. Whereas HULA will attain valuable aerothermal and structural response data toward advancing HIAD technology, it may also provide a largest-to-date scaled flight test of the MAR operation, which in turn would allow the examination of a nearly pristine post-entry aeroshell. By utilizing infrared camera imaging, HULA will also attain aft-side thermal response data, enhancing understanding of the aft side aerothermal environment, an area of high uncertainty. The aeroshell inflation will utilize a heritage design compressed gas system to minimize development costs. The data will be captured to both an onboard recorder and a recorder that is jettisoned and recovered separately from the reentry vehicle to mitigate risk. This paper provides an overview, including the architecture and flight concept of operations, for the proposed HULA flight experiment.

Dinonno, J. M.↗

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗

New Horizons in Cosmology with Spectral Distortions of the Cosmic Microwave Background

Following the pioneering observations with COBE in the early 1990s, studies of the cosmic mi- crowave background (CMB) have primarily focused on temperature and polarization anisotropies. CMB spectral distortions – tiny departures of the CMB energy spectrum from that of a perfect blackbody – provide a second, independent probe of fundamental physics, with a reach deep into the primordial Universe. The theoretical foundation of spectral distortions has seen major advances in recent years, highlighting the immense potential of this emerging field. Spectral distortions probe a fundamental property of the Universe – its thermal history – thereby providing additional insight into processes within the cosmological standard model(I) (CSM) as well as new physics beyond. Spectral distortions are an important tool for understanding inflation and the nature of dark matter. They shed new light on the physics of recombination and reionization, both prominent stages in the evolution of our Universe, and furnish critical information on baryonic feedback processes, in addition to probing primordial correlation functions at scales inaccessible to other tracers. In principle the range of signals is vast: many orders of magnitude of discovery space can be explored by detailed observations of the CMB energy spectrum. Several CSM signals are predicted and provide clear experimental targets that are observable with present-day technology. Confirmation of these signals would extend the reach of the CSM by orders of magnitude in physical scale as the Universe evolves from the initial stages to its present form. Their absence would pose a huge theoretical challenge, immediately pointing to new physics. Here, we advocate for a dedicated effort to measure CMB spectral distortions at the largest angular scales (greater than approximately 1°) within the ESA Voyage 2050 Program. We argue that an L-class mission with a pathfinder would allow a precise measurement of all the expected CSM distortions. With an M-class mission, the primordial distortions (created at z >~ 10(exp 3)) would still be detected at modest significance, while the late-time distortions will continue to be measured to high accuracy. Building on the heritage of COBE/FIRAS, a spectrometer that consists of multiple, cooled (approximately equal to 0.1 K), absolutely-calibrated Fourier Transform Spectrometers (FTS) with wide frequency coverage (ν approximately equal to 10 GHz to a few x THz) and all-sky spectral sensitivity at the level of 0.1 0.5 Jy/sr would be the starting point for the M-class option. A scaled and further optimized version of this concept is being envisioned as the L-class option. Such measurements can only be done from space and would deliver hundreds of absolutely-calibrated maps of the Universe at large scales, opening numerous science opportunities for cosmology and astrophysics. This will provide independent probes of inflation, dark matter and particle physics, recombination and the energy output of our Universe from at late times, turning the long-standing spectral distortion limits of COBE/FIRAS into clear detections.

Chluba, J.↗

Investigation of Boundary Layer Development in Multi-Stage Low Pressure

A review of recent literature has been made in the areas of unsteady measurement in turbomachinery and LP turbine design. This has included a detailed review of methods for extracting quantitative shear stress data from surface mounted hot-film arrays. Research goals were identified on the basis of the literature survey and following interaction with the GE and NASA contracts. Progress has also been made in the detailed planning of the research program. An array of hot-film sensors has been mounted at mid-span on a second stage nozzle blade ready for installation in the current turbine buildup. A new technique of applying the hot-film array using double sided adhesive is being tested. The temperature in the vicinity of the hot-films will be monitored using a thermocouple attached to the blade pressure surface. This will increase the accuracy of the data reduction process compared with the methods applied by Halstead et at. (1995) and others. Data obtained from this first set of sensors, along with data from the hot-wire investigation will help to determine the best locations for surface hot-film instrumentation for subsequent builds of the turbine. Other LSRT instrumentation issues which have been addressed include calibration of the torque measurement system and procurement of custom design hot-wire sensors required to compensate for the slope flow path. Preliminary attempts at modeling the boundary layer transition process have been completed. A steady, coupled viscous-inviscid flow solver (the MISES code of Drela and Youngren) was used to calculate the steady-flow boundary layer transition location.

Source record↗

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗

Additive Manufacturing of Low Cost Upper Stage Propulsion Components

NASA is currently developing Additive Manufacturing (AM) technologies and design tools aimed at reducing the costs and manufacturing time of regeneratively cooled rocket engine components. These Low Cost Upper Stage Propulsion (LCUSP) tasks are funded through NASA's Game Changing Development Program in the Space Technology Mission Directorate. The LCUSP project will develop a copper alloy additive manufacturing design process and develop and optimize the Electron Beam Freeform Fabrication (EBF3) manufacturing process to direct deposit a nickel alloy structural jacket and manifolds onto an SLM manufactured GRCop chamber and Ni-alloy nozzle. In order to develop these processes, the project will characterize both the microstructural and mechanical properties of the SLMproduced GRCop-84, and will explore and document novel design techniques specific to AM combustion devices components. These manufacturing technologies will be used to build a 25K-class regenerative chamber and nozzle (to be used with tested DMLS injectors) that will be tested individually and as a system in hot fire tests to demonstrate the applicability of the technologies. These tasks are expected to bring costs and manufacturing time down as spacecraft propulsion systems typically comprise more than 70% of the total vehicle cost and account for a significant portion of the development schedule. Additionally, high pressure/high temperature combustion chambers and nozzles must be regeneratively cooled to survive their operating environment, causing their design to be time consuming and costly to build. LCUSP presents an opportunity to develop and demonstrate a process that can infuse these technologies into industry, build competition, and drive down costs of future engines.

Protz, Christopher↗

Additively Manufactured Low Cost Upper Stage Combustion Chamber

Over the past two years NASA's Low Cost Upper Stage Propulsion (LCUSP) project has developed Additive Manufacturing (AM) technologies and design tools aimed at reducing the costs and manufacturing time of regeneratively cooled rocket engine components. High pressure/high temperature combustion chambers and nozzles must be regeneratively cooled to survive their operating environment, causing their design fabrication to be costly and time consuming due to the number of individual steps and different processes required. Under LCUSP, AM technologies in Sintered Laser Melting (SLM) GRCop-84 and Electron Beam Freeform Fabrication (EBF3) Inconel 625 have been significantly advanced, allowing the team to successfully fabricate a 25k-class regenerative chamber. Estimates of the costs and schedule of future builds indicate cost reductions and significant schedule reductions will be enabled by this technology. Characterization of the microstructural and mechanical properties of the SLM-produced GRCop-84, EBF3 Inconel 625 and the interface layer between the two has been performed and indicates the properties will meet the design requirements. The LCUSP chamber is to be tested with a previously demonstrated SLM injector in order to advance the Technology Readiness Level (TRL) and demonstrate the capability of the application of these processes. NASA is advancing these technologies to reduce cost and schedule for future engine applications and commercial needs.

Protz, Christopher↗