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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Incorporating ADAPT-VQE with a Sparse Wavefunction Circuit Simulator to Find Compact Quantum Circuits for Chemical Applications

We implemented the ADAPT-VQE algorithm into our recent classical sparse wavefunction circuit simulator to demonstrate that classical resources can (1) efficiently find a physically motivated compact wavefunction ansatz for further refinement on near-term quantum hardware and (2) benchmark expected results of VQE-based algorithms once the quantum hardware is available to study large-scale applications. In particular, we study the role of the ADAPT-VQE operator pool, molecular basis set selection, and variations such as TETRIS-ADAPT-VQE on the performance of our classical circuit simulator. This work demonstrates the promise of using classical resources to generate highly accurate wavefunctions that can be prepared on quantum hardware to initiate other quantum algorithms such as phase estimation. Our approach harnesses the power of high-performance computing resources with the more limited available quantum computers to map a path toward quantum advantage for electronic structure calculations in chemistry and materials science.

Quantum Computing↗
DOE OSTI2020

Decreasing wind speed extrapolation error via domain-specific feature extraction and selection

Abstract. Model uncertainty is a significant challenge in the wind energy industry and can lead to mischaracterization of millions of dollars' worth of wind resources. Machine learning methods, notably deep artificial neural networks (ANNs), are capable of modeling turbulent and chaotic systems and offer a promising tool to produce high-accuracy wind speed forecasts and extrapolations. This paper uses data collected by profiling Doppler lidars over three field campaigns to investigate the efficacy of using ANNs for wind speed vertical extrapolation in a variety of terrains, and it quantifies the role of domain knowledge in ANN extrapolation accuracy. A series of 11 meteorological parameters (features) are used as ANN inputs, and the resulting output accuracy is compared with that of both standard log-law and power-law extrapolations. It is found that extracted nondimensional inputs, namely turbulence intensity, current wind speed, and previous wind speed, are the features that most reliably improve the ANN's accuracy, providing up to a 65 % and 52 % increase in extrapolation accuracy over log-law and power-law predictions, respectively. The volume of input data is also deemed important for achieving robust results. One test case is analyzed in depth using dimensional and nondimensional features, showing that the feature nondimensionalization drastically improves network accuracy and robustness for sparsely sampled atmospheric cases.

17 WIND ENERGY↗
NASA NTRS1981

The 1979 Southeastern Virginia Urban Plume Study. Volume 1: Description of experiments and selected aircraft data

The Southeastern Virginia Urban Plume Study (SEV-UPS) utilizes remote sensors and satellite platforms to monitor the Earth's environment and resources. SEV-UPS focuses on the application of specific remote sensors to the monitoring and study of specific air quality problems. The 1979 SEV-UPS field program was conducted with specific objectives: (1) to provide correlative data to evaluate the Laser Absorption spectrometer ozone remote sensors; (2) to demonstrate the utility of the sensor for the study of urban ozone problems; (3) to provide additional insights into air quality phenomena occuring in Southeastern Virginia; and (4) to compare measurement results of various in situ measurement platforms. The field program included monitoring from 12 surface stations, 4 aircraft, 2 tethered balloons, 2 radiosonde release sites, and numerous surface meteorological observation sites. The aircraft monitored 03, NO, NOX, Bscat, temperature, and dewpoint temperature.

Gregory, G. L.↗
DOE OSTI2016

Optimal test selection for prediction uncertainty reduction

Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecise data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Exploration Laboratory Analysis FY13

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability (ExMC) risk, which is stated as the Risk of Inability to Adequately Treat an Ill or Injured Crew Member, and ExMC Gap 4.05: Lack of minimally invasive in-flight laboratory capabilities with limited consumables required for diagnosing identified Exploration Medical Conditions. To mitigate this risk, the availability of inflight laboratory analysis instrumentation has been identified as an essential capability in future exploration missions. Mission architecture poses constraints on equipment and procedures that will be available to treat evidence-based medical conditions according to the Space Medicine Exploration Medical Conditions List (SMEMCL), and to perform human research studies on the International Space Station (ISS) that are supported by the Human Health and Countermeasures (HHC) element. Since there are significant similarities in the research and medical operational requirements, ELA hardware development has emerged as a joint effort between ExMC and HHC. In 2012, four significant accomplishments were achieved towards the development of exploration laboratory analysis for medical diagnostics. These achievements included (i) the development of high priority analytes for research and medical operations, (ii) the development of Level 1 functional requirements and concept of operations documentation, (iii) the selection and head-to-head competition of in-flight laboratory analysis instrumentation, and (iv) the phase one completion of the Small Business Innovation Research (SBIR) projects under the topic Smart Phone Driven Blood-Based Diagnostics. To utilize resources efficiently, the associated documentation and advanced technologies were integrated into a single ELA plan that encompasses ExMC and HHC development efforts. The requirements and high priority analytes was used in the selection of the four in-flight laboratory analysis performers. Based upon the competition results, a down select process will be performed in the upcoming year. Looking ahead, this unified effort has positioned each element for an in-flight lab analysis demonstration of select diagnostics measurements in the 2015 timeframe.

Krihak, Michael↗
DOE OSTI2022

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimized V1G and V2G Electric Vehicle Fleet Management and Grid Transaction at Marine Corps Air Station Miramar in San Diego, CA

The overall technical goal of the project was to demonstrate an all-electric bi-directional non-tactical fleet at Marine Corps Air Station (MCAS) Miramar that was integrated and controlled with other distributed energy resources (DERs) (i.e., PV, stationary battery, and building loads) to provide resilience to critical electric loads in the event of grid outages, to minimize charging costs, and to provide economic energy resources to electricity markets. In this project, the specific, technical objectives were: 1. Demonstrate that bi-directional electric vehicles can provide critical complementary services to fixed storage batteries in microgrid applications while performing function as non-tactical vehicles. 2. Demonstrate participation of bi-directional (V2G) and unidirectional (V1G) PEVs for demand management and minimization of charging costs. 3. Demonstrate integration of multiple DERs for grid service participation. US Marine Corps Air Station (MCAS) Miramar in San Diego was the site of this electric vehicle-to-microgrid-utility grid test and demonstration project. Existing microgrid assets in this study included (1) a public works building; (2) a 30-kW rooftop photovoltaic (PV) system and (3) a separate 250 kW carport PV system. In this project, six bi-directional V2G vans were located at the MCAS Miramar’s showcase building-scale microgrid to develop and test technical capabilities that V2G can provide in microgrid applications (e.g., cost reduction and resiliency). These resources provided aggregated demand management and simulated participation in current retail DR programs. The vehicles used in this demonstration were selected because they provided functionality that MCAS Miramar needed, 15 passenger transport and facilities work cargo carrying capacity, and bi-directional charging capability that the research project required. All vehicles in this study were manufactured and distributed by VIA Motors, Inc. There were six vehicles total and each was VIA’s VTRUX eREV V2G model, a modified General Motors Chevrolet 2500 2WD van. Three of the vans were configured as passenger vans and the other three were configured as cargo vans. Each van had an on-board bi-direcrtional inverter/charger, Bel Power Solutions model 350INVCHGT150-120-240-8G nominally rated at +/-15 kW. The VIA van’s charging connector follows the J1772 charging protocol. The bi-directional EVSEs demonstrated in this study were manufactured by Coritech, Inc. Each VGI-80-AC charging station enabled enhanced V2G charging capability to a Clipper Creek CS-100 charging module. The enhanced capabilities included ethernet communication following the SEP2.0 protocol with a distributed energy resource function set and an operator screen displaying real-time SOC, voltage, and current. The VGI-80-AC charging stations are classified as level 2 with a maximum current output of 80 A or effectively 19 kW. The VIA van’s onboard charger limited the charging and discharging power to 15 kW in each direction. A control computer was installed in the EWOC and connected to an existing monitor. The V2G control communication network was a completely stand-alone closed system that did not have any connection to any other networks on the base. A cybersecure remote communication connection was created with a cellular modem, firewall hardware, and a virtual private network configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

Design of isolated renewable hybrid power systems

Isolated electrical power generating units can be used as an economically viable alternative to electrify remote villages where grid extension is not feasible. One of the options for building isolated power systems is by hybridizing renewable power sources like wind, solar, micro-hydro, etc. along with appropriate energy storage. A method to optimally size and to evaluate the cost of energy produced by a renewable hybrid system is proposed in this paper. The proposed method, which is based on the design space approach, can be used to determine the conditions for which hybridization of the system is cost effective. The simple and novel methodology, proposed in this paper, is based on the principles of process integration. It finds the minimum battery capacity when the availability and ratings of various renewable resources as well as load demand are known. The battery sizing methodology is used to determine the sizing curve and thereby the feasible design space for the entire system. Chance constrained programming approach is used to account for the stochastic nature of the renewable energy resources and to arrive at the design space. The optimal system configuration in the entire design space is selected based on the lowest cost of energy, subject to a specified reliability criterion. The effects of variation of the specified system reliability and the coefficient of correlation between renewable sources on the design space, as well as the optimum configuration are also studied in this paper. The proposed method is demonstrated by designing an isolated power system for an Indian village utilizing wind-solar photovoltaic-battery system. (author)

14 SOLAR ENERGY↗
DOE OSTI2017

Taxonomic and functional shifts in the beech rhizosphere microbiome across a natural soil toposequence

It has been rarely questioned as to whether the enrichment of specific bacterial taxa found in the rhizosphere of a given plant species changes with different soil types under field conditions and under similar climatic conditions. Understanding tree microbiome interactions is essential because, in contrast to annual plants, tree species require decades to grow and strongly depend on the nutritive resources of the soil. In this context, we tested using a natural toposequence the hypothesis that beech trees select specific taxa and functions in their rhizosphere based on the soil conditions and their nutritive requirements. Our 16S rRNA gene pyrosequencing analyses revealed that the soil type determines the taxa colonizing the beech rhizosphere. A rhizosphere effect was observed in each soil type, but a stronger effect was observed in the nutrient-poor soils. Although the communities varied significantly across the toposequence, we identified a core beech rhizosphere microbiome. Functionally, GeoChip analyses showed a functional redundancy across the toposequence, with genes related to nutrient cycling and to the bacterial immune system being significantly enriched in the rhizosphere. Altogether, the data suggest that, regardless of the soil conditions, trees enrich variable bacterial communities to maintain the functions necessary for their nutrition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Differences in resource use lead to coexistence of seed-transmitted microbial populations

Seeds are involved in the vertical transmission of microorganisms in plants and act as reservoirs for the plant microbiome. They could serve as carriers of pathogens, making the study of microbial interactions on seeds important in the emergence of plant diseases. We studied the influence of biological disturbances caused by seed transmission of two phytopathogenic agents, Alternaria brassicicola Abra43 (Abra43) and Xanthomonas campestris pv. campestris 8004 (Xcc8004), on the structure and function of radish seed microbial assemblages, as well as the nutritional overlap between Xcc8004 and the seed microbiome, to find seed microbial residents capable of outcompeting this pathogen. According to taxonomic and functional inference performed on metagenomics reads, no shift in structure and function of the seed microbiome was observed following Abra43 and Xcc8004 transmission. This lack of impact derives from a limited overlap in nutritional resources between Xcc8004 and the major bacterial populations of radish seeds. However, two native seed-associated bacterial strains belonging to Stenotrophomonas rhizophila displayed a high overlap with Xcc8004 regarding the use of resources; they might therefore limit its transmission. The strategy we used may serve as a foundation for the selection of seed indigenous bacterial strains that could limit seed transmission of pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An open-source framework for balancing computational speed and fidelity in production cost models

Studies of bulk power system operations need to incorporate uncertainty and sensitivity analyses, especially around exposure to weather and climate variability and extremes, but this remains a computational modeling challenge. Commercial production cost models (PCMs) have shorter runtimes, but also important limitations (opacity, license restrictions) that do not fully support stochastic simulation. Open-source PCMs represent a potential solution. They allow for multiple, simultaneous runs in high-performance computing environments and offer flexibility in model parameterization. Yet, developers must balance computational speed (i.e. runtime) with model fidelity (i.e. accuracy). In this paper, we present Grid Operations (GO), a framework for instantiating open-source, scale-adaptive PCMs. GO allows users to search across parameter spaces to identify model versions that appropriately balance computational speed and fidelity based on experimental needs and resource limits. Results provide generalizable insights on how to navigate the fidelity and computational speed tradeoff through parameter selection. We show that models with coarser network topologies can accurately mimic market operations, sometimes better than higher-resolution models. It is thus possible to conduct large simulation experiments that characterize operational risks related to climate and weather extremes while maintaining sufficient model accuracy.

42 ENGINEERING↗
DOE OSTI2011

Design, manufacture, and evaluation of an anthropomorphic pelvic phantom purpose-built for radiotherapy dosimetric intercomparison

Purpose: An anthropomorphic pelvic phantom was designed and constructed to meet specific criteria for multicenter radiotherapy dosimetric intercomparison. Methods: Three dimensional external and organ outlines were generated from a computed tomography image set of a male pelvis, forming the basis of design for an anatomically realistic phantom. Clinically relevant points of interest were selected throughout the dataset where point-dose values could be measured with thermoluminescence dosimeters and a small-volume ionization chamber. Following testing, three materials were selected and the phantom was manufactured using modern prototyping techniques into five separate coronal slices. Time lines and resource requirements for the phantom design and manufacture were recorded. The ability of the phantom to mimic the entire treatment chain was tested. Results: The phantom CT images indicated that organ densities and geometries were comparable to those of the original patient. The phantom proved simple to load for dosimetry and rapid to assemble. Due to heat release during manufacture, small air gaps and density heterogeneities were present throughout the phantom. The overall cost for production of the prototype phantom was comparable to other commercial anthropomorphic phantoms. The phantom was shown to be suitable for use as a ''patient'' to mimic the entire treatment chain for typical external beam radiotherapy for prostate and rectal cancer. Conclusions: The phantom constructed for the present study incorporates all characteristics necessary for accurate Level III intercomparison studies. Following use in an extensive Level III dosimetric comparison over a large time scale and geographic area, the phantom retained mechanical stability and did not show signs of radiation-induced degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Technology Deployment Annual Report 2013 December

Idaho National Laboratory (INL) is a Department of Energy (DOE) multi-program national laboratory that conducts research and development in all DOE mission areas. Like all other federal laboratories, INL has a statutory technology transfer mission to make its capabilities and technologies available to all federal agencies, to state and local governments, and to universities and industry. To fulfill this mission, INL encourages its scientific, engineering, and technical staff to disclose new inventions and creations to ensure the resulting intellectual property is captured, protected, and made available to others who might benefit from it. As part of the mission, intellectual property is licensed to industrial partners for commercialization, creating jobs and delivering the benefits of federally funded technology to consumers. In other cases, unique capabilities are made available to other federal agencies or to regional small businesses to solve specific technical challenges. INL employees also work cooperatively with researchers and technical staff from the university and industrial sectors to further develop emerging technologies. In a multinational global economy, INL is contributing to the development of the next generation of engineers and scientists by licensing software to educational institutions throughout the world. This report is a catalog of selected INL technology transfer and commercialization transactions during this past year. The size and diversity of INL technical resources, coupled with the large number of relationships with other organizations, virtually ensures that a report of this nature will fail to capture all interactions. Recognizing this limitation, this report focuses on transactions that are specifically authorized by technology transfer legislation (and corresponding contractual provisions) or involve the transfer of legal rights to technology to other parties. This report was compiled from primary records, which were readily available to the INL’s Office of Technology Deployment. However, the accomplishments cataloged in the report reflect the achievements and creativity of the researchers, technicians, support staff, and operators of the INL workforce.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Pre-Feasibility Analysis of Pellet Manufacturing on the Former Loring Air Force Base Site

The U.S. Environmental Protection Agency (EPA) Office of Solid Waste and Emergency Response, in accordance with the RE-Powering America's Lands initiative, engaged the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) to conduct feasibility studies to assess the viability of developing renewable energy generating facilities on contaminated sites. This site, in Limestone, Maine—formerly the location of the Loring Air Force Base but now owned by the Aroostook Band of Micmac—was selected for the potential to produce heating pellets from woody feedstock. Biomass was chosen as the renewable energy resource to evaluate based on abundant woody-biomass resources available in the area. NREL also evaluates potential savings from converting existing Micmac property from oil-fired heating to pellet heating.

09 BIOMASS FUELS↗
DOE OSTI2014

Technology Deployment Annual Report 2014

This report is a summary of key Technology Deployment activities and achievements for 2014, including intellectual property, granted copyrights, royalties, license agreements, CRADAs, WFOs and Technology-Based Economic Development. Idaho National Laboratory (INL) is a Department of Energy (DOE) multi-program national laboratory that conducts research and development in all DOE mission areas. Like all other federal laboratories, INL has a statutory, technology transfer mission to make its capabilities and technologies available to all federal agencies, to state and local governments, and to universities and industry. To fulfill this mission, INL encourages its scientific, engineering, and technical staff to disclose new inventions and creations to ensure the resulting intellectual property is captured, protected, and made available to others who might benefit from it. As part of the mission, intellectual property is licensed to industrial partners for commercialization, creating jobs and delivering the benefits of federally funded technology to consumers. In other cases, unique capabilities are made available to other federal agencies or to regional small businesses to solve specific technical challenges. INL employees also work cooperatively with researchers and technical staff from the university and industrial sectors to further develop emerging technologies. In our multinational global economy, INL is contributing to the development of the next generation of engineers and scientists by licensing software to educational instiutitons throughout the world. This report is a catalog of selected INL technology transfer and commercialization transactions during this past year. The size and diversity of INL technical resources, coupled with the large number of relationships with other organizations, virtually ensures that a report of this nature will fail to capture all interactions. Recognizing this limitation, this report focuses on transactions that are specifically authorized by technology transfer legislation (and corresponding contractual provisions) or involve the transfer of legal rights to technology to other parties. This report was compiled from primary records, which were readily available to the INL’s Office of Technology Deployment. However, the accomplishments cataloged in the report reflect the achievements and creativity of the researchers, technicians, support staff, and operators of the INL workforce.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Time dependent supervisory control update with FARM using rolling window

This report describes improvements to the Feasible Actuator Range Modifier (FARM) component of the RAVEN-based HYBRID framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON plug-in that solves the power dispatch problem. The solution to the dispatch problem involves economically optimal dispatches that satisfy limits on production variables and their rates of variation (explicit constraints) as well as process variables tied to the service life of equipment (implicit constraints). FARM serves to validate or confirm that a HERON solution for explicit constraints also satisfies the implicit constraints. FARM-alpha was released by Argonne National Laboratory in January 2021 followed by FARM-Beta in January 2022 with the latter providing increased flexibility for the user. In this report, FARM-Gamma, the latest version of the code, is described. The major improvement is the implementation of a system identification algorithm based on the Dynamic Mode Decomposition with Control (DMDc) coupled with a “Rolling Window” scheme that allows obtaining linear time-varying state-space models. This feature equips FARM with the most accurate approximation of system dynamics, and it relieves the user from the burden of performing an exhaustive off-line characterization of the dynamics. FARM-Gamma capabilities are assessed by solving the power dispatch problem for a representative IES unit. The simulation times corresponding to the different releases are estimated and compared. These values capture the increasing computational burden of the successively higher fidelity state-space models adopted by FARM-Alpha, FARM-Beta and FARM-Gamma. The code implementation provides significant flexibility, i.e., the user can always select the most suitable version of FARM according to the problem to be solved and the available computational resources. It is anticipated that FARM will play a role in addressing several future IES applications. We outline how it can support the coordinated management and safe operation of a nuclear plant coupled to industrial processes to produce hydrogen and synfuels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1982

Computational modeling of multispectral remote sensing systems: Background investigations

A computational model of the deterministic and stochastic process of remote sensing has been developed based upon the results of the investigations presented. The model is used in studying concepts for improving worldwide environment and resource monitoring. A review of various atmospheric radiative transfer models is presented as well as details of the selected model. Functional forms for spectral diffuse reflectance with variability introduced are also presented. A cloud detection algorithm and the stochastic nature of remote sensing data with its implications are considered.

Aherron, R. M.↗