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At least 19 records

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NASA NTRSDate not supplied

Pneumatic Sampler (P-Sampler) for the Martian Moons Exploration (MMX)

The Martian Moons eXploration (MMX) mission, led by the Japanese Aerospace Exploration Agency (JAXA), will focus on the exploration of the two Martian moons – Phobos and Deimos (Figure 1). The spacecraft will perform close-up remote sensing and observations of both moons and collect a sample from Phobos for Earth sample return. MMX has set the two mission goals: (1) determining the origin of the Martian moons and (2) observing processes in the circumplanetary environment of Mars, based on remote sensing, in-situ observations, and laboratory analyses of returned samples of Phobos regolith [1-2]. To fulfill the mission goals, MMX employs a double sampling approach: Coring and Pneumatic Samplers (Figure 2).The Coring Sampler (C-Sampler), a core soil tube deployed by a robotic arm, providing access to the building blocks of Phobos beneath the surface (>2 cm), and also collect a mixture of near surface material. The P-Sampler, on the other hand, would selectively sample the surface veneer and provides reference of surface component with the C-Sampler. The double sampling system not only enhances the scientific merits of MMX but also reduces risks associated with the sampling of Phobos. Without enough knowledge of the physical and chemical properties, and the geotechnical conditions of the surface of Phobos (e.g., compositions, temperature gradient/variation, porosity, grain size distribution), having two sampling systems that utilize entirely different sampling approaches is prudent.

Dylan Van Dyne↗

DOE OSTI2022

Modeling the use of mobile modular gas samplers in near-field detection

The Wireless Independent Noble Gas Sampler (WINGS) is a mobile, modular gas sampling system designed for use in low infrastructure environments. In the case of a suspected underground nuclear explosion (UNE), WINGS units could be deployed to detect noble gases emanating from the suspected explosion site or identify gases originating from another source entering the local area from offsite. In conclusion, this work uses the atmospheric transport modeling tool inline WRF-HYSPLIT to test the effectiveness of WINGS units around a suspected UNE site as a function of sampler density and distance from the emission point of gases from a UNE.

Air sampling↗

NASA NTRS2021

Pneumatic Sampler (P-Sampler) for the Martian Moons Exploration (MMX)

A Pneumatic Sampler (P-SMP)is being provided by Honeybee Robotics with support from NASA Planetary Missions Program Office (PMPO)for JAXA’s Martian Moons eXploration (MMX) mission. The goal of this mission is to closely survey the Martian moons Deimos and Phobos, and then to collect regolith from Phobos and return it to Earth. The P-SMP will be mounted to a leg of the lander and will be responsible for collecting surface regolith alongside the JAXA provide Core Sampler (C-SMP). The Sampling Funnel of the P-SMP utilizes two sets of sampling nozzles: one set of nozzles pointed directly at the surface to kick-up and loft material into the sampling head, and a second set of nozzles to direct the oncoming material into the sample return canister further up the lander leg. A robotic arm mounted underneath the lander will then remove the sample canister and place it inside the sample return capsule for Earth return. Several iterations of the P-Sampler have been designed and tested inside a vacuum chamber with Phobos regolith simulant. In all tests, the P-Sampler successfully acquired the sample, even in an extreme scenario where the sampling head was mounted 10 cm above a surface covered with gravel.

Dylan Van Dyne↗

DOE OSTI2017

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrain high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1979

Multispectral Resource Sampler (MRS): Proof of concept study on atmospheric corrections. Determinations of atmospheric optical parameters using the multispectral resource sampler atmospheric optical

An investigation was performed to determine which mathematical algorithms should be used in the calculation of atmospheric optical parameters using the Multispectral Resource Sampler (MRS) sensor. A simulation of the MRS sensor was performed using a radiative-transfer model. The simulation provides the spectral radiance at the satellite sensor in terms of various atmospheric parameters, such as optical thickness, solar zenith angle, nadir view angle, relative azimuth angle, bi-directional reflectance of the target, background albedo, and wavelength. Atmospheric correction algorithms were also developed for the determination of the total spectral optical thickness of the atmosphere for: (1) homogeneous (horizontal) hazy atmospheres with diffuse targets; (2) inhomogeneous (horizontal) hazy atmospheres with diffuse targets; and (3) homogeneous (horizontal) hazy atmospheres with non-diffuse targets.

Turner, R. E.↗

DOE OSTI2018

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on an embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Bioaccumulation Using Surrogate Samplers (Bass): Evaluation Of A Passive Sampler As An Alternative Monitoring Tool For Environmental Contaminants At The Savannah River Site

DOE sites conduct traditional environmental monitoring programs that require collecting, processing, and analyzing water, sediment, and fish samples. However, recently developed passive sampling technologies, such as Diffusive Gradient in Thin films (DGT), may measure the chemical phases that are available and toxic to organisms (the bioavailable fraction), thereby producing more accurate and economical results than traditional methods. Our laboratory study showed that dissolved copper concentrations measured by DGT probes were strongly correlated with the uptake of copper by Lumbriculus variegatus, an aquatic worm, and with concentrations of copper measured by conventional methods. Dissolved copper concentrations in DGT probes increased with time of exposure, paralleling the increase in copper with time that ocurred in Lumbriculus. Additional studies with a combination of seven dissolved metals showed similar results. These findings support the use of DGT as a biomimetic monitoring tool and provide a basis for refinement of these methods for cost-effective environmental monitoring at DOE sites.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

PNEUMATIC SAMPLER (P-SAMPLER) FOR THE MARTIAN MOONS EXPLORATION (MMX)

The Martian Moons eXploration (MMX) mission, led by the Japanese Aerospace Exploration Agency (JAXA), will focus on the exploration of the two Martian moons – Phobos and Deimos . The spacecraft will perform close-up remote sensing and observations of both moons, and collect a sample from Phobos for Earth sample return. MMX has set the two mission goals: (1) determining the origin of the Martian moons and (2) observing processes in the circumplanetary environment of Mars, based on remote sensing, in-situ observations, and laboratory analyses of returned Phobos regolith.

D. Van Dyne↗

NASA NTRSDate not supplied

Pneumatic Sampler (P-SAMPLER) for the Martian Moons Exploration (MMX)

D Van Dyne↗

DOE OSTI2015

Influence of Sulfide Nanoparticles on Dissolved Mercury and Zinc Quantification by Diffusive Gradient in Thin-Film Passive Samplers

Diffusive gradient in thin-film (DGT) passive samplers are frequently used to monitor the concentrations of metals such as mercury and zinc in sediments and other aquatic environments. The application of these samplers generally presumes that they quantify only the dissolved fraction and not particle-bound metal species that are too large to migrate into the sampler. However, metals associated with very small nanoparticles (smaller than the pore size of DGT samplers) can be abundant in certain environments, yet the implications of these nanoparticles for DGT measurements are unclear. The objective of this study was to determine how the performance of the DGT sampler is affected by the presence of nanoparticulate species of Hg and Zn. DGT samplers were exposed to solutions containing known amounts of dissolved Hg(II) and nanoparticulate HgS (or dissolved Zn(II) and nanoparticulate ZnS). The amounts of Hg and Zn accumulated onto the DGT samplers were quantified over hours to days, and the rates of diffusion of the dissolved metal (i.e., the effective diffusion coefficient D) into the sampler’s diffusion layer were calculated and compared for solutions containing varying concentrations of nanoparticles. The results suggested that the nanoparticles deposited on the surface of the samplers might have acted as sorbents, slowing the migration of the dissolved species into the samplers. The consequence was that the DGT sampler data underestimated the dissolved metal concentration in the solution. In addition, X-ray absorption spectroscopy was employed to determine the speciation of the Hg accumulated on the sampler binding layer, and the results indicated that HgS nanoparticles did not appear to directly contribute to the DGT measurement. Overall, our findings suggest that the deployment of DGT samplers in settings where nanoparticles are relevant (e.g., sediments) may result in DGT data that incorrectly estimated the dissolved metal concentrations. Models for metal uptake into the sampler may need to be reconsidered.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Characteristics of Non-metallic Inclusions in Steel Obtained from Different-Sized Samplers

To determine the effect of sampler size on the detection of inclusions in liquid steel, four different-sized samplers were designed for industrial sampling from a continuous casting tundish. The samples were evaluated via scanning electron microscopy and energy-dispersive spectroscopy. With increasing sample size, the cooling rate of the sample and velocity for particle engulfment decreased. The extent of encapsulation of complex inclusions increased from 0 pct with the smallest sampler to 48.2 pct with the largest sampler. In the samplers that cooled at 41.2 and 26.7 K s{sup −1}, the major inclusions were calcium aluminates; in the larger samplers, which cooled more slowly at 8.2 and 1.0 K s{sup −1}, the complex inclusions predominately comprised Al{sub 2}O{sub 3} + (Ca, Mn)S and Al{sub 2}O{sub 3} + CaS, respectively. The sizes of the sulfides gradually increased with increasing sampler size; for example, the sulfide average diameter increased from 2.5 to 3.5 μm when the sampler inner diameter increased from 50 to 70 mm. The main direction of movement of the inclusions during the sampling process was upward.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2000

Evaluation of portable air samplers for monitoring airborne culturable bacteria

Airborne culturable bacteria were monitored at five locations (three in an office/laboratory building and two in a private residence) in a series of experiments designed to compare the efficiency of four air samplers: the Andersen two-stage, Burkard portable, RCS Plus, and SAS Super 90 samplers. A total of 280 samples was collected. The four samplers were operated simultaneously, each sampling 100 L of air with collection on trypticase soy agar. The data were corrected by applying positive hole conversion factors for the Burkard portable, Andersen two-stage, and SAS Super 90 air samplers, and were expressed as log10 values prior to statistical analysis by analysis of variance. The Burkard portable air sampler retrieved the highest number of airborne culturable bacteria at four of the five sampling sites, followed by the SAS Super 90 and the Andersen two-stage impactor. The number of bacteria retrieved by the RCS Plus was significantly less than those retrieved by the other samplers. Among the predominant bacterial genera retrieved by all samplers were Staphylococcus, Bacillus, Corynebacterium, Micrococcus, and Streptococcus.

NASA Center JSC↗

NASA NTRS1996

Evaluation of three portable samplers for monitoring airborne fungi

Airborne fungi were monitored at five sample sites with the Burkard portable, the RCS Plus, and the SAS Super 90 air samplers; the Andersen 2-stage impactor was used for comparison. All samplers were calibrated before being used simultaneously to collect 100-liter samples at each site. The Andersen and Burkard samplers retrieved equivalent volumes of airborne fungi; the SAS Super 90 and RCS Plus measurements did not differ from each other but were significantly lower than those obtained with the Andersen or Burkard samplers. Total fungal counts correlated linearly with Cladosporium and Penicillium counts. Alternaria species, although present at all sites, did not correlate with total count or with amounts of any other fungal genera. Sampler and location significantly influenced fungal counts, but no interactions between samplers and locations were found.

NASA Center JSC↗

DOE OSTI2019

Kernel Density Estimators for SAMPLER Analyses [Slides]

This presentation discusses Sampler, specifically in terms of uncertainty quantification and states that for many simulation tasks nominal input parameters have complicated influence on the uncertainty in the final result. Sampler provides a convenient means to perform stochastic uncertainty quantification, brute force sampling parameter space and tallying changes in outputs, and it can be coupled with any SCALE modules. Perturbed responses can be collected and analyzed with standard statistical measures; however, two problems have been identified. The first problem is that for Monte Carlo simulations the individual response uncertainties are ignored, and the second problem is that features of distributions are easily hidden in histograms. They found that the solution is to add Kernel Density Estimator (KDE) analysis to the Sampler output. In conclusion, Sampler is a unique tool for stochastic uncertainty propagation, and it can be coupled with any module in SCALE. Current functionality is limited to histograms, and it may not adequately account for sample uncertainties and/or not adequately display underlying distribution features. Work is in progress to implement KDE in the Sampler module and no additional flagging is needed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Crossing the Streams – Sampler and the TemplateEngine [Slides]

This presentation discusses Sampler, which is a versatile UQ and parametric study tool that can be applied to any SCALE Sequence. Sampler can perturb any quantity in any SCALE input. Recent work at ORNL has developed new types of covariance data that allow Sampler UQ to be applied to nearly all SCALE applications, including reactor depletion, UNF fuel characterization, source term analysis, and decay heat calculation. In SCALE 6.2 releases, CE data in transport cannot be perturbed. Sampler was originally designed for stochastic sampling with any sequence within SCALE and Parametric capability added in SCALE 6.2.2. Sampler can be used for uncertainty quantification, including sample data in static or depletion calculations and sample inputs for uncertainties in compositions and dimensions. The SCALE TemplateEngine allows for expanding templates to full inputs and the combination provides a powerful UQ tool.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Remote Sampler Demonstration Isolok Configuration Test

The accuracy and precision of a new Isolok sampler configuration was evaluated using a recirculation flow loop. The evaluation was performed using two slurry simulants of Hanford high-level tank waste. Through testing, the capability of the Isolok sampler was evaluated. Sample concentrations were compared to reference samples that were simultaneously collected by a two-stage Vezin sampler. The capability of the Isolok sampler to collect samples that accurately reflect the contents in the test loop improved – biases between the Isolok and Vezin samples were greatly reduce for fast settling particles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Comparison of source-location algorithms for atmospheric samplers

Numerous algorithms have been developed to determine the source characteristics for an atmospheric release, e.g., (Bieringer et al., 2017). This study compares three models that have been applied to the data collected by the International Monitoring System operated by the Comprehensive Nuclear-Test-Ban Treaty Preparatory Commission to estimate source event parameters. Each model uses a different approach to estimate the parameters. A deterministic model uses a possible source region (PSR) approach (Ringbom et al., 2014) that is based on the correlation between predicted and measured sample values. An unnamed model developed at Pacific Northwest National Laboratory (herein called BAYEST) uses a Bayesian formulation (Eslinger et al., 2019; Eslinger et al., 2020; Eslinger and Schrom, 2016). The FREAR model uses a different Bayesian formulation (De Meutter and Hoffman, 2020; De Meutter et al., 2021; Pieter De Meutter, 2021). The performance of the three source-location models is evaluated with 100 synthetic release cases for the single xenon isotope, 133 Xe. The release cases resulted in detections in a fictitious network with 120 noble gas samplers. All three source-location models use the same sampling data. The two Bayesian models yield more accurate location estimates than the deterministic PSR model, with FREAR having slightly better location performance than BAYEST. Samplers with collection periods of 3, 6, 8, 12, and 24-h were used. Results from BAYEST show that location accuracy improves with each reduction in sample collection length. The BAYEST model is slightly better for estimating the start time of the release. The PSR model has about the same spread in start times as the FREAR model, but the PSR results have a better average start time. The Bayesian source-location algorithms give more accurate results than the PSR approach, and provide release magnitude estimates, while the base PSR model does not estimate the release magnitude. This investigation demonstrates that a reasonably dense sampling grid will sometimes yield poor location and time estimates regardless of the model. The poor estimates generally coincide with cases where there is a much larger distance between the release point and the first detecting sampler than the average sampler spacing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗