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DOE OSTI2024

Data-Driven Computation of Probabilistic Marching Cubes for Efficient Visualization of Level-Set Uncertainty

Uncertainty visualization is an important emerging research area. Being able to visualize data uncertainty can help scientists improve trust in analysis and decision-making. However, visualizing uncertainty can add computational overhead, which can hinder the efficiency of analysis. In this paper, we propose novel data-driven techniques to reduce the computational requirements of the probabilistic marching cubes (PMC) algorithm. PMC is an uncertainty visualization technique that studies how uncertainty in data affects level-set positions. However, the algorithm relies on expensive Monte Carlo (MC) sampling for the multivariate Gaussian uncertainty model because no closed-form solution exists for the integration of multivariate Gaussian. In this work, we propose the eigenvalue decomposition and adaptive probability model techniques that reduce the amount of MC sampling in the original PMC algorithm and hence speed up the computations. Our proposed methods produce results that show negligible differences compared with the original PMC algorithm demonstrated through metrics, including root mean squared error, maximum error, and difference images. We demonstrate the performance and accuracy evaluations of our data-driven methods through experiments on synthetic and real datasets.

Athawale, Tushar↗

DOE OSTI2017

Enhancing multi-step quantum state tomography by PhaseLift

Multi-photon system has been studied by many groups, however the biggest challenge faced is the number of copies of an unknown state are limited and far from detecting quantum entanglement. The difficulty to prepare copies of the state is even more serious for the quantum state tomography. One possible way to solve this problem is to use adaptive quantum state tomography, which means to get a preliminary density matrix in the first step and revise it in the second step. In order to improve the performance of adaptive quantum state tomography, we develop a new distribution scheme of samples and extend it to three steps, that is to correct it once again based on the density matrix obtained in the traditional adaptive quantum state tomography. Our numerical results show that the mean square error of the reconstructed density matrix by our new method is improved to the level from 10{sup −4} to 10{sup −9} for several tested states. In addition, PhaseLift is also applied to reduce the required storage space of measurement operator. - Highlights: • PhaseLift is firstly applied in the adaptive quantum state tomography and the required store space of measurement operator is reduced. • Traditional adaptive quantum state tomography is extended to three-step adaptive quantum state tomography. • A new scheme of copy distribution of state is proposed to effectively use the limited copies of state. • For several tested states, the mean square error of the reconstructed state is reduced to 10{sup −9} from 10{sup −4}. • Fidelity is more accurately estimated with limited copies of state compared with traditional adaptive quantum state tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Rigorous Data Fusion for Computationally Expensive Simulations

This manuscript comprises the final report for the 1-year, FY19 LDRD project "Rigorous Data Fusion for Computationally Expensive Simulations," wherein an alternative approach to Bayesian calibration was developed based a new sampling technique called VoroSpokes. Vorospokes is a novel quadrature and sampling framework defined with respect to Voronoi tessellations of bounded domains in $R^d$ developed within this project. In this work, we first establish local quadrature and sampling results on convex polytopes using randomly directed rays, or spokes, to approximate the quantities of interest for a specified target function. A theoretical justification for both procedures is provided along with empirical results demonstrating the unbiased convergence in the resulting estimates/samples. The local quadrature and sampling procedures are then extended to global procedures defined on more general domains by applying the local results to the cells of a Voronoi tessellation covering the domain in consideration. We then demonstrate how the proposed global sampling procedure can be used to define a natural framework for adaptively constructing Voronoi Piecewise Surrogate (VPS) approximations based on local error estimates. Finally, we show that the adaptive VPS procedure can be used to form a surrogate model approximation to a specified, potentially unnormalized, density function, and that the global sampling procedure can be used to efficiently draw independent samples from the surrogate density in parallel. The performance of the resulting VoroSpokes sampling framework is assessed on a collection of Bayesian inference problems and is shown to provide highly accurate posterior predictions which align with the results obtained using traditional methods such as Gibbs sampling and random-walk Markov Chain Monte Carlo (MCMC). Importantly, the proposed framework provides a foundation for performing Bayesian inference tasks which is entirely independent from the theory of Markov chains.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Postmortem analysis of sand grain crushing from pile interface using X-ray tomography

Pile foundations of offshore platforms, wind and water turbines are typically subjected to a variety of cyclic loading paths due to their complex environment. While many studies focus on global pile behaviour, the soil-pile interface is explored here by a micromechanical study of the soil layer in contact with the pile surface. This work is devoted to the analysis of frozen post-mortem silica sand samples recovered at the pile interface following installation and cyclic loading tests in a calibration chamber using x-ray tomography. An experimental procedure developed for three dimensional (3D) snow imaging was adapted for the recovery of the in-situ sand samples to preserve their structure during tomography scans. 3D images at a pixel size of 7 {mu}m were then obtained using a cryogenic cell. Results confirm the presence of a shear band at the pile surface as well as void ratios changes in the direction of the pile's radius.

36 MATERIALS SCIENCE↗

DOE OSTI2021

In vivo volumetric imaging of calcium and glutamate activity at synapses with high spatiotemporal resolution

Studying neuronal activity at synapses requires high spatiotemporal resolution. For high spatial resolution in vivo imaging at depth, adaptive optics (AO) is required to correct sample-induced aberrations. To improve temporal resolution, Bessel focus has been combined with two-photon fluorescence microscopy (2PFM) for fast volumetric imaging at subcellular lateral resolution. To achieve both high-spatial and high-temporal resolution at depth, we develop an efficient AO method that corrects the distorted wavefront of Bessel focus at the objective focal plane and recovers diffraction-limited imaging performance. Applying AO Bessel focus scanning 2PFM to volumetric imaging of zebrafish larval and mouse brains down to 500 µm depth, we demonstrate substantial improvements in the sensitivity and resolution of structural and functional measurements of synapses in vivo. This enables volumetric measurements of synaptic calcium and glutamate activity at high accuracy, including the simultaneous recording of glutamate activity of apical and basal dendritic spines in the mouse cortex.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Initial Characterization of ATR End Box Samples

Aluminum samples taken from discarded irradiated Advanced Test Reactor fuel element end boxes (upper and lower adapter ) were characterized to determine the chemical composition and hydration state of the surface oxides. The samples were analyzed using scanning electron microscope imaging and chemical identification, x-ray diffraction to evaluate crystalline morphology, and thermogravitational analysis to determine mass loss by dehydration. The samples were acquired from the discarded fuel element components stored in the ATR fuel handling canal and transferred to the Materials and Fuels Complex for analysis. The measurements indicate that the samples have limited oxide thickness, indicating that little corrosion has occurred beyond the initial passive layer that was intentionally formed prior to irradiation. The presence of minimal aluminum oxyhydroxide suggests that there will be minimal risk to store these fuels in air with limited risk for alteration of the base passive layer. These observations will be compared against samples that will be taken of the same type of fuel that has been in dry storage for more than 10 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Risk Ratio and Risk Difference Estimation in Case-cohort Studies

Background: In case-cohort studies with binary outcomes, ordinary logistic regression analyses have been widely used because of their computational simplicity. However, the resultant odds ratio estimates cannot be interpreted as relative risk measures unless the event rate is low. The risk ratio and risk difference are more favorable outcome measures that are directly interpreted as effect measures without the rare disease assumption. Methods: We provide pseudo-Poisson and pseudo-normal linear regression methods for estimating risk ratios and risk differences in analyses of case-cohort studies. These multivariate regression models are fitted by weighting the inverses of sampling probabilities. Also, the precisions of the risk ratio and risk difference estimators can be improved using auxiliary variable information, specifically by adapting the calibrated or estimated weights, which are readily measured on all samples from the whole cohort. Finally, we provide computational code in R (R Foundation for Statistical Computing, Vienna, Austria) that can easily perform these methods. Results: Through numerical analyses of artificially simulated data and the National Wilms Tumor Study data, accurate risk ratio and risk difference estimates were obtained using the pseudo-Poisson and pseudo-normal linear regression methods. Also, using the auxiliary variable information from the whole cohort, precisions of these estimators were markedly improved. Conclusion: The ordinary logistic regression analyses may provide uninterpretable effect measure estimates, and the risk ratio and risk difference estimation methods are effective alternative approaches for case-cohort studies. These methods are especially recommended under situations in which the event rate is not low.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Mercury Speciation and Quantification of Hanford 241-AP-107 Tank Waste Feed and Treated Samples

This report describes the second phase of a multi year project to adapt and develop an analytical technique for the low-level determination of total mercury (HgT), elemental mercury (Hg0), and monomethyl mercury (MeHg, hereafter referred to as methyl mercury) in Hanford tank waste. The focus of Phase II was to quantify the mercury (Hg) species total, elemental, and methyl mercury from a raw sample and treated (i.e., filtered and cesium-decontaminated) waste samples originating from Hanford waste tank 241-AP 107. The focus of Phase I work was to determine if mercury species can be preconcentrated from aqueous Hanford tank waste solution onto a solid adsorbent while simultaneously eliminating or very significantly reducing the parent radionuclide activity. This was demonstrated by developing protocols for the preparation, separation, and collection of total mercury and methyl mercury onto solid adsorbents, then measuring the adsorbents for radiological content at Pacific Northwest National Laboratory’s (PNNL’s) Radiochemical Processing Laboratory (RPL) on the Hanford Site. During Phase II, the Hanford tank waste material was preserved, separated (through distillation or digestion), then collected as either solid adsorbents or into liquid distillate form at the RPL and transferred to the PNNL Marine Sciences Laboratory (MSL) in Sequim, Washington, for analysis and quantification. Quantification of total, elemental, and methyl mercury was conducted under radiological control at the MSL using the ultra trace analytical capabilities available there.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

IR spectroscopic quantification of small molecule transport and desorption phenomena in polymers

The application, continued performance, and degradation behavior of polymers often depends on their interaction with small organic or gaseous volatiles. Understanding the underlying permeation and diffusion properties of materials is crucial for predicting their barrier properties (permeant flux), drying behavior, solvent loss or tendency to trap small molecules, as well as their interaction with materials in the vicinity due to off-gassing phenomena, perhaps leading to compatibility concerns. Further, the diffusion of low Mw organics is also important for mechanistic aspects of degradation processes. Based on our need for improved characterization methods, a FTIR-based spectroscopic gas/volatile quantification setup was designed and evaluated for determination of the diffusion, desorption and transport behavior of small IR-active molecules in polymers. At the core of the method, a modified, commercially available IR transmission gas cell monitors time-dependent gas concentration. Appropriate experimental conditions, e.g. desorption or permeation under continuous flow or static gas conditions, are achieved using easily adaptable external components such as flow controllers and sample ampoules. This study presents overview approaches using the same IR detection methodology to determine diffusivity (desorption into a static gas environment, continuous gas flow, or intermittent desorption) and permeability (static and dynamic flow detection). Further, the challenges encountered for design and setup of IR gas quantification experiments, related to calibration and gas interaction, are presented. These methods establish desorption and permeation behavior of solvents (water and methanol), CO 2 off-gassing from foam, and offer simultaneous measurements of the permeation of several gases in a gas mixture (CO 2 , CO and CH 4 ) through polymer films such as epoxy and Kapton. They offer complementary guidance for material diagnostics and understanding of basic properties in sorption and transport behavior often of relevance to polymer degradation or materials reliability phenomena.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Melting temperature measurement of refractory oxide ceramics as a function of oxygen fugacity using containerless methods

An aerodynamic conical nozzle levitator (CNL) has been used to measure the melting temperatures of refractory ceramics. The well-established method of cooling traces has been adapted to allow measurements for air-sensitive samples using a controlled atmosphere, where the oxygen partial pressure can be adjusted and monitored in real time. In this study, we explain the details of a system that we developed for use at the Spallation Neutron Source (Oak Ridge National Laboratory). Measurements of the melting behavior of (Fe,Cr,Al) 3 O 4 spinels were made between log (PO 2 (atm)) of -0.7 and -5. The melting temperature of hercynite is found to be oxygen potential dependent, ranging between 1692 and 1767°C at log (PO 2 ) values from -4.42 to -0.70.

36 MATERIALS SCIENCE↗

DOE OSTI2019

An Efficient, Globally Convergent Method for Optimization Under Uncertainty Using Adaptive Model Reduction and Sparse Grids

We present a new approach to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages two sources of inexactness that trade accuracy for speed: (1) stochastic collocation based on dimension-adaptive sparse grids (SGs), which approximates the stochastic objective function with a limited number of quadrature nodes, and (2) projection-based reduced-order models (ROMs), which generate efficient approximations to PDE solutions. These two sources of inexactness lead to inexact objective function and gradient evaluations, which are managed by a trust-region method that guarantees global convergence by adaptively refining the SG and ROM until a proposed error indicator drops below a tolerance specified by trust-region convergence theory. A key feature of the proposed method is that the error indicator---which accounts for errors incurred by both the SG and ROM---must be only an asymptotic error bound, i.e., a bound that holds up to an arbitrary constant that need not be computed. This allows the approach to be applicable to a wide range of problems, including those where sharp, computable error bounds are not available; this distinguishes the proposed method from previous works. Numerical experiments performed on a model problem from optimal flow control under uncertainty verify global convergence of the method and demonstrate the method's ability to outperform previously proposed alternatives.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Designing and Testing Broadly-Protective Filoviral Vaccines Optimized for Cytotoxic T-Lymphocyte Epitope Coverage

We report the rational design and in vivo testing of mosaic proteins for a polyvalent pan-filoviral vaccine using a computational strategy designed for the Human Immunodeficiency Virus type 1 (HIV-1) but also appropriate for Hepatitis C virus (HCV) and potentially other diverse viruses. Mosaics are sets of artificial recombinant proteins that are based on natural proteins. The recombinants are computationally selected using a genetic algorithm to optimize the coverage of potential cytotoxic T lymphocyte (CTL) epitopes. Because evolutionary history differs markedly between HIV-1 and filoviruses, we devised an adapted computational technique that is effective for sparsely sampled taxa; our first significant result is that the mosaic technique is effective in creating high-quality mosaic filovirus proteins. The resulting coverage of potential epitopes across filovirus species is superior to coverage by any natural variants, including current vaccine strains with demonstrated cross-reactivity. The mosaic cocktails are also robust: mosaics substantially outperformed natural strains when computationally tested against poorly sampled species and more variable genes. Furthermore, in a computational comparison of cross-reactive potential a design constructed prior to the Bundibugyo outbreak performed nearly as well against all species as an updated design that included Bundibugyo. These points suggest that the mosaic designs would be more resilient than natural-variant vaccines against future Ebola outbreaks dominated by novel viral variants. We demonstrate in vivo immunogenicity and protection against a heterologous challenge in a mouse model. This design work delineates the likely requirements and limitations on broadly-protective filoviral CTL vaccines.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Exploring the Mass-loss Histories of the Red Supergiants

We report mid- to far-infrared imaging and photometry from 7 to 37 μm with SOFIA/FORCAST and 2 μm adaptive optics imaging with LBTI/LMIRCam of a large sample of red supergiants (RSGs) in four Galactic clusters: RSGC1, RSGC2 = Stephenson 2, RSGC3, and NGC 7419. The RSGs in these clusters cover their expected range in luminosity and initial mass from ≈9 to more than 25 M {sub ⊙}. The population includes examples of very late-type RSGs such as MY Cep, which may be near the end of the RSG stage, high-mass-losing maser sources, yellow hypergiants, and post-RSG candidates. Many of the stars and almost all of the most luminous have spectral energy distributions (SEDs) with extended infrared excess radiation at the longest wavelengths. To best model their SEDs, we use the DUSTY code with a variable radial density distribution function to estimate their mass-loss rates. Our M-dot –luminosity relation for 42 RSGs basically follows the classical de Jager curve, but at luminosities below 10{sup 5} L{sub ⊙}, we find a significant population of RSGs with M-dot below the de Jager relation. At luminosities above 10{sup 5} L {sub ⊙}, there is a rapid transition to higher mass-loss rates that approximates and overlaps the de Jager curve. We recommend that instead of using a linear relation or single curve, the empirical M-dot –luminosity relation is better represented by a broad band. Interestingly, the transition to much higher M-dot at about 10{sup 5} L {sub ⊙} corresponds approximately to an initial mass of 18–20 M {sub ⊙}, which is close to the upper limit for RSGs becoming Type II supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Galaxy Merger Candidates in High-redshift Cluster Environments

We compile a sample of spectroscopically and photometrically selected cluster galaxies from four high-redshift galaxy clusters (1.59<z<1.71) from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS), and a comparison field sample selected from the UKIDSS Deep Survey. Using near-infrared imaging from the Hubble Space Telescope, we classify potential mergers involving massive (M{sub ∗}⩾3×10{sup 10} M{sub ⊙}) cluster members by eye, based on morphological properties such as tidal distortions, double nuclei, and projected near neighbors within 20 kpc. With a catalog of 23 spectroscopic and 32 photometric massive cluster members across the four clusters and 65 spectroscopic and 26 photometric comparable field galaxies, we find that after taking into account contamination from interlopers, 11.0{sub −5.6}{sup +7.0}% of the cluster members are involved in potential mergers, compared to 24.7{sub −4.6}{sup +5.3}% of the field galaxies. We see no evidence of merger enhancement in the central cluster environment with respect to the field, suggesting that galaxy–galaxy merging is not a stronger source of galaxy evolution in cluster environments compared to the field at these redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

The purpose of this technical report is to document the efforts to design and test two inlet systems for aerosol sampling suitable for deployment on a medium-sized fixed-wing Uncrewed Aerial System (UAS). This work, which was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, was conducted at the Pacific Northwest National Laboratory (PNNL) for the ARM Aircraft Facility (AAF) starting in November 2017. The current work is a part of AAF efforts to instrument the ArcticShark (a mid-sized UAS owned and operated by the AAF) for atmospheric research and develop a scientific payload for deployment on a similar-sized UAS with minimal adaptation and integration. An aerosol inlet system is necessary to sample and transport ambient air sample to the scientific instrumentation with minimal distortions to the aerosols. Two isokinetic aerosol inlets were designed: the first is a simple passive system for a single instrument suitable to be installed in a wing pylon; the second is a system with active control designed to sample and distribute air among several heterogeneous instruments and to provide basic humidity control of the air sample so that the measured aerosol parameters should correspond to “dry” conditions (a common requirement). Both systems could be easily adapted for deployment on another platform and/or with a different set of instrumentation. Several conducted flight tests showed that the inlets’ performance met our design goals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

42 ENGINEERING↗