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At least 1,297 records · Page 72

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Sample Collection Metadata for Soil Cores from the East River Watershed, Colorado collected in 2017

This data package contains sample collection metadata for soil cores from the East River Watershed in Colorado used in biogeochemical analyses by the Watershed Function SFA. Soil cores were collected seasonally during autumn, winter, snowmelt, and spring at a predominately montane meadow, high altitude field site. Information provided for each soil core sample assigned an International Geo Sample Number (IGSN) includes: sample name, IGSN, material, description, collection method, core depth, location, field program, collectors, and date. The full list of 53 IGSN's is listed in the Methods section. There is also a complete core sample list and metadata for the set of baseline data.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

Firex Water Tank, SWMU 069, Confirmatory Sampling Report: Revision 2

The National Aeronautics and Space Administration (NASA) Resource Conservation and Recovery Act (RCRA) permit requires identification and evaluation of known Solid Waste Management Units (SWMU) located at the Kennedy Space Center (KSC). Firex Water Tank (FWT), or the “site,” is designated as SWMU 069 under the NASA RCRA permit. This report summarizes the results of the Confirmatory Sampling (CS) field activities carried out during Fall 2021, at FWT, SWMU 069, KSC, Florida. Three locations of concern (LOCs) were identified by screening historical sample results to current State of Florida soil cleanup target levels (SCTL). A total of 18 soil samples were collected to investigate the historical exceedance locations. Samples at LOC 1 and 2 were analyzed for arsenic and the results for all were below the SCTL. Samples at LOC 3 were analyzed for polynuclear aromatic hydrocarbons and it was determined that certain locations have results that remain above the SCTL. The current land use controls will remain in place at FWT to mitigate potential risks.

Firex↗

NASA NTRS2024

Development of Cryogenic Phase Change Materials for Lunar Sample Return

One of the scientific goals of NASA’s Artemis missions is to return regolith samples from the lunar surface. To maintain scientific integrity of these samples, including any volatiles that may exist, cryogenic stowage is desired. FROSTE (Frozen Return Of Samples To Earth) is the element of the Moon to Mars architecture that is tasked with developing and advancing concepts related to this goal. Both active and passive solutions are being considered, but active solutions (cryo-coolers) have high mass and cost penalties. Phase change materials (PCMs) are commonly used as passive thermal management solutions, particularly for sensitive scientific samples. However, there are currently no PCMs capable of providing cooling at the cryogenic temperatures needed to enable lunar sample return with volatiles intact (<120 K). FROSTE has identified two possible candidate materials that could fill this gap. Testing is required to verify the thermal performance of these materials, as well as gain experience with their handling characteristics. We are conducting this testing at the Marshall Space Flight Center’s Space Environmental Effects laboratory, in vacuum, with liquid nitrogen providing cooling ability below the freezing point of the materials. In this talk, we will present an overview of the FROSTE program element and share results from the initial development testing of two cryogenic phase change materials.

phase change material↗

DOE OSTI2022

Dispersion-enhanced sequential batch sampling for adaptive contour estimation

In computer simulation and optimal design, sequential batch sampling offers an appealing way to iteratively stipulate optimal sampling points based upon existing selections and efficiently construct surrogate modeling. Nonetheless, the issue of near duplicates poses tremendous quandary for sequential learning. It refers to the situation that selected critical points cluster together in each sampling batch, which are individually but not collectively informative towards the optimal design. Near duplicates severely diminish the computational efficiency as they barely contribute extra information towards update of the surrogate. To address this issue, we impose a dispersion criterion on concurrent selection of sampling points, which essentially forces a sparse distribution of critical points in each batch, and demonstrate the effectiveness of this approach in adaptive contour estimation. Specifically, we adopt Gaussian process surrogate to emulate the simulator, acquire variance reduction of the critical region from new sampling points as a dispersion criterion, and combine it with the modified expected improvement (EI) function for critical batch selection. The critical region here is the proximity of the contour of interest. This proposed approach is vindicated in numerical examples of a two-dimensional four-branch function, a four-dimensional function with a disjoint contour of interest and a time-delay dynamic system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Benchtop-compatible sample processing workflow for proteome profiling of < 100 mammalian cells

Extending proteomics to smaller samples can enable the mapping of protein expression across tissues with high spatial resolution and can reveal sub-group heterogeneity. However, despite the continually improving sensitivity of LC-MS instrumentation, in-depth profiling of samples containing low-nanogram amounts of protein has remained challenging due to analyte losses incurred during preparation and analysis. To address this, we recently developed nanodroplet processing in one pot for trace samples (nanoPOTS), a robotic/microfluidic platform that generates ready-to-analyze peptides from cellular material in ~200 nL droplets with greatly reduced sample losses. In combination with ultrasensitive LC-MS, nanoPOTS has enabled >3000 proteins to be confidently identified from as few as 10 cultured human cells and ~700 proteins from single cells. However, the nanoPOTS platform requires a highly skilled operator and a costly in-house-built robotic nanopipetting instrument. In this work, we sought to evaluate the extent to which the benefits of nanodroplet processing could be preserved when upscaling reagent dispensing volumes by a factor of 10 to those addressable by commercial micropipette. We characterized the resulting platform, termed microdroplet processing in one pot for trace samples (µPOTS), for the analysis of as few as ~25 cultured HeLa cells (4 ng total protein) or 50 µm square mouse liver tissue thin sections and found that ~1800 and ~1200 unique proteins were respectively identified with high reproducibility. As such, the reduced equipment requirements should facilitate broad dissemination of nanoproteomics workflows by obviating the need for a capital-intensive custom liquid handling system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Image Registration of Cone-Beam Computer Tomography and Preprocedural Computer Tomography Aids in Localization of Adrenal Veins and Decreasing Radiation Dose in Adrenal Vein Sampling

PurposeWe assessed whether image registration of cone-beam computed tomography (CT) (CBCT) and contrast-enhanced CT (CE-CT) images indicating the locations of the adrenal veins can aid in increasing the success rate of first-attempts adrenal vein sampling (AVS) and therefore decreasing patient radiation dose.Materials and Methods CBCT scans were acquired in the interventional suite (Philips Allura Xper FD20) and rigidly registered to the vertebra in previously acquired CE-CT. Adrenal vein locations were marked on the CT image and superimposed with live fluoroscopy and digital-subtraction angiography (DSA) to guide the AVS. Seventeen first attempts at AVS were performed with image registration and retrospectively compared with 15 first attempts without image registration performed earlier by the same 2 interventional radiologists. First-attempt AVS was considered successful when both adrenal vein samples showed representative cortisol levels. Sampling time, dose-area product (DAP), number of DSA runs, fluoroscopy time, and skin dose were recorded.ResultsWithout image registration, the first attempt at sampling was successful in 8 of 15 procedures indicating a success rate of 53.3 %. This increased to 76.5 % (13 of 17) by adding CBCT and CE-CT image registration to AVS procedures (p = 0.266). DAP values (p = 0.001) and DSA runs (p = 0.026) decreased significantly by adding image registration guidance. Sampling and fluoroscopy times and skin dose showed no significant changes.ConclusionGuidance based on registration of CBCT and previously acquired diagnostic CE-CT can aid in enhancing localization of the adrenal veins thereby increasing the success rate of first-attempt AVS with a significant decrease in the number of used DSA runs and, consequently, radiation dose required.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

A sensitivity analysis to predict the neutronics behavior of samples irradiated in the VTR rabbit system

We report a low-order neutronics model is developed to carry out hundreds of simulations efficiently and investigate the neutronics behavior of samples being irradiated in a test reactor setting under different geometrical constraints. The low-order model allowed for simulations that yield the expected neutronics behavior of any irradiated sample in any environment and allows for the calculation of highly accurate spatially averaged statistics and idealized spatial distributions in the neutron flux. Several benchmarks are performed to evaluate the performance and limitations of the low-order model revealing many important findings. The low-order model predicted the LHGR in the EBR-II driver fuel to within 2.34% by only simulating the fuel rod by itself, which served as a validation for the model. Sensitivity studies investigated 3% enriched UO 2 and U-10Zr being irradiated in the Versatile Test Reactor rabbit system. The analyses investigated a range of combinations of 15 radii and 5 heights for each sample in the rabbit system. Similar data sets are also provided for irradiations in the Advanced Test Reactor’s B-10 irradiation position, which is a thermal neutron spectrum environment. Generalized fits and fit coefficients are obtained for sample heating, reaction rate densities, and local multiplication rate characteristics, allowing the predictions of the neutronics behavior of the samples based on their geometrical constraints. The analyses and fits laid the groundwork for developing a user-end Multiphysics analysis framework to assist and accelerate irradiation experiment design and optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Implicit sampling combined with reduced order modeling for the inversion of vadose zone hydrological data

Bayesian inverse modeling techniques are computationally expensive because many forward simulations are needed when sampling the posterior distribution of the parameters. Here, in this paper, we combine the implicit sampling method and generalized polynomial chaos expansion (gPCE) to significantly reduce the computational cost of performing Bayesian inverse modeling. There are three steps in this approach: (1) find the maximizer of the likelihood function using deterministic approaches; (2) construct a gPCE-based surrogate model using the results from a limited number of forward simulations; and (3) efficiently sample the posterior distribution of the parameters using implicit sampling method. The cost of constructing the gPCE-based surrogate model is further decreased by using sparse Bayesian learning to reduce the number of gPCE coefficients that have to be determined. We demonstrate the approach for a synthetic ponded infiltration experiment simulated with TOUGH2. The surrogate model is highly accurate with mean relative error that is < 0.035% in predicting saturation and < 0.25% in predicting the likelihood function. The posterior distribution of the parameters obtained using our proposed technique is nearly indistinguishable from the results obtained from either an implicit sampling method or a Markov chain Monte Carlo method utilizing the full mode.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

An efficient and cost-effective method for preparing transmission electron microscopy samples from powders

The preparation of transmission electron microcopy (TEM) samples from powders with particle sizes larger than ~100 nm poses a challenge. The existing methods are complicated and expensive, or have a low probability of success. Herein, we report a modified methodology for preparation of TEM samples from powders, which is efficient, cost-effective, and easy to perform. This method involves mixing powders with an epoxy on a piece of weighing paper, curing the powder–epoxy mixture to form a bulk material, grinding the bulk to obtain a thin foil, punching TEM discs from the foil, dimpling the discs, and ion milling the dimpled discs to electron transparency. Compared with the well established and robust grinding–dimpling–ion-milling method for TEM sample preparation for bulk materials, our modified approach for preparing TEM samples from powders only requires two additional simple steps. In this article, step-by-step procedures for our methodology are described in detail, and important strategies to ensure success are elucidated. Furthermore, our methodology has been applied successfully for preparing TEM samples with large thin areas and high quality for many different mechanically milled metallic powders.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Design and Evaluation of a Tethered, Open Port Sampling Interface for Liquid Extraction-Mass Spectrometry Chemical Analysis

Presented in this work is a tethered, liquid-extraction-sampling interface designed for the mass spectrometric surface sampling/analysis of 3D objects. The tethered, open port sampling interface (TOPSI) incorporates a vacuum line between the sampling probe and ionization source, which enables the ability for an extended, tethered sample transfer line. Herein, several designs of the hand-held TOPSI are presented and evaluated on the basis of the analytical metrics of analyte transport time, peak width, and analyte sensitivity. The best analytical metrics were obtained with capillary flow resistances arranged in a particular order and the vacuum region set at 6.2 kPa. This TOPSI design incorporated a transfer capillary 1 m in length, while retaining a fast analyte transport time (12 s), short signal peak width (5 s baseline-to-baseline), and high analyte signal at 90% of that obtained with a regular open port sampling interface (OPSI). The hand-held TOPSI was demonstrated for the characterization of extracted small molecules and metabolites from the surface of mint and rosemary leaves.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Improved explosive collection and detection with rationally assembled surface sampling materials

Sampling and detection of trace explosives is a key analytical process in modern transportation safety. In this work we have explored some of the fundamental analytical processes for collection and detection of trace level explosive on surfaces with the most widely utilized system, thermal desorption IMS. The performance of the standard muslin swipe material was compared with chemically modified fiberglass cloth. The fiberglass surface was modified to include phenyl functional groups. When compared to standard muslin, the phenyl functionalized fiberglass sampling material showed better analyte release from the sampling material as well as improved response and repeatability from multiple uses of the same swipe. The improved sample release of the functionalized fiberglass swipes resulted in a significant increase in sensitivity. Various physical and chemical properties were systematically explored to determine optimal performance. The results herein have relevance to improving the detection of other explosive compounds and potentially to a wide range of other chemical sampling and field detection challenges.

Explosive detection↗

DOE OSTI2019

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↗

DOE OSTI2021

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↗

DOE OSTI2019

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↗

DOE OSTI2016

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↗

DOE OSTI2022

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↗

DOE OSTI2022

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↗