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DOE OSTI2020

Principal Component Analysis for Extremes and Application to U.S. Precipitation

Here, we propose a method for analyzing extremal behavior through the lens of a most efficient basis of vectors. The method is analogous to principal component analysis, but is based on methods from extreme value analysis. Specifically, rather than decomposing a covariance or correlation matrix, we obtain our basis vectors by performing an eigendecomposition of a matrix that describes pairwise extremal dependence. We apply the method to precipitation observations over the contiguous United States. We find that the time series of large coefficients associated with the leading eigenvector shows very strong evidence of a positive trend, and there is evidence that large coefficients of other eigenvectors have relationships with El Niño–Southern Oscillation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Small Angle X-Ray Scattering and Polymers

Polymers are some of the most versatile and useful materials on this planet. Properties of polymers are a result of their processing history, chemical makeup, and physical structure. Therefore, characterization is necessary to develop new polymer formulations and processes. Many established techniques for polymer characterization are destructive, and alternative methods that don’t destroy samples are in high demand. Thermal analysis techniques such as differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) yield important characteristic information for polymer samples while destroying the sample. Non-destructive strategies such as X ray diffraction (XRD) or small angle X-ray scattering (SAXS) can also find polymer characteristics while preserving a sample’s attributes. Sample preservation is desirable when investigating novel formulation and processing methods. SAXS analysis will be done on two different polymers: polyethylene, and a triblock copolymer. Using these two polymers allows for confidence between tests as polyethylene is very common, and well understood. Polyethylene analysis will be done first, and when methods have been refined so that the SAXS data matches accepted thermal analysis values for HDPE, there will be confidence to use the same analysis on block copolymers. Block copolymers remain relatively unexplored, so SAXS data will yield valuable information on their characteristics. Understanding the mechanical properties of these polymers is paramount to their application in upcycling, a process by which waste plastic can be converted into a higher value commodity. For this project, the upcycling process will be done via 3-dimensional (3d) printing.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Sustainable Manufacturing and the Circular Economy

The term "zero waste" can be somewhat misleading, as it implies an idealization of a concept that may never be achieved in real-world practice. According to Waste360 , "many in the solid waste industry think zero waste is an impossible goal. (Zero-waste advocates) believe just the opposite that a zero-waste approach makes the most economical and environmental sense...Most everyone agrees, however, that actually reaching the point where absolutely no waste is created is unlikely" (Leroux 2001). "Zero waste is a goal. It's completely unachievable...It's not about perfection; it's about making better choices" (Kellogg 2018). The immediate value of moving towards a zero-waste society is not immediately clear, but since the world we live in is finite in its resources, at what point does that value become evident? How do we broaden our value analysis to better incorporate the longer-term view? What are strategies that we can easily incorporate now that will significantly increase that longer term value and mitigate the impacts for future generations? This report considers these questions through a series of case studies from different parts of the U.S. manufacturing sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Revised and New Proper Motions for Confirmed and Candidate Milky Way Dwarf Galaxies

A new derivation of systemic proper motions of Milky Way satellites is presented and applied to 59 confirmed or candidate dwarf galaxy satellites using Gaia Data Release 2. This constitutes all known Milky Way dwarf galaxies (and likely candidates) as of 2020 May, except for the Magellanic Clouds, the Canis Major and Hydra 1 stellar overdensities, and the tidally disrupting Bootes III and Sagittarius dwarf galaxies. We derive systemic proper motions for the first time for Indus 1, DES J0225+0304, Cetus 2, Pictor 2, and Leo T, but note that the latter three rely on photometry that is of poorer quality than that of the rest of the sample. We cannot resolve a signal for Bootes 4, Cetus 3, Indus 2, Pegasus 3, or Virgo 1. Our method is inspired by the maximum likelihood approach of Pace & Li and examines simultaneously the spatial, color–magnitude, and proper motion distribution of sources. Systemic proper motions are derived without the need to identify confirmed radial velocity members, although the proper motions of these stars, where available, are incorporated into the analysis through a prior on the model. The associated uncertainties on the systemic proper motions are on average a factor of ∼1.4 smaller than existing literature values. Analysis of the implied membership distribution of the satellites suggests that we accurately identify member stars with a contamination rate lower than 1 in 20.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Role of Fuels in Transforming Energy End-Use in Buildings and Industrial Processes

This book examines what role fuels have in the transformation of end-use in buildings and industrial processes. Energy efficient technologies are necessary to lower the carbon footprint for a transition towards clean energy in a sustainable manner. Efficient utilization of primary energy resources including renewables to support the current and future energy needs while targeting grid resiliency, energy and environmental security, at an affordable cost is of significant value. Analysis of configurations consisting of heat pumps, fuel driven thermal providers and power systems is presented. Sensitivity of electrical grid's carbon intensity towards carbon footprint in comparison with fuel driven technologies is necessary to recognize the true value proposition of currently available energy solutions for different end consumers. Similarly, the role of low carbon, zero carbon, and carbon negative fuels such as power to gas, power to liquid, hydrogen, biogas, etc. in conjunction with polygeneration technologies are discussed. Transformation of the primary energy resources from conventional fossil fuels to renewable fuels or electricity will have a significant impact on the overall carbon footprint of various end use sectors, including buildings. Hence, this book also examines two different scenarios focused on sensitivity of the pace of decarbonization of electrical grid and fuel supply on operational energy related carbon emissions.

Cheekatamarla, Praveen↗

DOE OSTI2024

Total metal, carbon, anion, iron speciation, and sulfide concentrations; Slate River, East River, and Trail Creek surface water and floodplains, Crested Butte, CO; May 2023–August 2023

This data package comprises analytical results and metadata from stream and groundwater samples collected from the Slate River, East River, Trail Creek, and their respective floodplains. This dataset contains five files: (1) a samples file (2023_SFA_Field_samples.csv) that contains site information; (2) a chemical analysis data file (2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv) that contains sample analysis values; (3) a file-level metadata file (flmd.csv) that lists each file contained in the dataset with associated metadata; (4) a data dictionary file (dd.csv) that contains column/row headers used throughout the files along with definitions, units, and data types; and (5) a methods file (methods.csv) that contains ID, type, description, instrument, and lab information for each method.The samples’ anion concentrations were measured using ion chromatography (IC), total metal concentrations using inductively coupled plasma emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), non-purgeable organic carbon using total organic carbon (TOC) analysis, dissolved sulfide concentration using methylene blue spectrophotometry, and iron speciation using the ferrozine assay. To support bulk chemical analyses and colloid characterization, samples were collected from multiple depths ranging from the surface to 3.5 meters below ground.Update on 2024-10-18: Updates were made to the 2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv and dd.csv files to correct units (ppb instead of ppm).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

One Electron Multiple Proton Transfer in Model Organic Donor–Acceptor Systems: Implications for High-Frequency EPR

EPR spectroscopy is an important spectroscopic method for identification and characterization of radical species involved in many biological reactions. The tyrosyl radical is one of the most studied amino acid radical intermediates in biology. Often in conjunction with histidine residues, it is involved in many fundamental biological electron and proton transfer processes, such as in the water oxidation in photosystem II. As biological processes are typically extremely complicated and hard to control, molecular bio-mimetic model complexes are often used to clarify the mechanisms of the biological reactions. In this work, we present theoretical calculations to investigate the sensitivity of magnetic resonance parameters to proton-coupled electron transfer events, as well as conformational substates of the molecular constructs which mimic the tyrosine-histidine (Tyr-His) pairs found in a large variety of proteins. Upon oxidation of the phenol, the Tyr analog, these complexes can perform not only one-electron one-proton transfer (EPT), but also one-electron two-proton transfers (E2PT). It is shown that in aprotic environment the g X -components of the electronicg-tensor are extremely sensitive to the first proton transfer from the phenoxyl oxygen to the imidazole nitrogen (EPT product), leading to a significant increase of the g X -value of up to 0.003, but are not sensitive to the second proton transfer (E2PT). In the latter case, the change of the g X -value is much smaller (ca. 0.0001), which is too small to be distinguished even by high-frequency EPR. The 14 N hyperfine values are also too similar to allow differentiation between the different protonation states in EPT and E2PT. The magnetic resonance parameters were also calculated as a function of the rotation angles around single bonds. It was demonstrated that rotation of the phenoxyl group results in large positive changes (> 0.001) in the g X -values. Analysis of the data reveals that the main source of these changes is related to the strength of the H-bond between phenoxyl oxygen and the proton(s) on N 1 and N 2 positions of the imidazole.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Leveraging Extremal Dependence to Better Characterize the 2021 Pacific Northwest Heatwave

Abstract In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causing hundreds of fatalities. The observed 2021 daily maximum temperature across much of the U.S. Pacific Northwest exceeded upper bound estimates obtained from single-station temperature records even after accounting for anthropogenic climate change, meaning that the event could not have been predicted under standard univariate extreme value analysis assumptions. In this work, we utilize a flexible spatial extremes model that considers all stations across the Pacific Northwest domain and accounts for the fact that many stations simultaneously experience extreme temperatures. Our analysis incorporates the effects of anthropogenic forcing and natural climate variability in order to better characterize time-varying changes in the distribution of daily temperature extremes. We show that greenhouse gas forcing, drought conditions and large-scale atmospheric modes of variability all have significant impact on summertime maximum temperatures in this region. Our model represents a significant improvement over corresponding single-station analysis, and our posterior medians of the upper bounds are able to anticipate more than 96% of the observed 2021 high station temperatures after properly accounting for extremal dependence. Supplementary materials accompanying this paper appear online.

Zhang, Likun (ORCID:0000000154584556)↗

DOE OSTI2022

Study of synergistic effects and compositional dependence of hydrogen evolution reaction on MoxNiy alloy thin films in alkaline media

In this paper hydrogen evolution reaction (HER) on the molybdenum-nickel thin films has been studied. The Mo x Ni y thin films were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). A change in the crystal structure of the samples prepared at different temperatures was observed. The structure of the samples prepared at 25 °C are bcc or amorphous. The structure of alloys sputtered at 800 °C changed to fcc. Tafel plots were constructed for each Mo x Ni y alloy sample. The mechanism of HER was determined from Tafel slope analysis. Values of charge transfer resistance were also determined by impedance spectroscopy. The compositional dependence of activity and the stability of Mo x Ni y thin films in 1 M NaOH were determined by cycling and chronoamperometry. Our results demonstrate that Mo x Ni y thin films prepared at 800 °C show significantly improved activity compared to pure Mo and Ni metals. On the other hand, Mo x Ni y thin films sputtered at 25°C do not show increased activity in comparison to pure Ni metal. Furthermore, this points to a synergistic effect between fcc Mo and fcc Ni in thin films sputtered at elevated temperatures. Mo 63 Ni 67 thin films alloy prepared at 800 °C shows the best values of catalytic activity for HER from all investigated compositions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

A database of global storm surge reconstructions

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A machine learning aided interpretable model for rupture strength prediction in Fe-based martensitic and austenitic alloys

Abstract The class of 9–12% Cr ferritic-martensitic alloys (FMA) and austenitic stainless steels have received considerable attention due to their numerous applications in high temperature power generation industries. To design high strength steels with prolonged service life requires a thorough understanding of the long-term properties, e.g., creep rupture strength, rupture life, etc., as a function of the chemical composition and processing parameters that govern the microstructural characteristics. In this article, the creep rupture strength of both 9–12% Cr FMA and austenitic stainless steel has been parameterized using curated experimental datasets with a gradient boosting machine. The trained model has been cross validated against unseen test data and achieved high predictive performance in terms of correlation coefficient ( $$R^{2} > 0.98 $$ R 2 > 0.98 for 9–12% Cr FMA and $$R^{2} > 0.95 $$ R 2 > 0.95 for austenitic stainless steel) thus bypassing the need for additional comprehensive tensile test campaigns or physical theoretical calculations. Furthermore, the feature importance has been computed using the Shapley value analysis to understand the complex interplay of different features.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Floods of Egypt’s Nile in the 21st century

Extreme precipitation and flooding events are rising globally, necessitating a thorough understanding and sustainable management of water resources. One such setting is the Nile River’s source areas, where high precipitation has led to the filling of Lake Nasser (LN) twice (1998–2003; 2019–2022) in the last two decades and the diversion of overflow to depressions west of the Nile, where it is lost mainly to evaporation. Using temporal satellite-based data, climate models, and continuous rainfall-runoff models, we identified the primary contributor to increased runoff that reached LN in the past two decades and assessed the impact of climate change on the LN’s runoff throughout the twenty-first century. Findings include: (1) the Blue Nile subbasin (BNS) is the primary contributor to increased downstream runoff, (2) the BNS runoff was simulated in the twenty-first century using a calibrated (1965–1992) rainfall-runoff model with global circulation models (GCMs), CCSM4, HadGEM3, and GFDL-CM4.0, projections as model inputs, (3) the extreme value analysis for projected runoff driven by GCMs’ output indicates extreme floods are more severe in the twenty-first century, (4) one adaptation for the projected twenty-first century increase in precipitation (25–39%) and flood (2%-20%) extremes is to recharge Egypt’s fossil aquifers during high flood years.

Climate change↗

DOE OSTI2023

The influence of counterion structure identity on conductivity, dynamical correlations, and ion transport mechanisms in polymerized ionic liquids

We used equilibrium and non-equilibrium atomistic simulations to probe the influence of anion chemistry on the true conductivity, dynamical correlations, and ion transport mechanisms in polymeric ionic liquids. An inverse correlation was found between anion self-diffusivities, ionic mobilities, and the anion size for spherical anions. While some larger asymmetric anions had higher diffusivities than smaller spherical anions, their diffusivities and mobilities did not exhibit a direct correlation to the anion volumes. Here, the conductivity and anion dynamical correlations also followed the same trends as displayed by the diffusivity and mobility of anions. All the systems we examined displayed positively correlated motion among anions, suggesting a contribution that enhances the conductivity beyond the ideal Nernst–Einstein value. Analysis of ion transport mechanisms demonstrated very similar hopping characteristics among the spherical anions despite differences in their sizes.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Machine learning of factors for improving oyster hatchery production

Oyster aquaculture and restoration in the Chesapeake Bay are vital, yet hatcheries frequently struggle with inconsistent larval growth and sudden mass mortality events. Unpredictable disruptions in larval production cause large economic losses, represent a perceived risk to growers, and impede industry expansion. To better understand associations between production yield and its potential predictors, we applied machine learning (random forest, and neural network) and statistical (generalized additive model) models to a comprehensive dataset of environmental, water quality, and operational parameters from a Maryland oyster hatchery, aiming to identify key yield predictors and develop a robust forecasting tool. We used recursive Boruta algorithm for variable selection, pinpointing critical predictors, and employed cross-validation to fine-tune model settings. Shapley value analysis offered crucial insights into model interpretations, highlighting week number, Normalized Difference Vegetation Index, salinity, turbidity, and fecundity as primary drivers of yield variability. For low-yield cases, salinity-related variables were particularly important. Our findings provide an early warning system for potential production downturns, empowering hatchery operators to make data-driven decisions for optimizing water conditions, feeding schedules, and broodstock management. By boosting predictability and efficiency, this research directly supports economic stability of the oyster industry and ecological health of the Chesapeake Bay.

Vishwakarma, Srishti [Oak Ridge National Laborator↗

DOE OSTI2022

Total metals, sulfur and organic carbon data; Slate River floodplain, Crested Butte, CO; March 2021-October 2021

This data package includes processed and undiluted measurements for metal, sulfur and organic carbon concentrations from pore water (groundwater) samples from the Slate River floodplain of Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? Samples were collected between March and October of 2021. These measurements were all recorded at the Environmental Measurements Facility (EM-1) at Stanford University in Stanford, CA. Groundwater samples were extracted from a network of installed rhizon (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the river floodplain. All water samples were shaded from sun exposure during extraction from the subsurface and preserved at 2C until measured at EM-1.Analysis by ICP-MS:Measurements for total metals were performed on an inductively coupled plasma optical emission spectrometer (ICP-OES; iCAP 6300, Thermo Scientific, Cambridge, U.K.). Calibration standards were prepared from the mulit element stock solution (Sigma-Aldrich Multielement standard for ICP, St. Louis, MO) using matrix matched to sample solutions (2% HNO3). Calibration curves included 5 points with correlation coefficients of >0.99. The QC protocol includes a continuing calibration blank and quality control samples that are analyzed just after calibration and again every 20 samples and at the completion of the run. Acceptable QC responses must be between 90-110% of the certified value. Analysis by Total Organic Carbon:Dissolved organic carbon concentrations were quantified on a total organic carbon (TOC) analyzer (TOC-L, Shimadzu, Kyoto, Japan) running the NPOC method. Standard curves were developed using an Organic Carbon Standard from RICCA Chemical Company (Arlington,TX). A series of 4 to 6 standards were automatically diluted by the instrument in a concentration range that spans that of the samples. A blank sample was run just after the calibration curve and at the end of the run. A QC sample was run every 25 samples. Acceptable QC responses must be between 90-110% of the certified value.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Assessing and mapping extreme wave height along the Gulf of Mexico coast

The effect of extreme waves on the coastal community includes inundation, loss of habitats, increasing shoreline erosion, and increasing risks to coastal infrastructures (e.g., ports, breakwaters, oil and gas platforms), important for supporting coastal resilience. The coastal communities along the US Gulf of Mexico are very low-lying, which makes the region particularly vulnerable to impacts of extreme waves generated by storm events. We propose assessing and mapping the risks from extreme waves for the Gulf of Mexico coast to support coastal resiliency planning. The risks will be assessed by computing n-year recurring wave height (e.g., 1, 5, 50, 100-year) using 32-year wave hindcast data and various extreme value analysis techniques including Peak- Over-Threshold and Annual Maxima method. The characteristics of the extreme waves, e.g., relations between the mean and extreme wave climates, directions associated with extreme waves, will be investigated. Hazard maps associated with extreme wave heights at different return periods will be generated to help planners identify potential risks and envision places that are less susceptible to future storm damage.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Bridging the Gap on Data and Analysis for Distribution System Planning: Information That Utilities Can Provide Regulators, State Energy Offices and Other Stakeholders

Electric utilities conduct planning annually to ensure their distribution system meets technical standards, policies, and regulations; addresses forecasted grid conditions; satisfies customer needs; and advances utility priorities. The plan identifies grid deficiencies, analyzes potential solutions, and prioritizes capital investments and other expenditures. About 20 U.S. states and jurisdictions require regulated utilities to file some type of distribution system plan with the public utility commission for review. Requirements for sharing distribution system data and analyses vary widely, from few specific requirements to a detailed list of information that must be provided. While utilities conduct extensive analysis to develop distribution system plans, in most jurisdictions regulators and stakeholders do not know what data are available and how the utility uses the data in planning and investing. This report aims to bridge the gap by increasing understanding of the types of data and analyses utilities employ to develop distribution system plans and how the information affects their decision-making. The report describes information that states and stakeholders can ask for related to 11 data categories: -Forecasting loads and distributed energy resources (DERs) -Scenario analysis -Worst-performing circuits -Asset management strategy -Hosting capacity analysis -Value of DERs -Grid needs assessment -Cost-effectiveness framework for investments -Distribution system investment strategy and implementation -Geotargeted programs -Non-wires alternatives procurements.

24 POWER TRANSMISSION AND DISTRIBUTION↗