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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Crystallization and preliminary X-ray diffraction study of recombinant adenine phosphoribosyltransferase from the thermophilic bacterium Thermus thermophilus strain HB27

Adenine phosphoribosyltransferase (APRT) belongs to the type I phosphoribosyltransferase family and catalyzes the formation of adenosine monophosphate via transfer of the 5-phosphoribosyl group from phosphoribosyl pyrophosphate to the nitrogen atom N9 of the adenine base. Proteins of this family are involved in a salvage pathway of nucleotide synthesis, thus providing purine base utilization and maintaining the optimal level of purine bases in the body. Adenine phosphoribosyltransferase from the extremely thermophilic Thermus thermophilus strain HB27 was produced using a highly efficient E. coli producer strain and was then purified by affinity and gel-filtration chromatography. This enzyme was successfully employed as a catalyst for the cascade biosynthesis of biologically important nucleotides. The screening of crystallization conditions for recombinant APRT from T. thermophilus HB27 was performed in order to determine the enzyme structure by X-ray diffraction. The crystallization conditions, which were found by the vapor-diffusion technique, were then optimized to apply the counter-diffusion technique. The crystals of the enzyme were grown by the capillary counter-diffusion method. The crystals belong to sp. gr. P12{sub 1}1 and have the following unitcell parameters: a = 69.86 Å, b = 82.16 Å, c = 91.39 Å, α = γ = 90°, β = 102.58°. The X-ray diffraction data set suitable for the determination of the APRT structure at 2.6 Å resolution was collected from the crystals at the SPring-8 synchrotron facility (Japan).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Performing Bayesian Analyses With AZURE2 Using BRICK: An Application to the 7 Be System

Phenomenological R-matrix has been a standard framework for the evaluation of resolved resonance cross section data in nuclear physics for many years. It is a powerful method for comparing different types of experimental nuclear data and combining the results of many different experimental measurements in order to gain a better estimation of the true underlying cross sections. Yet a practical challenge has always been the estimation of the uncertainty on both the cross sections at the energies of interest and the fit parameters, which can take the form of standard level parameters. Frequentist (χ 2 -based) estimation has been the norm. In this work, a Markov Chain Monte Carlo sampler, emcee, has been implemented for the R-matrix code AZURE2, creating the Bayesian R-matrix Inference Code Kit (BRICK). Bayesian uncertainty estimation has then been carried out for a simultaneous R-matrix fit of the 3 He (α,γ) 7 Be and 3 He (α,α) 3 He reactions in order to gain further insight into the fitting of capture and scattering data. Both data sets constrain the values of the bound state α-particle asymptotic normalization coefficients in 7 Be. The analysis highlights the need for low-energy scattering data with well-documented uncertainty information and shows how misleading results can be obtained in its absence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Efficient water allocation is one of the most prominent issues in water resources management. In this research, a two-stage interval-parameter stochastic fuzzy programming with type 2 membership functions was used to allocate water resources optimally to different users under uncertainty. This method can handle uncertainties expressed as probability distributions, discrete intervals, and fuzzy sets. The model considers treated wastewater as an allocable water resource in a scenario, in addition to water that is extracted from wellheads, springs, and qanats. Moreover, the loss rate of water during distribution, surplus water in the reservoir in the previous and the next period, and treated wastewater parameters have been incorporated into the model. This model was applied to a case study of water resources allocation within a multi-user and multi-reservoir context in the Zarand region of Kerman, Iran. The results indicate that reasonable solutions have been generated, in the form of interval and fuzzy information under different scenarios that could help managers provide optimal water resources allocation plans. The results also demonstrate that establishing a wastewater treatment station increases the system net benefits, surplus water in wellheads for the next period, and system reliability (level of satisfying the fuzzy goal and constraints), and decreases encountering water shortages.

58 GEOSCIENCES↗
DOE OSTI2017

An improved method for determining carrier densities via drive level capacitance profiling

In this paper, we demonstrate that an analytic relationship between coefficients in the Taylor expansion of the junction capacitance can be exploited to yield more precise determinations of carrier densities in drive level capacitance profiling (DLCP). Improvements are demonstrated on data generated according to the DLCP theory and in measurements performed on a CuIn x Ga 1–x Se 2 device. We argue that the improved DLCP method is especially important for non-uniform devices, which are more susceptible to noise in the capacitance data used in DLCP because they require that the amplitude of the drive level be restricted. Importantly, the analysis does not require the collection of any data other than what is typically collected during a DLCP measurement while employing fewer independent parameters than the model that is typically used in DLCP. Finally and thus, we expect that it will be readily adoptable by those who perform DLCP measurements.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2015

SU-E-J-36: Comparison of CBCT Image Quality for Manufacturer Default Imaging Modes

Purpose CBCT is being increasingly used in patient setup for radiotherapy. Often the manufacturer default scan modes are used for performing these CBCT scans with the assumption that they are the best options. To quantitatively assess the image quality of these scan modes, all of the scan modes were tested as well as options with the reconstruction algorithm. Methods A CatPhan 504 phantom was scanned on a TrueBeam Linear Accelerator using the manufacturer scan modes (FSRT Head, Head, Image Gently, Pelvis, Pelvis Obese, Spotlight, & Thorax). The Head mode scan was then reconstructed multiple times with all filter options (Smooth, Standard, Sharp, & Ultra Sharp) and all Ring Suppression options (Disabled, Weak, Medium, & Strong). An open source ImageJ tool was created for analyzing the CatPhan 504 images. Results The MTF curve was primarily dictated by the voxel size and the filter used in the reconstruction algorithm. The filters also impact the image noise. The CNR was worst for the Image Gently mode, followed by FSRT Head and Head. The sharper the filter, the worse the CNR. HU varied significantly between scan modes. Pelvis Obese had lower than expected HU values than most while the Image Gently mode had higher than expected HU values. If a therapist tried to use preset window and level settings, they would not show the desired tissue for some scan modes. Conclusion Knowing the image quality of the set scan modes, will enable users to better optimize their setup CBCT. Evaluation of the scan mode image quality could improve setup efficiency and lead to better treatment outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

The Backscattering Phase Function for a Sphere with a Two-Scale Relief of Rough Surface

The backscattering of light from spherical surfaces characterized by one and two-scale roughness reliefs has been investigated. The analysis is performed using the three-dimensional Monte-Carlo program POKS-RG (geometrical-optics approximation), which makes it possible to take into account the roughness of objects under study by introducing local geometries of different levels. The geometric module of the program is aimed at describing objects by equations of second-order surfaces. One-scale roughness is set as an ensemble of geometric figures (convex or concave halves of ellipsoids or cones). The two-scale roughness is modeled by convex halves of ellipsoids, with surface containing ellipsoidal pores. It is shown that a spherical surface with one-scale convex inhomogeneities has a flatter backscattering phase function than a surface with concave inhomogeneities (pores). For a sphere with two-scale roughness, the dependence of the backscattering intensity is found to be determined mostly by the lower-level inhomogeneities. The influence of roughness on the dependence of the backscattering from different spatial regions of spherical surface is analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Component 5: Imaging Protein Conformations, Shapes & Assemblies in Solution & Administration project (Final Scientific/Technical Report, Subcontract No. 6974584)

We set ambitious goals to examine microorganism communities and measure both their chemical input and output as a read out of specific biochemical activity. These scientific goals are driving the development of sophisticated algorithms to analyze large amounts of experimental measurements made using high throughput technologies to explain and predict how the environment influences biological function at multiple scales and how the microbial systems in tum modify the environment. By examining how bacteria communities rely on symbiotic metabolic relationships for survival and reproductive success, and how these relationships consequently affect their biochemical capabilities. This was accomplished using state-of-the-art mass spectrometry-based methods, and metabolic fingerprinting approaches with a high degree of chemical specificity and sensitivity. During this period the original effort transitioned and was consolidated into what is now ENIGMA, the efforts on technology development expanded to include more untargeted metabolomics and its application to organisms on a systems level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Advanced Graphite Creep Uncertainty Analysis

Radiation damage estimation is an important component of the post irradiation analysis of the Advanced Graphite Creep (AGC) experiment. It depends primarily on the fast fluence, which is determined using well established methods of spectral adjustment. These are based on best estimates from models such as Monte Carlo N-Particle (MCNP), input cross-sections, and measured activities from flux wires in the experiment. Each of these parameters can propagate uncertainties which will affect the uncertainty in the calculated dose levels for AGC, or any experiment irradiated within a reactor. While the methods of propagating uncertainty are well-established, the final uncertainty estimates they provide are only as good as the estimates of uncertainty in the inputs on which they are based. The purpose of this work is to outline some deficiencies in the ways these input uncertainties are presently estimated, and to outline a methodology by which they can be improved. The fast fluence and radiation damage received by graphite specimens irradiated in the Advanced Graphite Creep (AGC) experiments is presently estimated using spectral adjustment methods that are based on both flux wire activity measurements, and MCNP model predictions. This work describes an ongoing effort to quantify and propagate uncertainties in inputs to the spectral adjustment process, and thereby quantify the resultant error in radiation damage (dpa) estimates. The effort is multi-faceted, and we consider the impacts of both the set of flux wires selected, and the counting process. An expanded set of flux wires is identified that provides a more comprehensive data set on the fast spectrum. To address the counting process itself, a series of round-robin measurements in several reactor metrology laboratories across the Department of Energy (DOE) complex and nuclear industry are being undertaken to refine the American Society for Testing and Materials (ASTM) standards for flux wire measurements. To address the contribution of uncertainty in the MCNP model predictions, an uncertainty quantification (UQ) tool has been developed that statistically samples the model input parameters, runs a series of cases, and assimilates the results to provide an overall uncertainty. The impact of the MCNP UQ tool results is demonstrated by re-analyzing previous AGC flux wire and irradiation data. While the expanded flux wire set obviously cannot be added to these experiments retroactively, plans for future graphite irradiations are outlined.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

A pedagogical intrinsic approach to relative entropies as potential functions of quantum metrics: The q–z family

The so-called q-z-Rényi Relative Entropies provide a huge two parameter family of relative entropies which include almost all well-known examples of quantum relative entropies for suitable values of the parameters. In this paper we consider a log-regularized version of this family and use it as a family of potential functions to generate covariant (0,2) symmetric tensors on the space of invertible quantum states in finite dimensions. The geometric formalism developed here allows us to obtain the explicit expressions of such tensor fields in terms of a basis of globally defined differential forms on a suitable unfolding space without the need to introduce a specific set of coordinates. To make the reader acquainted with the intrinsic formalism introduced, we first perform the computation for the qubit case, and then, we extend the computation of the metric-like tensors to a generic n-level system. By suitably varying the parameters q and z, we are able to recover well-known examples of quantum metric tensors that, in our treatment, appear written in terms of globally defined geometrical objects that do not depend on the coordinates system used. In particular, we obtain a coordinate-free expression for the von Neumann–Umegaki metric, for the Bures metric and for the Wigner–Yanase metric in the arbitrary n-level case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Bioaugmentation of an Engineered Metal Treatment Wetland with Cupriavidus SRS

There are many chemical methods to remediate copper (Cu) from the environment. However, the use of microorganisms has been identified to be cheaper and more efficient in remediating toxic compounds in a method known as bioremediation. A microorganism, Cupriavidus SRS, is a metal resistant, rod shaped, gram negative bacteria that was isolated from a location with heavy metal contamination. As a predator this isolate has the ability to attack gram-negative and gram-positive bacteria. It is highly tolerant to Cu, and the isolates growth initiation is stimulated by Cu. Wang et al. (2015) determined that efflux pump activity is one of the most important mechanisms of heavy metal tolerance and the Cupriavidus genus demonstrates this behavior. In this study, Cupriavidus SRS will be inoculated to sediment and water from an area with high concentrations of Cu and zinc, to determine the ability of the isolate to grow and survive in a high level Cu wetland as well as the bioremoval efficiency. The H-02 wetland in the AL1 outfall area is an engineered wetland that was constructed to utilize natural processes associated with sediments and microbial communities to remove contaminants from waste waters at the Savannah River Site. Specifically, this wetland treats the building processes and runoff form the Tritium Processing Facility in H-area to prevent Cu and Zn from entering the water before the contaminants go in the Savannah River. Distributions of Cu and Zn follow organic matter levels with higher densities along the shoreline showing that metal concentrations correlate with organic matter content. Cupriavidus SRS Growth: Cupriavidus SRS was isolated at the Savannah River Site from an area with heavy metal contamination. Cultures were grown in R2A medium at 25 deg. C and shaken at 80 rpm for liquid cultures for 5 days. Sediment and Water Collection: All samples were collected from the AL1 Outfall area within the Department of Energy's Savannah River Site. Sediment cores, organic layer samples, and water samples were collected from the Inlet and Outlet cells in triplicate. Only water samples were collected from the basin. Cell Pellet: After centrifugation at 10,000 RPM for 10 minutes the supernatant was removed. 1 mL of phosphate buffer saline was added to the tube, vortexed, and recentrifuged. Inoculation of Sediment and Water: All samples were done in triplicate, vortexed after inoculation, and put on the shaker for 72 hours. Day 0 begins when the samples are removed from the shaker. Experimental Set-Up: All samples were done in triplicate. All sediment samples were centrifuged at 7500 RPM for 10 minutes on Day 0 and Day 5. All the sediment and water samples were filtered with a 0.2 μm nylon filters to obtain approximately 10 mL of supernatant on Day 0 and Day 3. pH was taken 24, 48, and 72 hours after the samples had been on the shaker. Plate Count: Plate counts were done on Day 0 and Day 3 to determine Cupriavidus SRS growth following a quantitative counting method from Seely et al. (1972). This project is ongoing and the goal is to determine if Cupriavidus SRS has the ability to uptake excess Cu out of the environment. These could be some possible results for the experiment: - The isolate uptakes too much Cu, dies, and releases Cu back into the environment. - The isolate is able to uptake Cu, continue to live, but chemically changes the environment introducing new problems. - The isolate is able to uptake Cu, continue to live, and does not disrupt the environment with toxic chemical changes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

A time-dependent momentum-resolved scattering approach to core-level spectroscopies

While new light sources allow for unprecedented resolution in experiments with X-rays, a theoretical understanding of the scattering cross-section is lacking. In the particular case of strongly correlated electron systems, numerical techniques are quite limited, since conventional approaches rely on calculating a response function (Kramers-Heisenberg formula) that is obtained from a perturbative analysis of scattering processes in the frequency domain. This requires a knowledge of a full set of eigenstates in order to account for all intermediate processes away from equilibrium, limiting the applicability to small tractable systems. In this work, we present an alternative paradigm, recasting the problem in the time domain and explicitly solving the time-dependent Schrödinger equation without the limitations of perturbation theory: a faithful simulation of the scattering processes taking place in actual experiments, including photons and core electrons. We show how this approach can yield the full time and momentum resolved Resonant Inelastic X-Ray Scattering (RIXS) spectrum of strongly interacting many-body systems. We demonstrate the formalism with an application to Mott insulating Hubbard chains using the time-dependent density matrix renormalization group method, which does not require a priory knowledge of the eigenstates and can solve very large systems with dozens of orbitals. This approach can readily be applied to systems out of equilibrium without modification and generalized to other spectroscopies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

TH-EF-BRB-11: Volumetric Modulated Arc Therapy for Total Body Irradiation

Purpose: To develop a modern, patient-comfortable total body irradiation (TBI) technique suitable for standard-sized linac vaults. Methods: An indexed rotatable immobilization system (IRIS) was developed to make possible total-body CT imaging and radiation delivery on conventional couches. Treatment consists of multi-isocentric volumetric modulated arc therapy (VMAT) to the upper body and parallel-opposed fields to the lower body. Each isocenter is indexed to the couch and includes a 180° IRIS rotation between the upper and lower body fields. VMAT fields are optimized to satisfy lung dose objectives while achieving a uniform therapeutic dose to the torso. End-to-end tests with a rando phantom were used to verify dosimetric characteristics. Treatment plan robustness regarding setup uncertainty was assessed by simulating global and regional isocenter setup shifts on patient data sets. Dosimetric comparisons were made with conventional extended distance, standing TBI (cTBI) plans using a Monte Carlo-based calculation. Treatment efficiency was assessed for eight courses of patient treatment. Results: The IRIS system is level and orthogonal to the scanned CT image plane, with lateral shifts <2mm following rotation. End-to-end tests showed surface doses within ±10% of the prescription dose, field junction doses within ±15% of prescription dose. Plan robustness tests showed <15% changes in dose with global setup errors up to 5mm in each direction. Local 5mm relative setup errors in the chest resulted in < 5% dose changes. Local 5mm shift errors in the pelvic and upper leg junction resulted in <10% dose changes while a 10mm shift error causes dose changes up to 25%. Dosimetric comparison with cTBI showed VMAT-TBI has advantages in preserving chest wall dose with flexibility in leveraging the PTV-body and PTV-lung dose. Conclusion: VMAT-TBI with the IRIS system was shown clinically feasible as a cost-effective approach to TBI for standard-sized linac vaults.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Bound-preserving finite element approximations of the Keller–Segel equations

We report this paper aims to develop numerical approximations of the Keller–Segel equations that mimic at the discrete level the lower bounds and the energy law of the continuous problem. We solve these equations for two unknowns: the organism (or cell) density, which is a positive variable, and the chemoattractant density, which is a non-negative variable. We propose two algorithms, which combine a stabilized finite element method and a semi-implicit time integration. The stabilization consists of a nonlinear artificial diffusion that employs a graph-Laplacian operator and a shock detector that localizes local extrema. As a result, both algorithms turn out to be nonlinear and can generate cell and chemoattractant numerical densities fulfilling lower bounds. However, the first algorithm requires a suitable constraint between the space and time discrete parameters, whereas the second one does not. We design the latter to attain a discrete energy law on acute meshes. We report some numerical experiments to validate the theoretical results on blowup and nonblowup phenomena. In the blowup setting, we identify a locking phenomenon that relates the L ∞ (Ω)-norm to the L 1 (Ω)-norm limiting the growth of the singularity when supported on a macroelement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Evolving Trust in Robots: Specification Through Sequential and Comparative Meta-Analyses

Objective The objectives of this meta-analysis are to explore the presently available empirical findings on the antecedents of trust in robots and use this information to expand upon a previous meta-analytic review of the area. Background Human–robot interaction (HRI) represents an increasingly important dimension of our everyday existence. Currently, the most important element of these interactions is proposed to be whether the human trusts the robot or not. We have identified three overarching categories that exert effects on the expression of trust. These consist of factors associated with (a) the human, (b) the robot, and (c) the context in which any specific HRI event occurs. Method The current body of literature was examined and all qualifying articles pertaining to trust in robots were included in the meta-analysis. A previous meta-analysis on HRI trust was used as the basis for this extended, updated, and evolving analysis. Results Multiple additional factors, which have now been demonstrated to significantly influence trust, were identified. The present results, expressed as points of difference and points of commonality between the current and previous analyses, are identified, explained, and cast in the setting of the emerging wave of HRI. Conclusion The present meta-analysis expands upon previous work and validates the overarching categories of trust antecedent (human-related, robot-related, and contextual), as well as identifying the significant individual precursors to trust within each category. A new and updated model of these complex interactions is offered. Application The identified trust factors can be used in order to promote appropriate levels of trust in robots.

Behavioral Sciences↗
DOE OSTI2021

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-J-09: Image Quality Comparison and Dose Quantification for 2.5 MV

Purpose: To compare the image quality of the 2.5MV imaging beam (2.5X-IMB) to that of a 6MV beam and to quantify the imaging dose of a 2.5X-IMB for constancy as specified by AAPM TG-142 Methods: The image quality of the 2.5X-IMB was compared to the 6MV imaging beam using the SNC ImagePro MV-QA phantom and the Varian supplied Las Vegas phantom (LVP). High resolution (1280×1280×16, 2 frames at 1.5MU/frame) and low resolution (640×640×16, 2 frames at 0.75MU/frame) images were compared for each phantom. MV-QA phantom images were evaluated quantitatively, and the LVP images were evaluated qualitatively. The imaging dose for 2.5X-IMB was quantified using the procedure outlined in TG51. PTWCC13-31013 chambers were used to measure a percent depth dose (PDD) curve for the 2.5X-IMB. All the factors described in TG51 were calculated using the 2.5X-IMB and a PTW30013 farmer chamber. Results: A comparison between 2.5X-IMB and 6MV image quality was performed both visually and with DoseLab software. The optimal window and level were set for each image of the LVP by the user. Visual inspection showed greater contrast resolution with the 2.5MV beam, but no significant difference with the change in imaging resolution. DoseLab reported similar spatial resolutions between the two energies, but the contrast-to-noise ratio (CNR) was greater for 2.5MV. The PDDx(10cm) for a 10x10cm2 field was measured to be 51.5%. Although this PDD value is off the scale of Figure 4 in TG51, the trend of the curve corresponding to the PTW31003 (equivalent) chamber led to an approximate kQ value of 1.00. Conclusion: When compared to 6MV imaging, 2.5X-IMB results in a better CNR. At low resolution, the DoseLab results for the two energies are comparable, but visual analysis favors the 2.5X-IMB images. Imaging dose was quantified for the 2.5X-IMB after following the TG51 methodology with appropriate approximations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Track Seeding and Labelling with Embedded-space Graph Neural Networks

To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, graph neural networks (GNN), process the event as a graph that connects track measurements (detector hits corresponding to nodes) with candidate line segments between the hits (corresponding to edges). Detector information can be associated with nodes and edges, enabling a GNN to propagate the embedded parameters around the graph and predict node-, edge- and graph-level observables. Previously, message-passing GNNs have shown success in predicting doublet likelihood, and we here report updates on the state-of-the-art architectures for this task. In addition, the Exa.TrkX project has investigated innovations in both graph construction, and embedded representations, in an effort to achieve fully learned end-to-end track finding. Hence, we present a suite of extensions to the original model, with encouraging results for hitgraph classification. In addition, we explore increased performance by constructing graphs from learned representations which contain non-linear metric structure, allowing for efficient clustering and neighborhood queries of data points. We demonstrate how this framework fits in with both traditional clustering pipelines, and GNN approaches. The embedded graphs feed into high-accuracy doublet and triplet classifiers, or can be used as an end-to-end track classifier by clustering in an embedded space. A set of post-processing methods improve performance with knowledge of the detector physics. Finally, we present numerical results on the TrackML particle tracking challenge dataset, where our framework shows favorable results in both seeding and track finding.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Radiological data consolidation and 3D modeling of a building - 15473

A portion of a building at an industrial facility that conducted monazite sands-processing operations in the 1950's under contract to the Atomic Energy Commission (AEC) became contaminated. Subsequently the U.S. Department of Energy designated the facility for remedial action under the Formerly Used Sites Remedial Action Program (FUSRAP). Remedial investigation, remedial actions and post-remediation surveys have been conducted in portions of the building. Radiological data for the interior of the building were compiled, evaluated and presented in a three dimensional (3-D) model (the model) created by AMEC Foster Wheeler in order to identify areas that meet the Record of Decision (ROD) cleanup criteria, and identity areas that may require remedial action or may require additional investigation due to data gaps. The data from different phases of investigation and remediation cover different portions of the building and in some cases overlap. In addition, the data were collected over a period of more than ten years, for different objectives, and thus the instruments and methods for establishing efficiency were not necessarily consistent. The data consolidation process included determining the relative quality of data points to include in the model and the development of rationale associated with assigning a quality level (i.e. ranking) to each data point. The rationale for ranking data quality included, as the primary determining factors, chronological order of the data (most recent was ranked as more reliable), certainty of the sample locations within the building, and analytical data quality. A 3-D model of the building was created using a laser point cloud scan which was then converted into a 3-D design model. Sample locations were then entered into the model and linked with the analytical database to allow display of the radiological results in the model. The visual model allows both strategic and tactical decisions to be made, depending on the level of detail examined. The evaluation process allowed maximum use of the historical data set, rather than requiring older data to be disregarded, and provided at a minimum a qualitative sense of data quality/confidence in the data. The (authors)process also highlights the importance of collecting high quality data from the very beginning with a consistent locational coordinate system, and the need for a good visualization model in order to assess contaminant locations during remedial action or post-remediation surveys.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗