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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Lessons Learned From the Construction of a Portable Cleanroom for NASA OSIRIS-REx Mission Deintegration

NASA Johnson Space Center (JSC) Infrastructure and Astromaterials Acquisition & Curation Office completed construction and commissioning of the OSIRIS-REx (OREx) Deintegration portable cleanroom at the Utah Test and Training Range (UTTR). The new portable cleanroom was designed to receive the OREx sample return capsule from the landing point on the range to an ISO7 environment. Scientists used the portable clean-room to deintegrate the sample canister from the sample return capsule. Once separated, the sample canister was put in a container under nitrogen purge for transportation to B31 at the Johnson Space Center for astromaterial sample extraction, preliminary analysis, and long-term curation. The portable cleanroom was built by a subcontractor at their facility and then deconstructed to be transported to the remote location at UTTR. Since construction was completed in a remote location all tools and materials had to be transported from contractor site in Dallas, TX. The cleanroom was constructed within an existing facility, which provided conditioned air, electric power, and protection from the elements. Careful coordination was required between the host facility, cleanroom contractor, mission scientists, and JSC facilities and curation personnel. An existing anteroom at JSC was transported to UTTR and added to the portable cleanroom after there was concern about contamination without one for personnel entry/exit. The scientific study of organics is critical for the mission, so a stringent contamination control plan was implemented for low organics. Given these mission requirements the cleanroom construction materials were carefully selected to not hinder the scientific search for amino acids and the study of organics in the samples. The same cleanroom contractor that built the long-term astromaterial curation cleanroom back at JSC Houston, TX was selected to build the portable cleanroom and instructed to use the same materials. The cleanroom had double doors to open and allow the sample return capsule to fit into the cleanroom on its stand and be transferred to a clean stand already in the cleanroom. The portable cleanroom successfully completed its mission and the sample canister was safely deintegrated and transported to JSC under nitrogen purge.

astromaterials curation↗
DOE OSTI2022

Kingdom-Wide Analysis of Fungal Protein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2015

Modeling and Analysis of Realistic Fire Scenarios in Spacecraft

An accidental fire inside a spacecraft is an unlikely, but very real emergency situation that can easily have dire consequences. While much has been learned over the past 25+ years of dedicated research on flame behavior in microgravity, a quantitative understanding of the initiation, spread, detection and extinguishment of a realistic fire aboard a spacecraft is lacking. Virtually all combustion experiments in microgravity have been small-scale, by necessity (hardware limitations in ground-based facilities and safety concerns in space-based facilities). Large-scale, realistic fire experiments are unlikely for the foreseeable future (unlike in terrestrial situations). Therefore, NASA will have to rely on scale modeling, extrapolation of small-scale experiments and detailed numerical modeling to provide the data necessary for vehicle and safety system design. This paper presents the results of parallel efforts to better model the initiation, spread, detection and extinguishment of fires aboard spacecraft. The first is a detailed numerical model using the freely available Fire Dynamics Simulator (FDS). FDS is a CFD code that numerically solves a large eddy simulation form of the Navier-Stokes equations. FDS provides a detailed treatment of the smoke and energy transport from a fire. The simulations provide a wealth of information, but are computationally intensive and not suitable for parametric studies where the detailed treatment of the mass and energy transport are unnecessary. The second path extends a model previously documented at ICES meetings that attempted to predict maximum survivable fires aboard space-craft. This one-dimensional model implies the heat and mass transfer as well as toxic species production from a fire. These simplifications result in a code that is faster and more suitable for parametric studies (having already been used to help in the hatch design of the Multi-Purpose Crew Vehicle, MPCV).

life support↗
NASA NTRS2008

Automated and Adaptive Mission Planning for Orbital Express

The Orbital Express space mission was a Defense Advanced Research Projects Agency (DARPA) lead demonstration of on-orbit satellite servicing scenarios, autonomous rendezvous, fluid transfers of hydrazine propellant, and robotic arm transfers of Orbital Replacement Unit (ORU) components. Boeing's Autonomous Space Transport Robotic Operations (ASTRO) vehicle provided the servicing to the Ball Aerospace's Next Generation Serviceable Satellite (NextSat) client. For communication opportunities, operations used the high-bandwidth ground-based Air Force Satellite Control Network (AFSCN) along with the relatively low-bandwidth GEO-Synchronous space-borne Tracking and Data Relay Satellite System (TDRSS) network. Mission operations were conducted out of the RDT&E Support Complex (RSC) at the Kirtland Air Force Base in New Mexico. All mission objectives were met successfully: The first of several autonomous rendezvous was demonstrated on May 5, 2007; autonomous free-flyer capture was demonstrated on June 22, 2007; the fluid and ORU transfers throughout the mission were successful. Planning operations for the mission were conducted by a team of personnel including Flight Directors, who were responsible for verifying the steps and contacts within the procedures, the Rendezvous Planners who would compute the locations and visibilities of the spacecraft, the Scenario Resource Planners (SRPs), who were concerned with assignment of communications windows, monitoring of resources, and sending commands to the ASTRO spacecraft, and the Mission planners who would interface with the real-time operations environment, process planning products and coordinate activities with the SRP. The SRP position was staffed by JPL personnel who used the Automated Scheduling and Planning ENvironment (ASPEN) to model and enforce mission and satellite constraints. The lifecycle of a plan began three weeks outside its execution on-board. During the planning timeframe, many aspects could change the plan, causing the need for re-planning. These variable factors, ranging from shifting contact times to ground-station closures and required maintenance times, are discussed along with the flexibility of the ASPEN tool to accommodate changes to procedures and the daily or long-range plan, which contributed to the success of the mission. This paper will present an introduction to ASPEN, a more in-depth discussion on its use on the Orbital Express mission, and other relative work. A description of ground operations after the SRP deliveries were made is included, and we briefly discuss lessons learned from the planning perspective and future work.

scheduling↗
DOE OSTI2023

In-pixel AI for lossy data compression at source for X-ray detectors

Integrating neural networks for data compression directly in the Read-Out Integrated Circuits (ROICs), i.e. the pixelated front-end, would result in a significant reduction in off-chip data transfer, overcoming the I/O bottleneck. Our ROIC test chip (AI-In-Pixel-65) is designed in a 65 nm Low Power CMOS process for the readout of pixelated X-ray detectors. Each pixel consists of an analog front-end for signal processing and a 10b analog-to-digital converter operating at 100KSPS. Here, we compare two non-reconfigurable techniques, Principal Component Analysis (PCA) and an AutoEncoder (AE) as lossy data compression engines implemented within the pixelated area. The PCA algorithm achieves 50$×$ compression, adds one clock cycle latency, and results in a 21% increase in the pixel area. The AE achieves 70$×$ compression, adds 30 clock cycle latency, and results in a similar area increase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2006

Ground Testing A 20-Meter Inflation Deployed Solar Sail

Solar sails have been proposed for a variety of future space exploration missions and provide a cost effective source of propellantless propulsion. Solar sails span very large areas to capture and reflect photons from the Sun and are propelled through space by the transfer of momentum from the photons to the solar sail. The thrust of a solar sail, though small, is continuous and acts for the life of the mission without the need for propellant. Recent advances in materials and ultra-low mass gossamer structures have enabled a host of useful space exploration missions utilizing solar sail propulsion. The team of L Garde, NASA Jet Propulsion Laboratory (JPL), Ball Aerospace, and NASA Langley Research Center, under the direction of the NASA In-Space Propulsion Office (ISP), has been developing a scalable solar sail configuration to address NASA s future space propulsion needs. The 100-m baseline solar sail concept was optimized around the one astronomical unit (AU) Geostorm mission, and features a Mylar sail membrane with a striped-net sail suspension architecture with inflation-deployed sail support beams consisting of inflatable sub-Tg (glass transition temperature) rigidizable semi-monocoque booms and a spreader system. The solar sail has vanes integrated onto the tips of the support beams to provide full 3-axis control of the solar sail. This same structural concept can be scaled to meet the requirements of a number of other NASA missions. Static and dynamic testing of a 20m scaled version of this solar sail concept have been completed in the Space Power Facility (SPF) at the NASA Glenn Plum Brook facility under vacuum and thermal conditions simulating the operation of a solar sail in space. This paper details the lessons learned from these and other similar ground based tests of gossamer structures during the three year solar sail project.

Mann, Troy↗
DOE OSTI2023

Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. In conclusion, our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Using Digital and Web-Based Platforms to Enhance Nuclear Power Plant Knowledge Transfer - 20203

As the workforce ages, the loss of experienced personnel can result in a loss of important knowledge. Updating Electric Power Research Institute (EPRI) research and guidance with the latest technology developments and operating experience is an important method to transfer knowledge between the retiring and incoming workforce. Studies suggest that the incoming workforce is accustomed to using digital and/or internet-based platforms to find information and may have a higher comfort with these types of platforms than they have with static, written reports. Additionally, the ease and speed of updating and delivering content through digital formats may offer an effective method for knowledge transfer and combining information from multiple reports into a single access point. EPRI has recently produced an online Decommissioning Hub available to members and is working on replicating the effort in the area of radioactive waste management called the Radwaste Web References. EPRI has extensive guidance in both disciplines. The Decommissioning Hub uses a wiki format to provide a platform that allows for both the updating of that guidance resulting from new research and new operating experiences, and combining related topical information from multiple reports. It also allows users to access the information based on key words and topical searches, and can be a tool for users to input experience to share with others. The Decommissioning Hub is accessed via a web-based portal and includes topical pages; experience summaries; a question and answer capability; and a smart search function of all EPRI decommissioning reports. Use of a wiki format allows users to input new experiences or modify existing experience summaries to add additional detail. EPRI moderates all content. The experience data base has been initially populated with information available in published EPRI reports and unpublished information currently available within EPRI. Moving forward, population of the database will continue with information available within the open literature, new information developed from current decommissioning projects, and user inputs. The web site became active in late 2017, and a major update will be issued in early 2020. Larger scale updates are planned biannually, and smaller-scale updates will occur continuously. Capturing and applying lessons learned from industry experiences is a hallmark of the global nuclear industry. This is even more important in the decommissioning technology area since very few plant staff have relevant experience and thus there is a steep learning curve. Moreover, decommissioning involves a number of complex, non-routine and specialized tasks. The web-accessible and searchable experience database provides an easy-to-use resource for capturing and disseminating practical experiences from completed and ongoing decommissioning projects. The EPRI Radwaste Web References will build upon the philosophy and objectives of the Radwaste Desk References that were published in the 1990's. The purpose of the original Radwaste Desk References was to provide nuclear power plant professionals with a how-to manual for managing radioactive waste. The Radwaste Web References will adopt this original purpose and will be a wiki type web site that provide fundamental practical and theoretical information, operating experience (OE), and information about advanced technologies and methods. As much as practicable, features that allow for interaction between users to share OE, best practices, and benchmarking will be added. Where they exist and are appropriate, the various EPRI Guidelines documents on radwaste topics will be updated and incorporated into the Radwaste Web References. The first Radwaste Web Reference will be on Low Level Waste Characterization and will build upon the EPRI Low Level Waste Characterization Guidelines (EPRI Report TR-107201, 1996) and will be available in 2020. The next Radwaste Web Reference will be on the topic of liquid radioactive waste processing and management, tentatively set for unveiling in 2021. This paper summarizes the EPRI's previous experiences with web-based platforms and future plans in this area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2008

Investigation of Condensing Ice Heat Exchangers for MTSA Technology Development

Metabolic heat regenerated Temperature Swing Adsorption (MTSA) technology is being developed for thermal, carbon dioxide (CO2) and humidity control for a Portable Life Support Subsystem (PLSS). Metabolically-produced CO2 present in the ventilation gas of a PLSS is collected using a CO2selective adsorbent via temperature swing adsorption. The temperature swing is initiated through cooling to well below metabolic temperatures. Cooling is achieved with a sublimation heat exchanger using water or liquid carbon dioxide (LCO2) expanded below sublimation temperature when exposed to low pressure or vacuum. Subsequent super heated vapor, as well as additional coolant, is used to further cool the astronaut. The temperature swing on the adsorbent is then completed by warming the adsorbent with a separate condensing ice heat exchanger (CIHX) using metabolic heat from moist ventilation gas. The condensed humidity in the ventilation gas is recycled at the habitat. The water condensation from the ventilation gas is a significant heat transfer mechanism for the warming of the adsorbent bed because it represents as much as half of the energy potential in the moist ventilation gas. Designing a heat exchanger to efficiently transfer this energy to the adsorbent bed and allow the collection of the water is a challenge since the CIHX will operate in a temperature range from 210K to 280K. The ventilation gas moisture will first freeze and then thaw, sometimes existing in three phases simultaneously. A NASA Small Business Innovative Research (SBIR) Phase 1 contract was performed to investigate condensing and icing as applied to MTSA to enable higher fidelity modeling and assess the impact of geometry variables on CIHX performance for future CIHX design optimization. Specifically, a design tool was created using analytical relations to explore the complex, interdependent design space of a condensing ice heat exchanger. Numerous variables were identified as having nontrivial contributions to performance such as hydraulic diameter, heat exchanger effectiveness, ventilation gas mass flow rate and surface roughness. Using this tool, four test articles were designed and manufactured to map to a full MTSA subassembly (the adsorbent bed, the sublimation heat exchanger for cooling and the condensing ice heat exchanger for warming). The design mapping considered impacts due to CIHX geometry as well as subassembly impacts such as thermal mass and thermal resistance through the adsorbent bed. The test articles were tested at simulated PLSS ventilation loop temperature, moisture content and subambient pressure. Ice accumulation and melting were observed. Data and test observations were analyzed to identify drivers of the condensing ice heat exchanger performance. This paper will discuss the analytical models, the test article designs, and testing procedures. Testing issues will be discussed to better describe data and share lessons learned. Data analysis and subsequent conclusions will be presented.

Padilla, Sebastian↗
NASA NTRS1994

Spectral filtering for plant production

Both plants and animals have one general commonality in their perception of light. They both are sensitive primarily to the 400 to 700 nm wavelength portion of the electromagnetic spectrum. This is referred to as the visible spectrum for animals and as the photosynthetically active radiation (PAR) spectrum for plants. Within this portion of the spectrum, animals perceive colors. Relatively recently it has been learned that within this same spectral range plants also demonstrate varying responses at different wavelengths, somewhat analogous to the definition of various colors at specific wavelengths. Although invisible to the human eye, portions of the electromagnetic spectrum on either side of the visible range are relatively inactive photosynthetically but have been found to influence important biological functions. These portions include the ultraviolet (UV approximately equal to 280-400 nm) and the far-red (FR approximately equal to 700-800 nm). The basic photoreceptor of plants for photosynthesis is chlorophyll. It serves to capture radiant energy which combined with carbon dioxide and water produces oxygen and assimulated carbon, used for the synthesis of cell wall polysaccarides, proteins, membrane lipids and other cellular constituents. The energy and carbon building blocks of photosynthesis sustain growth of plants. On the other hand, however, there are other photoreceptors, or pigments, that function as signal transducers to provide information that controls many physiological and morphological responses of how a plant grows. Known photomorphogenic receptors include phytochrome (the red/far-red sensor in the narrow bands of 655-665 nm and 725-735 nm ranges, respectively) and 'cryptochrome' (the hypothetical UV-B sensor in the 280-320 nm range). Since the USDA team of W. L. Butler, S. B. Hendricks, H. A. Borthwick, H. A. Siegleman and K. Norris in Beltsville, MD detected by spectroscopy, extracted and identified phytochrome as a protein in the 1950's, many other investigators have found evidence of its control functions in plants. Considerably less, however, is known about the yet non-isolated cryptochrome. The information-transferring roles of photoreceptors in plants at specific spectral ranges quite naturally stimulated plant scientists and engineers to consider physically manipulating light to achieve desired physiological and morphological characteristics. One way to manipulate light is to filter it through materials that selectively transmit portions of the sun's spectrum in and near the PAR range.

Young, Roy E.↗
DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗
NASA NTRS2017

NASA's Bio-Inspired Acoustic Absorber Concept

Transportation noise pollutes our worlds cities, suburbs, parks, and wilderness areas. NASAs fundamental research in aviation acoustics is helping to find innovative solutions to this multifaceted problem. NASA is learning from nature to develop the next generation of quiet aircraft.The number of road vehicles and airplanes has roughly tripled since the 1960s. Transportation noise is audible in nearly all the counties across the US. Noise can damage your hearing, raise your heart rate and blood pressure, disrupt your sleep, and make communication difficult. Noise pollution threatens wildlife when it prevents animals from hearing prey, predators, and mates. Noise regulations help drive industry to develop quieter aircraft. Noise standards for aircraft have been developed by the International Civil Aviation Organization and adopted by the US Federal Aviation Administration. The US National Park Service is working with the Federal Aviation Administration to try to balance the demand for access to the parks and wilderness areas with preservation of the natural soundscape. NASA is helping by conceptualizing quieter, more efficient aircraft of the future and performing the fundamental research to make these concepts a reality someday. Recently, NASA has developed synthetic structures that can absorb sound well over a wide frequency range, and particularly below 1000 Hz, and which mimic the acoustic performance of bundles of natural reeds. We are adapting these structures to control noise on aircraft, and spacecraft. This technology might be used in many other industrial or architectural applications where acoustic absorbers have tight constraints on weight and thickness, and may be exposed to high temperatures or liquids. Information about this technology is being made available through reports and presentations available through the NASA Technical Report Server, http:ntrs.nasa.gov. Organizations who would like to collaborate with NASA or commercialize NASAs technology are encouraged to contact the NASA Glenn Technology Transfer Office, https:technology.grc.nasa.gov. The NASA Glenn Office of Education https:www.nasa.govcentersglenneducationindex.html and the NASA Glenn Virtual Interchange for Nature-Inspired Exploration https:www.grc.nasa.govvine are also helping to make research like this accessible to the public and students of all ages.

Acoustics↗
NASA NTRSDate not supplied

A Deep Neural Network for Achieving Spectrally Consistent and Seamless Infrared Radiance Measurements Across Geostationary Satellite Domains

The NASA Clouds and the Earth's Radiant Energy System (CERES) project provides the scientific community with observed top-of-atmosphere (TOA) shortwave and longwave fluxes for climate monitoring and climate model validation. To achieve this goal, CERES relies on TOA broadband fluxes derived from geostationary satellite (GEO) imagery to account for the diurnal flux variations between the CERES observation intervals. Consistent global flux derivation depends on accurate and consistent cloud retrievals. Scene-dependent spectral measurement inconsistency of the instruments that make up the contiguous ring of GEO observations (GEO-Ring), as well as limb darkening effects, can cause discontinuities in derived cloud properties and radiative fluxes at the boundaries of adjacent imager domains. Although the algorithms utilize radiative transfer models to account for instrument-band-dependent atmospheric correction and viewing zenith angle (VZA) dependency, small discontinuities may persist due to uncertainties inherent to the multiple imager-specific algorithms. Furthermore, while hyperspectral-instrument-based spectral band adjustment factors may effectively account for spectrally induced bias, they are less effective at reducing variance owed to the specific composition of the viewed scene, which is challenging to robustly characterize. As such, this article highlights the use of a deep neural network (DNN) to resolve spectral-and VZA-induced biases between GEO-Ring imagers. The DNN uses available infrared (IR) channels from the GEO instruments, along with viewing and solar illumination geometry, to estimate homogenized, VIIRS-like IR radiances for use in the GEO cloud algorithm. This approach is effective at mitigating scene-dependent spectral variance and VZA dependency, resulting in consistent radiance measurements across the GEO-Ring, thereby leading toward a more seamless global cloud assessment.

deep learning↗
NASA NTRS2007

The Transition of NASA EOS Datasets to WFO Operations: A Model for Future Technology Transfer

The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.

Darden, C.↗
DOE OSTI2025

Lattice Anisotropy-Driven Reduction of Phonon Velocities in Black Phosphorus

Phonon dynamics and transport determine how heat is utilized and dissipated in materials. In 2D systems for optoelectronics and thermoelectrics, the impact of nanoscale material structure on phonon propagation is central to controlling thermal conduction. Here, we directly observe in-plane coherent acoustic phonon propagation in black phosphorus (BP) using ultrafast electron microscopy. We identify a significant reduction of the group velocities in directions intermediate to the armchair and zigzag lattice directions. Using a machine learning-based model with an >8000 atom supercell, we find that this slowing results from the mixing of in-plane transverse and longitudinal acoustic phonons and is independent of broken symmetries of edge reconstructions. In conclusion, this work demonstrates how coherent phonon transport is sensitive to propagation direction in the lattice plane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks

To date, no method utilizing satellite imagery exists for detailing the locations and functions of critical infrastructure across the United States, making response to natural disasters and other events challenging due to complex infrastructural interdependencies. This paper presents a repeatable, transferable, and explainable method for critical infrastructure analysis and implementation of a robust model for critical infrastructure detection in satellite imagery. This model consists of a DenseNet-161 convolutional neural network, pretrained with the ImageNet database. The model was provided additional training with a custom dataset, containing nine infrastructure classes. The resultant analysis achieved an overall accuracy of 90%, with the highest accuracy for airports (97%), hydroelectric dams (96%), solar farms (94%), substations (91%), potable water tanks (93%), and hospitals (93%). Critical infrastructure types with relatively low accuracy are likely influenced by data commonality between similar infrastructure components for petroleum terminals (86%), water treatment plants (78%), and natural gas generation (78%). Local interpretable model-agnostic explanations (LIME) was integrated into the overall modeling pipeline to establish trust for users in critical infrastructure applications. The results demonstrate the effectiveness of a convolutional neural network approach for critical infrastructure identification, with higher than 90% accuracy in identifying six of the critical infrastructure facility types.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

High operating temperature heat transfer fluids for solar thermal power generation. Final report

This is the final technical report for the DOE MURI project on developing high-operating temperature heat transfer fluids for solar thermal power generation. This project aimed to evaluate liquid metals as a heat-transport fluid and potential energy storage medium for concentrated solar powered (CSP) systems. The project consisted of five phases, starting with fluid selection and screen and ending with potential CSP integration. The initial fluid selection arrived at heavy liquid metals as candidate fluids such as lead bismuth eutectic (LBE) as the prime liquid-alloy candidate to be studied, given the conditions above. Fifty-seven liquid compositions were initially identified with liquidus temperatures lower than 200°C, composed of elements that provide no driving force to the reduction of Cr 2 O 3 or Al 2 O 3 passivation layers in pipe material which is required for corrosion prevention. LBE was identified as the primary candidate fluid after these compositions were compared against computational thermodynamic modeling to screen all of the selected systems that would be compatible with our design objectives. Twenty-eight of these compositions were also investigated with the rapid characterization methods; the accuracies of the liquidus temperature and the specific heats predicted by the computations were better than 3 percent and 9 percent, respectively. We conducted numerus corrosion tests of various Fe-Cr-Al based steels in LBE and its variants at temperate as high as 800°C. It was found that minor additions to the liquid did not provide sufficient corrosion protection to warrant their use in real applications. Furthermore, we investigated the detailed mechanism of corrosion between heavy liquid metal and the pipe material at these very high temperatures. A liquid metal loop was constructed to operate at these high temperatures. The loop construction and operation lead to valuable lessons learned that will be needed for industrial scale loops. Furthermore, we learned that electromagnetic pumps at these extreme temperatures will have to be reengineered and redesigned to be used for CSP applications.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. Key activities over the last year were the release of an improved “Version 07” of all GPM precipitation and latent heating products, boosting the orbit of the GPM Core Observatory (GPM CO) to 435 km, and improving quality control on precipitation retrievals from the GPM constellation of passive microwave satellites. This presentation summarizes key improvements to the GPM products and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM CO. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. Maintaining the GPM CO orbital altitude in the the current very active solar cycle has been forcing the use of more fuel than planned and consequently shortening the forecasted life of the mission from the early 2030's to the late 2020's. It was considered vital to regain some of this lifetime to ensure overlap with the upcoming Atmosphere Observing System mission to provide crosscalibration of instruments. To accomplish this, the orbital altitude was raised from 400 to 435 km on 7-8 November 2023. Thereafter, the primary GPM CO algorithms had to be revised to account for the change in observing parameters. By meeting time this action should be complete. Recently, a screening algorithm based on auto-encoding was developed that uncovered 162 orbits (out of the many thousands of orbits across all years and all satellites) of passive microwave retrievals that had highly anomalous values. Removing these defective retrievals has improved the integrity of both the GPROF and IMERG records. However, the nature of the IMERG processing interacted sufficiently badly with the now-discovered anomalous orbits that it was necessary to completely reprocess the IMERG Final Run record, now labeled Version 07B. The presentation also considers major issues that require continued attention, including the use of machine learning algorithms and the operational challenge of swarms of “small”, perhaps short-lived satellites.

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