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At least 901 records · Page 50

Cosmic ray sampling of a clumpy interstellar medium

How cosmic rays sample the multi-phase interstellar medium (ISM) in starburst galaxies has important implications for many science goals, including evaluating the cosmic ray calorimeter model for these systems, predicting their neutrino fluxes, and modeling their winds. Here, we use Monte Carlo simulations to study cosmic ray sampling of a simple, two-phase ISM under conditions similar to those of the prototypical starburst galaxy M82. The assumption that cosmic rays sample the mean density of the ISM in the starburst region is assessed over a multi-dimensional parameter space where we vary the number of molecular clouds, the galactic wind speed, the extent to which the magnetic field is tangled, and the cosmic ray injection mechanism. We evaluate the ratio of the emissivity from pion production in molecular clouds to the emissivity that would be observed if the cosmic rays sampled the mean density, and seek areas of parameter space where this ratio differs significantly from unity. The assumption that cosmic rays sample the mean density holds over much of parameter space; however, this assumption begins to break down for high cloud density, injection close to the clouds, and a very tangled magnetic field. We conclude by evaluating the extent to which our simulated starburst region behaves as a proton calorimeter and constructing the time-dependent spectrum of a burst of cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗

Alignment of sample position and rotation during in situ synchrotron X-ray micro-diffraction experiments using a Laue cross-correlation approach

Laue micro-diffraction has proven to be able to reveal material properties at the sub-grain scale for many polycrystalline materials and is now routinely available at several synchrotron facilities, providing an approach for nondestructive three-dimensional probing of the microstructures and mechanical states of materials. However, for in situ experiments, maintaining the positioning of the sample throughout the experiment, to achieve a good alignment of the characterized volumes, is a challenging issue. The aim of the present work is to address this problem by developing an approach based on digital image correlation of focused-beam Laue diffraction patterns. The method uses small changes in the diffraction signal as a focused X-ray beam is scanned over a surface region to allow corrections to be made for both sample lateral movement and rotation. The method is demonstrated using a tensile deformation experiment on an Al sample with 2.5 µm average grain size. The results demonstrate an accuracy of 0.5 µm for sample position registration and a precision in sample rotation of ~0.01°. Finally, the proposed method is fast to implement and does not require the use of additional surface markers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗

Sample Complexity of Power System State Estimation Using Matrix Completion

In this paper, we propose an analytical framework to quantify the amount of data samples needed to obtain accurate state estimation in a power system - a problem known as sample complexity analysis in computer science. Motivated by the increasing adoption of distributed energy resources into the distribution-level grids, it becomes imperative to estimate the state of distribution grids in order to ensure stable operation. Traditional power system state estimation techniques mainly focus on the transmission network which involve solving an overdetermined system and eliminating bad data. However, distribution networks are typically underdetermined due to the large number of connection points and high cost of pervasive installation of measurement devices. In this paper, we consider the recently proposed state-estimation method for underdetermined systems that is based on matrix completion. In particular, a constrained matrix completion algorithm was proposed, wherein the standard matrix completion problem is augmented with additional equality constraints representing the physics (namely power-flow constraints). We analyze the sample complexity of this general method by proving an upper bound on the sample complexity that depends directly on the properties of these constraints that can lower number of needed samples as compared to the unconstrained problem. To demonstrate the improvement that the constraints add to state estimation, we test the method on a 141-bus distribution network case study and compare it to the traditional least squares minimization state estimation method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

False-Negative Rate and Recovery Efficiency Performance of a Validated Sponge Wipe Sampling Method

Recovery of spores from environmental surfaces varies due to sampling and analysis methods, spore size and characteristics, surface materials, and environmental conditions. Tests were performed to evaluate a new, validated sponge wipe method using Bacillus atrophaeus spores. Testing evaluated the effects of spore concentration and surface material on recovery efficiency (RE), false-negative rate (FNR), limit of detection (LOD), and their uncertainties. Ceramic tile and stainless steel had the highest mean RE values (48.9 and 48.1%, respectively). Faux leather, vinyl tile, and painted wood had mean RE values of 30.3, 25.6, and 25.5, respectively, while plastic had the lowest mean RE (9.8%). Results show roughly linear dependences of RE and FNR on surface roughness, with smoother surfaces resulting in higher mean REs and lower FNRs. REs were not influenced by the low spore concentrations tested (3.10x10^-3 to 1.86 CFU/cm^2). Stainless steel had the lowest mean FNR (0.123), and plastic had the highest mean FNR (0.479). The LOD90 (>1 CFU detected 90% of the time) varied with surface material, from 0.015 CFU/cm^2 on stainless steel up to 0.039 on plastic. It may be possible to improve sampling results by considering surface roughness in selecting sampling locations and interpreting spore recovery data. Further, FNR values (calculated as a function of concentration and surface material) can be used presampling to calculate the numbers of samples for statistical sampling plans with desired performance and postsampling to calculate the confidence in characterization and clearance decisions.

Anthrax↗

Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling

The increasing complexity of both scientific simulations and high-performance computing system architectures are driving the need for adaptive workflows, in which the composition and execution of computational and data manipulation steps dynamically depend on the evolutionary state of the simulation itself. Consider, for example, the frequency of data storage. Critical phases of the simulation should be captured with high frequency and with high fidelity for postanalysis; however, we cannot afford to retain the same frequency for the full simulation due to the high cost of data movement. We can instead look for triggers, indicators that the simulation will be entering a critical phase, and adapt the workflow accordingly. In this paper, we present a methodology for detecting triggers and demonstrate its use in the context of direct numerical simulations of turbulent combustion using S3D. We show that chemical explosive mode analysis (CEMA) can be used to devise a noise-tolerant indicator for rapid increase in heat release. However, exhaustive computation of CEMA values dominates the total simulation, and thus is prohibitively expensive. To overcome this computational bottleneck, we propose a quantile sampling approach. Our sampling-based algorithm comes with provable error/confidence bounds, as a function of the number of samples. Most importantly, the number of samples is independent of the problem size, and thus our proposed sampling algorithm offers perfect scalability. Our experiments on homogeneous charge compression ignition and reactivity controlled compression ignition simulations show that the proposed method can detect rapid increases in heat release, and its computational overhead is negligible. Our results will be used to make dynamic workflow decisions regarding data storage and mesh resolution in future combustion simulations.

97 MATHEMATICS AND COMPUTING↗

Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling.

The recent growth in multifidelity uncertainty quantification has given rise to a large set of variance reduction techniques that leverage information from model ensembles to provide variance reduction for estimates of the statistics of a high-fidelity model. In this paper we provide two contributions: (1) we utilize an ensemble estimator to account for uncertainties in the optimal weights of approximate control variate (ACV) approaches and derive lower bounds on the number of samples required to guarantee variance reduction; and (2) we extend an existing multifidelity importance sampling (MFIS) scheme to leverage control variates. Our approach directly addresses a limitation of many multifidelity sampling strategies that require the usage of pilot samples to estimate covariances. As such we make significant progress towards both increasing the practicality of approximate control variates—for instance, by accounting for the effect of pilot samples—and using multifidelity approaches more effectively for estimating low-probability events. The numerical results indicate our hybrid MFIS-ACV estimator achieves up to 50% improvement in variance reduction over the existing state-of-the-art MFIS estimator, which had already shown an outstanding convergence rate compared to the Monte Carlo method, on several problems of computational mechanics.

97 MATHEMATICS AND COMPUTING↗

Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Related sensor data are published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054. This data package was originally published September 2022. It was updated May 2023 (modified files) and November 2024 (new and modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), ions, and benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol (8) readme; (9) methods codes; (10) international generic-sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We thank the United States Forest Service, Washington Department of Natural Resources, Washington Department of Fish and Wildlife, Washington State Parks, Confederated Tribes and Bands of the Yakama Nation, and Cowiche Canyon Conservancy for access to field locations where these samples were collected. We also thank 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↗

Technical Basis for the Removal of Unremediated Nitrate Salt Sampling (UNS) to Support LANL Treatment Studies

The sampling of unremediated nitrate salts (UNS) was originally proposed by the U.S. Department of Energy (DOE) and Los Alamos National Security, LLC (LANS) (collectively, the Permittees) as a means to ensure adequate understanding and characterization of the problematic waste stream created when the Permittees remediated these nitrate salts-bearing waste with an organic absorbent. The proposal to sample the UNS was driven by a lack of understanding with respect to the radioactive contamination release that occurred within the underground repository at the Waste Isolation Pilot Plant (WIPP) in February 14, 2014, as well as recommendations made by a Peer Review Team. As discussed, the Permittees believe that current knowledge and understanding of the waste has sufficiently matured such that this additional sampling is not required. Perhaps more importantly, the risk of both chemical and radiological exposure to the workers sampling the UNS drum material is unwarranted. This memo provides the technical justification and rationale for excluding the UNS sampling from the treatment studies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of solid materials for UF 6 sampling: FY16 Annual Report

A handheld implementation of the ABACC-developed Cristallini method, which captures uranium hexafluoride samples as an inert salt, was organized in FY17 and succeeded in demonstrating the handheld sampler concept with reactive hexafluoride gases. The Cristallini method relies on the use of a hydrated substrate to react the incoming hexafluoride resulting in the formation of a stable uranyl fluoride salt. The Cristallini method has been demonstrated as a facility modification installed near the sampling tap of a gas centrifuge enrichment plant. While very successful in reducing the hazards of uranium hexafluoride sample, the method still takes a considerable amount of time and can only be used in facilities where the apparatus has been installed; this arrangement generally prohibits the sampling of filled cylinders that have already exited the facility and have been deposited in the on-site tank storage yard. The handheld unit under development will allow the use of the Cristallini method at facilities that have not been converted as well as tanks in the storage yard. The handheld system utilizes an active vacuum system, rather than a passive vacuum system in the facility setup, to drive the uranium hexafluoride onto the adsorbing media. The handheld unit will be battery operated for fully autonomous operation and will include onboard pressure sensing and flushing capability. To date, the system concept of operations was demonstrated with tungsten hexafluoride that showed the active vacuum pump with multiple cartridges of adsorbing media was viable. Concurrently, the hardened prototype system was developed and tested; removable sample cartridges were developed (the only non-COTS component to date); and preparations were made for uranium tests and a domestic field test.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analysis Results for Sub-Samples of SRS Tanks 30, 32, and 39 to Support Evaluations of the I-129 Inventory

In order to appropriately model and predict the chemical integrity and performance of cementitious materials used for waste immobilization at the Savannah River Site (SRS), it is critical to understand the I-129 solubility and distribution within the tank farm. Iodine in radioactive waste and in environmental media is typically highly mobile and long lived. Iodine is ubiquitous in SRS tank waste and waste forms. The iodine is assumed to be soluble and present at low levels in Performance Assessments (PAs) for SRS Tank Farms, and is one of the dose drivers in the PAs for both the SRS Salt Disposal Facility (SDF) and the H-Area Tank Farm (HTF). Analysis of tank waste samples is critical to understanding the Tank Farm iodine inventory and reducing disposal uncertainty. Higher than expected iodine levels have recently been observed in residual solids isolated from some SRS tanks prior to closure, indicating uncertainty regarding the chemical species involved. If the iodine inventory uncertainty is larger than anticipated, future work may be necessary to reduce the uncertainty. This memorandum satisfies a portion of the work scope identified in Task Plan SRNL-RP-2016-00651. A separate memorandum issued previously, reported historical unpublished I-129 data, a significant portion of which was below detectable analytical limits. This memorandum includes iodine and general chemical analysis results for six archived SRNL samples which were previously reported to have I-129 concentrations below detectable limits. Lower sample dilution factors were used for the current analyses in order to obtain concentrations above detection. The samples analyzed included surface and depth samples from SRS tanks 30, 32, and 39.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data Validation Package May and June 2015 Groundwater and Surface Water Sampling at the Bluewater, New Mexico, Disposal Site, August 2015

Groundwater samples were collected from monitoring wells at the Bluewater, New Mexico, Disposal Site to monitor groundwater contaminants as specified in the 1997 Long-Term Surveillance Plan for the DOE Bluewater (UMTRCA Title II) Disposal Site Near Grants, New Mexico (LTSP). Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). Duplicate samples were collected from locations 14(SG) and 21(M). Sampling originally scheduled for the week of May 11, 2015 was interrupted by heavy rainfall and later completed in June.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package October 2016 Groundwater and Surface Water Sampling at the Monticello, Utah, Disposal and Processing Sites January 2017

Sampling Period: October 10–12, 2016. This semiannual event includes sampling groundwater and surface water at the Monticello Disposal and Processing Sites. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated) and Program Directive MNT-2016-01. Samples were collected from 54 of 64 planned locations (16 of 17 former mill site wells, 15 of 18 downgradient wells, 7 of 9 downgradient permeable reactive barrier wells, 3 of 3 bedrock wells, 4 of 7 seeps and wetlands, and 9 of 10 surface water locations).

54 ENVIRONMENTAL SCIENCES↗

Methylmercury and Ethylmercury Analytical Performance in SRR Samples Measured by SRNL and Eurofins Frontier Global Sciences

Existing models and simulants of tank disposition media at the Savannah River Site (SRS) have presumed the presence of high concentrations of inorganic mercury. However, quarterly Tank 50 analyses have shown that mercury is present as organomercurial species at concentrations that may present challenges to its remediation and disposition and may challenge the Waste Acceptance Criteria (WAC) for Saltstone. Todate, methylmercury analyses for Savannah River Remediation (SRR) have been performed at an off-site laboratory by Eurofins Frontier Global Sciences (FGS) in Bothell, WA. Savannah River Remediation requested the development of methylmercury and ethylmercury determination capabilities at the Savannah River National Laboratory (SRNL) to support the Liquid Waste Operations at SRS. As part of that method development, SRR requested that SRNL Analytical Development (AD) compare their results with those obtained from their outside contract laboratory, Eurofins FGS. This document reports on this method development work as well as the comparative analyses conducted between the two laboratories. A series of optimization and validation experiments has been performed at SRNL, which has resulted in the development of on-site methylmercury and ethylmercury speciation capabilities using purge and trap (P&T) gas chromatography (GC) coupled with thermal desorption (TD) cold vapor – atomic fluorescence spectroscopy (CVAFS). Speciation has been achieved for both species, with a methylmercury method reporting limit (MRL) value of 1.13 pg and an overall uncertainty (1σ) of 5.1%. An ethylmercury MRL of 11.5 pg and an overall uncertainty (1σ) of 4.8% were obtained. These analytical parameters compare favorably with Eurofins FGS, which demonstrates uncertainties (1σ) for methylmercury and ethylmercury of 13% and 9.1%, respectively. Results obtained by SRNL from the routine analysis of Tanks 21, 40, 50, and 51 samples have provided statistically indistinguishable results compared with Eurofins FGS. Based upon the work performed by SRNL-AD and the data currently available, the following recommendations can be made: Further work should be performed to determine a “best practices” for sample holding time prior to analysis (both preserved and non-preserved samples), as well as any detrimental effects sample age may have on data quality. Analysis of ethylmercury is only recommended for tank samples that are reasonably expected to have significant quantities of ethylmercury, such as from the DWPF SMECT. Trace levels of ethylmercury in the presence of large quantities of methylmercury can be difficult or impossible to quantify. SRNL-AD development of methods for total mercury, purgeable mercury (which includes Hg(0) and dimethylmercury), inorganic mercury (Hg(I) and Hg(II)), dissolved mercury, and particulate mercury are underway and will be reported upon separately.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Calendar Year 2021 Underground Test Area Annual Sampling Letter Report Nevada National Security Site, Nevada (Rev. 1) WITH ROTC-1

This calendar year (CY) 2021 annual sampling letter report presents Plan implementation and a summary of field activities, sampling methods, well completion diagrams, and analytical laboratory results from sampling of wells on Pahute Mesa. The CY 2021 letter report also presents data from samples collected in CY 2019. These CY 2019 results were not reported in previous sampling reports because they were not available from the specialized laboratory (Lawrence Livermore National Laboratory [LLNL]) at the time of the previous reports’ publication.

54 ENVIRONMENTAL SCIENCES↗

Representativeness-based Sampling Network Design for the State of Alaska

This data set collection consists of data products described in Hoffman et. al., 2013. Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks is described here. Multivariate spatiotemporal clustering was applied to down-scaled general circulation model results and data for the State of Alaska at 4 km2 resolution to define multiple sets of ecoregions across two decadal time periods. Maps of ecoregions for the present (2000-2009) and future (2090-2099) were produced, showing how combinations of 37 characteristics are distributed and how they may shift in the future. Representative sampling locations are identified on present and future ecoregion maps. A representativeness metric was developed, and representativeness maps for eight candidate sampling locations were produced. This metric was used to characterize the environmental similarity of each site. This analysis provides model-inspired insights into optimal sampling strategies, offers a framework for up-scaling measurements, and provides a down-scaling approach for integration of models and measurements. These techniques can be applied at different spatial and temporal scales to meet the needs of individual measurement campaigns. This dataset contains one zipped file, one .txt file, and one .sh file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Sequential Importance Sampling for Rare Event Estimation with Computer Experiments

Importance sampling often drastically improves the variance of percentile and quantile estimators of rare events. We propose a sequential strategy for iterative refinement of importance distributions for sampling uncertain inputs to a computer model to estimate quantiles of model output or the probability that the model output exceeds a fixed or random threshold. A framework is introduced for updating a model surrogate to maximize its predictive capability for rare event estimation with sequential importance sampling. Examples of the proposed methodology involving materials strength and nuclear reactor applications will be presented. The conclusions are: (1) Importance sampling improves UQ of percentile and quantile estimates relative to brute force approach; (2) Benefits of importance sampling increase as percentiles become more extreme; (3) Iterative refinement improves importance distributions in relatively few iterations; (4) Surrogates are necessary for slow running codes; (5) Sequential design improves surrogate quality in region of parameter space indicated by importance distributions; and (6) Importance distributions and VRFs stabilize quickly, while quantile estimates may converge slowly.

97 MATHEMATICS AND COMPUTING↗

Extended Characterization of Chemical Processes in Hot Cells Using Environmental Swipe Samples

Environmental sampling is used extensively by the International Atomic Energy Agency (IAEA) for verification of information from State declarations or a facility’s design regarding nuclear activities occurring within the country or a specific facility. Environmental sampling of hot cells within a facility under safeguards is conducted using 10.2 cm x 10.2 cm cotton swipe material or cellulose swipes. Traditional target analytes used by the IAEA to verify operations within a facility include a select list of gamma-emitting radionuclides and total and isotopic U and Pu. Analysis of environmental swipe samples collected within a hot-cell facility where chemical processing occurs may also provide information regarding specific chemicals used in fuel processing. However, using swipe material to elucidate what specific chemical processes were/are being used within a hot cell has not been previously evaluated. Staff from Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) teamed to evaluate the potential use of environmental swipe samples as collection media for volatile and semivolatile organic compounds. This evaluation was initiated with sample collection during a series of Coupled End-to-End (CETE) reprocessing runs at ORNL. The study included measurement of gamma emitting radionuclides, total and isotopic U and Pu, and volatile and semivolatile organic compounds. These results allowed us to elucidate what chemical processes used in the hot cells during reprocessing of power reactor and identify other legacy chemicals used in hot cell operations which predate the CETE process.

Environmental Sampling↗