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NASA NTRS2023

Evaluation of the Interference of Tenax®TA Adsorbent With Dimethylformamide Dimethyl Acetal Reagent for Gas Chromatography-Dragonfly Mass Spectrometry and Future Gas Chromatography-Mass Spectrometry in Situ Analysis

Among future space missions, national aeronautics and space administration (NASA) selected two of them to analyze the diversity in organic content within Martian and Titan soil samples using a gas chromatograph – mass spectrometer (GC–MS) instrument. The Dragonfly space mission is planned to be launched in 2027 to Titan's surface and explore the Shangri-La surface region for years. One of the main goals of this mission is to understand the past and actual abundant prebiotic chemistry on Titan, which is not well characterized yet. The ExoMars space mission is planned to be launched in 2028 to Mars’ surface and explore the Oxia Planum and Mawrth Vallis region for years. The main objectives focus on the exploration of the subsurface soil samples, potentially richer in organics, that might be relevant for the search of past life traces on Mars where irradiation does not impact the matrices and organics. One recently used sample pre-treatment for gas chromatography – mass spectrometry analysis is planned on both space missions to detect refractory organic molecules of interest for astrobiology. This pre-treatment is called derivatization and uses a chemical reagent – called dimethylformamide dimethyl acetal (DMF-DMA) – to sublimate organic compounds keeping them safe from thermal degradation and conserving the chirality of the molecules extracted from Titan or Mars’ matrices. Indeed, the detection of building blocks of life or enantiomeric excess of some organics (e.g. amino acids) after DMF-DMA pre-treatment and GC–MS analyses would be both bioindicators. The main results highlighted by our work on DMF-DMA and Tenax®TA interaction and efficiency to detect organic compounds at ppb levels in a fast and single preparation are first that Tenax®TA did not show the onset of degradation until after 150 experiments – a 120 h at 300 °C experiment – which greatly exceeds the experimental lifetimes for the DraMS and GC-space in situ investigations. Tenax®TA polymer and DMF-DMA produce many by-products (about 70 and 46, respectively, depending on the activation temperature). Further, the interaction between the two leads to the production of 22 additional by-products from DMF-DMA degradation, but these listed by-products do not prevent the detection of trace-level organic molecules after their efficient derivatization and volatilization by DMF-DMA in the oven ahead the GC–MS trap and column.

DraMS-Dragonfly mission↗

DOE OSTI2013

Failure Impact Analysis of Key Management in AMI Using Cybernomic Situational Assessment (CSA)

In earlier work, we presented a computational framework for quantifying the security of a system in terms of the average loss a stakeholder stands to sustain as a result of threats to the system. We named this system, the Cyberspace Security Econometrics System (CSES). In this paper, we refine the framework and apply it to cryptographic key management within the Advanced Metering Infrastructure (AMI) as an example. The stakeholders, requirements, components, and threats are determined. We then populate the matrices with justified values by addressing the AMI at a higher level, rather than trying to consider every piece of hardware and software involved. We accomplish this task by leveraging the recently established NISTR 7628 guideline for smart grid security. This allowed us to choose the stakeholders, requirements, components, and threats realistically. We reviewed the literature and selected an industry technical working group to select three representative threats from a collection of 29 threats. From this subset, we populate the stakes, dependency, and impact matrices, and the threat vector with realistic numbers. Each Stakeholder s Mean Failure Cost is then computed.

Algorithms↗

DOE OSTI2013

Electrochemically Modulated Separation for Plutonium Safeguards

Accurate and timely analysis of plutonium in spent nuclear fuel is critical in nuclear safeguards for detection of both protracted and rapid plutonium diversions. Gamma spectroscopy is a viable method for accurate and timely measurements of plutonium provided that the plutonium is well separated from the interfering fission and activation products present in spent nuclear fuel. Electrochemically modulated separation (EMS) is a method that has been used successfully to isolate picogram amounts of Pu from nitric acid matrices. With EMS, Pu adsorption may be turned "on" and "off" depending on the applied voltage, allowing for collection and stripping of Pu without the addition of chemical reagents. In this work, we have scaled up the EMS process to isolate microgram quantities of Pu from matrices encountered in spent nuclear fuel during reprocessing. Several challenges have been addressed including surface area limitations, radiolysis effects, electrochemical cell performance stability, and chemical interferences. After these challenges were resolved, 6 µg Pu was deposited in the electrochemical cell with approximately an 800-fold reduction of fission and activation product levels from a spent nuclear fuel sample. Modeling showed that these levels of Pu collection and interference reduction may not be sufficient for Pu detection by gamma spectroscopy. The main remaining challenges are to achieve a more complete Pu isolation and to deposit larger quantities of Pu for successful gamma analysis of Pu. If gamma analyses of Pu are successful, EMS will allow for accurate and timely on-site analysis for enhanced Pu safeguards.

Pratt, Sandra H.↗

DOE OSTI2014

Disposable and removable nucleic acid extraction and purification cartridges for automated flow-through systems

Removable cartridges are used on automated flow-through systems for the purpose of extracting and purifying genetic material from complex matrices. Different types of cartridges are paired with specific automated protocols to concentrate, extract, and purifying pathogenic or human genetic material. Their flow-through nature allows large quantities sample to be processed. Matrices may be filtered using size exclusion and/or affinity filters to concentrate the pathogen of interest. Lysed material is ultimately passed through a filter to remove the insoluble material before the soluble genetic material is delivered past a silica-like membrane that binds the genetic material, where it is washed, dried, and eluted. Cartridges are inserted into the housing areas of flow-through automated instruments, which are equipped with sensors to ensure proper placement and usage of the cartridges. Properly inserted cartridges create fluid- and air-tight seals with the flow lines of an automated instrument.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

The Cementitious Barriers Partnership Experimental Programs and Software Advancing DOE’s Waste Disposal/Tank Closure Efforts – 15436

The U.S. Department of Energy Environmental Management (DOE-EM) Office of Tank Waste Management-sponsored Cementitious Barriers Partnership (CBP) is chartered with providing the technical basis for implementing cement-based waste forms and radioactive waste containment structures for long-term disposal. DOE needs in this area include the following to support progress in final treatment and disposal of legacy waste and closure of High-Level Waste (HLW) tanks in the DOE complex: long-term performance predictions, flow sheet development and flow sheet enhancements, and conceptual designs for new disposal facilities. The DOE-EM Cementitious Barriers Partnership is producing software and experimental programs resulting in new methods and data needed for end-users involved with environmental cleanup and waste disposal. Both the modeling tools and the experimental data have already benefited the DOE sites in the areas of performance assessments by increasing confidence backed up with modeling support, leaching methods, and transport properties developed for actual DOE materials. In 2014, the CBP Partnership released the CBP Software Toolbox –“Version 2.0” which provides concrete degradation models for 1) sulfate attack, 2) carbonation, and 3) chloride initiated rebar corrosion, and includes constituent leaching. These models are applicable and can be used by both DOE and the Nuclear Regulatory Commission (NRC) for service life and long-term performance evaluations and predictions of nuclear and radioactive waste containment structures across the DOE complex, including future SRS Saltstone and HLW tank performance assessments and special analyses, Hanford site HLW tank closure projects and other projects in which cementitious barriers are required, the Advanced Simulation Capability for Environmental Management (ASCEM) project which requires source terms from cementitious containment structures as input to their flow simulations, regulatory reviews of DOE performance assessments, and Nuclear Regulatory Commission reviews of commercial nuclear power plant (NPP) structures which are part of the overall US Energy Security program to extend the service life of NPPs. In addition, the CBP experimental programs have had a significant impact on the DOE complex by providing specific data unique to DOE sodium salt wastes at Hanford and SRS which are not readily available in the literature. Two recent experimental programs on cementitious phase characterization and on technetium (Tc) mobility have provided significant conclusions as follows: recent mineralogy characterization discussed in this paper illustrates that sodium salt waste form matrices are somewhat similar to but not the same as those found in blended cement matrices which to date have been used in long-term thermodynamic modeling and contaminant sequestration as a first approximation. Utilizing the CBP generated data in long-term performance predictions provides for a more defensible technical basis in performance evaluations. In addition, recent experimental studies related to technetium mobility indicate that conventional leaching protocols may not be conservative for direct disposal of Tc-containing waste forms in vadose zone environments. These results have the potential to influence the current Hanford supplemental waste treatment flow sheet and disposal conceptual design.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Supervised Gamma Process Poisson Factorization

This thesis develops the supervised gamma process Poisson factorization (S- GPPF) framework, a novel supervised topic model for joint modeling of count matrices and document labels. S-GPPF is fully generative and nonparametric: document labels and count matrices are modeled under a uni ed probabilistic framework and the number of latent topics is controlled automatically via a gamma process prior. The framework provides for multi-class classification of documents using a generative max-margin classifier. Several recent data augmentation techniques are leveraged to provide for exact inference using a Gibbs sampling scheme. The first portion of this thesis reviews supervised topic modeling and several key mathematical devices used in the formulation of S-GPPF. The thesis then introduces the S-GPPF generative model and derives the conditional posterior distributions of the latent variables for posterior inference via Gibbs sampling. The S-GPPF is shown to exhibit state-of-the-art performance for joint topic modeling and document classification on a dataset of conference abstracts, beating out competing supervised topic models. The unique properties of S-GPPF along with its competitive performance make it a novel contribution to supervised topic modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Nano-Composite Material Development for 3-D Printers

Graphene possesses excellent mechanical properties with a tensile strength that may exceed 130 GPa, excellent electrical conductivity, and good thermal properties. Future nano-composites can leverage many of these material properties in an attempt to build designer materials for a broad range of applications. 3-D printing has also seen vast improvements in recent years that have allowed many companies and individuals to realize rapid prototyping for relatively low capital investment. This research sought to create a graphene reinforced, polymer matrix nano-composite that is viable in commercial 3D printer technology, study the effects of ultra-high loading percentages of graphene in polymer matrices and determine the functional upper limit for loading. Loadings varied from 5 wt. % to 50 wt. % graphene nanopowder loaded in Acrylonitrile Butadiene Styrene (ABS) matrices. Loaded sample were characterized for their mechanical properties using three point bending, tensile tests, as well as dynamic mechanical analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Smisc - A collection of miscellaneous functions

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAs d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).

Landon Sego, PNNL↗

DOE OSTI2016

A Bayesian approach to multivariate measurement system assessment

This article considers system assessment for multivariate measurements and presents a Bayesian approach to analyzing gauge R&R study data. The evaluation of variances for univariate measurement becomes the evaluation of covariance matrices for multivariate measurements. The Bayesian approach ensures positive definite estimates of the covariance matrices and easily provides their uncertainty. Furthermore, various measurement system assessment criteria are easily evaluated. The approach is illustrated with data from a real gauge R&R study as well as simulated data.

random effects↗

DOE OSTI2010

Teko v. 1.0

Teko is a C++ library for implementation of blocked and segregated preconditioners in the context of iterative solvers for linear systems. Capabilities for decomposing larger matrices into user defined sub blocks are also provided. Additional functionality for creating approximate inverse operators utilizing solver and preconditioning packages in the Trilinos framework has also been implemented. Teko's primary application is in multiphysics simulation environment where a decomposition of the linear system in to physically meaningful blocks can be utilized to enhance performance of an iterative solver. However, applicability may extend to other problem domains where matrices can be decomposed into meaningful blocks.

Cyr, Eric↗

DOE OSTI2016

Merced

Merced performs a multi-dimensional integral tl generate so-called 'transfer matrices' for use in deterministic radiation transport applications. It produces transfer matrices on the user-defind energy grid. The angular dependence of outgoing products is captured in a Legendre expansion, up to a user-specified maximun Legendre order. Merced calculations can use multi-threading for enhanced performance on a single compute node.

Hedstrom, Gerald↗

DOE OSTI2016

Variational Nodal 2D/1D Transport/Diffusion Solutions of the C5G7 Benchmark Problems

This work is the continuation of our effort to generalize the variational nodal method (VNM) for application to pin resolved whole-core PWR problems. To this end, a 2D/1D VNM method without spatial homogenization is formulated and implemented in the PANX code. We employ diffusion theory in the axial direction combined with two-dimensional transport in the x-y plane. In our initial work, we employed the standard spherical harmonics method. To increase accuracy and reduce computational effort, we present two refinements: First, the even-parity integral method within the nodes reduces the computational effort required to form the response matrices. Second, the use of quasi-reflected interface conditions reduces the dimension of the resulting response matrices and therefore the CPU time required to solve the equations. We apply the method to the three-dimensional, unrodded C5G7 benchmark problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Design of a One-Dimensional Sextupole Using Semi-Analytic Methods

Sextupole magnets provide position-dependent momentum kicks and are tuned to provide the correct kicks to parti- cles within a small acceptance region in phase space. Sextupoles are useful and even necessary in circular accelerators for chromaticity corrections. They are routinely used in most rings, i.e. CESR. Although sextupole magnets are necessary for particle energy corrections, they also have undesirable effects on dynamic aperture, especially because of their non- linear coupling term in the momentum kick. Studies of integrable systems suggest that there is an analytic way to create transport lattices with specific transfer matrices that limit the momentum kick to one dimension. A one-dimension sex- tupole is needed for chromaticity corrections: a horizontal sextupole for horizontal bending magnets. We know how to make a “composite” horizontal sextupole using regular 2D sextupoles and linear transfer matrices in an ideal thin-lens approximation. Thus, one could create an accelerator lattice using linear elements, in series with sextupole magnets to create a “1D sextupole”. This paper describes progress to- wards realizing a realistic focusing lattice resulting in a 1D sextupole.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

The Role of Anisotropy on the Self-Organization of Gas Bubble Superlattice

Self-organization of nanoscale void/gas bubble superlattices has been widely observed in irradiation experiments however yet to be well understood. The recent discovery of incoherent face-centered-cubic (fcc) Xe bubble lattice in body-centered-cubic (bcc) UMo challenges the widely accepted coherency between superlattices and matrices. A complete mechanistic understanding of bubble lattice self-organization may have a large impact to materials science and nuclear energy advancement, and is the objective of this project. The knowledge obtained through a coherent integration of experimental and computational approach will advance the current understanding of self-organization mechanisms of nanostructures under irradiation. To realize this goal, two appealing self-organization mechanisms previously proposed in open literatures have been identified: anisotropic elastic interaction between voids and kinetic anisotropy such as one-dimensional (1D) self-interstitial atoms (SIA) diffusion. For the first year, the focus is on the effect 1D diffusion using bcc Mo and W, with the former being elastically anisotropic while the latter isotropic. Efforts have been made to investigate the fundamental interaction between inert gas and metal matrices, the mechanism for void/bubble superlattice formation and their stabilities under irradiation and annealing, and the experimental conditions for bubble superlattice formation and evolution, and to establish advanced characterization techniques for bubble superlattice.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Continuous energy cross section adjustment: a new method to generalize nuclear data assimilation for a wider range of applications.

This work presents a new method to perform continuous-energy cross section adjustment. The proposed method is based on recently developed Monte Carlo perturbation capabilities with continuous-energy sensitivity functions implemented in an extended Serpent version. The generation of continuous energy basis functions aseigendecomposition of the covariance matrices and the Generalized Least Squares method applied to these functions are described. The new approach is verified against standard, multi-group adjustment methodologies in a case study involving four different response functions in Jezebel. The results obtained by the two approaches for the selected case study are presented and compared in term of adjusted cross sections, adjusted covariance matrices, and uncertainty reduction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

AGR Irradiated Specimen Air/Moisture Heating Test Plan

The Advanced Gas Reactor (AGR) program has a need to perform high-temperature oxidation testing of tristructural isotropic (TRISO)-coated particle fuel and reactor core materials to evaluate their performance under conditions relevant to air- and moisture-ingress events in high-temperature gas-cooled reactors (HTGRs). The objectives of these tests are to assess the impact of oxidizing environments on fission product release from exposed fuel kernels, compact matrix, and nuclear grade graphite, and to determine the impact of oxidizing environments on TRISO coating integrity. The program is currently developing a capability for testing irradiated fuel, matrix, and graphite specimens inside a hot cell. The Air/Moisture Ingress Experiment (AMIX) system will be capable of temperatures up to 1650°C in atmospheres containing oxygen or moisture with varying concentrations. The system will be capable of collecting fission gases as well as condensable fission products, in order to quantify total released inventory from the heated specimens. A basis for establishing experimental test matrices, and the test matrices themselves, are presented in this document. This includes considerations on specific objectives for the tests, types of oxidizing environments that should be tested, and the expected availability of irradiated specimens from the various AGR program irradiation experiments. This document only briefly discusses post-test analysis of the heated specimens, and it is recognized that in many cases the post-test analysis may be extensive. It is expected that this will be a “living” document, subject to revision as data are collected and scoping calculations are performed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Study on Fracture of Fiber-Reinforced Polymeric Composites Using Spiral Notch Torsion Test

Fiber-reinforced polymer-matrix composites have been widely applied in various areas due to their excellent mechanical properties. In this study, carbon fiber-reinforced polymer-matrix composites and glass fiber-reinforced polymer-matrix composites failure tests under quasi static torsion have been demonstrated by using spiral notch torsion test methodology. Three types of cylindrical specimens with different fiber orientations were prepared and tested. For both composites, after increase stage, A type exhibited limited stress variations before the sudden failure, whereas B type showed gradual failure with torque drops. Displacement contours, stress contours and energy release rates were acquired using the anisotropic elastic finite element models. Microscopic characterization exhibited that the failure of A type occurred along interfaces between fibers and matrices, whereas circular cracks in B type propagated alternatively between polymeric matrices and interfaces. Type C failure is similar to type A whereas with a curvature observed on the fracture surface.

Du, Fen↗