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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Key Perseverance Sampling Locations for the Ancient Martian Crust and Implications for Mars Science

Since Feb 2021, the Perseverance rover has collected samples in the Jezero crater. The plan baselined at the 2018 landing site selection, subsequently further developed by the Mars-2020 team, and presented to the Decadal Survey included the exploration and sampling of the Jezero crater rim and the Nili Planum area, a rock record that is important to preserving the science return of the endeavor. Specifically, the science team identified the following prioritized science objectives aligned with community objectives that are not covered by the current sample cache: 1) Investigate the habitable environments with potential biosignatures from a more ancient time interval and from a diverse set of geological environments (incl. exposed subsurface) than the Jezero crater sedimentary deposits (Fig. 2). (2) Determine radioisotopic ages for well-defined craterretaining surfaces and/or the Isidis basin impact event. (3) Characterize ancient aqueous environments to study climate, environmental transitions, and habitability on ancient Mars. (4) Investigate planetary accretion, crustal evolution, and dynamo activity through analysis and sampling of igneous lithologies. (5) Study the geology of basin-forming impacts. In addition, for the Jezero rim and any Jezero ejecta: (6) Analyze Jezero impactites for potentially habitable hydrothermal environments and radioisotopic dating of the Jezero crater formation. From 2018 to now, we used a combination of High Resolution Imaging Experiment (HiRISE) and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data to further characterize Jezero rim and Nili Planum, culminating in our prioritized sample location recommendations: (1) Monument Valley and (2) Northwest Jezero rim.

Mars sample return↗
DOE OSTI2011

Concepts for Environmental Radioactive Air Sampling and Monitoring

Environmental radioactive air sampling and monitoring is becoming increasingly important as regulatory agencies promulgate requirements for the measurement and quantification of radioactive contaminants. While researchers add to the growing body of knowledge in this area, events such as earthquakes and tsunamis demonstrate how nuclear systems can be compromised. The result is the need for adequate environmental monitoring to assure the public of their safety and to assist emergency workers in their response. Two forms of radioactive air monitoring include direct effluent measurements and environmental surveillance. This chapter presents basic concepts for direct effluent sampling and environmental surveillance of radioactive air emissions, including information on establishing the basis for sampling and/or monitoring, criteria for sampling media and sample analysis, reporting and compliance, and continual improvement.

emissions↗
DOE OSTI2012

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↗
DOE OSTI2012

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↗
DOE OSTI2017

Method for Hot Real-Time Sampling of Pyrolysis Vapors

Biomass Pyrolysis has been an increasing topic of research, in particular as a replacement for crude oil. This process utilizes moderate temperatures to thermally deconstruct the biomass which is then condensed into a mixture of liquid oxygenates to be used as fuel precursors. Pyrolysis oils contain more than 400 compounds, up to 60 percent of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during the condensation and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors, many challenges must be overcome. Sampling must occur within a narrow range of temperatures to reduce product composition changes from overheating or partial condensation or plugging of lines from condensed products. Residence times must be kept at a minimum to reduce further reaction chemistries. Pyrolysis vapors also form aerosols that are carried far downstream and can pass through filters resulting in build-up in downstream locations. The co-produced bio-char and ash from the pyrolysis process can lead to plugging of the sample lines, and must be filtered out at temperature, even with the use of cyclonic separators. A practical approach for considerations and sampling system design, as well as lessons learned are integrated into the hot analytical sampling system of the National Renewable Energy Laboratory's (NREL) Thermochemical Process Development Unit (TCPDU) to provide industrially relevant demonstrations of thermochemical transformations of biomass feedstocks at the pilot scale.

09 BIOMASS FUELS↗
DOE OSTI2018

Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch

Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Sample Complexity of Power System State Estimation using Matrix Completion: Preprint

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 \emph{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 \emph{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 \emph{matrix completion}. In particular, a \emph{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

An Efficient Sampling-Based Method for Sensitivity and Uncertainty Analysis Through RAVEN

Sensitivity analysis (SA) and uncertainty quantification (UQ) are now widely recognized as essential parts of analyses for complex nuclear systems. Plenty of well-established methodologies are already available for performing SA and UQ, such as Monte Carlo analysis, adjoint-based method, and variance decomposition. The focus of this summary is on developing an efficient sampling-based approach to perform SA and UQ through RAVEN. RAVEN (Risk Analysis and Virtual control Environment) is a software framework able to perform SA and UQ, currently under development at the Idaho National Laboratory. In literature, a number of approaches have been developed to accelerate the process of SA and UQ for large complex systems, such as principal component analysis (PCA) of input space, input-output correlation analysis, and intersection subspace methods. The fundamental idea is to identify the dominant active directions in the parameter space prior to conducting SA and UQ. The premise is that the number of active directions is much less than the dimensionality of input space. In this work, the PCA or Karhunen-Loeve expansion or SVD method is implemented in RAVEN to identify the active directions. This approach is also combined with the forward sampling approaches, such as Monte Carlo, Grid, Latin Hypercube, and Response Surface Design sampling approaches that are currently available in RAVEN, to perform SA and UQ more efficiently. The summary is organized as follows. In the following section, we present the PCA-based forward sampling approach. The effectiveness and efficiency are discussed in the numerical results section. The paper then ends with a concluding summary. In this summary, we have presented PCA-based forward sampling approach to perform SA and UQ. The goal is to reduce the computational overhead for repetitive executions of complex nuclear systems that are generally required when performing SA and UQ. The control of correlations between input parameters is implemented in RAVEN to better represent the input relationships. In addition, we are currently examining our implementations with more realistic models, and we are also focusing on implementation of some new high-dimensional input reduction techniques in RAVEN. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Improvement of Drop‐Hammer Impact Testing for Safety Assessment of High Explosives Using 10‐mg Samples

Here, in this study, we established an improved method for drop-hammer impact testing of small quantities of high explosives (10 mg). We performed about seven hundred impact tests under various experimental conditions (e.g., sandpaper vs bare anvil, different sample masses, drop-weights, and striker diameters) to determine an optimal set of conditions and reaction detection methods (e.g., gas analysis, video, and sound recordings) that give the most statistically reliable results with 10 mg samples. We used both Frequentist and Bayesian statistical approaches to compare estimates of the drop height (DH50) that initiates a reaction 50% of the time, and to quantify the associated uncertainty. Gas analysis proved to be the most reliable reaction detection method, showing unambiguous rises in HE decomposition products (e.g., CO 2 ) even when the other indicators (e.g., sound, video) were inconclusive. The impact tests performed with a bare anvil showed much better reproducibility than those conducted with sandpaper, reducing the largest uncertainty observed in the data sets by a factor of 1.7. The DH 50 values obtained from three different sample masses (10, 20, and 35 mg) fell within the uncertainties of the measurements. We demonstrated the improved procedure (i.e., 10-mg samples, gas analysis, bare anvil, and Bayesian approach) on a variety of PETN samples having different surface areas and thermal histories.

PETN↗
DOE OSTI2016

Fukushima Daiichi reactor source term attribution using cesium isotope ratios from contaminated environmental samples

Source term attribution of environmental contamination following the Fukushima Daiichi Nuclear Power Plant (FDNPP) disaster is complicated by a large number of possible similar emission source terms (e.g. FDNPP reactor cores 1–3 and spent fuel ponds 1–4). Cesium isotopic analyses can be utilized to discriminate between environmental contamination from different FDNPP source terms and, if samples are sufficiently temporally resolved, potentially provide insights into the extent of reactor core damage at a given time. In this work, rice, soil, mushroom, and soybean samples taken 100–250 km from the FDNPP site were dissolved using microwave digestion. Radiocesium was extracted and purified using two sequential ammonium molybdophosphate-polyacrylonitrile columns, following which 135 Cs/ 137 Cs isotope ratios were measured using thermal ionization mass spectrometry (TIMS). Results were compared with data reported previously from locations to the northwest of FDNPP and 30 km to the south of FDNPP. 135 Cs/ 137 Cs isotope ratios from samples 100–250 km to the southwest of the FDNPP site show a consistent value of 0.376 ± 0.008. 135 Cs/ 137 Cs versus 134 Cs/ 137 Cs correlation plots suggest that radiocesium to the southwest is derived from a mixture of FDNPP reactor cores 1, 2, and 3. Conclusions from the cesium isotopic data are in agreement with those derived independently based upon the event chronology combined with meteorological conditions at the time of the disaster. In conclusion, cesium isotopic analyses provide a powerful tool for source term discrimination of environmental radiocesium contamination at the FDNPP site. For higher precision source term attribution and forensic determination of the FDNPP core conditions based upon cesium, analyses of a larger number of samples from locations to the north and south of the FDNPP site (particularly time-resolved air filter samples) are needed. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

ToF-SIMS Depth Profiling Of Insulating Samples, Interlaced Mode Or Non-interlaced Mode?

Dual beam depth profiling strategy has been widely adopted in ToF-SIMS depth profiling, in which two basic operation modes, interlaced mode and non-interlaced mode, are commonly used. Generally, interlaced mode is recommended for conductive or semi-conductive samples, whereas non-interlaced mode is recommended for insulating samples, where charge compensation can be an issue. Recent publications, however, show that the interlaced mode can be used effectively for glass depth profiling, despite the fact that glass is an insulator. In this study, we provide a simple guide for choosing between interlaced mode and non-interlaced mode for insulator depth profiling. Two representative cases are presented: (1) depth profiling of a leached glass sample, and (2) depth profiling of a single crystal MgO sample. In brief, the interlaced mode should be attempted first, because (1) it may provide reasonable-quality data, and (2) it is time-saving for most cases, and (3) it introduces low H/C/O background. If data quality is the top priority and measurement time is flexible, non-interlaced mode is recommended because interlaced mode may suffer from low signal intensity and poor mass resolution. A big challenge is tracking trace H/C/O in a highly insulating sample (e.g., MgO), because non-interlaced mode may introduce strong H/C/O background but interlaced mode may suffer from low signal intensity. Meanwhile, a C or Au coating is found to be very effective to improve the signal intensity. Surprisingly, the best analyzing location is not on the C or Au coating, but at the edge (outside) of the coating.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Sample size estimation for case‐crossover studies

Case‐crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case‐crossover study is self‐controlled, its advantages include better control for confounding because the design controls for any time‐invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self‐matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case‐crossover study, investigators currently use Dupont's formula ( Biometrics 1988; 43 :1157‐1168), which was originally developed for a matched case‐control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self‐controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case‐crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.

Dharmarajan, Sai↗
DOE OSTI2024

Robust surfactant-assisted one-pot sample preparation for label-free single-cell and nanoscale proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.

Single-cell proteomics, nanoscale proteomics, SOP-↗
DOE OSTI2018

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Rapid Determination Of Radiostrontium In Large Soil Samples

A new method for the determination of radiostrontium in large soil samples has been developed at the Savannah River Environmental Laboratory (Aiken, SC, USA) that allows rapid preconcentration and separation of strontium in large soil samples for the measurement of strontium isotopes by gas flow proportional counting. The need for rapid analyses in the event of a Radiological Dispersive Device (RDD) or Improvised Nuclear Device (IND) event is well-known. In addition, the recent accident at Fukushima Nuclear Power Plant in March, 2011 reinforces the need to have rapid analyses for radionuclides in environmental samples in the event of a nuclear accident. The method employs a novel pre-concentration step that utilizes an iron hydroxide precipitation (enhanced with calcium phosphate) followed by a final calcium fluoride precipitation to remove silicates and other matrix components. The pre-concentration steps, in combination with a rapid Sr Resin separation using vacuum box technology, allow very large soil samples to be analyzed for {sup 89,90}Sr using gas flow proportional counting with a lower method detection limit. The calcium fluoride precipitation eliminates column flow problems typically associated with large amounts of silicates in large soil samples.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2015

Rapid fusion method for the determination of Pu, Np, and Am in large soil samples

A new rapid sodium hydroxide fusion method for the preparation of 10-20 g soil samples has been developed by the Savannah River National Laboratory (SRNL). The method enables lower detection limits for plutonium, neptunium, and americium in environmental soil samples. The method also significantly reduces sample processing time and acid fume generation compared to traditional soil digestion techniques using hydrofluoric acid. Ten gram soil aliquots can be ashed and fused using the new method in 1-2 hours, completely dissolving samples, including refractory particles. Pu, Np and Am are separated using stacked 2mL cartridges of TEVA and DGA Resin and measured using alpha spectrometry. The method can be adapted for measurement by inductively-coupled plasma mass spectrometry (ICP-MS). Two 10 g soil aliquots of fused soil may be combined prior to chromatographic separations to further improve detection limits. Total sample preparation time, including chromatographic separations and alpha spectrometry source preparation, is less than 8 hours.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Rapid method to determine actinides and 89/90 Sr in limestone and marble samples

A new method for the determination of actinides and radiostrontium in limestone and marble samples has been developed that utilizes a rapid sodium hydroxide fusion to digest the sample. Following rapid pre-concentration steps to remove sample matrix interferences, the actinides and 89/90 Sr are separated using extraction chromatographic resins and measured radiometrically. The advantages of sodium hydroxide fusion versus other fusion techniques will be discussed. Lastly, this approach has a sample preparation time for limestone and marble samples of <4 hours.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Theoretical realization of three-dimensional nanolattice structure fabrication based on high-order waveguide-mode interference and sample rotation

A theoretical method of using high-order waveguide-mode interference combined with sample rotation is proposed to fabricate different kinds of three-dimensional nanolattice structures. The lithography sample is assisted by an asymmetric metal-cladding dielectric waveguide structure. High-order waveguide modes can be excited in the photoresist layer by both transverse magnetic and transverse electric polarized light. By utilizing multiple exposures of high-order waveguide-mode interference combined with sample-rotation, various three-dimensional nanolattice structures can be obtained. The resulting optical field distributions are simulated using the finite element method in this study, and sample rotation is expressed by coordinate matrix transformation. As examples, the three-dimensional optical field distributions resulting from fifth-order waveguide-mode interference were simulated with 90° and 60° sample rotations and multiple exposures. The results show that a quasi-cuboid structure with a simple tetragonal arrangement and a quasi-hexagonal structure with a hexagonal close-packed lattice can be obtained. Moreover, the numerical simulation results revealed that the shapes, sizes, arrangements, and periods of the structures can be controlled by the rotation method, photoresist thickness, waveguide modes used for exposure, and so on.

77 NANOSCIENCE AND NANOTECHNOLOGY↗