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DOE OSTI2021

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

NASA NTRSDate not supplied

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗

DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

Xie, Yu↗

DOE OSTI2016

A Fast All-sky Radiation Model for Solar applications (FARMS): Algorithm and performance evaluation

Not Available

Xie, Yu↗

DOE OSTI2026

Heat load measurements for the PIP-II pHB650 cryomodule

Phase-3 testing of the pHB650 cryomodule at the PIP-II Injector Test Facility was conducted to evaluate the effectiveness of heat load mitigations performed after earlier phases of testing and to continue pinpointing any sources of unexpectedly high heat loads.. The programme measured HTTS, LTTS, and 2 K isothermal/non-isothermal loads under "standard", "linac", and "simulated dynamic" operating modes, recording data both inside the cryomodule and across the bayonet can circuits. Thermal-acoustic oscillations were eliminated by replacing the original G10 cooldown-valve stem with a stainless-steel stem fitted with wipers. A newly developed Python script automated acquisition of ACNET data, performed real-time heat-load calculations, and generated plots and tables that were posted to the electronic logbook within minutes, vastly reducing manual effort and accelerating feedback between SRF and cryogenics teams. Analysis showed that JT heat-exchanger effectiveness and temperature stratification in the two-phase and relief piping strongly influence the observed loads and helped isolate sources of excess heat. The campaign demonstrates that rigorous pre-test planning, real-time diagnostics, and automated reporting can improve both accuracy and efficiency, providing a template for future PIP-II cryomodule tests and for implementing targeted heat-load mitigations.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.] (ORCID:↗

DOE OSTI2015

Hydropower Projects: Fiscal Years 2008 - 2014

The Water Power Program helps industry harness this renewable, emissions-free resource to generate environmentally sustainable and cost-effective electricity. Through support for public, private, and nonprofit efforts, the Water Power Program promotes the development, demonstration, and deployment of advanced hydropower devices and pumped storage hydropower applications. These technologies help capture energy stored by diversionary structures, increase the efficiency of hydroelectric generation, and use excess grid energy to replenish storage reserves for use during periods of peak electricity demand. In addition, the Water Power Program works to assess the potential extractable energy from domestic water resources to assist industry and government in planning for our nation’s energy future. From FY 2008 to FY 2014, DOE’s Water Power Program announced awards totaling approximately $62.5 million to 33 projects focused on hydropower. Table 1 provides a brief description of these projects.

13 HYDRO ENERGY↗

NASA NTRS1992

A survey of commercial object-oriented database management systems

The object-oriented data model is the culmination of over thirty years of database research. Initially, database research focused on the need to provide information in a consistent and efficient manner to the business community. Early data models such as the hierarchical model and the network model met the goal of consistent and efficient access to data and were substantial improvements over simple file mechanisms for storing and accessing data. However, these models required highly skilled programmers to provide access to the data. Consequently, in the early 70's E.F. Codd, an IBM research computer scientists, proposed a new data model based on the simple mathematical notion of the relation. This model is known as the Relational Model. In the relational model, data is represented in flat tables (or relations) which have no physical or internal links between them. The simplicity of this model fostered the development of powerful but relatively simple query languages that now made data directly accessible to the general database user. Except for large, multi-user database systems, a database professional was in general no longer necessary. Database professionals found that traditional data in the form of character data, dates, and numeric data were easily represented and managed via the relational model. Commercial relational database management systems proliferated and performance of relational databases improved dramatically. However, there was a growing community of potential database users whose needs were not met by the relational model. These users needed to store data with data types not available in the relational model and who required a far richer modelling environment than that provided by the relational model. Indeed, the complexity of the objects to be represented in the model mandated a new approach to database technology. The Object-Oriented Model was the result.

Atkins, John↗

DOE OSTI2024

Measuring Economy-Wide Circularity of the United States: An Input-Output Model in Mass Units

The ideal of creating closed material cycles by transforming the way we make, use and repurpose goods has become known as the circular economy. Besides its visionary appeal, material efficiency strategies central to circular economy can allow us to meet decarbonization goals that are otherwise out of reach. Production of basic materials such as cement, iron and steel and petrochemicals is one of the largest drivers of greenhouse gas emissions. Measuring circularity, and understanding its relationship with other sustainability metrics, however, is still difficult due to lack of data in mass units covering the entire economic system. Input-output (I-O) tables were originally created as a means of tracking the monetary flows that represent exchanges of goods and services within an economy, but have found additional uses in life cycle assessment and material flow accounts. In the traditional approach of environmentally extended I-O tables, emissions and energy data augment monetary flows. This approach can lead to price effects that distort physical quantities. Also, circular economy strategies and their goals relate to mass, not monetary flows. Therefore, it is best to simulate them using physical quantities. With these issues in mind, we have developed I-O tables in mass units to measure the flow of goods in the U.S. economy. This allows us to better measure how circular the economy really is, and how policy changes to affect this circularity may also affect decarbonization goals. Improving knowledge of these linkages could allow manufacturers to make changes in their production to achieve their sustainability and decarbonization targets. Our tool also provides a standard approach and public repository for data in physical units, making such data more available, useful, and meaningful. Following an established set of material flow metrics used by the European Union, we have used our tool to calculate material footprints over time differentiated by oil and gas versus other extractive industries. This approach also shows the relative trade balances of the U.S. in materials. We have developed a case study for the iron and steel sector, showing how different decarbonization scenarios affect not only economy-wide greenhouse gas emissions, but also total material use.

circular economy↗

DOE OSTI2020

Calculating Potential Radiological Emissions for Waste Management Activities at INL - 20068

At Idaho National Laboratory (INL), work involving radionuclides is evaluated for potential emissions from a project in order to comply with the National Emission Standards for Hazardous Air Pollutants (NESHAP) regulations, 40 CFR 61 Subpart H. Emission calculations are documented in an Air Permitting Applicability Determination (APAD) to analyze unmitigated and mitigated emissions and determine if an Application to Construct (ATC) or continuous monitoring is required. To calculate the unmitigated and mitigated emissions, a spreadsheet was developed to provide ease in determining potential emissions by providing the maximum operating temperature and the material being used. The spreadsheet aids in determining the potential emissions for research projects and waste management activities at Materials and Fuels Complex (MFC) and other locations across the INL site. Furthermore, it can also be used for periodic confirmatory measurements (PCM) to justify low emissions. Elements that factor into the unmitigated and mitigated calculations include the amount of each radionuclide used (in curies or grams), specific activity (if amount is given in grams), the temperature the material is heated to in Celsius, the dose conversion factor which is derived from Clean Air Act Assessment Package - 1988 (CAP-88) modeling, and the number of HEPA filters used for mitigated measures. The main drivers for calculating the unmitigated emissions for a project are the amount used per radionuclide, the maximum operating temperature, and the location of the work. The maximum operating temperature determines the airborne release factor which is dependent on the physical state of the radionuclide. Prior to October 2017, if the radionuclide was heated to greater than 100 deg. C, the radionuclide was assumed to be a gas, which has the highest airborne release factor. This assumption would be overly conservative for radionuclides with high melting and boiling points, which provided a challenge to demonstrate low emissions. In October 2017, the Environmental Protection Agency (EPA) approved an alternative method for INL. This method allows the airborne release factor to be determined by using the melting point and 90% of the boiling point of the radionuclide. This methodology was included in the spreadsheet to allow unmitigated emission calculations for APADs to be completed more efficiently and effectively. Results show a reduction in time completing air emission calculations as well as lower total emissions across all facilities at INL. MFC annual emissions were reduced by 62% from the previous year and Research and Education Campus (REC) facilities were reduced by 38% due to implementation of the approved alternative method. Time spent on APADs, PCMs, and documentation for the annual NESHAP report was also reduced significantly. The spreadsheet provided in Table I provides the potential emission calculations for the 'Advanced Retrieval and Disposition Techniques for Remote Handled Mixed Low Level Waste (RH MLLW) at the Radioactive Scrap and Waste Facility (RSWF)' project. Calculations show the Potential Effective Dose Equivalent (PEDE) at RSWF to be 7.27 E-04 mrem/yr (7.27 E-09 Sv/yr) which is well below the 0.1 mrem/yr threshold. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗

DOE OSTI2011

GROUNDWATER MONITORING REPORT GENERATION TOOLS - 12005

Compliance with National and State environmental regulations (e.g. Resource Conservation and Recovery Act (RCRA) and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) aka SuperFund) requires Savannah River Site (SRS) to extensively collect and report groundwater monitoring data, with potential fines for missed reporting deadlines. Several utilities have been developed at SRS to facilitate production of the regulatory reports which include maps, data tables, charts and statistics. Components of each report are generated in accordance with complex sets of regulatory requirements specific to each site monitored. SRS developed a relational database to incorporate the detailed reporting rules with the groundwater data, and created a set of automation tools to interface with the information and generate the report components. These process improvements enhanced quality and consistency by centralizing the information, and have reduced manpower and production time through automated efficiencies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Toward Improved Modeling of Spectral Solar Irradiance for Solar Energy Applications: Preprint

This study introduces the National Renewable Energy Laboratory's (NREL's) recent efforts to extend the capability of the Fast All-sky Radiation Model for Solar applications (FARMS) by computing spectral solar irradiances over both horizontal and inclined surfaces. A new model is developed by computing the optical thickness of the atmosphere using a spectral irradiance model for clear-sky conditions, SMARTS2. A comprehensive lookup table (LUT) of cloud bidirectional transmittance distribution functions (BTDFs) is precomputed for 2002 wavelength bands using an atmospheric radiative transfer model, libRadtran. The solar radiation transmitted through the atmosphere is given by considering all possible paths of photon transmission and the relevent scattering and absorption attenuation. Our results indicate that this new model has an accuracy that is similar to that of state-of-the-art radiative transfer models, but it is significantly more efficient.

14 SOLAR ENERGY↗

DOE OSTI2012

Groundwater Monitoring Report Generation Tools - 12005

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Understanding Solar Photovoltaic System Performance: An Assessment of 75 Federal Photovoltaic Systems

This report presents a performance analysis of 75 photovoltaic systems based on PV system production data collected as part of a FEMP Federal PV Performance Assessment project combined with co-incident insolation, and ambient temperature to analyze how actual performance compares with a performance model. FEMP collaborated with 17 Federal agencies and sub-agencies to collect the information required to analyze the performance of each system. The systems represent a total capacity of 30,714 kW and range in size from 1 kW to 4,043 kW, with an average size of 410 kW, and were installed between 2011 and 2020. The data is analyzed for Key Performance Indicators, Availability, Performance Ratio and Energy Ratio by comparing the measured production data to model production data. The System Advisor Model (SAM) combines a description of the system (such as inverter capacity, de-rating for temperature, balance-of-system efficiency) with environmental parameters (coincident solar and temperature data) to calculate predicted performance. The performance metrics are calculated by lining up the measured production data with the model estimate on an hour-by-hour, day-by-day, or month-by-month basis (depending on the interval resolution of the production data). A report with system description, photo of the system, special assumptions made for the site, graph of measured production and model production, table of key performance indicators, and links to O&M resources that might improve performance was produced and delivered to site and agency staff with a short on-line briefing.

14 SOLAR ENERGY↗

NASA NTRS2019

Space Communications and Navigation Validation: Extracting Data for the Strategic Center for Networking, Integration, and Communications Scheduling Algorithms

Efficiency in communication system architecture performance between Space Communications and Navigation (SCaN) assets and missions is crucial, as space communication is varied, complex, and often not utilized to its full potential. The SCaN Strategic Center for Networking, Integration, and Communications (SCENIC) new scheduling algorithms, which are designed to simulate the allocation of resources between SCaN assets and missions, have the potential to simulate an increase of this efficiency; however, they require real-world data to be validated against. The purpose of this project was to extract said validation data, which details the frequency and duration of utilized contact windows between missions and assets in the Near Earth Network (NEN), Space Network (SN), and Deep Space Network (DSN). Stored as images in daily operations summaries (DOSs), the tabular data existed in a variety of file formats such as.pdf, .docx, and .doc. Since the tables were stored as images, ABBYY® FineReader® (ABBYY Software Ltd.) optical character recognition (OCR) was implemented, which is a proprietary software that reads images from text. The comma separated value (CSV) output was utilized as input to a series of MATLAB® (The MathWorks, Inc.) methods for reformatting, at which point it was ready to be machine-read. Finally, the results were converted to a Microsoft Excel format for human readability. Along with being used for validation purposes, the data will also be used to map equipment degradation as a function of time to analyze the reliability of network assets.

Kontur, Noah P.↗

NASA NTRS2001

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

NASA Discipline Cardiopulmonary↗

DOE OSTI2024

ETHOS: An automated framework to generate multi-fidelity constitutive data tables and propagate uncertainties to hydrodynamic simulations

Accurate constitutive data, such as equations of state and plasma transport coefficients, are necessary for reliable hydrodynamic simulations of plasma systems such as fusion targets, planets, and stars. Here, we develop a framework for automatically generating transport-coefficient tables using a parameterized model that incorporates data from both high-fidelity sources (e.g., density functional theory calculations and reference experiments) and lower-fidelity sources (e.g., average-atom and analytic models). The framework incorporates uncertainties from these multi-fidelity sources, generating ensembles of optimally diverse tables that are suitable for uncertainty quantification of hydrodynamic simulations. We illustrate the utility of the framework with magnetohydrodynamic simulations of magnetically launched flyer plates, which are used to measure material properties in pulsed-power experiments. We explore how changes in the uncertainties assigned to the multi-fidelity data sources propagate to changes in simulation outputs and find that our simulations are most sensitive to uncertainties near the melting transition. The presented framework enables computationally efficient uncertainty quantification that readily incorporates new high-fidelity measurements or calculations and identifies plasma regimes where additional data will have high impact.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1992

Evaluation of RDBMS packages for use in astronomy

Tabular data sets arise in many areas of astronomical data analysis, from raw data (such as photon event lists) to final results (such as source catalogs). The Starlink catalog access and reporting package, SCAR, was originally developed to handle IRAS data and it has been the principal relational DBMS in the Starlink software collection for several years. But SCAR has many limitations and is VMS-specific, while Starlink is in transition from VMS to Unix. Rather than attempt a major re-write of SCAR for Unix, it seemed more sensible to see whether any existing database packages are suitable for general astronomical use. The authors first drew up a list of desirable properties for such a system and then used these criteria to evaluate a number of packages, both free ones and those commercially available. It is already clear that most commercial DBMS packages are not very well suited to the requirements; for example, most cannot carry out efficiently even fairly basic operations such as joining two catalogs on an approximate match of celestial positions. This paper reports the results of the evaluation exercise and notes the problems in using a standard DBMS package to process scientific data. In parallel with this the authors have started to develop a simple database engine that can handle tabular data in a range of common formats including simple direct-access files (such as SCAR and Exosat DBMS tables) and FITS tables (both ASCII and binary).

Page, C. G.↗