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At least 883 records · Page 49

Novel Geometric Operations for Linear Programming

This report summarizes the work performed under the project "Linear Programming in Strongly Polynomial Time." Linear programming (LP) is a classic combinatorial optimization problem heavily used directly and as an enabling subroutine in integer programming (IP). Specifically IP is the same as LP except that some solution variables must take integer values (e.g. to represent yes/no decisions). Together LP and IP have many applications in resource allocation including general logistics, and infrastructure design and vulnerability analysis. The project was motivated by the PI's recent success developing methods to efficiently sample Voronoi vertices (essentially finding nearest neighbors in high-dimensional point sets) in arbitrary dimension. His method seems applicable to exploring the high-dimensional convex feasible space of an LP problem. Although the project did not provably find a strongly-polynomial algorithm, it explored multiple algorithm classes. The new medial simplex algorithms may still lead to solvers with improved provable complexity. We describe medial simplex algorithms and some relevant structural/complexity results. We also designed a novel parallel LP algorithm based on our geometric insights and implemented it in the Spoke-LP code. A major part of the computational step is many independent vector dot products. Our parallel algorithm distributes the problem constraints across processors. Current commercial and high-quality free LP solvers require all problem details to fit onto a single processor or multicore. Our new algorithm might enable the solution of problems too large for any current LP solvers. We describe our new algorithm, give preliminary proof-of-concept experiments, and describe a new generator for arbitrarily large LP instances.

97 MATHEMATICS AND COMPUTING↗

Light Isotopes and Trace Organics Analysis of Mars Samples with Mass Spectrometry

Precision measurement of light isotopes in Mars surface minerals and comparison of this isotopic composition with atmospheric gas and other, well-mixed reservoirs such as surface dust are necessary to understand the history of atmospheric evolution from a possibly warmer and wetter Martian surface to the present state. Atmospheric sources and sinks that set these ratios are volcanism, solar wind sputtering, photochemical processes, and weathering. Measurement of a range of trace organic species with a particular focus on species such as amino acids that are the building blocks of terrestrial life are likewise important to address the questions of prebiotic and present or past biological activity on Mars. The workshop topics "isotopic mineralogy" and "biology and pre-biotic chemistry" will be addressed from the point of view of the capabilities and limitations of insitu mass spectrometry (MS) techniques such as thermally evolved gas analysis (TEGA) and gas chromatography (GC) surface experiments using MS, in both cases, as a final chemical and isotopic composition detector. Insitu experiments using straightforward adaptations of existing space proven hardware can provide a substantial improvement in the precision and accuracy of our present knowledge of isotopic composition both in molecular and atomic species in the atmosphere and those chemically bound in rocks and soils. Likewise, detection of trace organic species with greatly improved sensitivity from the Viking GCMS experiment is possible using gas enrichment techniques. The limits to precision and accuracy of presently feasible insitu techniques compared to laboratory analysis of returned samples will be explored. The insitu techniques are sufficiently powerful that they can provide a high fidelity method of screening samples obtained from a diverse set of surface locations such as the subsurface or the interior of rocks for selection of those that are the most interesting for return to Earth.

Mahaffy, P.↗

Numerical Experiment with Time and Spatial Accuracy of Navier-Stokes Computation For Helicopter Problems

Helicopter flowfields are highly unsteady, nonlinear and three-dimensional. In forward flight and in hover, the rotor blades interact with the tip vortex and wake sheet developed by either itself or the other blades. This interaction, known as blade-vortex interactions (BVI), results in unsteady loading of the blades and can cause a distinctive acoustic signature. Accurate and cost-effective computational fluid dynamic solutions that capture blade-vortex interactions can help rotor designers and engineers to predict rotor performance and to develop designs for low acoustic signature. Such a predictive method must preserve a blade's shed vortex for several blade revolutions before being dissipated. A number of researchers have explored the requirements for this task. This paper will outline some new capabilities that have been added to the NASA Ames' OVERFLOW code to improve its overall accuracy for both vortex capturing and unsteady flows. To highlight these improvements, a number of case studies will be presented. These case studies consist of free convection of a 2-dimensional vortex, dynamically pitching 2-D airfoil including light-stall, and a full 3-D unsteady viscous solution of a helicopter rotor in forward flight In this study both central and upwind difference schemes are modified to be more accurate. Central difference scheme is chosen for this simulation because the flowfield is not dominated by strong shocks. The feature of shock-vortex interaction in such a flow is less important than the dominant blade-vortex interaction. The scheme is second-order accurate in time and solves the thin-layer Navier-Stokes equations in fully-implicit manner at each time-step. The spatial accuracy is either second and fourth-order central difference or third-order upwind difference using Roe-flux and MUSCLE scheme. This paper will highlight and demonstrate the methods for several sample cases and for a helicopter rotor. Preliminary computations on a rotor were performed by using this method and are in the process of documentation.

Ahmad, Jasim↗

Sample processor for the automatic extraction of families of compounds from liquid samples and/or homogenized solid samples suspended in a liquid

A sample processor and method for the automatic extraction of families of compounds, known as extracts, from liquid and/or homogenized solid samples are disclosed. The sample processor includes a tube support structure which supports a plurality of extraction tubes, each containing a sample from which families of compounds are to be extracted. The support structure is moveable automatically with respect to one or more extraction stations, so that as each tube is at each station a solvent system, consisting of a solvent and reagents, is introduced therein. As a result an extract is automatically extracted from the tube. The sample processor includes an arrangement for directing the different extracts from each tube to different containers, or to direct similar extracts from different tubes to the same utilization device.

Jahnsen, Vilhelm J.↗

Assessing Risk Due to Small Sample Size in Probability of Detection Analysis Using Tolerance Intervals

Small sample size (e.g.6-30) poses risk in results of probability of detection (POD) analysis using tolerance intervals. This method is also called as the limited sample or LS POD. The analysis is performed either during NDE procedure qualification or for assessment of reliability of an NDE procedure. The risk is primarily due to sampling error. Smaller samples are not likely to be random to the population or representative of the population. The small samples are likely to be biased. Biased samples have smaller standard deviation compared to the population. POD analysis with small biased sample can lead to overestimation of POD. Many sampling schemes are available in statistics to mitigate sampling risk. Primary objective of POD analysis is to determine a decision threshold from signal response measurements of a sample such that it is less than or equal to population decision threshold for 90% POD. Sampling error implies that this NDE reliability condition is violated. One of sampling types is called a representative sample. Representative samples reduce variance in POD estimates but also reduce magnitude of the error. Sampling sensitivity analysis for some sampling types is performed here using repetitive random sampling or Monte Carlo method. Six sampling types are considered for comparison. Some of the sampling types are similar to drawing a representative sample. LS POD model assumes random sampling. Therefore, random sampling is used as a basis for comparison with each sampling type. The sampling types used in the analysis are, A. Nominal and worst-case sampling, B. Worst-case sampling, C. Nominal case sampling, D. Random sampling, E. Random target, and sub-target sampling. F. Nominal target and sub-target sampling. Results of Monte Carlo simulation indicate that type F sampling can mitigate sampling risk and is also more practical to implement. Type A sampling may also mitigate the sampling risk, but it may be less practical to implement.

Ajay M Koshti↗

Determination of Silicon in Hydrazine

Inductively coupled plasma-mass spectrometry (ICP-MS) is a highly sensitive technique sometimes used for the trace determination of silicon at a mass-to-charge (m/z) ratio of 28, the most abundant natural isotope of silicon. Unfortunately, ICP-MS is unable to differentiate between other sources of m/z 28 and false positive results for silicon will result when other sources of m/z 28 are present. Nitrogen was a major source of m/z 28 and contributes to the m/z 28 signal when hydrazine sample or nitric acid preservative is introduced into the plasma. Accordingly, this work was performed to develop a sample preparation step coupled with an ICP-MS analysis that minimized non-silicon sources of m/z 28. In the preparatory step of this method, the hydrazine sample was first decomposed predominately to nitrogen gas and water with copper-catalyzed hydrogen peroxide. In the analysis step, ICP-MS was used without nitric acid preservative in samples or standards. Glass, a potential source of silicon contamination, was also avoided where possible. The method was sensitive, accurate, and reliable for the determination of silicon in monopropellant grade hydrazine (MPH) in AF-E-332 elastomer leaching tests. Results for silicon in MPH were comparable to those reported in the literature for other studies.

McClure, Mark B.↗

Climatic Analysis of Oceanic Water Vapor Transports Based on Satellite E-P Datasets

Understanding the climatically varying properties of water vapor transports from a robust observational perspective is an essential step in calibrating climate models. This is tantamount to measuring year-to-year changes of monthly- or seasonally-averaged, divergent water vapor transport distributions. This cannot be done effectively with conventional radiosonde data over ocean regions where sounding data are generally sparse. This talk describes how a methodology designed to derive atmospheric water vapor transports over the world oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets circumvents the problem of inadequate sampling. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E and P datasets obtained from satellite measurements. Independent P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain transports by solving a potential function for the divergence of water vapor transport as balanced by large scale E - P conditions.

Smith, Eric A.↗

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

54 ENVIRONMENTAL SCIENCES↗

Dynamic control modification techniques in teleoperation of a flexible manipulator

The objective of this research is to reduce the end-point vibration of a large, teleoperated manipulator while preserving the usefulness of the system motion. A master arm is designed to measure desired joint angles as the user specifies a desired tip motion. The desired joint angles from the master arm are the inputs to an adaptive PD control algorithm that positions the end-point of the manipulator. As the user moves the tip of the master, the robot will vibrate at its natural frequencies which makes it difficult to position the end-point. To eliminate the tip vibration during teleoperated motions, an input shaping method is presented. The input shaping method transforms each sample of the desired input into a new set of impulses that do not excite the system resonances. The method is explained using the equation of motion for a simple, second-order system. The impulse response of such a system is derived and the constraint equations for vibrationless motion are presented. To evaluate the robustness of the method, a different residual vibration equation from Singer's is derived that more accurately represents the input shaping technique. The input shaping method is shown to actually increase the residual vibration in certain situations when the system parameters are not accurately specified. Finally, the implementation of the input shaping method to a system with varying parameters is shown to induce a vibration into the system. To eliminate this vibration, a modified command shaping technique is developed. The ability of the modified command shaping method to reduce vibration at the system resonances is tested by varying input perturbations to trajectories in a range of possible user inputs. By comparing the frequency responses of the transverse acceleration at the end-point of the manipulator, the modified method is compared to the original PD routine. The control scheme that produces the smaller magnitude of resonant vibration at the first natural frequency is considered the more effective control method.

Magee, David Patrick↗

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution, appendix 3

The Always-Convergent Iterative Noise Removal and Deconvolution Method of Ioup is applied as a single-filter in the transform domain to deconvolution with both narrow and wide Gaussian impulse response functions. The wraparound error for both cases is also studied. A method is developed by which one can find the optimum iteration number for single-filter iterative deconvolution of sampled data. The method employs the mean square error (MSE), the square of the difference between the deconvolved result and the input, for optimization. The MSE decreases as the deconvolution iterations proceed, but at the optimum iteration number, the MSE starts to increase. This procedure is repeated for signal-to-noise ratio of 10 to 150. The optimum iteration number and the MSE are plotted vs SNR. By knowing the SNR for a particular experiment, one can find the optimum iteration number and MSE.

Ioup, George E.↗

Non-Contact Conductivity Measurement for Automated Sample Processing Systems

A new method has been developed for monitoring and control of automated sample processing and preparation especially focusing on desalting of samples before analytical analysis (described in more detail in Automated Desalting Apparatus, (NPO-45428), NASA Tech Briefs, Vol. 34, No. 8 (August 2010), page 44). The use of non-contact conductivity probes, one at the inlet and one at the outlet of the solid phase sample preparation media, allows monitoring of the process, and acts as a trigger for the start of the next step in the sequence (see figure). At each step of the muti-step process, the system is flushed with low-conductivity water, which sets the system back to an overall low-conductivity state. This measurement then triggers the next stage of sample processing protocols, and greatly minimizes use of consumables. In the case of amino acid sample preparation for desalting, the conductivity measurement will define three key conditions for the sample preparation process. First, when the system is neutralized (low conductivity, by washing with excess de-ionized water); second, when the system is acidified, by washing with a strong acid (high conductivity); and third, when the system is at a basic condition of high pH (high conductivity). Taken together, this non-contact conductivity measurement for monitoring sample preparation will not only facilitate automation of the sample preparation and processing, but will also act as a way to optimize the operational time and use of consumables

Beegle, Luther W.↗

Resonance Scattering Treatment with the Windowed Multipole Formalism

A new method for directly sampling the resonance upscattering effect is presented. Alternatives have relied on inefficient rejection sampling techniques or large tabular storage of relative velocities. None of these approaches, which require pointwise energy data, are particularly well suited to the windowed multipole cross-section representation. The new method, called multipole analytic resonance scattering, overcomes these limitations by inverse transform sampling from the target relative velocity distribution where the cross section is expressed in the multipole formalism. The closed-form relative speed distribution contains a novel special function we deem the incomplete Faddeeva function, and we present the first results on its efficient numerical evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Earth recovery mode analysis for a Martian sample return mission

The analysis has concerned itself with evaluating alternative methods of recovering a sample module from a trans-earth trajectory originating in the vicinity of Mars. The major modes evaluated are: (1) direct atmospheric entry from trans-earth trajectory; (2) earth orbit insertion by retropropulsion; and (3) atmospheric braking to a capture orbit. In addition, the question of guided vs. unguided entry vehicles was considered, as well as alternative methods of recovery after orbit insertion for modes (2) and (3). A summary of results and conclusions is presented. Analytical results for aerodynamic and propulsive maneuvering vehicles are discussed. System performance requirements and alternatives for inertial systems implementation are also discussed. Orbital recovery operations and further studies required to resolve the recovery mode issue are described.

Green, J. P.↗

A new method for quantifying 64 Cu in nuclear debris samples

Quantifying 64 Cu in post-detonation nuclear debris samples can provide important diagnostic information regarding the structural materials used within a nuclear device. However, this task is challenging due to the weak gamma emissions associated with the decay of 64 Cu, its short half-life (12.701 h), and the presence of interfering fission product radioisotopes. Large quantities of debris sample are generally needed to accurately quantify 64 Cu, which can be problematic in sample-limited scenarios where other radiometric analyses are required. Herein, we present a new method for the separation of 64 Cu from solutions of mixed fission products and demonstrate the quantification of its activity through use of gas-flow proportional beta counting. Here, the new method was validated through a series of rigorous tests and was shown to improve the detection limit of 64 Cu by over two orders of magnitude, from 2.5 × 10 6 to 1.3 × 10 4 atoms/sample for 100 min measurements.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

ABSTRACT Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances. IMPORTANCE Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Lui, Lauren M.↗