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At least 1,351 records · Page 75

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

A Unified Metric for Fast Frequency Response in Low-Inertia Power Systems: Preprint

Future power system with more inverter-based resources (IBRs) is vulnerable to the frequency-decline contingency. Fast frequency response (FFR) provided by IBRs is a good candidate to arrest the frequency excursion. Diverse types of FFRs have been integrated into the power system. Without a unified quantification of FFRs, it is hard for the grid operators to fully leverage the FFR capabilities of IBRs. This work introduces potential unified metrics of prevailing FFRs. We utilized the metric-to-frequency (M2F) mapping to validate the accuracy of the metrics. The results show the proposed metric to be simple yet accurate.

effective inertia↗

Investigation of the utility of ERTS-1 imagery for updating land use and resource data in Guatemala

The author has identified the following significant results. An intensive analysis of the imagery received has been completed and findings are reported. Conclusions are restricted by receipt of only limited amounts of cloud-free coverage of test areas. In most cases the interpretation findings were as anticipated from previous experience with multiband images. Band 7 provides promising indication of some economically important environmental communities. It also permits viewing through thin cirrus cloud layers for features of medium to high contrast. Band 4 provides information of submerged reefs and of movement of suspended sediment bodies in water areas. ERTS-1 bulk images have positional mapping accuracy adequate for representation at 1:1,000,000 scale maps. Cloud cover is a true constraint to useable satellite coverage.

Garcia, L. E.↗

Transcription factor bHLH121 regulates root cortical aerenchyma formation in maize

Root anatomical phenotypes present a promising yet underexploited avenue to deliver major improvements in yield and climate resilience of crops by improving water and nutrient uptake. For instance, the formation of root cortical aerenchyma (RCA) significantly increases soil exploration and resource capture by reducing the metabolic costs of root tissue. A key bottleneck in studying such phenotypes has been the lack of robust high-throughput anatomical phenotyping platforms. We exploited a phenotyping approach based on laser ablation tomography, termed Anatomics , to quantify variation in RCA formation of 436 diverse maize lines in the field. Results revealed a significant and heritable variation for RCA formation. Genome-wide association studies identified a single-nucleotide polymorphism mapping to a root cortex-expressed gene-encoding transcription factor bHLH121. Functional studies identified that the bHLH121 Mu transposon mutant line and CRISPR/Cas9 loss-of-function mutant line showed reduced RCA formation, whereas an overexpression line exhibited significantly greater RCA formation when compared to the wild-type line. Characterization of these lines under suboptimal water and nitrogen availability in multiple soil environments revealed that bHLH121 is required for RCA formation developmentally as well as under studied abiotic stress. Overall functional validation of the bHLH121 gene’s importance in RCA formation provides a functional marker to select varieties with improved soil exploration and thus yield under suboptimal conditions.

59 BASIC BIOLOGICAL SCIENCES↗

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.5)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the federated microservice architecture specification. This document represents the science use case design pattern catalog of the INTERSECT Open Architecture Specification.

42 ENGINEERING↗

INTERSECT Architecture Specification: Microservice Architecture (V.0.5)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the microservice architecture specification. This document represents the microservice architecture specification of the INTERSECT Open Architecture Specification.

97 MATHEMATICS AND COMPUTING↗

INTERSECT Architecture Specification: Microservice Architecture (V.0.9)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the microservice architecture specification. This document represents the microservice architecture specification of the INTERSECT Open Architecture Specification.

97 MATHEMATICS AND COMPUTING↗

Atlas of albedo and absorbed solar radiation derived from Nimbus 6 earth radiation budget data set, July 1975 to May 1978

An atlas of monthly mean global contour maps of albedo and absorbed solar radiation is presented. The atlas is based on 35 months of continuous measurements from July 1975 through May 1978. The data were retrieved from measurements made by the shortwave wide field-of-view radiometer of the first Earth Radiation Budget (ERB) instrument, which flew on the Nimbus 6 spacecraft in 1975. Profiles of zonal mean albedos and absorbed solar radiation are tabulated. These geographical distributions are provided as a resource for studying the radiation budget of the earth. This atlas of albedo and absorbed solar radiation complements the atlases of outgoing longwave radiation by Bess and Smith in NASA-RP-1185 and RP-1186, also based on the Nimbus 6 and 7 ERB data.

Smith, G. Louis↗

Grid Technology as a Cyber Infrastructure for Earth Science Applications

This paper describes how grids and grid service technologies can be used to develop an infrastructure for the Earth Science community. This cyberinfrastructure would be populated with a hierarchy of services, including discipline specific services such those needed by the Earth Science community as well as a set of core services that are needed by most applications. This core would include data-oriented services used for accessing and moving data as well as computer-oriented services used to broker access to resources and control the execution of tasks on the grid. The availability of such an Earth Science cyberinfrastructure would ease the development of Earth Science applications. With such a cyberinfrastructure, application work flows could be created to extract data from one or more of the Earth Science archives and then process it by passing it through various persistent services that are part of the persistent cyberinfrastructure, such as services to perform subsetting, reformatting, data mining and map projections.

Hinke, Thomas H.↗

Land Use Planning

Computer technology, aerial photography and space imagery are being combined in a NASA community services program designed to help solve land use and natural resource planning problems. As urban areas grow, so grows the need for comprehensive, up-to-date information on which to base intelligent decisions regarding land use. State and local planners need information such as the nature of urban change, where the changes are occurring, how they affect public safety, transportation, the economy, tax assessment, sewer systems, water quality, flood hazard, noise impact and a great variety of other considerations. Most importantly they need continually updated maps. Preparing timely maps, gathering the essential data and maintaining it in orderly fashion are becoming matters of increasing difficulty. The NASA project, which has nationwide potential for improving efficiency in the planning process, is a pilot program focused on Tacoma, Washington and surrounding Pierce County. Its key element, developed by Jet Propulsion Laboratory (JPL), is a computerized Land Use Management Information System (LUMIS).

Source record↗

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Standardization of the Distributed Ledger Technology cybersecurity stack for power and energy applications

The global trend towards the integration of distributed energy resources is opening the doors to advanced, complex, and distributedmarketplaces. Such advanced ecosystems, where utility-owned and non utility-owned assets can contribute towards grid operations,generally require distributed communication and grid architectures, which can be supported by Distributed Ledger Technologies(DLTs). However, the potential of DLTs for long-term scalable solutions in operational technology applications has not been fullyutilized, partly due to the lack of standardization across and between different DLTs, as well as other supporting building blocks(e.g., communication protocols). This paper attempts to address this gap by proposing a DLT cybersecurity stack specificallydesigned for researchers, DLT technology developers, and end users (such as utilities). The DLT cybersecurity stack has beennotionally mapped to related cybersecurity components, namely: the Open Systems Interconnection (OSI) model, the TransmissionControl Protocol/Internet Protocol (TCP/IP) suite, and existing Smart Grid architecture frameworks. In addition, the paper discussesseveral cybersecurity implications, and demonstrates the potential uses of the DLT stack through multiple power and energy usecases. It is important to note that the stack can be also applied to the DLT use cases that are outside the power and energy domain.This work has been performed by the Cybersecurity Task Force under the IEEE P2418.5 Blockchain for Energy Standard workinggroup that is stationed under the IEEE Power and Energy Society’s Smart Buildings, Loads, and Customer Systems (SBLC)technical committee.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Applications of remote sensing (ERTS) to resource management and development in Sahelien Africa (Republic of Mali)

The primary resource management problem in Sub-Saharan Africa (the Sahel) is increasing aridity or desertification. Space observations of sand streams, dune orientations, moisture and vegetation changes and other factors associated with desertification have been made. A second major interest is grazing of cattle, sheep and goats which is associated with major movements of people and animals twice yearly to obtain forage. The changes in available forage are being observed. The location of the cultivators is also being mapped from ERTS imagery. Hydrological analysis is being carried on in the Niger and Bani river watersheds. So far, good imagery of the maximum flood stage has been obtained and assessed.

Macleod, N. H.↗

NREPS Applications for Water Supply and Management in California and Tennessee

Management of water resources is a balancing act between temporally and spatially limited sources and competitive needs which can often exceed the supply. In order to manage water resources over a region such as the San Joaquin Valley or the Tennessee River Valley, it is pertinent to know the amount of water that has fallen in the watershed and where the water is going within it. Since rain gauge networks are typically sparsely spaced, it is typical that the majority of rainfall on the region may not be measured. To mitigate this under-sampling of rainfall, weather radar has long been employed to provide areal rainfall estimates. The Next-Generation Weather Radars (NEXRAD) make it possible to estimate rainfall over the majority of the conterminous United States. The NEXRAD Rainfall Estimation Processing System (NREPS) was developed specifically for the purpose of using weather radar to estimate rainfall for water resources management. The NREPS is tailored to meet customer needs on spatial and temporal scales relevant to the hydrologic or land-surface models of the end-user. It utilizes several techniques to mitigate artifacts in the NEXRAD data from contaminating the rainfall field. These techniques include clutter filtering, correction for occultation by topography as well as accounting for the vertical profile of reflectivity. This presentation will focus on improvements made to the NREPS system to map rainfall in the San Joaquin Valley for NASA s Water Supply and Management Project in California, but also ongoing rainfall mapping work in the Tennessee River watershed for the Tennessee Valley Authority and possible future applications in other areas of the continent.

Gatlin, P.↗

Feature Learning for Multispectral Satellite Imagery Classification Using Neural Architecture Search

Automated classification of remote sensing data is an integral tool for earth scientists, and deep learning has proven very successful at solving such problems. However, building deep learning models to process the data requires expert knowledge of machine learning. We introduce DELTA, a software toolkit to bridge this technical gap and make deep learning easily accessible to earth scientists. Visual feature engineering is a critical part of the machine learning lifecycle, and hence is a key area that will be automated by DELTA. Hand-engineered features can perform well, but require a cross functional team with expertise in both machine learning and the specific problem domain, which is costly in both researcher time and labor. The problem is more acute with multispectral satellite imagery, which requires considerable computational resources to process. In order to automate the feature learning process, a neural architecture search samples the space of asymmetric and symmetric autoencoders using evolutionary algorithms. Since denoising autoencoders have been shown to perform well for feature learning, the autoencoders are trained on various levels of noise and the features generated by the best performing autoencoders evaluated according to their performance on image classification tasks. The resulting features are demonstrated to be effective for Landsat-8 flood mapping, as well as benchmark datasets CIFAR10 and SVHN.

Robert Campbell↗

Extraction and utilization of space acquired physiographic data for water resources development

ERTS-1 satellite imagery was evaluated as a means of providing useful watershed physiography information. From these data physiographic parameters such as drainage basin area and shape, drainage density, stream length and sinuosity, and the percentage of a watershed occupied by major land use types were obtained in three study areas. The study areas were: (1) Southwestern Wisconsin; (2) Eastern Colorado, and (3) portions of the Middle Atlantic States. Using ERTS-1 imagery at 1:250,000 and 1:100,000 scales it was found that drainage basin area and shape and stream sinuosity were comparable (within 10%) in all study areas to physiographic measurements derived from conventional topographic maps at the same scales.

Rango, A.↗

Evaluation of riverbed magnetic susceptibility for mapping biogeochemical hot spots in groundwater‐impacted rivers

Abstract Redox hot spots occurring as metal‐rich anoxic groundwater discharges through oxic wetland and river sediments commonly result in the formation of iron (Fe) oxide precipitates. These redox‐sensitive precipitates influence the release of nutrients and metals to surface water and can act as ‘contaminant sponges’ by absorbing toxic compounds. We explore the feasibility of a non‐invasive, high‐resolution magnetic susceptibility (MS) technique to efficiently map the spatial variations of magnetic Fe oxide precipitates in the shallow bed of three rivers impacted by anoxic groundwater discharge. Laboratory analyses on Mashpee River (MA, USA) sediments demonstrate the sensitivity of MS to sediment Fe concentrations. Field surveys in the Mashpee and Quashnet rivers (MA, USA) reveal several discrete high MS zones, which are associated with likely anoxic groundwater discharge as evaluated by riverbed temperature, vertical head gradient, and groundwater chemistry measurements. In the East River (CO, USA), widespread cobbles/rocks exhibit high background MS from geological ferrimagnetic minerals, thereby obscuring the relatively small enhancement of MS from groundwater induced Fe oxide precipitates. Our study suggests that, in settings with low geological sources of magnetic minerals such as lowland rivers and wetlands, MS may serve as a complementary tool to temperature methods for efficiently mapping Fe oxide accumulation zones due to anoxic groundwater discharges that may function as biogeochemical hot spots and water quality control points in gaining systems.

Wang, Chen↗