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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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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Sampling Low-Level Waste - Building a Program - 16101

Low level radioactive waste is routinely sampled and analyzed to demonstrate compliance with Title 10 Code of Federal Regulations Part 61. The sample results are frequently used to create scaling factors to relate the activity of hard to detect (HDT) radionuclides to gamma emitting activity if there is a correlation between the key and scaled radionuclide pair. The activity of gamma emitters can be used with these scaling factors to calculate activity of the low level waste generated in the plant. Another method is to use the sample results directly and scale the total activity to the volume or weight of the waste in the container. Either method assumes that the sample results are representative of the total waste in the container. This requires that the waste streams be accurately defined and that the samples contain radionuclides at ratios that are representative of the bulk waste. This is not always the case and deviations between the sample results and the actual radionuclide concentrations in the waste can lead to miss-classification of the waste resulting in regulatory non-compliance, increased waste disposal costs or both. A deliberate sampling methodology that considers the context of the waste generation and the inherent limitations in practical sampling methodologies will enhance the licensee's ability to demonstrate the analytical results from the sample are representative and defendable. A good sampling program starts with the establishment of waste streams that are consistent with both production mechanisms and plant systems. Once waste streams have been established, data quality objectives can be determined and then the methods for obtaining an appropriate sample can be developed along with the identification of sample points and sample schedules. Sometimes it may not be practical or even possible to obtain a truly representative sample in which case the results from the measurement of the sample must be evaluated within the context of the expected values and the factors inhibiting the collection of a truly representative sample. This paper will explore objectives of a sampling program in relation to the regulations and identify methods that can be used to obtain and evaluate sample data that can be defended as 'representative'. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Determining Compression Characteristics of Honeycomb Material - 19674

The objective is to determine compression test characteristics of stainless steel honeycomb material to be able to represent honeycomb structures accurately in analytical models used to simulate hypothetical accident scenarios of shipping packages. Honeycomb is a material used primary in the aerospace industry due to its high strength-to-weight ratio. Because it doesn't have a shelf life and can withstand high heats, it is an excellent candidate for a structural material in package designs. Honeycomb has orthotropic material properties. The honeycomb currently being evaluated is made of metal ribbons spot welded together to form hexagon pattern between metal plates. The hexagon ribbons are brazed to the metal plates. The complexity of the honeycomb significantly lengthens the simulation time, which is further complicated when the brazing, welding, and imperfections of the material is considered. This means to affectively represent the honeycomb in simulation programs, such as Abaqus, the material needs to be approximated as a uniform orthotropic material. This requires material properties in each of the three directions, T, W, and L. The T direction is defined as the 'strong' direction, perpendicular to the honeycomb sheet. The L direction is parallel the ribbon and the W direction is perpendicular to the ribbon. Honeycomb has 3 different compression stages. Stage 1 is the initial compression where the honeycomb maintains its structural integrity and does not permanently deform from loads from normal operations. Stage 2 is when the initial buckling causes irreversible damage to the honeycomb. Stage 2 is the one we are most interested in because it absorbs the most energy from a hypothetical accident scenario. During Stage 2, the honeycomb fails layer-by-layer, indicating that the more layers, the longer material crushing is sustained, and thus the more energy that is absorbed. Stage 3 is final compression, similar to compressing solid metal. During stage 3 the stress increases with a diminishing rate of elongation and the honeycomb is completely failed where the plates between the honeycomb core sandwich the crushed honeycomb ribbon. The stress-strain graph bellow shows compression test of 3 different samples in the T direction. The red lines divide the three stages. The far left is Stage 1, the middle stage 2, and the right stage 3. The data collected is displayed in the table below. The expressions in the table represent the regression formula that represents each stage of the compression on a stress-strain graph. Stage 1 is assumed to intersect with the origin; data for stage 3 for the crush in W and L directions where unable to be gathered due to the nature of failure for those directions. Stage 1 and 2 are linear regressions while stage 3 is a degree 2, to best match the curve. Linear regression is used on stage 2 because ultimately that represents the energy absorbed. With more data, a degree n x 2 regression would be a more appropriate regression for stage 2, where n is the number of layers. The table below is the approximation of each scenario and stage. Each stage starts and ends at the intersection of the next stage. There where two main objectives for these tests: firstly to understand how honeycomb performs under extreme compression, and secondly to be able to numerically represent the honeycomb structure. Both of these where completed to varying degrees. It is important understood how the honeycomb fails. If it is crushed in the T direction it retains its integrity even after being crushed, however when crushed in the L and W crush direction, if it fails, it disintegrates, and loses all integrity. Also, the more layers the more time the material spends in stage 2. Failure is started by buckling, thus if there is any imperfection, the stress will not spike but transition straight into stage 2. The data collected and aggregated can be used for initial simulation of honeycomb used in packages. The initial testing has set the ground work for more data to be collected in order to verify results and to allow more confidence in the simulation results. This is only the initial data collected. The next steps is to continue to collect more data to verify results and to test more variants of honeycomb, with different brazing, layers, and shape.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Pore-Scale Simulation of Intragranular Diffusion: Effects of Incomplete Mixing on Macroscopic Manifestations

Diffusive mass transfer into and out of intragranular micropores ("intragranular diffusion") plays an important role in the large-scale transport of some groundwater contaminants. We are interested in understanding the combined effect of pore-scale advection and intragranular diffusion on solute transport at the effective porous medium scale. To study this problem, we have developed a three-dimensional pore-scale model of fluid flow and solute transport that incorporates diffusion into and out of intragranular pore spaces. Our model is based on the Smoothed Particle Hydrodynamics (SPH) simulation method, which represents fluid and solid phases by a mesh-free particle discretization. In the pore spaces, fluid flow is simulated by discretizing the Navier-Stokes equations using the SPH approach. Solute transport is represented by advection, diffusion within the fluid phase, and diffusion between the fluid and solid phases. Our model is implemented on large-scale parallel computing hardware, allowing us to simulate millions of computational particles and represent fully three-dimensional systems of pores and grains with arbitrarily complex physical geometry. We have used this model system to perform numerical experiments using various model porous media systems, which allows us to draw comparisons between macroscopic measures computed from the pore-scale simulations (such as breakthrough curves) and those predicted by macroscopic formulations that assume complete mixing over the representative volume. In this paper we present results of 3D simulations of pore-scale flow and transport, including cases with and without intragranular diffusion, in two model porous media, one with randomly-packed uniform spherical grains and a second with randomly-packed spheres drawn from a binary grain size distribution. Breakthrough curves were computed from the 3D simulations at various transport distances. Comparable breakthrough curves were computed using 1D macroscopic models with parameters determined independently to the degree possible. Based on comparisons of the pore-scale and macroscopic model results, we draw two primary conclusions. First, non-Fickian behavior is persistent and ubiquitous at the scales considered, and most cases are better represented by a multi-rate mass transfer model even when there is no distinct secondary porosity (i.e., no intragranular diffusion). This suggests that diffusive mass transfer processes between preferential flow paths and relatively immobile zones within the primary porosity may have significant impact on transport, particular in low-concentration tails. Second, the application of mass transfer rate parameters based on an assumption of well-mixed concentrations at the pore-scale tend to overestimate the amount of mass transfer that occurs in heterogeneous pore geometries in which preferential flow leads to incomplete pore-scale lateral mixing.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

Comparison of CO 2 trapping in highly heterogeneous reservoirs with Brooks-Corey and van Genuchten type capillary pressure curves

Geological heterogeneities affect the dynamics of carbon dioxide (CO 2 ) plumes in subsurface environments in important ways. Previously, we showed how the dynamics of CO 2 plumes are influenced by the multiscaled sedimentary architecture in deep brine fluvial-type reservoirs. The results confirm that representing small-scale features and the corresponding heterogeneity in saturation functions, along with hysteresis in saturation functions, are all critical to understanding capillary trapping processes. Here, we show that when heterogeneity and hysteresis are represented, the two conventional approaches for defining saturation functions, Brooks-Corey and van Genuchten, represent fundamentally different physical systems. The Brooks-Corey approach represents heterogeneity in entry pressures, and leads to trapping by capillary pinning. The van Genuchten approach represents a network of pores transporting the nonwetting fluid, across rock types, with negligible capillary entry pressure, and leads to capillary retardation. We conclude these differences significantly affect the large-scale characteristics of CO 2 plumes (i.e., their mass, shape, and position).

58 GEOSCIENCES↗
DOE OSTI2015

Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling.

Archaea represent a significant fraction of Earth's biodiversity, yet they remain much less well understood than Bacteria. Gene surveys, a few metagenomic studies, and some single-cell sequencing projects have revealed numerous little-studied archaeal phyla. Certain lineages appear to branch deeply and may be part of a major phylum radiation. The structure of this radiation and the physiology of the organisms remain almost unknown.We used genome-resolved metagenomic analyses to investigate the diversity, genomes sizes, metabolic capacities, and potential roles of Archaea in terrestrial subsurface biogeochemical cycles. We sequenced DNA from complex sediment and planktonic consortia from an aquifer adjacent to the Colorado River (USA) and reconstructed the first complete genomes for Archaea using cultivation-independent methods. To provide taxonomic context, we analyzed an additional 151 newly sampled archaeal sequences. We resolved two new phyla within a major, apparently deep-branching group of phyla (a superphylum). The organisms have small genomes, and metabolic predictions indicate that their primary contributions to Earth's biogeochemical cycles involve carbon and hydrogen metabolism, probably associated with symbiotic and/or fermentation-based lifestyles.The results dramatically expand genomic sampling of the domain Archaea and clarify taxonomic designations within a major superphylum. This study, in combination with recently published work on bacterial phyla lacking cultivated representatives, reveals a fascinating phenomenon of major radiations of organisms with small genomes, novel proteome composition, and strong interdependence in both domains.

Castelle, Cindy J↗
DOE OSTI2019

Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing

Analysis of reactive-diffusion simulations representing complex mixing processes requires a large number of independent model runs. For each high-fidelity model simulation, the model inputs are varied and the predicted mixing behavior is represented by temporal and spatial changes in species concentration. It is then required to discern how the model inputs (such as diffusivity, dispersion, anisotropy, and velocity field properties) impact the mixing process. This task is challenging and typically involves interpretation of large model outputs representing temporal and spatial changes of species concentration within the model domain. Yet, the task can be automated and substantially simplified by applying Machine Learning (ML) methods. Here, we present an application of an unsupervised ML method (called NTF k ) using Non-negative Tensor Factorization (NTF) coupled with a custom clustering procedure based on k-means to reveal the temporal and spatial features in product concentrations. An attractive and unique aspect of the proposed ML method is that it ensures the extracted features are non-negative, which is important to obtain a meaningful deconstruction of the mixing processes. The ML methodology is applied to a large set of high-resolution finite-element model simulations representing anisotropic reaction-diffusion processes in perturbed vortex-based velocity fields. The applied finite-element method ensures that spatial and temporal species concentration are always non-negative, even in the case of high anisotropic contrasts. The simulated reaction is a fast irreversible bimolecular reaction A+B→C , where species A and B react to form species C. The reactive-diffusion model input parameters that control mixing include properties of the velocity field (such as vortex structures), anisotropic dispersion, and molecular diffusion. We demonstrate the applicability of the ML feature extraction method to produce a meaningful deconstruction of model outputs to discriminate between different physical processes impacting the reactants, their mixing, and the spatial distribution of the product C. The introduced ML analysis allowed us to identify additive temporal and spatial features that characterize mixing behavior. The application of the proposed NTF k approach is not limited to reactive-mixing. NTFk can be readily applied to any observed or simulated datasets that can be represented as tensors (multi-dimensional arrays) and have separable latent signatures or features.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of miniapps has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively represent these performance issues. We applied this methodology to four miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, ''Under what conditions does a miniapp represent a key performance characteristic in a full app?''

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Learning and meta-learning of stochastic advection–diffusion–reaction systems from sparse measurements

Physics-informed neural networks (PINNs) were recently proposed in [18] as an alternative way to solve partial differential equations (PDEs). A neural network (NN) represents the solution, while a PDE-induced NN is coupled to the solution NN, and all differential operators are treated using automatic differentiation. Here, we first employ the standard PINN and a stochastic version, sPINN, to solve forward and inverse problems governed by a non-linear advection–diffusion–reaction (ADR) equation, assuming we have some sparse measurements of the concentration field at random or pre-selected locations. Subsequently, we attempt to optimise the hyper-parameters of sPINN by using the Bayesian optimisation method (meta-learning) and compare the results with the empirically selected hyper-parameters of sPINN. In particular, for the first part in solving the inverse deterministic ADR, we assume that we only have a few high-fidelity measurements, whereas the rest of the data is of lower fidelity. Hence, the PINN is trained using a composite multi-fidelity network, first introduced in [12], that learns the correlations between the multi-fidelity data and predicts the unknown values of diffusivity, transport velocity and two reaction constants as well as the concentration field. For the stochastic ADR, we employ a Karhunen–Loève (KL) expansion to represent the stochastic diffusivity, and arbitrary polynomial chaos (aPC) to represent the stochastic solution. Correspondingly, we design multiple NNs to represent the mean of the solution and learn each aPC mode separately, whereas we employ a separate NN to represent the mean of diffusivity and another NN to learn all modes of the KL expansion. For the inverse problem, in addition to stochastic diffusivity and concentration fields, we also aim to obtain the (unknown) deterministic values of transport velocity and reaction constants. The available data correspond to 7spatial points for the diffusivity and 20 space–time points for the solution, both sampled 2000 times. We obtain good accuracy for the deterministic parameters of the order of 1–2% and excellent accuracy for the mean and variance of the stochastic fields, better than three digits of accuracy. In the second part, we consider the previous stochastic inverse problem, and we use Bayesian optimisation to find five hyper-parameters of sPINN, namely the width, depth and learning rate of two NNs for learning the modes. Here, we obtain much deeper and wider optimal NNs compared to the manual tuning, leading to even better accuracy, i.e., errors less than 1% for the deterministic values, and about an order of magnitude less for the stochastic fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

QM Investigation of Rare Earth Ion Interactions with First Hydration Shell Waters and Protein-Based Coordination Models

Here, conventional methods for extracting rare earth metals (REMs) from mined mineral ores are inefficient, expensive, and environmentally damaging. Recent discovery of lanmodulin (LanM), a protein that coordinates REMs with high-affinity and selectivity over competing ions, provides inspiration for new REM refinement methods. Here, we used quantum mechanical (QM) methods to investigate trivalent lanthanide cation (Ln 3+ ) interactions with coordination systems representing bulk solvent water and protein binding sites. Energy decomposition analysis (EDA) showed differences in the energetic components of Ln 3+ interaction with representatives of solvent (water, H 2 O) and protein binding sites (acetate, CH 3 COO – ), highlighting the importance of accurate description of electrostatics and polarization in computational modeling of REM interactions with biological and bioinspired molecules. Relative binding free energies were obtained for Ln 3+ with coordination complexes originating from binding sites in PDB structures of a lanthanum binding peptide (PDB entry 7CCO) and LanM, with explicit consideration of the first hydration shell waters, according to quasi-chemical theory (QCT). Beyond the first shell, the bulk solvent environment was represented with an implicit continuum model. Ln 3+ interactions with (H 2 O) 9 and both binding site models became more favorable, moving down the periodic series. This trend was more pronounced with the protein binding site models than with water, resulting in affinity increasing with periodic number, except for the last REM, Lu 3+ , which bound less favorably than the preceding element, Yb 3+ . Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. Conversely, the previously reported experimental data for LanM show a preference for the earlier lanthanides; this is likely due to longer-range interactions and cooperative effects, which are not represented by the reduced models. Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. In contrast to the previously reported experimental data for LanM, the peptide preferentially binds the earlier lanthanides. This difference likely arises due to longer-range interactions and cooperative effects not represented by the peptide. Further investigation of Ln 3+ interactions with whole proteins using polarizable molecular mechanics models with explicit solvent is warranted to understand the influence of longer-ranged interactions, cooperativity, and bulk solvent. Nevertheless, the present work provides new insights into Ln 3+ interactions with biomolecules and presents an effective computational platform for designing specific single-site REM binding peptides more efficiently.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Time‐And‐Space Averaging Applied to Intermittent Multiphase Flow Experiments

Abstract Various researchers have studied fluctuations in pore‐scale phase occupancy during multiphase flow in porous media using synchrotron‐based X‐ray microcomputed tomography (micro‐CT). However, the impact of these fluctuations on the concept of a representative volume is not yet fully understood. In this study, we performed spatial and temporal averaging of multiphase flow experiments visualized with synchrotron‐based micro‐CT, focusing on oil saturation as the key parameter to determine a representative time‐and‐space average. Our findings revealed that a saturation value representative of both time and space was achieved during fractional flow experiments in drainage mode with fractional flows of 0.8, 0.5, and 0.3. Furthermore, we computed a range of relative permeabilities on the basis of whether momentaneous saturation or time‐and‐space averaged saturation was utilized for direct simulation. Our results highlighted the importance of time‐and‐space averaging in determining a representative relative permeability and indicated that the temporal and spatial scales covered in a typical micro‐CT flow experiment were sufficient to obtain a representative saturation value for sandstone rock under intermittent flow conditions.

Environmental Sciences & Ecology↗
DOE OSTI2026

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗
DOE OSTI2023

Achieving Realistic Runoff in the Western United States with a Land Surface Model Forced by Dynamically Downscaled Meteorology

Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.

Meteorology & Atmospheric Sciences↗
DOE OSTI2014

Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO)

The Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO) program brought together a team of representatives from government, academia, and private industry to enhance the availability of energy efficiency services for small livestock producers in the State of Missouri. The Missouri Department of Agriculture (MDA) managed the project via a subcontract with the University of Missouri (MU), College of Agriculture Food and Natural Resources, MU Extension, the MU College of Human Environmental Sciences, the MU College of Engineering, and the Missouri Agricultural and Small Business Development Authority (MASBDA). MU teamed with EnSave, Inc, a nationally-recognized expert in agricultural energy efficiency to assist with marketing, outreach, provision of farm energy audits and customer service. MU also teamed with independent home contractors to facilitate energy audits of the farm buildings and homes of these livestock producers. The goals of the project were to: (1) improve the environment by reducing fossil fuel emissions and reducing the total energy used on small animal farms; (2) stimulate the economy of local and regional communities by creating or retaining jobs; and (3) improve the profitability of Missouri livestock producers by reducing their energy expenditures. Historically, Missouri scientists/engineers conducted programs on energy use in agriculture, such as in equipment, grain handling and tillage practices. The MAESTRO program was the first to focus strictly on energy efficiency associated with livestock production systems in Missouri and to investigate the applicability and potential of addressing energy efficiency in animal production from a building efficiency perspective. A. Project Objectives The goal of the MAESTRO program was to strengthen the financial viability and environmental soundness of Missouri's small animal farms by helping them implement energy efficient technologies for the production facility, farm buildings, and the homes on these farms. The expected measurable outcomes of the project were to improve the environment and stimulate the economy by: • Reducing annual fossil fuel emissions by 1,942 metric tons of carbon dioxide equivalent, reducing the total annual energy use on at least 323 small animal farms and 100 farm homes by at least 8,000 kWh and 2,343 therms per farm. • Stimulating the economy by creating or retaining at least 69 jobs, and saving small animal farmers an average of $2,071 per farm in annual energy expenditures. B. Project Scope The MAESTRO team chose the target population of small farms because while all agriculture is traditionally underserved in energy efficiency programs, small farms were particularly underserved because they lack the financial resources and access to energy efficiency technologies that larger farms deploy. The MAESTRO team reasoned that energy conservation, financial and educational programs developed while serving the agricultural community could serve as a national model for other states and their agricultural sectors. The target population was approximately 2,365 small animal farm operations in Missouri, specifically those farms that were not by definition a confined animal feeding operation (CAFO). The program was designed to create jobs by training Missouri contractors and Missouri University Extension staff how to conduct farm audits. The local economy would be stimulated by an increase in construction activity and an increasing demand for energy efficient farm equipment. Additionally, the energy savings were deemed critical in keeping Missouri farms in business. This project leveraged funds using a combination of funds from the Missouri Department of Natural Resources’ Missouri Energy Center and its Soil and Water Conservation Program, from the state's Linked Deposits, MASBDA's agricultural loan guarantee programs, and through the in-kind contribution of faculty and staff time to the project from these agencies and MU. Several hundred Missouri livestock producers were contacted during the MAESTRO project. Of the livestock producers, 254 invited the team to conduct a farm energy assessment which complied with ASABE 612. A total of 147 livestock farm upgrades were implemented, representing 57.5 percent of the farms for which a farm energy assessment was completed. This represented a statewide average annual savings of 1,088,324 kWh and 75,516 therms. The team also reviewed the condition of the livestock producer’s home(s). A total of 106 home energy assessments were completed and 48 individual homes implemented their recommended upgrades, representing 45 percent of the farm homes for which an energy assessment was completed. This represented a statewide average annual savings of 323,029 kWh, and 769.4 therms. More of these farmers likely would have updated their homes but the funding to incentivize them fell short. In spite of the shortfall in incentive funds, some farmers still updated their homes as they saw the value in making these changes to their home.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Determining the Release of Radionuclides from Tank Waste Residual Solids: FY2015 Report

Methodology development for pore water leaching studies has been continued to support Savannah River Site High Level Waste tank closure efforts. For FY2015, the primary goal of this testing was the achievement of target pH and Eh values for pore water solutions representative of local groundwater in the presence of grout or grout-representative (CaCO 3 or FeS) solids as well as waste surrogate solids representative of residual solids expected to be present in a closed tank. For oxidizing conditions representative of a closed tank after aging, a focus was placed on using solid phases believed to be controlling pH and E h at equilibrium conditions. For three pore water conditions (shown below), the target pH values were achieved to within 0.5 pH units. Tank 18 residual surrogate solids leaching studies were conducted over an E h range of approximately 630 mV. Significantly higher Eh values were achieved for the oxidizing conditions (ORII and ORIII) than were previously observed. For the ORII condition, the target Eh value was nearly achieved (within 50 mV). However, E h values observed for the ORIII condition were approximately 160 mV less positive than the target. E h values observed for the RRII condition were approximately 370 mV less negative than the target. Achievement of more positive and more negative E h values is believed to require the addition of non-representative oxidants and reductants, respectively. Plutonium and uranium concentrations measured during Tank 18 residual surrogate solids leaching studies under these conditions (shown below) followed the general trends predicted for plutonium and uranium oxide phases, assuming equilibrium with dissolved oxygen. The highest plutonium and uranium concentrations were observed for the ORIII condition and the lowest concentrations were observed for the RRII condition. Based on these results, it is recommended that these test methodologies be used to conduct leaching studies with actual Tank 18 residual solids material. Actual waste testing will include leaching evaluations of technetium and neptunium, as well as plutonium and uranium.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Summer term 2018 work with IMC radiative transport in binary stochastic media

In the quest for new and improved methods to solve thermal radiation transport in stochastic media, this summer project was to characterize radation transport in a deterministic lattice problem that represents a real, binary stochastic media. A representative geometry for a binary stochastic media consisting of a cube of a high volume fraction media containing constant-diameter non-overlappying spheres randomly distributed within was run previously. Previous thermal radiation wave problems in binary stochastic media displayed three characteristic thermal energy deposition wavefronts in the following order, front of the spheres, bulk material, and the backs of the spheres. Several physical aspects of the representative geometry for a stochastic binary media using an optically thin background with optically thick spheres were analyzed. This analysis includes wave speed propagation using a one dimensional diffusion approximation, energy fluence transmission, and material energy deposition. The approaches to analysis included representing one sphere of the high opacity material in a diffusive background of the low opacity material, as well as repeating spheres in a column con guration with reflective boundary conditions to approximate a lattice. Additionally, both atomic mix and Levermore-Pomraning homogenization schemes were compared against the representative cube geometry as well as the sphere column lattice geometry. The wave speed analysis with a one dimensional Marshak diffusion wave was largely ineffective at determining an effective opacity value to which a problem could be homogenized, likely due to low mean free path resolution within the problem. However, the sphere column lattice geometry showed promising results for approximating the energy fluence transmitted through the problem domain. One concern with the sphere column lattice geometry indicated the high forward-bias effect of fluence reaching the problem boundary due to streaming paths around the spheres in the case of small mean free path resolution of the background material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hydropower Geotechnical Foundations: Current Practice and Innovation Opportunities for Low-Head Applications

Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to challenges frequently encountered with traditional approaches. With this understanding, it is critically important to understand and document the current state of practice for hydropower geotechnical foundations, identify key challenges, and define opportunities for innovative solutions. To this end, this report documents the current state of practice across the three main phases of geotechnical foundation development: (1) geotechnical site assessment, (2) design, and (3) construction for hydropower systems. It also describes the major challenges with conventional approaches and identifies opportunities for innovation to reduce hydropower foundations costs, timelines, and risks. Key takeaways from this report include the following: Approximately 80% of available low-head sites are expected to have foundations on soil beds rather than rock beds, suggesting that rockfill and earthfill dams may be the most cost-effective conventional dam type for new projects.; Geotechnical and geologic investigation activities are time-consuming and expensive but are essential to define the parameters and criteria needed for foundation design.; Certain riverbed soil and bedrock types present significant technical challenges or require expensive foundation construction, which can prove financially prohibitive for low-head project development.; Modular hydropower design and prefabricated modular foundations represent a promising but unproven paradigm for new hydropower development. Design and construction approaches using optimized and highly repeatable, reliable components would benefit project cost, time, and risk but require additional research and development.; Temporary construction features for foundations, including cofferdams, water diversion, and water control systems, can prove costly and have inherent construction risk.; For economically viable development, hydropower geotechnical foundations should be limited to 4 to 15% of the project’s total initial capital costs. Many proposed projects have experienced cost overruns attributable to foundation difficulties or surprises during construction. These overruns may have been due to inadequate investigations, lack of adequate engineering effort to tailor the structures to site geology and topography, and/or contractual terms, among other considerations.; Challenges for hydropower foundations and opportunities for innovative technology solutions are identified in the following areas (consistent with the three main phases of foundation development): Geotechnical site assessment, Foundation design and materials, Construction methods and technology. Ultimately, this report aims to provide information about geotechnical foundations for low-head hydropower and to motivate transformative technologies to support hydropower growth.

13 HYDRO ENERGY↗
DOE OSTI2024

EPCAPE-PT-LANL Measurements: Wideband Integrated Bioaerosol Sensor

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Wideband Integrated Bioaerosol Sensor (Droplet Measurements Technology) Data Notes: The WIBS is an online single-particle measurement that detects FBAPs (within a size range of 0.5 - 30 microns in diameter) based on the excitation and emission wavelengths of the individual particles. Using two xenon lamps, the WIBS excites FBAPs at 280 nm and 370 nm. Their emission is detected across two wavebands of 310-400 nm and 420-650 nm. We classified the FBAPs into seven different categories (A, B, C, AB, BC, AC, and ABC) using the classification scheme in Perring et. al. (2015) [1]. Averaged number concentration of FBAPs (total and by category) and particles that non-fluorescent bioaerosols particles (NFBAPs). In separate files, we also present one-minute-averaged size distributions and the asymmetry factor (AF, a surrogate for shape) of all FBAPs and NFBAPs. The logarithmic bin width of the size bins are the same as the average bin width of the AOS's optical particle counter (OPC, Grimm) for the range of sizes in which they overlap (26 bins from 0.5 - 30 microns). AF of the particles ranges from 0-100 and is divided into five bins with a linear spacing at increments of 20. The smallest AF bin represents more spherical particles while the largest bin represents more rod-shaped particles. [1] Perring, A. E., et al. (2015), Airborne observations of regional variation in fluorescent aerosol across the United States, J. Geophys. Res. Atmos., 120, 1153–1170, doi:10.1002/2014JD022495. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2023epcape-pt-lanl. Files data_10min_WIBS_AFDist.csv Header: - FBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of FBAPs detected during the measurement. - NFBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of non-fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of NFBAPs detected during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. AF Bins: • Bin 1: 0 – 20 [unitless] • Bin 2: 21 – 40 [unitless] • Bin 3: 41 – 60 [unitless] • Bin 4: 61 – 80 [unitless] • Bin 5: 81 – 100 [unitless] Files data_10min_WIBS_Conc.csv Header: - NumberConcentrationA[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel A, measured in particles per cubic centimeter. - NumberConcentrationB[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel B, measured in particles per cubic centimeter. - NumberConcentrationC[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel C, measured in particles per cubic centimeter. - NumberConcentrationAB[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and B, measured in particles per cubic centimeter. - NumberConcentrationBC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels B and C, measured in particles per cubic centimeter. - NumberConcentrationAC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and C, measured in particles per cubic centimeter. - NumberConcentrationABC[/cm3]: Combined number concentration of bioaerosol particles detected by all three fluorescence channels A, B, and C, measured in particles per cubic centimeter. - NumberConcentrationNFBAP[/cm3]: Number concentration of non-fluorescent bioaerosol particles, measured in particles per cubic centimeter. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Files data_10min_WIBS_SizeDist.csv Header: - FBAP_SizeDist[/cm3]_Bin_1 to FBAP_SizeDist[/cm3]_Bin_26: Number concentrations of FBAP in each of 26 size bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle sizes, capturing the size distribution of FBAPs detected during the measurement. - NFBAP_SizeDist[/cm3]_Bin_1 to NFBAP_SizeDist[/cm3]_Bin_26: Number concentrations of NFBAP in each of 26 size bins, measured in particles per cubic centimeter. Similar to FBAP, each bin covers a specific range of particle sizes, detailing the size distribution of NFBAPs detected. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Size Bins: • Bin 1: 0.48 to 0.57 μm • Bin 2: 0.57 to 0.67 μm • Bin 3: 0.67 to 0.79 μm • Bin 4: 0.79 to 0.93 μm • Bin 5: 0.93 to 1.1 μm • Bin 6: 1.1 to 1.29 μm • Bin 7: 1.29 to 1.52 μm • Bin 8: 1.52 to 1.8 μm • Bin 9: 1.8 to 2.11 μm • Bin 10: 2.11 to 2.5 μm • Bin 11: 2.5 to 2.94 μm • Bin 12: 2.94 to 3.46 μm • Bin 13: 3.46 to 4.08 μm • Bin 14: 4.08 to 4.81 μm • Bin 15: 4.81 to 5.67 μm • Bin 16: 5.67 to 6.68 μm • Bin 17: 6.68 to 7.88 μm • Bin 18: 7.88 to 9.29 μm • Bin 19: 9.29 to 10.96 μm • Bin 20: 10.96 to 12.92 μm • Bin 21: 12.92 to 15.23 μm • Bin 22: 15.23 to 17.96 μm • Bin 23: 17.96 to 21.17 μm • Bin 24: 21.17 to 24.96 μm • Bin 25: 24.96 to 29.43 μm • Bin 26: 29.43 to 34.70 μm

54 ENVIRONMENTAL SCIENCES↗