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At least 523 records · Page 29

Distributed Acoustic Sensing as a Distributed Hydraulic Sensor in Fractured Bedrock

Distributed acoustic sensing (DAS) was originally intended to measure oscillatory strain at frequencies of 1 Hz or more on a fiber optic cable. Recently, measurements at much lower frequencies have opened the possibility of using DAS as a dynamic strain sensor in boreholes. A fiber optic cable mechanically coupled to a geologic formation will strain in response to hydraulic stresses in pores and fractures. A DAS interrogator can measure dynamic strain in the borehole, which can be related to fluid pressure through the mechanical compliance properties of the formation. Because DAS makes distributed measurements, it is capable of both locating hydraulically active features and quantifying the fluid pressure in the formation. We present field experiments in which a fiber optic cable was mechanically coupled to two crystalline rock boreholes. The formation was stressed hydraulically at another well using alternating injection and pumping. The DAS instrument measured oscillating strain at the location of a fracture zone known to be hydraulically active. Rock displacements of less than 1 nm were measured. Laboratory experiments confirm that displacement is measured correctly. These results suggest that fiber optic cable embedded in geologic formations may be used to map hydraulic connections in three-dimensional fracture networks. A great advantage of this approach is that strain, an indirect measure of hydraulic stress, can be measured without beforehand knowledge of flowing fractures that intersect boreholes. The technology has obvious applications in water resources, geothermal energy, CO 2 sequestration, and remediation of groundwater in fractured bedrock.

54 ENVIRONMENTAL SCIENCES↗

Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces

The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces .

59 BASIC BIOLOGICAL SCIENCES↗

CAPE for CaPE

In an effort to improve short-term forecasting for the Kennedy Space Center region, Holle et al. (1992) investigated the effects of low level wind regimes on the distribution of cloud-to-ground lightning in central Florida. With a study period of 455 days, Holle et al. (1992) found 'southwest flow contributed 66 percent of the total network flashes while also occurring on the most days (142).' Relationships among mesoscale thermodynamic variables and precipitation and/or lightning have been addressed in previous studies in Canada and the Tennessee valley. Zawadzki et al. (1981) found 'soundings, surface pressure, temperature and humidity obtained from a standard observation network were correlated with rain rates given by raingages and radar.' Buechler et al. (1990) found 'a fair relationship between CAPE (convective available potential energy) and daily cloud-to-ground activity' with a correlation coefficient of r = 0.68. The present research will investigate the relationships among rainfall, cloud-to-ground (CG) lightning, CAPE, and low level wind flow using data collected during the CaPE (Convection and Precipitation/Electrification Experiment) field program. The CaPE field program was conducted in east central Florida from July 8, 1991 to August 18, 1991.

Brooks, Joni↗

NASA Tech Briefs, August 2013

Topics covered include: Radial Internal Material Handling System (RIMS) for Circular Habitat Volumes; Conical Seat Shut-Off Valve; Impact-Actuated Digging Tool for Lunar Excavation; Flexible Mechanical Conveyors for Regolith Extraction and Transport; Remote Memory Access Protocol Target Node Intellectual Property; Soft Decision Analyzer; Distributed Prognostics and Health Management with a Wireless Network Architecture; Minimal Power Latch for Single-Slope ADCs; Bismuth Passivation Technique for High-Resolution X-Ray Detectors; High-Strength, Super-elastic Compounds; Cu-Cr-Nb-Zr Alloy for Rocket Engines and Other High-Heat- Flux Applications; Microgravity Storage Vessels and Conveying-Line Feeders for Cohesive Regolith; CRUQS: A Miniature Fine Sun Sensor for Nanosatellites; On-Chip Microfluidic Components for In Situ Analysis, Separation, and Detection of Amino Acids; Spectroscopic Determination of Trace Contaminants in High-Purity Oxygen; Method of Separating Oxygen From Spacecraft Cabin Air to Enable Extravehicular Activities; Atomic Force Microscope Mediated Chromatography; Sample Analysis at Mars Instrument Simulator; Access Control of Web- and Java-Based Applications; Tool for Automated Retrieval of Generic Event Tracks (TARGET); Bilayer Protograph Codes for Half-Duplex Relay Channels; Influence of Computational Drop Representation in LES of a Droplet-Laden Mixing Layer.

Source record↗

Implementation of Ada protocols on Mil-STD-1553 B data bus

Standardization activity of data communication in avionic systems started in 1968 for the purpose of total system integration and the elimination of heavy wire bundles carrying signals between various subassemblies. The growing complexity of avionic systems is straining the capabilities of MIL-STD-1553 B (first issued in 1973), but a much greater challenge to it is posed by Ada, the standard language adopted for real-time, computer embedded-systems. Hardware implementation of Ada communication protocols in a contention/token bus or token ring network is proposed. However, during the transition period when the current command/response multiplex data bus is still flourishing and the development environment for distributed multi-computer Ada systems is as yet lacking, a temporary accomodation of the standard language with the standard bus could be very useful and even highly desirable. By concentrating all status informtion and decisions at the bus controller, it was found to be possible to construct an elegant and efficient harware impelementation of the Ada protocols at the bus interface. This solution is discussed.

Ruhman, Smil↗

The use of ion mobility spectrometry and gas chromatography/mass spectrometry for the detection of illicit drugs on clandestine records

Illicit drug distribution has over the past decade grown tremendously from simple 'drug pushing' where drugs were distributed from poorly organized individuals to today's well organized and well financed drug cartels. This change to a more 'corporate-like' atmosphere has resulted in a greater use of record keeping to monitor the profits generated. The use of record keeping by drug distributors is not restricted to high level drug smugglers but is used at all levels within the distribution network. Dealers at all levels including street dealers are generally 'fronted', given on consignment quantities of drugs that they in turn sell to customers, thereby requiring the need for records to keep track of drug sales versus liabilities. These records because of their illicit nature are often encrypted to hide the fact that they are indeed records of drug transactions. The creation of a handwritten notation concerning a drug transaction is normally brought on because of a purchase or sale. In a sale, this is commonly accomplished through a consignment, or the designation of a quantity to a customer to whom that amount has been 'fronted'. Because this activity generates a debt, it follows that an accounting for payments made, as well as new transactions completed, is only logical. One of the most common means of representing these is through an 'accounting flow', in which payments are subtracted from a running balance while new sales are added to it. The examination of illicit drug records has been the key to the prosecution of numerous federal, state, and local drug cases for a number of years. The Document Section of the FBI Laboratory, through its Racketeering Records Analysis Unit (RRAU), has been involved in such analytical efforts since 1983. Detailed analytical research brought about an evolution in the systematic approach utilized in the RRAU since that time. The close proximity of the drugs to the records often results in trace drug evidence being transferred to the records. The detection of trace drug residue on surfaces by ion mobility spectrometry (IMS) is well documented in literature. The following procedure will deal primarily with the newer techniques of trace drug analysis and drug record analysis developed by the Chemistry/Toxicology Unit of the FBI Laboratory since the more traditional techniques of latent finger print analysis and document analysis are well known.

Donnelly, Brian↗

Aerosol responses to precipitation along North American air trajectories arriving at Bermuda

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location a suitable natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 µm normalized by the enhancement of carbon monoxide above background (PM 2.5 /ΔCO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December–February (DJF) show that most trajectories come from North America and have the highest APTs, resulting in a significant reduction (by 53 %) in PM 2.5 /ΔCO under high-APT conditions (> 13.5 mm) relative to low-APT conditions (< 0.9 mm). Moreover, PM 2.5 /ΔCO was most sensitive to increases in APT up to 5 mm (–0.044 µg m –3 ppbv –1 mm –1 ) and less sensitive to increases in APT over 5 mm. While anthropogenic PM 2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt, in contrast, was comparable between high- and low-APT conditions owing to enhanced local wind and sea salt emissions in high-APT conditions. The greater sensitivity of the fine-mode volume concentrations (versus coarse mode) to wet scavenging is evident from AErosol RObotic NETwork (AERONET) volume size distribution data. A combination of GEOS-Chem model simulations of the 210 Pb submicron aerosol tracer and its gaseous precursor 222 Rn reveals that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter and spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222 Rn tracer emissions contribute most to surface 210 Pb concentrations at Bermuda in winter (~75 %–80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the US East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the US East Coast.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA Tech Briefs, December 2011

Topics covered include: 1) SNE Industrial Fieldbus Interface; 2) Composite Thermal Switch; 3) XMOS XC-2 Development Board for Mechanical Control and Data Collection; 4) Receiver Gain Modulation Circuit; 5) NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions; 6) Digital Interface Board to Control Phase and Amplitude of Four Channels; 7) CoNNeCT Baseband Processor Module; 8) Cryogenic 160-GHz MMIC Heterodyne Receiver Module; 9) Ka-Band, Multi-Gigabit-Per-Second Transceiver; 10) All-Solid-State 2.45-to-2.78-THz Source; 11) Onboard Interferometric SAR Processor for the Ka-Band Radar Interferometer (KaRIn); 12) Space Environments Testbed; 13) High-Performance 3D Articulated Robot Display; 14) Athena; 15) In Situ Surface Characterization; 16) Ndarts; 17) Cryo-Etched Black Silicon for Use as Optical Black; 18) Advanced CO2 Removal and Reduction System; 19) Correcting Thermal Deformations in an Active Composite Reflector; 20) Umbilical Deployment Device; 21) Space Mirror Alignment System; 22) Thermionic Power Cell To Harness Heat Energies for Geothermal Applications; 23) Graph Theory Roots of Spatial Operators for Kinematics and Dynamics; 24) Spacesuit Soft Upper Torso Sizing Systems; 25) Radiation Protection Using Single-Wall Carbon Nanotube Derivatives; 26) PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure; 27) Lidar Luminance Quantizer; 28) Distributed Capacitive Sensor for Sample Mass Measurement; 29) Base Flow Model Validation; 30) Minimum Landing Error Powered-Descent Guidance for Planetary Missions; 31) Framework for Integrating Science Data Processing Algorithms Into Process Control Systems; 32) Time Synchronization and Distribution Mechanisms for Space Networks; 33) Local Estimators for Spacecraft Formation Flying; 34) Software-Defined Radio for Space-to-Space Communications; 35) Reflective Occultation Mask for Evaluation of Occulter Designs for Planet Finding; and 36) Molecular Adsorber Coating

Source record↗

Tall Lunar Towers: Systems Analysis of a Lunar-Surface-Assembled Power, Communication, and Navigation Infrastructure

The National Aeronautics and Space Administration (NASA) intends to develop and maintain a human-lunar presence, requiring infrastructure on the Lunar South Pole. To keep pace with the continued growth in cislunar activity, there is national interest in developing a global lunar infrastructure network for power and Communication, Position, Navigation, and Timing (CPNT). Demonstrating autonomous construction capabilities is an infrastructure-enabling objective. This study explores several architecture trade studies to assess the feasibility of alternative lunar infrastructure concepts. 50 m towers, for instance, enable solar power generation up to 99% of a lunar year in addition to acting as wide-range communication and navigation surface relays. The infrastructure network considered in this study consisted of tower platforms, utilities hosted on the towers, and both crewed and robotic end users. High-level trades were analyzed, such as tower height, location, and distributed vs centralized power grids. Results indicated that even with minimal permanent surface assets (darkness survival power loads on the order of 5 kW or greater), at any of the five locations considered, taller towers resulted in lower infrastructure mass than shorter towers; up to 24% system mass savings were realized by reducing battery mass. Simultaneously, taller towers increased the range of communication coverage; a 50 m tower on the Connecting Ridge had 5 kg more structure and 76% more line-of-sight coverage to a two-meter-tall end user than a 10 m tower with the same location and user height. Leveraging a grid of tall towers for nominal power and communication would not only save up to 2,800 kg in battery mass but would be more maintainable and allow users to take advantage of generational upgrades.

lunar infrastructure↗

Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring

A document discusses the utilization of embedded clocks inside of operating network data links as an auxiliary clock source to satisfy local oscillator monitoring requirements. Modem network interfaces, typically serial network links, often contain embedded clocking information of very tight precision to recover data from the link. This embedded clocking data can be utilized by the receiving device to monitor the local oscillator for tolerance to required specifications, often important in high-integrity fault-tolerant applications. A device can utilize a received embedded clock to determine if the local or the remote device is out of tolerance by using a single link. The local device can determine if it is failing, assuming a single fault model, with two or more active links. Network fabric components, containing many operational links, can potentially determine faulty remote or local devices in the presence of multiple faults. Two methods of implementation are described. In one method, a recovered clock can be directly used to monitor the local clock as a direct replacement of an external local oscillator. This scheme is consistent with a general clock monitoring function whereby clock sources are clocking two counters and compared over a fixed interval of time. In another method, overflow/underflow conditions can be used to detect clock relationships for monitoring. These network interfaces often provide clock compensation circuitry to allow data to be transferred from the received (network) clock domain to the internal clock domain. This circuit could be modified to detect overflow/underflow conditions of the buffering required and report a fast or slow receive clock, respectively.

Pollock, Julie↗

AmeriFlux FLUXNET-1F US-xBR NEON Bartlett Experimental Forest (BART)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART). This is the FLUXNET version of the carbon flux data for the site US-xBR NEON Bartlett Experimental Forest (BART) produced by applying the standard ONEFlux (1F) software. Site Description - The Bartlett Experimental Forest is an actively managed forest; managed portions (30%) reflect a range of forest patch sizes and structural distributions. The Bartlett forest has a history of logging dating from colonial times through the beginning of the 20th century. Approximately 70% of the land area has remained uncut since the early 1900s. Natural disturbances include late 19th century fire, beech scale-Nectria complex (beech bark disease) beginning in the 1940s, severe wind disturbance resulting from hurricanes in 1938 and 1954 and a damaging ice storm in 1998.

Network), NEON (National Ecological Observatory↗

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗

MEASURE: An integrated data-analysis and model identification facility

The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.

Singh, Jaidip↗

Feasibility of Correlated Extensive Air Shower Detection with a Distributed Cosmic-Ray Network

We explore the sensitivity offered by a global network of cosmic-ray detectors to a novel, unobserved phenomenon: widely separated simultaneous extended air showers. Existing localized observatories work independently to observe individual showers, offering insight into the source and nature of ultrahigh-energy cosmic rays. However no current observatory is large enough to provide sensitivity to anticipated processes such as the Gerasimova–Zatsepin effect or potential new physics that generate simultaneous air showers separated by hundreds to thousands of kilometers. A global network of consumer electronics (the Cosmic Rays Found In Smartphones (CRAYFIS) experiment), may provide a novel opportunity for observation of such phenomena. Two user scenarios are explored. In the first, with maximal user adoption, we find that statistically significant discoveries of spatially separated but coincident showers are possible within a couple years. In the second, more practical adoption model with 10 6 active devices, we find a worldwide CRAYFIS to be sensitive to novel "burst" phenomena where many simultaneous extensive air showers (EAS) occur at once.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗

Incremental planning to control a blackboard-based problem solver

To control problem solving activity, a planner must resolve uncertainty about which specific long-term goals (solutions) to pursue and about which sequences of actions will best achieve those goals. A planner is described that abstracts the problem solving state to recognize possible competing and compatible solutions and to roughly predict the importance and expense of developing these solutions. With this information, the planner plans sequences of problem solving activities that most efficiently resolve its uncertainty about which of the possible solutions to work toward. The planner only details actions for the near future because the results of these actions will influence how (and whether) a plan should be pursued. As problem solving proceeds, the planner adds new details to the plan incrementally, and monitors and repairs the plan to insure it achieves its goals whenever possible. Through experiments, researchers illustrate how these new mechanisms significantly improve problem solving decisions and reduce overall computation. They briefly discuss current research directions, including how these mechanisms can improve a problem solver's real-time response and can enhance cooperation in a distributed problem solving network.

Durfee, E. H.↗