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DOE OSTI2020

Process-based balance of system cost modeling for offshore wind power plants in the United States

This paper describes the development of a process-based and open-source balance of system cost model that provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays caused by weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation. Installation times show reasonable agreement with real data. Project cost sensitivities are investigated to compute the system-level impact of different design choices. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. These values quantify the cost-benefit tradeoffs and show a net-cost savings of decreasing numbers of turbines, increased turbine spacing, and fewer turbine terminations. These results demonstrate that the balance of system model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗

NASA NTRS1977

A review of applications of microwave radiometry to oceanography

The emissivity of sea ice and atmospheric precipitation was investigated. Using the above physics, the data from the Electrically Scanning Microwave Radiometers (ESMR's) on the Nimbus-5 and Nimbus-6 satellites operating at wavelengths of 1.55 cm and 8mm, respectively, can be interpreted in terms of rain rate, ice coverage, and first year versus multi-year ice determination. The rain rate data is being used to establish a climatology of rainfall over the oceans. Both ice and rain data sets have been generated for the Global Atmospheric Research Project Data Systems Test.

Wilheit, T. T., Jr.↗

DOE OSTI2021

Investigation of Delayed Neutron Sensitivities for Several ICSBEP Benchmarks using MCNP

The effective delayed neutron (β$_{eff}$) is a very important parameter for reactor and criticality applications. This parameter is equal to the difference in reactivity between delayed critical ($k_{eff}$ = 1, which requires both prompt and delayed neutrons to achieve criticality) and prompt critical ($k_p$ = 1, which requires only prompt neutrons to achieve criticality). This is often referred to as the delayed critical "window" (the region of criticality between delayed and prompt critical). β$_{eff}$ is a reactor kinetics parameters and depends on the nuclides in the system that undergo fission as well as the spectral characteristics of the system. Measurements of β$_{eff}$ have been performed for many criticality experiments. The EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) project at Los Alamos National Laboratory (LANL) aims to constrain nuclear data by using a suite of measurement types beyond $k_{eff}$. Our team has recently investigated the use of pulsed spheres for nuclear data validation. Several other measurement methods are also of interest, including β$_{eff}$ (investigated here) and reactivity coefficients (investigated in a separate work at this same meeting). One focus of our work is to determine if other methods are complimentary to the critical experiments already utilized for nuclear data validation. This is important because if a method has similar sensitivities then it will not be particularly useful for nuclear data validation as it will provide the same information as the critical experiments already being used. Here "similar" could refer to several characteristics, one being the shape of a sensitivity profile over energy. In the future, these methods will be utilized (with both existing and new experiments) in machine learning algorithms for nuclear validation, similar to what is currently done for criticality experiments. In order to use a measurement type for nuclear validation, it is necessary to obtain cross-section sensitivities for that parameter. This work looks at one approach to estimate β$_{eff}$ sensitivities by utilizing $k_{eff}$ sensitivities within Monte Carlo N-Particle ® Code Version 6.2. This is applied to several criticality benchmarks. Results are compared and the benefits and limitations of this approach are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

SFA-VirOmics

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information. PNNL’s Soil Microbiome SFA Virome Dataset Annotation page is an extension to the PNNL Soil Microbiome SFA repository on DataHub allows for exploring and downloading integrated experimental omics dataset annotations, associated experimental metadata, pre- and post-processed viral data files, and other associated materials directly related to experimental viral project data.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1983

Comparison of satellite and in situ data

A variety of data sets were available and analyzed. The data sets discussed here are: (1) SMMR-A: The Nimbus Project data release; (2) SMMR-D: The revised SMMR version produced by Wilheit and Milman; (3) SMMR-C: The SMMR version produced by Prabhakara; (4) Fleet Numerical Oceanography Center (PNOC): The individual ship reports; and (5) Reynolds Climatology. Data from SMMR and PNOC ships were compared in three different ways: (1) The difference between individual ship and SMMR observations which were close in space and time. (2) The difference between the 20 degree lat-lon one month averages for SMMR and ship, respectively. (3) The difference between the 20 degree averages and climatology, for both SMMR and ship.

Bernstein, R. L.↗

NASA NTRS1989

A rapid prototyping/artificial intelligence approach to space station-era information management and access

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Carnahan, Richard S., Jr.↗

DOE OSTI2022

Investigating Fission Reaction Rate Ratio Sensitivities [Abstract]

Reaction rate ratios are a measurable parameter for reactor and criticality applications. A number of foil irradiations and fission chamber measurements have been performed for critical assemblies at Los Alamos National Laboratory starting in the 1950’s including (i) Godiva, a bare HEU spherical assembly; (ii) Flattop-25, a spherical assembly consisting of an HEU core and a natural uranium reflector; (iii) Jezebel, a bare 239 Pu assembly; and (iv) Flattop-Pu, a spherical assembly consisting of a 239Pu core and a natural uranium reflector. Fission ratio data for 238 U(n,f)/ 235 U(n,f), 237 Np(n,f)/ 235 U(n,f), 233 U(n,f)/ 235 U(n,f) and 239 Pu(n,f)/ 235 U(n,f) were obtained and reported. The EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) project at Los Alamos National Laboratory (LANL) aims to constrain nuclear data by using a suite of measurement types beyond k-effective. Recent investigations include the use of pulsed spheres for nuclear data validation and other measurement methods of interest. One focus of the work is to determine if other methods are complimentary to the critical experiments utilized for nuclear data validation. It is anticipated the investigations will help inform methods that may be utilized in machine learning algorithms for nuclear validation. In order to use a measurement type for nuclear validation, it is necessary to obtain cross-section sensitivities for parameters. This work looks at reaction rate ratio sensitivities with SENSMG and Monte Carlo N-Particle R Code Version 6.21.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Scientific data from precipitation driver response model intercomparison project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

Scientific Data From Precipitation Driver Response Model Intercomparison Project

Precipitation Driver Response Model Intercompariso↗

NASA NTRS1993

Assessing efficiency of software production for NASA-SEL data

This paper uses production models to identify and quantify efficient allocation of resources and key drivers of software productivity for project data in the NASA-SEL database. While analysis allows identification of efficient projects, many of the metrics that could have provided a more detailed analysis are not at a level of measurement to allow production model analysis. Production models must be used with proper parameterization to be successful. This may mean a new look at which metrics are helpful for efficiency assessment.

Vonmayrhauser, Anneliese↗

DOE OSTI2025

Pipeline for Integrated Projects in Energy Systems (PIPES): A Tool for Integrated System Planning [Slides]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1992

National Space Science Data Center data archive and distribution service (NDADS) automated retrieval mail system user's guide

The National Space Science Data Center (NSSDC) has developed an automated data retrieval request service utilizing our Data Archive and Distribution Service (NDADS) computer system. NDADS currently has selected project data written to optical disk platters with the disks residing in a robotic 'jukebox' near-line environment. This allows for rapid and automated access to the data with no staff intervention required. There are also automated help information and user services available that can be accessed. The request system permits an average-size data request to be completed within minutes of the request being sent to NSSDC. A mail message, in the format described in this document, retrieves the data and can send it to a remote site. Also listed in this document are the data currently available.

Perry, Charleen M.↗

DOE OSTI2024

PIPES (Pipeline for Integrated Projects in Energy Systems) [SWR-24-89]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. https://github.com/nrel-pipes/pipes-api https://github.com/nrel-pipes/pipes-web https://github.com/nrel-pipes/nrel-pipes

Gu, Jianli↗

NASA NTRS1975

Skylab vectorcardiograph: System description and in flight operation

A vectorcardiograph system was used to measure cardiac electrical activity of Skylab crewmen. This system was chosen because of its data-quantification advantages. The vectorcardiograph was required to meet recommended American Heart Association specifications, to withstand space environmental extremes, and to facilitate data gathering in the weightless environment. The vectorcardiograph system performed without failure, and all projected data were acquired. The appendix lists the design specifications used for the Skylab vectorcardiograph system.

Lintott, J.↗

NASA NTRS1978

The free jet as a simulator of forward velocity effects on jet noise

A thorough theoretical and experimental study of the effects of the free-jet shear layer on the transmission of sound from a model jet placed within the free jet to the far-field receiver located outside the free-jet flow was conducted. The validity and accuracy of the free-jet flight simulation technique for forward velocity effects on jet noise was evaluated. Transformation charts and a systematic computational procedure for converting measurements from a free-jet simulation to the corresponding results from a wind-tunnel simulation, and, finally, to the flight case were provided. The effects of simulated forward flight on jet mixing noise, internal noise and shock-associated noise from model-scale unheated and heated jets were established experimentally in a free-jet facility. It was illustrated that the existing anomalies between full-scale flight data and model-scale flight simulation data projected to the flight case, could well be due to the contamination of flight data by engine internal noise.

Ahuja, K. K.↗

NASA NTRS2006

A Whale of a Tale: Creating Spacecraft Telemetry Data Analysis Products for the Deep Impact Mission

A description of the Whale product generation utility and its means of analyzing project data for Deep Impact Missions is presented. The topics include: 1) Whale Definition; 2) Whale Overview; 3) Whale Challenges; 4) Network Configuration; 5) Network Diagram; 6) Whale Data Flow: Design Decisions; 7) Whale Data Flow Diagram; 8) Whale Data Flow; 9) Whale Team and Users; 10) Creeping Requirements; 11) Whale Competition; 12) Statistics: Processing Time; 13) CPU and Disk Usage; 14) The Ripple Effect of More Data; and 15) Data Validation and the Automation Challenge.

ground data systems↗

DOE OSTI2023

Understanding the impact of nuclear-data covariances on various integral responses using adjustment

The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project created a library of sensitivities for nine different integral responses with respect to nuclear data. These integral responses were obtained from measurements at LLNL (Lawrence Livermore National Laboratory) pulsed spheres, critical and sub-critical assemblies. At the same time, covariances for ENDF/B-VIII.0 were processed at LANL (Los Alamos National Laboratory). The combination of these data allow us to study the impact of nuclear-data covariances on various integral responses, either by forward-propagating covariances via sensitivities, or by using nuclear data, integral responses, and sensitivities for adjustment. Here, we will present: the impact of 1 H, 9 Be, 12 C, 27 Al, 56 Fe, 235,238 U, and 239,240 Pu ENDF/B-VIII.0 covariances on simulated bounds of the following integral responses: LLNL pulsed-spheres neutron-leakage spectra, the effective neutron multiplication factor, reaction rates, and reactivity coefficients of ICSBEP critical assemblies. Also, adjustment results with the same nuclear-data covariances and responses will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

An Edge Alignment-Based Orientation Selection Method for Neutron Tomography

Neutron computed tomography (nCT) is a 3D char-acterization technique used to image the internal morphology or chemical composition of samples in biology and materials sciences. A typical workflow involves placing the sample in the path of a neutron beam, acquiring projection data at a predefined set of orientations, and processing the resulting data using an analytic reconstruction algorithm. Typical nCT scans require hours to days to complete and are then processed using conventional filtered back-projection (FBP), which performs poorly with sparse views or noisy data. Hence, the main methods in order to reduce overall acquisition time are the use of an improved sampling strategy combined with the use of advanced reconstruction methods such as model-based iterative reconstruction (MBIR). In this paper, we propose an adaptive orientation selection method in which an MBIR reconstruction on previously-acquired measurements is used to define an objective function on orientations that balances a data-fitting term promoting edge alignment and a regularization term promoting orientation diversity. Using simulated and experimental data, we demonstrate that our method produces high-quality reconstructions using significantly fewer total measurements than the conventional approach.

Yang, Diyu↗