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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Annual Summary Report for the Remote-Handled Low-Level Waste Disposal Facility—FY 2020

This Fiscal Year (FY) 2020 annual summary report documents the continued adequacy of the performance assessment (PA), the composite analysis (CA) and associated operating disposal-authorization statement (ODAS) technical basis documents for the Remote Handled (RH) Low-Level Waste (LLW) Disposal Facility at Idaho National Laboratory. Annual review of the adequacy of the PA and CA for the RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of Department of Energy (DOE) Order 435.1 Change 1, “Radioactive Waste Management.” In FY 2020, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility closure design, or institutional controls. Fifteen total waste-canister shipments were received at the RHLLW Disposal Facility, and 15 total waste canisters were emplaced.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Presentation on the INL Remote-Handled Low-Level Waste Disposal Facility FY-2024 Annual Summary Report

The abstract below is from the report INL/RPT-24-82600. The powerpoint presentation contains information taken from the report. This Fiscal Year (FY) 2024 annual summary report (ASR) documents the continued adequacy of the performance assessment (PA), the composite analysis (CA), and associated operating disposal authorization statement (ODAS) technical basis documents for the Remote Handled Low Level Waste (RHLLW) Disposal Facility at Idaho National Laboratory (INL). Annual review of the adequacy of the PA and CA for RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of the U.S. Department of Energy (DOE) Order 435.1, “Radioactive Waste Management.” In FY 2024, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility closure design, or institutional controls. Nineteen waste canister shipments were received at the RHLLW Disposal Facility, and all nineteen waste canisters were emplaced in disposal vaults.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2024

Presentation on the INL Remote-Handled Low-Level Waste Disposal Facility FY-2023 Annual Summary Report

The abstract below is from the report INL/RPT-24-76103. The powerpoint presentation contains information taken from the report. This Fiscal Year (FY) 2023 annual summary report (ASR) documents the continued adequacy of the performance assessment (PA), the composite analysis (CA) and associated operating disposal-authorization statement (ODAS) technical basis documents for the Remote Handled (RH) Low-Level Waste (LLW) Disposal Facility at Idaho National Laboratory. Annual review of the adequacy of the PA and CA for the RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of Department of Energy (DOE) Order 435.1, “Radioactive Waste Management.” In FY 2023, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility closure design, or institutional controls. Sixteen total waste-canister shipments were received at the RHLLW Disposal Facility, and 15 total waste canisters were emplaced.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2023

Obesity is associated with biliary tract cancer mortality and incidence: A pooled analysis of 21 cohort studies in the Asia Cohort Consortium

Abstract Body fatness is considered a probable risk factor for biliary tract cancer (BTC), whereas cholelithiasis is an established factor. Nevertheless, although obesity is an established risk factor for cholelithiasis, previous studies of the association of body mass index (BMI) and BTC did not take the effect of cholelithiasis fully into account. To better understand the effect of BMI on BTC, we conducted a pooled analysis using population‐based cohort studies in Asians. In total, 905 530 subjects from 21 cohort studies participating in the Asia Cohort Consortium were included. BMI was categorized into four groups: underweight (<18.5 kg/m 2 ); normal (18.5‐22.9 kg/m 2 ); overweight (23‐24.9 kg/m 2 ); and obese (25+ kg/m 2 ). The association between BMI and BTC incidence and mortality was assessed using hazard ratios (HR) and 95% confidence intervals (CIs) by Cox regression models with shared frailty. Mediation analysis was used to decompose the association into a direct and an indirect (mediated) effect. Compared to normal BMI, high BMI was associated with BTC mortality (HR 1.19 [CI 1.02‐1.38] for males, HR 1.30 [1.14‐1.49] for females). Cholelithiasis had significant interaction with BMI on BTC risk. BMI was associated with BTC risk directly and through cholelithiasis in females, whereas the association was unclear in males. When cholelithiasis was present, BMI was not associated with BTC death in either males or females. BMI was associated with BTC death among females without cholelithiasis. This study suggests BMI is associated with BTC mortality in Asians. Cholelithiasis appears to contribute to the association; and moreover, obesity appears to increase BTC risk without cholelithiasis.

Oze, Isao↗
DOE OSTI2022

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality

Background: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions.Objectives: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables.Methods: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping.Results: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients.Conclusions: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Comparison of chromium poisoning between lanthanum strontium manganite and lanthanum strontium ferrite composite cathodes in solid oxide fuel cells

Degradation mechanisms of chromium poisoning have been extensively investigated for last two decades on various cathode materials for solid oxide fuel cells. While most researchers used half-cell experiments to investigate the effects of chromium impurities, this paper compares the degradation phenomena of LSM-YSZ and LSF-GDC cathodes in full cells under different operating conditions, namely polarized current density and humidity over the cathode. Under cathodic load, performance degradation of LSF-GDC cathode is significantly less than that of LSM-YSZ cathode. Most interestingly, under humidified air condition, LSF-based cell hardly experiences performance degradation while LSM-based cell shows a catastrophic degradation. Cr deposition in LSM-based cells occurs mainly near the electrolyte under both dry and humidified air conditions. In contrast, Cr deposition in LSF-based cell concentrates at the cathode surface under dry air condition, but concentrates both at cathode surface and near electrolyte under humidified air condition. Microstructure analysis reveals Mn-associated Cr deposits in LSM-based cathode, and Sr- and Fe-associated Cr deposits in LSF-based cathode. With the help of distribution of relaxation time analysis, the different electrochemical behaviors of LSM- and LSF-based cells are carefully interpreted. The effects of electrochemical deposition, Sr surface segregation, and humidity on LSM- and LSF-based cathodes are discussed.

25 ENERGY STORAGE↗
DOE OSTI2022

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent results have shown that HNF4a defective function and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein an integrative analysis of hepatic RNAseq and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to identify plasma protein signatures for mild and severe AH patients. Alcohol-related liver disease cirrhosis (ALD)(AC), non-alcoholic fatty liver disease (NALFD), and healthy subjects (HC) were used as comparator groups. Identified proteins primarily involved in hepatocellular function were decreased in AH patients which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified including thrombin (THRB), hepatocyte growth factor alpha (HGFA), clusterin (CLUS), human serum factor H-related protein (FHR1) and kallistatin (KAIN), which exhibited large abundance shifts between severe and non-severe AH. The combination of THRB and HGFA discriminated between severe and non-severe AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Understanding Competing Risks

Highlights: • Clinicians and researchers need to be cognizant of competing risks (ie, the occurrence of an event that precludes future development of the outcome of interest). • Censoring is appropriate when a patient being censored at a particular time (eg, owing to loss to follow-up) is deemed to have approximately the same future risk of developing the outcome of interest as patients still being followed, and when the reason for censoring is not related to events of interest. • Censoring is not appropriate in many scenarios; for example, a dead patient can never develop a future cancer recurrence or late effect. • Kaplan-Meier (KM) analysis is commonly used for a time-to-event analysis when the primary outcome (eg, overall survival) has no meaningful competing risk and censoring is appropriate. Cox proportional hazards modeling can be used for multivariable analysis to examine the association between covariates and the primary outcome. • In the presence of competing events, incorrect use of the KM analysis will likely lead to an overestimation of the risk of the outcome of interest and biased estimates from both univariable and multivariable analyses. Therefore, KM usually should not be used to determine local recurrence risk because humanity is always at risk for dying, which is a competing risk. • A competing risk analysis is therefore most appropriate when there are competing events to the primary outcome of interest. The most commonly used multivariable model in these situations is the Fine-Gray model. • Many fundamental questions in radiation oncology—local and regional recurrence, treatment-related toxicity—are best addressed using competing risk methodologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Unveiling shared genetic regulators of plant architectural and biomass yield traits in the Sorghum Association Panel

Abstract Sorghum is emerging as an ideal genetic model for designing high-biomass bioenergy crops. Biomass yield, a complex trait influenced by various plant architectural characteristics, is typically regulated by numerous genes. This study aimed to dissect the genetic regulators underlying 14 plant architectural traits and 10 biomass yield traits in the Sorghum Association Panel across two growing seasons. We identified 321 associated loci through genome-wide association studies (GWAS), involving 234 264 single nucleotide polymorphisms (SNPs). These loci include genes with known associations to biomass traits, such as maturity, dwarfing (Dw), and leafbladeless1, as well as several uncharacterized loci not previously linked to these traits. We also identified 22 pleiotropic loci associated with variation in multiple phenotypes. Three of these loci, located on chromosomes 3 (S03_15463061), 6 (S06_42790178; Dw2), and 9 (S09_57005346; Dw1), exerted significant and consistent effects on multiple traits across both growing seasons. Additionally, we identified three genomic hotspots on chromosomes 6, 7, and 9, each containing multiple SNPs associated with variation in plant architecture and biomass yield traits. Chromosome-wise correlation analyses revealed multiple blocks of positively associated SNPs located near or within the same genomic regions. Finally, genome-wide correlation-based network analysis showed that loci associated with flowering, plant height, leaf traits, plant density, and tiller number per plant were highly interconnected with other genetic loci influencing plant architectural and biomass yield traits. The pyramiding of favorable alleles related to these traits holds promise for enhancing the future development of bioenergy sorghum crops.

Singh, Anuradha (ORCID:0000000197149095)↗
DOE OSTI2024

ORNL Peer Review Summary and Recommendations for: Advanced Reactor Designs Security Analysis, Risk, and Recommendations: Risks, Consequences, and Possible Design Mitigation Approaches Associated with Select Advanced Reactors Study

The purpose of this document is to provide a summary of the peer review conducted for the "Advanced Reactor Designs Security Analysis, Risk, and Recommendations: Risks, Consequences, and Possible Design Mitigation Approaches Associated with Select Advanced Reactors" study prepared by researchers at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), and Oak Ridge National Laboratory (ORNL). The National Nuclear Security Administration (NNSA) International Nuclear Security (INS) program team requested that ORNL perform a peer review of the study report prior to publication as a final peer check before distributing the report to a broader audience.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysis

Thomson scattering measurements in high energy density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an important and sometimes the dominant source of measurement uncertainty. In this paper, we present a formal method of accounting for the presence of streak camera noise in our measurements. We present a phenomenological description of the noise generation mechanisms and present a statistical model that may be used to construct the covariance matrix associated with a given measurement. This model is benchmarked against simulations of streak camera images. We demonstrate how this covariance may then be used to weight fitting of the data and provide quantitative assessments of the uncertainty in the fitting parameters determined by the best fit to the data and build confidence in the ability to make statistically significant measurements in the low-signal regime, where spatial correlations in the noise become apparent. These methods will have general applicability to other measurements made using optical streak cameras.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

MoorPy (Quasi-Static Mooring Analysis in Python)

MoorPy is a quasi-static mooring model and a suite of associated functions for mooring system analysis. The core model supports quasi-static analysis of moored floating systems including any arrangement of mooring lines and floating platforms. It solves the distributed position and tension of each mooring line segment using standard catenary equations. Floating platforms can be represented with linear hydrostatic characteristics. MoorPy automatically computes a floating system's equilibrium state and can be queried to identify a mooring system's nonlinear force-displacement relationships. Linearized stiffness matrices are efficiently computed using semi-analytic Jacobians. MoorPy also includes plotting functions and a library of mooring component property and cost coefficients. MoorPy can be used directly from Python scripts to perform mooring design and analysis tasks, or it can be coupled with other tools to compute quasi-static mooring reactions as part of a larger simulation.

Hall, Mathew↗
DOE OSTI2025

Data and scripts associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration”

This data package is associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration” published in EGU Biogeosciences (Stegen et al., 2026; https://doi.org/10.5194/bg-23-3981-2026). It contains cotton strip decomposition rates (Kcd and Kdd) collected across the Yakima River Basin (YRB), Washington, USA. These data were collected to support a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. Associated data used in analysis, metadata, and field protocols can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1969566, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1987520. This data package is associated with the repository found at https://github.com/river-corridors-sfa/rcsfa-ST-2B-SSS-cotton-strip. A preliminary version of this data package was published in December 2025 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This data package consists of (1) readme; (2) data dictionary (dd); (3) file level metadata (flmd); and (4) four folders: (1) R-scripts; (2) figures; (3) outputs from the scripts; and (4) published data. The published data folder contains a readme directing the user to download data in order to run the R-scripts. All files are .csv, .pdf, .R, .Rmd, and .txt. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

On the Viability of Video Imaging in Leak Rate Quantification: A Theoretical Error Analysis

Optical gas imaging through multispectral cameras is a promising technique for mitigation of methane emissions through localization and quantification of emissions sources. While more advanced cameras developed in recent years have led to lower uncertainties in measuring gas concentrations, a systematic analysis of the uncertainties associated with leak rate estimation have been overlooked. We present a systematic categorization of the involved uncertainties with a focus on a theoretical analysis of projection uncertainties that are inherent to this technique. The projection uncertainties are then quantified using Large Eddy Simulation experiments of a point source release into the atmosphere. Our results show that while projection uncertainties are typically about 5% of the emission rate, low acquisition times and observation of the gas plume at small distances from the emission source (<10 m) can amount to errors of about 20%. Further, we found that acquisition times on the order of tens of seconds are sufficient to significantly reduce (>50%) the projection uncertainties. These findings suggest robust procedures on how to reduce projection uncertainties, however, a balance between other sources of uncertainty due to operational conditions and the employed instrumentation are required to outline more practical guidelines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Data and scripts associated with the manuscript "Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling"

This package contains the data and scripts used in "Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling" (Jiang et al., 2022). The ARW_SWAT.zip file contains the SWAT simulation and the sensitivity analysis result in the American River Watershed. The Portage_SWAT.zip file contains the SWAT simulation and the sensitivity analysis result in the Portage River Watershed. The src folder contains the source code of sensitivity analysis and plotting functions. The notebooks folder contains the Jupyter notebooks for performing sensitivity analysis and other post analyses.Global Sensitivity Analysis (GSA) often is applied to assess the sensitivity of model outputs to their inputs using ensemble simulations. However, increasing model complexity and the associated computational cost have limited the use of most GSA approaches for process-based watershed models. We propose to use Mutual Information (MI) as a computationally efficient GSA method for watershed modeling. Such MI computed from several hundred realizations usually can capture nonlinear relationships between inputs and outputs of interest. We perform MI-based watershed sensitivity analyses in studies of the Portage River Watershed in Ohio and the American River Watershed in Washington. In these studies, MI is used to evaluate the sensitivity of river discharges simulated by the Soil and Water Assessment Tool to no less than 20 parameters for each watershed. Our MI-based sensitivity analyses achieved convergence with about 300~500 realizations, a small fraction of the ensemble size (i.e., several thousand) required by the Sobol method. Nevertheless, MI yields similar sensitivity ranking compared to the Sobol method, especially for sensitive parameters. Our study thus sheds new light on the use of MI as an affordable GSA method for computationally intensive models such as the hyper-resolution, watershed hydrobiogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Status Update on NETL Techno-Economic Analysis of Solid Oxide Cells

This is a presentation delivered at the Solid Oxide Fuel Cell Project Review Meeting portion of the 2023 FECM / NETL Spring R&D Project Review Meeting on April 19, 2023. The presentation highlights recently completed techno-economic analysis of solid oxide cell systems including a brief overview of pairing SOFC technology with energy storage, an analysis of the tradeoffs associated with reversible SOC technology versus paired SOFC/SOEC, and highlights of the recently released NGFC and IGFC pathway studies. A more detailed description of analysis conducted on hydrogen fueled SOFC systems is also included.

Hackett, Gregory↗
DOE OSTI2023

A systematic analysis and data mining of opioid-related adverse events submitted to the FAERS database

The opioid epidemic has become a serious national crisis in the United States. An indepth systematic analysis of opioid-related adverse events (AEs) can clarify the risks presented by opioid exposure, as well as the individual risk profiles of specific opioid drugs and the potential relationships among the opioids. In this study, 92 opioids were identified from the list of all Food and Drug Administration (FDA)-approved drugs, annotated by RxNorm and were classified into 13 opioid groups: buprenorphine, codeine, dihydrocodeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, tapentadol, and tramadol. A total of 14,970,399 AE reports were retrieved and downloaded from the FDA Adverse Events Reporting System (FAERS) from 2004, Quarter 1 to 2020, Quarter 3. After data processing, Empirical Bayes Geometric Mean (EBGM) was then applied which identified 3317 pairs of potential risk signals within the 13 opioid groups. Based on these potential safety signals, a comparative analysis was pursued to provide a global overview of opioid-related AEs for all 13 groups of FDA-approved prescription opioids. The top 10 most reported AEs for each opioid class were then presented. Both network analysis and hierarchical clustering analysis were conducted to further explore the relationship between opioids. Results from the network analysis revealed a close association among fentanyl, oxycodone, hydrocodone, and hydromorphone, which shared more than 22 AEs. In addition, much less commonly reported AEs were shared among dihydrocodeine, meperidine, oxymorphone, and tapentadol. On the contrary, the hierarchical clustering analysis further categorized the 13 opioid classes into two groups by comparing the full profiles of presence/absence of AEs. The results of network analysis and hierarchical clustering analysis were not only consistent and cross-validated each other but also provided a better and deeper understanding of the associations and relationships between the 13 opioid groups with respect to their adverse effect profiles.

Research & Experimental Medicine↗