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DOE OSTI2022

Recent Improvements in the National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) has significantly evolved since the first release of the point source database in 1993. The NSRDB has been widely used by the solar energy industry to provide long-term time-series solar resource data for various project phases. The NSRDB represents the state of the art in the satellite-based estimation of solar resource information and uses a unique physics-based modeling approach that allows improvements in accuracy with the deployment of the next-generation geostationary satellites. This poster provides an overview of (1) the improved spatiotemporal resolution; (2) on-demand services and their applications; (3) future Improvements, such as a new direct normal irradiance model and new methods to gap-fill missing data using physics-guided machine learning; (4) data quality; and (5) data dissemination.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗

DOE OSTI2023

Tabulated Database of Closed-Loop Geothermal Systems Performance for Cloud-Based Technical and Economic Modeling of Heat Production and Electricity Generation: Preprint

To better understand the heat production, electricity generation performance and economic viability of closed loop geothermal systems in hot-dry-rock, the Closed Loop Geothermal Group, a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and super-critical CO2) while varying seven continuous independent parameters of interest (i.e., mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an Organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the TEA (techno-economic analysis) script are provided.

co-axial↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

In the face of increasing frequency of extreme events, enhancing resilience and reliability of energy infrastructure demands innovative solutions. Hydropower, with its inherent generation flexibility and grid-forming capability, offers significant potential for enhancing power grid resilience through the establishment of microgrids. To enable informed decision-making and strategic planning, we present the Hydropower Resilience Database (HRD) that integrates data from various sources such as Oakridge National Laboratory (ORNL) HydroSource, National Inventory of Dams, and US Western Grid database. By integrating relevant information on hydropower plant characteristics, including dams, reservoirs, and connected electrical grid, this resource enables hydropower plant owners, utilities, and community stakeholders to identify and evaluate the feasibility of using hydropower resources in microgrids to support nearby communities and critical infrastructure in various challenging scenarios. Using HRD, a set of metrics are evaluated to quantify the capability of hydropower plants to support essential microgrid functions. An interactive tool is developed using ArcGIS, enabling the visualization and analysis using HRD. Our research contributes to strategic planning efforts for fortifying energy infrastructure, ensuring reliable power supply during disruptions, and advancing the development of robust and resilient energy systems in regions susceptible to grid vulnerabilities.

13 HYDRO ENERGY↗

DOE OSTI2023

Hydropower Resilience Database for Assessing Microgrid Formation Capability and Enhancing Power Grid Resilience

13 HYDRO ENERGY↗

DOE OSTI2020

Automatic and rapid calibration of urban building energy models by learning from energy performance database

Urban building energy modeling (UBEM) is attracting increasing attention in the energy modeling filed. Unlike modeling a single building using detailed building systems information, UBEM generally uses limited high-level building stock data to infer default assumptions about building characteristics and operations. Additionally, this practice inherently brings uncertainty to UBEM. This study introduced a novel method of automatic and rapid calibration of UBEM based on the annual electricity and natural gas energy use data by learning the correlations between crucial model input parameters and the building energy use from the reference building models. A case study was presented to calibrate 72 large office buildings built before 1978 in San Francisco. Seventeen model parameters were selected and Monte Carlo sampling was used to create 1000 samples that reasonably represent the parameter space. Then 1000 simulations were performed for the reference building model to create an energy performance database. The results showed that by learning from the energy performance database, it took less than four simulation runs on average to calibrate a building model. After the calibration, the distributions of each parameter were obtained to replace their single predefined default values. For example, the default lighting power density of 21.39 W/m 2 was calibrated to be 7.50 W/m 2 on average. The case study successfully demonstrated the effectiveness of the novel calibration method for UBEM in the mild climate. The method will be further tested in future for other climate zones and other building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Evaluation of trace elements in U.S. coals using the USGS COALQUAL database version 3.0. Part I: Rare earth elements and yttrium (REY)

Coal is a potential source of valuable elements such as rare earth elements and yttrium (REY). In this work, REY concentrations in U.S. domestic coals were evaluated using data from the USGS COALQUAL Database Version 3.0. The database contains a total of 7657 non-weathered, full-bed coal samples. The number of samples containing REY data points varies among elements. Assessment of data quality indicates that some of the REY data are semi-quantitative and should be used with caution. Different analytical instruments and methods with varying accuracies and precisions are thought to be the main sources of errors. Inclusion of qualified data also accounts for the sawtooth pattern of the UCC-normalized REY distribution. A new set of Q factor values was thus proposed to adjust qualified data. Consequently, mean concentrations of REY in U.S. coals were obtained with a total REY concentration of 65.5 ppm on a moisture-free whole coal basis. Further evaluation of REY in 5378 selected coal samples indicates that about 9–13% of the samples fall into the combined category of promising and highly promising coals for REY, according to the classification of Dai et al. (2017). Taking sampling bias into consideration, we further found that bituminous coal, particularly from the central Appalachian region, has the highest probability of being a source for beneficial recovery of REY. More specifically, bituminous coal from eastern Kentucky is likely to be the best option. Lastly, we conclude that U.S. domestic coal is a promising, alternative source for beneficial recovery of REY to meet the U.S. REY demand for economic growth.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2019

Urban-scale building energy consumption database: a case study for Wuhan, China

Building energy consumption accounts for 30% of the overall energy end use worldwide. This number is even much higher in urban areas. With rapid urbanization in China, cities are expanding with new constructions. It is essential to create an updated urban-scale building energy consumption database to represent energy use for different types of buildings in China, which could help urban planners, managers and decision makers to understand temporal and spatial building energy consumption distribution and ensure required electricity and/or gas supply. However, such urban-scale database is rarely found in China. This paper creates baseline EnergyPlus models for residential, small office and large office buildings and validates the baseline models using survey data from literature. Parametric simulations are conducted to consider different design factors, such as building enclosure, lighting power density, equipment power density, HVAC schedule, etc. In total 351 EnergyPlus models are generated to cover different energy use intensity scenarios. Data-driven regression analysis is conducted to predict building energy consumption using building price/rent. The prediction results are expected to provide design decision support for urban planning and power distribution for new constructions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Environmental contaminants of emerging concern in seafood – European database on contaminant levels

Marine pollution gives rise to concern not only about the environment itself but also about the impact on food safety and consequently on public health. European authorities and consumers have therefore become increasingly worried about the transfer of contaminants from the marine environment to seafood. So-called “contaminants of emerging concern” are chemical substances for which no maximum levels have been laid down in EU legislation, or substances for which maximum levels have been provided but which require revision. Adequate information on their presence in seafood is often lacking and thus potential risks cannot be excluded. Assessment of food safety issues related to these contaminants has thus become urgent and imperative. A database ( (www.ecsafeseafooddbase.eu)), containing available information on the levels of contaminants of emerging concern in seafood and providing the most recent data to scientists and regulatory authorities, was developed. The present paper reviews a selection of contaminants of emerging concern in seafood including toxic elements, endocrine disruptors, brominated flame retardants, pharmaceuticals and personal care products, polycyclic aromatic hydrocarbons and derivatives, microplastics and marine toxins. Current status on the knowledge of human exposure, toxicity and legislation are briefly presented and the outcome from scientific publications reporting on the levels of these compounds in seafood is presented and discussed. - Highlights: • Development of a European database regarding contaminants of emerging concern. • Current status on knowledge of human exposure, toxicity and legislation. • Review on the occurrence of contaminants of emerging concern in seafood.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Prevalence and Predictors of Neoadjuvant Therapy for Stage IIIA Non-Small Cell Lung Cancer in the National Cancer Database: Importance of Socioeconomic Status and Treating Institution

Purpose: The optimal locoregional therapy for stage IIIA non-small cell lung cancer (NSCLC) is controversial, with definitive chemoradiation therapy (CRT) and neoadjuvant therapy followed by surgery (NT-S) serving as competing strategies. In this study, we used the National Cancer Database to determine the prevalence and predictors of NT in a large, modern cohort of patients. Methods and Materials: Patients with stage IIIA NSCLC treated with CRT or NT-S between 2003 and 2010 at programs accredited by the Commission on Cancer were included. Predictors were categorized as clinical, time/geographic, socioeconomic, and institutional. In accord with the National Cancer Database, institutions were classified as academic/research program and as comprehensive and noncomprehensive community cancer centers. Logistic regression and random effects multilevel logistic regression were performed for univariable and multivariable analyses, respectively. Results: The cohort consisted of 18,581 patients, 3,087 (16.6%) of whom underwent NT-S (10.6% induction CRT, 6% induction chemotherapy). The prevalence of NT-S was constant over time, but there were significant relative 31% and 30% decreases in pneumonectomy and right-sided pneumonectomy, respectively, over time (P trend <.02). In addition to younger age, lower T stage, and favorable comorbidity score, indicators of higher socioeconomic status were strong independent predictors of NT-S, including white race, higher income, and private/managed insurance. The type of institution (academic/research program vs comprehensive or noncomprehensive community cancer centers, odds ratio 1.54 and 2.08, respectively) strongly predicted NT-S, but treatment volume did not. Conclusions: Neoadjuvant therapy followed by surgery was an uncommon treatment approach in Commission on Cancer programs, and the prevalence of postinduction pneumonectomy decreased over time. Higher socioeconomic status and treatment at academic institutions were significant predictors of NT-S. Further research should be performed to enable a better understanding of these disparities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Improved Survival With Radiation Therapy in Stage I-II Primary Mediastinal B Cell Lymphoma: A Surveillance, Epidemiology, and End Results Database Analysis

Background: Primary mediastinal B cell lymphoma (PMBCL) is an uncommon lymphoma for which trials are few with small patient numbers. The role of radiation therapy (RT) after standard immunochemotherapy for early-stage disease has never been studied prospectively. We used the Surveillance, Epidemiology, and End Results (SEER) database to evaluate PMBCL and the impact of RT on outcomes. Methods and Materials: We queried the SEER database for patients with stage I-II PMBCL diagnosed from 2001 to 2011. Retrievable data included age, gender, race (white/nonwhite), stage, extranodal disease, year of diagnosis, and use of RT as a component of definitive therapy. Kaplan-Meier overall survival (OS) estimates, univariate (UVA) log-rank and multivariate (MVA) Cox proportional hazards regression analyses were performed. Results: Two hundred fifty patients with stage I-II disease were identified, with a median follow-up time of 39 months (range, 3-125 months). The median age was 36 years (range, 18-89 years); 61% were female; 76% were white; 45% had stage I disease, 60% had extranodal disease, and 55% were given RT. The 5-year OS for the entire cohort was 86%. On UVA, OS was improved with RT (hazard ratio [HR] 0.446, P=.029) and decreased in association with nonwhite race (HR 2.70, P=.006). The 5-year OS was 79% (no RT) and 90% (RT). On MVA, white race and RT remained significantly associated with improved OS (P=.007 and .018, respectively). The use of RT decreased over time: 61% for the 67 patients whose disease was diagnosed from 2001 to 2005 and 53% in the 138 patients treated from 2006 to 2010. Conclusion: This retrospective population-based analysis is the largest PMBCL dataset to date and demonstrates a significant survival benefit associated with RT. Nearly half of patients treated in the United States do not receive RT, and its use appears to be declining. In the absence of phase 3 data, the use of RT should be strongly considered for its survival benefit in early-stage disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

National Cancer Database Analysis of Proton Versus Photon Radiation Therapy in Non-Small Cell Lung Cancer

Purpose: To analyze outcomes and predictors associated with proton radiation therapy for non-small cell lung cancer (NSCLC) in the National Cancer Database. Methods and Materials: The National Cancer Database was queried to capture patients with stage I-IV NSCLC treated with thoracic radiation from 2004 to 2012. A logistic regression model was used to determine the predictors for utilization of proton radiation therapy. The univariate and multivariable association with overall survival were assessed by Cox proportional hazards models along with log–rank tests. A propensity score matching method was implemented to balance baseline covariates and eliminate selection bias. Results: A total of 243,822 patients (photon radiation therapy: 243,474; proton radiation therapy: 348) were included in the analysis. Patients in a ZIP code with a median income of <$46,000 per year were less likely to receive proton treatment, with the income cohort of $30,000 to $35,999 least likely to receive proton therapy (odds ratio 0.63 [95% confidence interval (CI) 0.44-0.90]; P=.011). On multivariate analysis of all patients, non-proton therapy was associated with significantly worse survival compared with proton therapy (hazard ratio 1.21 [95% CI 1.06-1.39]; P<.01). On propensity matched analysis, proton radiation therapy (n=309) was associated with better 5-year overall survival compared with non-proton radiation therapy (n=1549), 22% versus 16% (P=.025). For stage II and III patients, non-proton radiation therapy was associated with worse survival compared with proton radiation therapy (hazard ratio 1.35 [95% CI 1.10-1.64], P<.01). Conclusions: Thoracic radiation with protons is associated with better survival in this retrospective analysis; further validation in the randomized setting is needed to account for any imbalances in patient characteristics, including positron emission tomography–computed tomography staging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Comprehensive analysis of common polymers using hyphenated TGA-FTIR-GC/MS and Raman spectroscopy towards a database for micro- and nanoplastics identification, characterization, and quantitation

Environmental contamination by micro- and nanoplastics (MNPs) is well documented with potential for their increased accumulation globally. Growing public concern over environmental, ecological, and human exposure to MNPs has led to exponential increase in publications, news articles, and reports. Significant knowledge gap exists in standardized analytical methods for the identification and quantification of MNPs from real world environmental samples. Here, in this study, we report comprehensive datasets utilizing thermogravimetric analyzer (TGA) coupled to a Fourier transformed infrared spectrometer (FTIR) and a gas chromatography/mass spectrometer (GC/MS) with corresponding Raman spectral data for the most common polymers documented to be present in the environment (35 plastics of 12 polymer types), to serve as a base line reference for the identification and quantitation of MNPs. Various parameters for TGA-FTIR-GC/MS data acquisition were optimized. Commercial consumer plastic product compositions were identified using this analytical database. Case studies to showcase the utility of the method for polymer mixtures analysis is included. This dataset would serve towards the development of a collaborative, global, comprehensive, and curated public database for the identification of various MNPs and mixtures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

Gradient-based constrained optimization using a database of linear reduced-order models

A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Developments of the EXFOR Database: Possible New Formats

The EXFOR database is a collection of experimental nuclear reaction data, maintained by the IAEA on behalf of the International Network of Nuclear Reaction Data Centres (NRDC). The format for the storage of such data was first described in 1969 and while there have been many incremental changes over the years so that the format is now capable of containing a very wide range of measurement results, there is a growing realisation that a major change is required. Consequently the IAEA Nuclear Data Section (NDS) organised a Consultant's Meeting on ‘Further Development of EXFOR’ in 2012. This was an opportunity for a range of international experts to discuss ways of improving EXFOR and while this focused on new formats there was also discussion on ways of storing new data, new output formats and software tools such as editors. This paper will discuss recent and proposed changes to enable new quantities to be stored (such as coincidence measurements and covariances), the range of output formats available (e.g. C4 and X4+) which make interaction with the data more user friendly and the possible use of XML to modernise the database.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Cross-checking of Large Evaluated and Experimental Nuclear Reaction Databases

Automated methods are presented for the verification of large experimental and evaluated nuclear reaction databases (e.g. EXFOR, JEFF, TENDL). These methods allow an assessment of the overall consistency of the data and detect aberrant values in both evaluated and experimental databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl. gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Database-wide hazard modelling of the onset of DIII-D tearing modes with field features

The rate of onset (hazard) of tearing modes is modelled probabilistically using statistical learning algorithms. Axisymmetric energy-density equilibrium fields are taken as raw high-dimensional input features which are reduced with principal component analysis. Signal processing of non-axisymmetric magnetics fluctuation array data provides the target information from which to learn. Model selection, visualization and calibration assessment procedures are detailed. Here, the analysis is deployed at large scale across the DIII-D tokamak database. Standard model selection criteria suggest that the energy-density post-processed feature is a better choice for modelling the onset rate compared to the non-processed equilibrium reconstruction solution. Two example applications of the learned rate function are demonstrated: (i) proximity-to-onset discharge monitoring and (ii) database analysis showing an (expected) observational global trend that the general hazard increases as a plasma performance metric increases. An important connection between the hazard function and its use as a conditional probability generator is reviewed in the Appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Efficient Use of an Adapting Database of Ab Initio Calculations To Generate Accurate Newtonian Dynamics

We develop and demonstrate a method to efficiently use density functional calculations to drive classical dynamics of complex atomic and molecular systems. The method has the potential to scale to systems and time scales unreachable with current ab initio molecular dynamics schemes. It relies on an adapting dataset of independently computed Hellmann–Feynman forces for atomic configurations endowed with a distance metric. The metric on configurations enables fast database lookup and robust interpolation of the stored forces. Here, we discuss mechanisms for the database to adapt to the needs of the evolving dynamics, while maintaining accuracy, and other extensions of the basic algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗