Sensitivity Analysis of Validation Strategies for the National Solar Radiation Database
This poster provides an overview of the sensitivity analysis of validation strategies for the National Solar Radiation Database.
14 SOLAR ENERGY↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Improving the Accuracy of the National Solar Radiation Database (NSRDB) Using High-Resolution Data
This presentation provides an overview of improving the accuracy of the National Solar Radiation Database (NSRDB) using high-resolution data.
14 SOLAR ENERGY↗
A Status Update on the National Solar Radiation Database (NSRDB)
This presentation provides a status update on the National Solar Radiation Database (NSRDB).
long-term variability↗
India Solar Resource Data: National Solar Radiation Database (NSRDB)
The National Solar Radiation Database (NSRDB) provides high-resolution solar radiation data for long periods of time, which allows user to have a clear understanding of the spatial and temporal correlation of the data to determine the true impact of solar variability on the grid. This fact sheet specifically outlines solar resource data for India included in NSRDB.
energy systems↗
Database Management Module Framework for Dynamic Contingency Analysis and Visualization
The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.
Cascading, dynamic simulations, database managemen↗
The National Solar Radiation Database: Current Status
This presentation provides and overview of the current status of the National Solar Radiation Database (NSRDB).
FARMS↗
COVID ‐19 outcomes in patients with cancer: Findings from the University of California health system database
Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings.
60 APPLIED LIFE SCIENCES↗
Engineering evaluation of the EQSIM simulated ground-motion database: The San Francisco Bay Area region
Ground-motion simulations for infrequent earthquake scenarios are gaining increasing interest in the engineering community for their potential to inform performance-based structural design and assessment, particularly in regions where major earthquakes are expected, but recordings from consistent historical events are not available. However, the absence of empirical data makes the evaluation of such scenarios and the interpretation of the simulation results very challenging. In this context, this paper presents the evaluation of the first EQSIM (v.1.1.0) ground-motion simulations generated for the San Francisco Bay Area (SFBA) region. The current database, which is at the first stages of development, includes eight realizations of a Hayward Fault M w 7 event. The evaluation of the simulated motions is first conducted on the average ground-motion amplitudes through comparison against the NGA-W2 GMPEs and a selected population of real records. A methodology for selecting a population of real records consistent with the simulated event is proposed. The objective of the proposed evaluation is twofold: (1) build confidence in the realistic character of the simulated motions for their use in engineering applications and (2) offer a critical physics-based interpretation of the simulation results that can help improve key features of the simulation models. To further investigate the implications of using the simulated ground motions for site-specific structural assessments, the ASCE7-16 approach is employed for the analysis of two hazard-consistent near-field sites in the SFBA. Results are discussed. Furthermore, this study offers a critical review of the EQSIM (v.1.1.0) SFBA ground-motion simulations and suggestions for improving the earthquake rupture models.
58 GEOSCIENCES↗
Distance Restraints from Crosslinking Mass Spectrometry: Mining a Molecular Dynamics Simulation Database to Evaluate Lysine-Lysine Distances
Integrative structural biology models the structures of protein complexes that are intractable by classical structural methods (because of extreme size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such method is chemical cross-linking mass spectrometry (XL-MS), in which cross-linked peptides, derived from a covalently cross-linked protein complex and identified by liquid chromatography-mass spectrometry, pinpoint protein residues close in three-dimensional space. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 Å long when fully extended. However, XL-MS studies on proteins of known structure frequently report cross-links that exceed this distance. Typically, a tolerance of ~3 Å is added to the theoretical maximum to account for this observation, with little justification for the value chosen. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of all protein folds, to investigate the change in lysine-lysine distances resulting from native-state dynamics on the time-scale of tens of nanoseconds. We conclude that observed cross-links are consistent with a protein structure if the distance between cross-linked lysine Nζ atoms is less than the cross-linker length plus 11.3 Å. For DSS or BS3, this corresponds to a Cα to Cα distance of 30.4 Å. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures, and indicates the appropriate values of an XLMS derived distance constraint to use in structural modeling.
Environmental Molecular Sciences Laboratory↗
Non-uniform active learning for Gaussian process models with applications to trajectory informed aerodynamic databases
The ability to non-uniformly weight the input space is desirable for many applications, and has been explored for space-filling approaches. Increased interests in linking models, such as in a digital twinning framework, increases the need for sampling emulators where they are most likely to be evaluated. In particular, here we apply non-uniform sampling methods for the construction of aerodynamic databases. This paper combines non-uniform weighting with active learning for Gaussian Processes (GPs) to develop a closed-form solution to a non-uniform active learning criterion. We accomplish this by utilizing a kernel density estimator as the weight function. We demonstrate the need and efficacy of this approach with an atmospheric entry example that accounts for both model uncertainty as well as the practical state space of the vehicle, as determined by forward modeling within the active learning loop.
42 ENGINEERING↗
Energetics of cobalt alloys and compounds and solute–vacancy binding in fcc cobalt: A first-principles database
Using extensive first-principles density functional calculations, we calculate thermodynamic properties of binary fcc cobalt-based alloys with 25 different solute elements. For each solute element X, we calculate its (a) nearest- and next-nearest-neighbor solute–vacancy binding energy, (b) dilute impurity mixing energy with respect to the equilibrium and hypothetical fcc-based reference states of the solute, (c) enthalpy of formation of cobalt-rich binary ordered compounds in the Co–X system, (d) solubility enthalpy, and other derived quantities. Here, we find that the solute–vacancy binding energies of all the studied solutes in fcc cobalt are positive (indicating favorable binding), in contrast to nickel, aluminum, magnesium, and copper-based alloys, where mid 3d transition metal solutes have unfavorable solute–vacancy binding. We study the physical and chemical effects influencing solute–vacancy binding energy, and find that (a) it correlates broadly with solute size—larger solute atoms possess stronger binding with vacancies—and this is understood in terms of strain relief and secondary next-nearest-neighbor interactions, and (b) it follows a parabolic trend as a function of d-occupancy across the transition metal series—falling to a minimum at the middle of the series—and this is understood in terms of a d-band filling effect. We also find this d-band filling effect in other calculated quantities such as the dilute impurity volumes and dilute impurity mixing energies. To aid in building thermodynamic databases, we tabulate all the calculated thermodynamic quantities, and compare them with experimental phase diagrams data and previous literature, and find good agreement where such data is available.
36 MATERIALS SCIENCE↗
A regression-based approach to estimating retrofit savings using the Building Performance Database
Retrofitting building systems is known to provide cost-effective energy savings. This article addresses how the Building Performance Database is used to help identify potential savings. Currently, prioritizing retrofits and computing their expected energy savings and cost/benefits can be a complicated, costly, and an uncertain effort. Prioritizing retrofits for a portfolio of buildings can be even more difficult if the owner must determine different investment strategies for each of the buildings. Meanwhile, we are seeing greater availability of data on building energy use, characteristics, and equipment. These data provide opportunities for the development of algorithms that link building characteristics and retrofits empirically. In this paper we explore the potential of using such data for predicting the expected energy savings from equipment retrofits for a large number of buildings. We show that building data with statistical algorithms can provide savings estimates when detailed energy audits and physics-based simulations are not cost- or time-feasible. We develop a multivariate linear regression model with numerical predictors (e.g., operating hours, occupant density) and categorical indicator variables (e.g., climate zone, heating system type) to predict energy use intensity. The model quantifies the contribution of building characteristics and systems to energy use, and we use it to infer the expected savings when modifying particular equipment. We verify the model using residual analysis and cross-validation. We demonstrate the retrofit analysis by providing a probabilistic estimate of energy savings for several hypothetical building retrofits. We discuss the ways understanding the risk associated with retrofit investments can inform decision making. The contributions of this work are the development of a statistical model for estimating energy savings, its application to a large empirical building dataset, and a discussion of its use in informing building retrofit decisions.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
The International Database of Efficient Appliances (IDEA): A new tool to support appliance energy-efficiency deployment
Appliance energy-efficiency programs are a central component of many countries’ energy-policy portfolios. A major barrier to optimal implementation of these programs is lack of data to determine market baselines, assess the potential for cost-effective energy savings, and track markets over time to evaluate and verify program impacts. To address this gap, we have developed the International Database of Efficient Appliances (IDEA), a suite of software tools that automatically gathers data that is currently dispersed across various online sources and compiles it into a unified repository of information on efficiency, price, and features for a diversity of appliances and devices in markets around the world. In this article we describe the framework and functionality of IDEA, and we demonstrate its power as a resource for research and policy development related to appliance energy efficiency. Using IDEA data for refrigerators in China and India, we assess the potential for cost-effective energy savings within each market by computing robust indicators that can also be easily compared across different appliances and markets. We find that significant cost-effective savings are available on both markets. We discuss implications for the development of future energy-efficiency deployment programs.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Coordination environment of Si in calcium silicate hydrates, silicate minerals, and blast furnace slags: A XANES database
Understanding the silicate polymerization of calcium silicate hydrate (C-S-H) gel and its crystalline polymorphs is important in cement science. NMR can determine Si environments, but the measurement can be time-consuming and provides no spatial information. X-ray absorption near-edge structure (XANES) spectroscopy is a fast tool for probing Si coordination, possibly with spatial information. However, there lacks an understanding of Si K-edge XANES spectra of cement-related silicate phases. Here, a Si K-edge XANES spectral database of nanocrystalline C-S-H, C-S-H minerals, blast-furnace slags, and metakaolin is provided. Si K-edge of C-S-H minerals shifts to higher energies with higher polymerized Si and lower CaSi connectivity in the Si second nearest neighbor shell. Si K-edge energy shows weak correlations with Ca/Si ratio, average SiO bond length, and SiO{sub 4} distortion due to the structural complexity of silicates. The substitution of Al for Si shifts the Si K-edge of tobermorite and slags to higher energies.
36 MATERIALS SCIENCE↗
Timing of Radiation Therapy in Pediatric Wilms Tumor: A Report From the National Cancer Database
To determine, using the National Cancer Database (NCDB), the impact of the surgery to radiation therapy interval (SRI) on survival in contemporary patients with Wilms tumor (WT).
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Phase stability and thermodynamic database validation in a set of non-equiatomic Al-Co-Cr-Fe-Nb-Ni high-entropy alloys
A series of six high-entropy alloys in non-equiatomic proportions were produced to study the phase stability across a range of compositions within the Al-Co-Cr-Fe-Nb-Ni system. Phase identification was performed using SEM, TEM, and XRD and computational tools were employed for comparison to the experimental findings. Complex microstructures were obtained following exposure at 900 °C with precipitation of Laves, NiAl, γ' and δ phases. Primary and secondary Laves populations were identified and found to become more stable with increasing Fe and Nb content. Additions of Nb promoted the formation of thin, plate-like, δ phase at the expense of the secondary Laves. The NiAl phase was observed to precipitate in the alloys with high Fe content, above the γ' solvus temperature. Overall, the thermodynamic predictions using Thermo-Calc with the TCNi8 database were accurate with respect to identifying the phase composition, while TTNi8 provided good phase stability results. Furthermore, significant differences were observed with respect to the solvus temperatures of the precipitate phases.
36 MATERIALS SCIENCE↗
Scintillator Library: A database of inorganic and organic scintillator properties
The Scintillator Library (scintillator.lbl.gov) is a database of scintillator properties hosted by Lawrence Berkeley National Laboratory in a web-accessible format. It contains a variety of measured inorganic and organic scintillator properties extracted from peer-reviewed literature and manufacturer specifications. Data housed within the Scintillator Library supply an important resource for developers of scintillator-based detection systems and an aid for scientists seeking to establish connections between fundamental material and chemical properties and the associated scintillation performance.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Improved correlations of the fuel/cladding liquid penetration rate with the out-of-pile transient database
Here, utilizing data from the Out-of-Pile Transient Database (OPTD), we developed advanced correlations for the cladding liquid penetration rate in metallic fuels used in sodium-cooled fast reactors (SFRs). Based on the available OPTD data, our research highlights the key role of Pu concentration in influencing the liquid penetration behavior, showing different threshold fuel-cladding interaction temperatures, with burnup playing a substantial role, particularly in fuels with a 19% Pu concentration. The penetration rate exhibits a parabolic, diffusion-limited behavior, thereby facilitating predictions of maximum liquid penetration depth over time. These correlations are significantly more accurate, under a variety of conditions, compared to existing single-parameter models, and enhance our understanding of SFR metallic fuel behavior, promoting safer and more efficient reactor operations.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗