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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sampling and resolution characteristics in reduced order models of shallow water equations: Intrusive vs nonintrusive

We investigate the sensitivity of reduced order models (ROMs) to training data spatial resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD), coupled with Galerkin projection (POD-GP), as an intrusive reduced order modeling technique. For non-intrusive ROMs, we consider two frameworks. The first is using dynamic mode decomposition (DMD), and the second is based on artificial neural networks (ANNs). For ANN, we utilized a residual deep neural network, and for DMD we have studied two versions of DMD approaches; one with hard thresholding and the other with sorted bases selection. Also, we highlight the differences between mean-subtracting the data (centering) and using the data without mean-subtraction. We tested these ROMs using a system of 2D shallow water equations for four different numerical experiments, adopting combinations of sampling rates and spatial resolutions. For these cases, we found that the DMD basis obtained with hard threshodling is sensitive to sampling rate. The sorted DMD algorithm helps to mitigate this problem and yields more stabilized and converging solution. Furthermore, we demonstrate that both DMD approaches without mean subtraction provide significantly more accurate results than DMD with mean-subtracting the data. On the other hand, POD is relatively insensitive to sampling rate and yields better representation of the flow field. Meanwhile, spatial resolution has little effect on both POD and DMD performances. Here, the numerical results reveal that an ANN on POD subspace (POD-ANN) performs remarkably better than POD-GP and DMD in capturing system dynamics, even with a small number of modes.

42 ENGINEERING↗
DOE OSTI2013

Continuous Flow Liquid Microjunction Surface Sampling Probe Connected On-line with HPLC/MS for Spatially Resolved Analysis of Small Molecules and Proteins

RATIONALE: A continuous flow liquid microjunction surface sampling probe extracts soluble material from surfaces for direct ionization and detection by MS. Demonstrated here is the on-line coupling of such a probe with HPLC/MS enabling extraction, separation and detection of small molecules and proteins from surfaces in a spatially resolved (~0.5 mm diameter spots) manner. Methods: A continuous flow liquid microjunction surface sampling probe was connected to a 6-port, 2-position valve for extract collection and injection to an HPLC column. A QTRAP 5500 hybrid triple quadrupole linear ion trap equipped with a Turbo V ion source operated in positive ESI mode was used for all experiments. System operation was tested with extraction, separation and detection of propranolol and associated metabolites from drug dosed tissues and proteins from dried sheep blood spots on paper. Results: Confirmed in the tissue were the parent drug and two different hydroxypropranolol glucuronides. The mass spectrometric response for these compounds from different locations in the liver showed an increase with increasing extraction time (5, 20 and 40 s extractions). For on-line separation and detection/identification of extracted proteins from dried sheep blood spots, two major protein peaks dominated the chromatogram and could be correlated with the expected masses for the hemoglobin and chains. Conclusions: Spatially resolved sampling, separation, and detection of small molecules and proteins from surfaces can be accomplished using a continuous flow liquid microjunction surface sampling probe coupled on-line with HPLC/MS detection.

dried blood spots↗
DOE OSTI2013

Large Deviations and Importance Sampling for Systems of Slow-Fast Motion

In this paper we develop the large deviations principle and a rigorous mathematical framework for asymptotically efficient importance sampling schemes for general, fully dependent systems of stochastic differential equations of slow and fast motion with small noise in the slow component. We assume periodicity with respect to the fast component. Depending on the interaction of the fast scale with the smallness of the noise, we get different behavior. We examine how one range of interaction differs from the other one both for the large deviations and for the importance sampling. We use the large deviations results to identify asymptotically optimal importance sampling schemes in each case. Standard Monte Carlo schemes perform poorly in the small noise limit. In the presence of multiscale aspects one faces additional difficulties and straightforward adaptation of importance sampling schemes for standard small noise diffusions will not produce efficient schemes. It turns out that one has to consider the so called cell problem from the homogenization theory for Hamilton-Jacobi-Bellman equations in order to guarantee asymptotic optimality. We use stochastic control arguments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A Novel Method of Adrenal Venous Sampling via an Antecubital Approach

PurposeCurrently, almost all adrenal venous sampling (AVS) procedures are performed by femoral vein access. The purpose of this study was to establish the technique of AVS via an antecubital approach and evaluate its safety and feasibility.Materials and MethodsFrom January 2012 to June 2015, 194 consecutive patients diagnosed as primary aldosteronism underwent AVS via an antecubital approach without ACTH simulation. Catheters used for bilateral adrenal cannulations were recorded. The success rate of bilateral adrenal sampling, operation time, fluoroscopy time, dosage of contrast, and incidence of complications were calculated.ResultsA 5F MPA1 catheter was first used to attempt right adrenal cannulation in all patients. Cannulation of the right adrenal vein was successfully performed in 164 (84.5%) patients. The 5F JR5, Cobra2, and TIG catheters were the ultimate catheters for right adrenal cannulation in 16 (8.2%), 5 (2.6%), and 9 (4.6%) patients, respectively. For left adrenal cannulation, JR5 and Cobra2 catheters were used in 19 (9.8%) and 10 (5.2%) patients, respectively, while only TIG catheters were used in the remaining 165 (85.1%) patients. The rate of successful adrenal sampling on the right, left, and bilateral sides was 91.8%, 93.3%, and 87.6%, respectively. The mean time of operation was (16.3 ± 4.3) minutes, mean fluoroscopy time was (4.7 ± 1.3) minutes, and the mean use of contrast was (14.3 ± 4.7) ml. The incidence of adrenal hematoma was 1.0%.ConclusionsThis study showed that AVS via an antecubital approach was safe and feasible, with a high rate of successful sampling.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints

The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, here we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is $\mathscr{O}$(ϵ -3-δ ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be $\mathscr{O}$(ϵ -1 ), we demonstrate that the result can be improved to $\mathscr{O}$(ϵ -2 ) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain $\mathscr{O}$(ϵ -1 log(1/ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

On-matrix Derivatization for Dynamic Headspace Sampling of Nonvolatile Surface Residues

The goal of this study is to extend sampling by the field and laboratory emission cell (FLEC) purge-and-trap technique to applications that target nonvolatile residues. On-matrix derivatization of residues to render analytes stable and more volatile is explored to achieve this goal. Results show that on-matrix derivatizations of nerve agent hydrolysis products (monoalkyl methylphosphonic acids and methylphosphonic acid [MPA]) with diazomethane were successful on glass and painted wallboard (at the 10-µg level). It also was successful on the more difficult concrete (at the 500-µg level) and carpet (at the 20-µg level) substrates that cannot be successfully sampled using swipe techniques. Analysis of additional chemical warfare (CW)-associated residues can be approached by on-matrix derivatization with trifluoroacetic anhydride (TFAA). For example, amines (used as stabilizers or present as decomposition products of the nerve agent VX) or thiodiglycol (hydrolysis product of sulfur mustard) could be sampled as their TFAA derivatives from glass, painted wallboard, and concrete (at the 40-µg level), as well as carpet (at the 80-µg level) surfaces. Although the amine and thiodiglycol are semi-volatile and could be sampled directly, derivatization improves the recovery and chromatographic behavior of these analytes.

On-matrix derivatization, in-situ derivatization, ↗
DOE OSTI2018

Basis adaptive sample efficient polynomial chaos (BASE-PC)

For a large class of orthogonal basis functions, there has been a recent identification of expansion methods for computing accurate, stable approximations of a quantity of interest. Here this paper presents, within the context of uncertainty quantification, a practical implementation using basis adaptation, and coherence motivated sampling, which under assumptions has satisfying guarantees. This implementation is referred to as Basis Adaptive Sample Efficient Polynomial Chaos (BASE-PC). A key component of this is the use of anisotropic polynomial order which admits evolving global bases for approximation in an efficient manner, leading to consistently stable approximation for a practical class of smooth functionals. This fully adaptive, non-intrusive method, requires no a priori information of the solution, and has satisfying theoretical guarantees of recovery. A key contribution to stability is the use of a presented correction sampling for coherence-optimal sampling in order to improve stability and accuracy within the adaptive basis scheme. Theoretically, the method may dramatically reduce the impact of dimensionality in function approximation, and numerically the method is demonstrated to perform well on problems with dimension up to 1000.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Emergence and consequences of lateral sample heterogeneity in glow discharge spectrometry

We report conventional glow discharge emission or mass spectrometry requires the assumption that the surface of the sample is homogeneous. However, recent developments in glow discharge imaging appear to offer an opportunity to obtain three-dimensional concentration maps, in which this assumption is no longer necessary. Here, experiments, models, and a summary of earlier work are combined to examine the sputtering behavior of elemental and morphological heterogeneities in a sample. The theoretical model reveals gaps in current knowledge of glow discharge sputtering of heterogeneous samples, particularly indicating that heterogeneity in the sample leads to roughened crater bottoms and how additional morphology can evolve. Additionally, a three-dimensional profiling microscope is used to characterize the effects of surface inclusions on the sputtering process in a DC glow discharge in a reduced-pressure argon environment. Findings have important implications for bulk analysis, depth-profiling, and elemental surface mapping with glow discharge spectrometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Reduced electron exposure for energy-dispersive spectroscopy using dynamic sampling

Analytical electron microscopy and spectroscopy of biological specimens, polymers, and other beam sensitive materials has been a challenging area due to irradiation damage. There is a pressing need to develop novel imaging and spectroscopic imaging methods that will minimize such sample damage as well as reduce the data acquisition time. The latter is useful for high-throughput analysis of materials structure and chemistry. Here, in this work, we present a novel machine learning based method for dynamic sparse sampling of EDS data using a scanning electron microscope. Our method, based on the supervised learning approach for dynamic sampling algorithm and neural networks based classification of EDS data, allows a dramatic reduction in the total sampling of up to 90%, while maintaining the fidelity of the reconstructed elemental maps and spectroscopic data. In conclusion, we believe this approach will enable imaging and elemental mapping of materials that would otherwise be inaccessible to these analysis techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Effects of sample treatments on genome recovery via single-cell genomics

It is known that single-cell genomics is a powerful tool for accessing genetic information from uncultivated microorganisms. Methods of handling samples before single-cell genomic amplification may affect the quality of the genomes obtained. Using three bacterial strains we demonstrate that, compared to cryopreservation, lower-quality single-cell genomes are recovered when the sample is preserved in ethanol or if the sample undergoes fluorescence in situ hybridization, while sample preservation in paraformaldehyde renders it completely unsuitable for sequencing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Provable bounds for noise-free expectation values computed from noisy samples

Quantum computing has emerged as a powerful computational paradigm capable of solving problems beyond the reach of classical computers. However, today’s quantum computers are noisy, posing challenges to obtaining accurate results. Here, we explore the impact of noise on quantum computing, focusing on the challenges in sampling bit strings from noisy quantum computers and the implications for optimization and machine learning. We formally quantify the sampling overhead to extract good samples from noisy quantum computers and relate it to the layer fidelity, a metric to determine the performance of noisy quantum processors. Further, we show how this allows us to use the conditional value at risk of noisy samples to determine provable bounds on noise-free expectation values. We discuss how to leverage these bounds for different algorithms and demonstrate our findings through experiments on real quantum computers involving up to 127 qubits. The results show strong alignment with theoretical predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An unattended device for high-voltage sampling and passive measurement of thoron decay products

An integrating measurement device for the concentration of airborne thoron decay products was designed and calibrated. It is suitable for unattended use over up to several months also in inhabited dwellings. The device consists of a hemispheric capacitor with a wire mesh as the outer electrode on ground potential and the sampling substrates as the inner electrode on +7.0 kV. Negatively charged and neutral thoron decay products are accelerated to and deposited on the sampling substrates. As sampling substrates, CR39 solid-state nuclear track detectors are used in order to record the alpha decay of the sampled decay products. Nuclide discrimination is achieved by covering the detectors with aluminum foil of different thickness, which are penetrated only by alpha particles with sufficient energy. Devices of this type were calibrated against working level monitors in a thoron experimental house. The sensitivity was measured as 9.2 tracks per Bq/m{sup 3} × d of thoron decay products. The devices were used over 8 weeks in several houses built of earthen material in southern Germany, where equilibrium equivalent concentrations of 1.4–9.9 Bq/m{sup 3} of thoron decay products were measured.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Communication: Estimating the initial biasing potential for λ-local-elevation umbrella-sampling (λ-LEUS) simulations via slow growth

In a recent article [Bieler et al., J. Chem. Theory Comput. 10, 3006–3022 (2014)], we introduced a combination of the λ-dynamics (λD) approach for calculating alchemical free-energy differences and of the local-elevation umbrella-sampling (LEUS) memory-based biasing method to enhance the sampling along the alchemical coordinate. The combined scheme, referred to as λ-LEUS, was applied to the perturbation of hydroquinone to benzene in water as a test system, and found to represent an improvement over thermodynamic integration (TI) in terms of sampling efficiency at equivalent accuracy. However, the preoptimization of the biasing potential required in the λ-LEUS method requires “filling up” all the basins in the potential of mean force. This introduces a non-productive pre-sampling time that is system-dependent, and generally exceeds the corresponding equilibration time in a TI calculation. In this letter, a remedy is proposed to this problem, termed the slow growth memory guessing (SGMG) approach. Instead of initializing the biasing potential to zero at the start of the preoptimization, an approximate potential of mean force is estimated from a short slow growth calculation, and its negative used to construct the initial memory. Considering the same test system as in the preceding article, it is shown that of the application of SGMG in λ-LEUS permits to reduce the preoptimization time by about a factor of four.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Compact low temperature scanning tunneling microscope with in-situ sample preparation capability

We report on the design of a compact low temperature scanning tunneling microscope (STM) having in-situ sample preparation capability. The in-situ sample preparation chamber was designed to be compact allowing quick transfer of samples to the STM stage, which is ideal for preparing temperature sensitive samples such as ultra-thin metal films on semiconductor substrates. Conventional spring suspensions on the STM head often cause mechanical issues. To address this problem, we developed a simple vibration damper consisting of welded metal bellows and rubber pads. In addition, we developed a novel technique to ensure an ultra-high-vacuum (UHV) seal between the copper and stainless steel, which provides excellent reliability for cryostats operating in UHV. The performance of the STM was tested from 2 K to 77 K by using epitaxial thin Pb films on Si. Very high mechanical stability was achieved with clear atomic resolution even when using cryostats operating at 77 K. At 2 K, a clean superconducting gap was observed, and the spectrum was easily fit using the BCS density of states with negligible broadening.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Operator-level quantum acceleration of non-logconcave sampling

Sampling from probability distributions of the form 𝝈 ∝ e −𝜷V , where V is a continuous potential, is a fundamental task across physics, chemistry, biology, computer science, and statistics. However, when V is nonconvex, the resulting distribution becomes non-logconcave, and classical methods such as Langevin dynamics often exhibit poor performance. We introduce a quantum algorithm that provably accelerates a broad class of continuous-time sampling dynamics. For Langevin dynamics, our method encodes the target Gibbs measure into the amplitudes of aquantum state, identified as the kernel of a block matrix derived from a factorization of the Witten Laplacian operator. This connection enables Gibbs sampling via singular value thresholding and yields up to a quartic quantum speedup over best-knownclassical Langevin-based methods in the non-logconcave setting. Building on this framework, we further develop the first quantum algorithm that accelerates replica exchange Langevin diffusion, a widely used method for sampling from complex, rugged energy landscapes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

On the validity of the Poisson assumption in sampling nanometer-sized aerosols

A Poisson process is traditionally believed to apply to the sampling of aerosols. For a constant aerosol concentration, it is assumed that a Poisson process describes the fluctuation in the measured concentration because aerosols are stochastically distributed in space. Recent studies, however, have shown that sampling of micrometer-sized aerosols has non-Poissonian behavior with positive correlations. The validity of the Poisson assumption for nanometer-sized aerosols has not been examined and thus was tested in this study. Its validity was tested for four particle sizes - 10 nm, 25 nm, 50 nm and 100 nm - by sampling from indoor air with a DMA- CPC setup to obtain a time series of particle counts. Five metrics were calculated from the data: pair-correlation function (PCF), time-averaged PCF, coefficient of variation, probability of measuring a concentration at least 25% greater than average, and posterior distributions from Bayesian inference. To identify departures from Poissonian behavior, these metrics were also calculated for 1,000 computer-generated Poisson time series with the same mean as the experimental data. For nearly all comparisons, the experimental data fell within the range of 80% of the Poisson-simulation values. Essentially, the metrics for the experimental data were indistinguishable from a simulated Poisson process. The greater influence of Brownian motion for nanometer-sized aerosols may explain the Poissonian behavior observed for smaller aerosols. Although the Poisson assumption was found to be valid in this study, it must be carefully applied as the results here do not definitively prove applicability in all sampling situations.

concentration measurement↗
DOE OSTI2013

Annealed Importance Sampling Reversible Jump MCMC algorithms

It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappings underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.

annealed importance sampling↗