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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Implementation of Software Tools for Hybrid Control Rooms in the Human Systems Simulation Laboratory

The Institute for Energy Technology (IFE) and Idaho National Laboratory have designed, implemented, tested and installed a functioning prototype of a set of large screen overview and procedure support displays for the Generic Pressurized Water Reactor (GPWR) simulator in the U.S. Department of Energy’s Human Systems Simulation Laboratory. The overview display is based on IFE’s extensive experiences with large screen overview displays in the Halden Man-Machine Laboratory (HAMMLAB), and presents the main control room indicators on a combined three-screen display. The procedure support displays are designed and implemented to provide a compact but still comprehensive overview of the relevant process measurements and indicators to support operators' good situational awareness during the performance of various types of procedures and plant conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Fragment-based {sup 13}C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

We assess the quality of fragment-based ab initio isotropic {sup 13}C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic {sup 13}C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

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

CRPropa 3.1—a low energy extension based on stochastic differential equations

The propagation of charged cosmic rays through the Galactic environment influences all aspects of the observation at Earth. Energy spectrum, composition and arrival directions are changed due to deflections in magnetic fields and interactions with the interstellar medium. Today the transport is simulated with different simulation methods either based on the solution of a transport equation (multi-particle picture) or a solution of an equation of motion (single-particle picture). We developed a new module for the publicly available propagation software CRPropa 3.1, where we implemented an algorithm to solve the transport equation using stochastic differential equations. This technique allows us to use a diffusion tensor which is anisotropic with respect to an arbitrary magnetic background field. The source code of CRPropa is written in C++ with python steering via SWIG which makes it easy to use and computationally fast. In this paper, we present the new low-energy propagation code together with validation procedures that are developed to proof the accuracy of the new implementation. Furthermore, we show first examples of the cosmic ray density evolution, which depends strongly on the ratio of the parallel κ{sub ∥} and perpendicular κ{sub ⊥} diffusion coefficients. This dependency is systematically examined as well the influence of the particle rigidity on the diffusion process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Steady-State Thermal-Hydraulic Analysis and Bowing Reactivity Evaluation Methods Based on Neutron and Gamma Transport Calculations

With the advancement of computer technology, the variational nodal transport code VARIANT is now routinely used for sodium-cooled fast reactor (SFR) design analysis. In particular, VARIANT transport calculations are usually performed for whole core neutronics analyses and for fuel cycle analyses with REBUS-3. However, the steady-state thermal hydraulics analysis with the SE2-ANL coed and the assembly bowing reactivity calculation with the structural analysis with the NUBOW-3D code are still performed with the DIF3D finite difference diffusion theory code. Furthermore, the DIF3D diffusion calculation for these applications is performed with only six triangular meshes per hexagonal assembly, and the SE2-ANL code determines the pin power distributions approximately by assuming that the power distribution within an assembly is separable in the radial and axial directions. In order to overcome the limitations and to improve the accuracy of the existing methods, it was proposed to develop the relevant computational methods based on the transport calculations with the VARIANT and PROTEUS-SN codes. The objectives of this study are to develop a new heating calculation method based on the coupled neutron and gamma transport calculations with VARIANT, to implement the new heating calculation method into the SE2-ANL steady-state thermal-hydraulics analysis code with improved numerical algorithms and additional capabilities for automatic flow allocation calculations, and to develop a method to calculate bowing reactivity coefficients based on the VARIANT core solutions and the PROTEUS-SN assembly solutions, which can be used in NUBOW-3D calculations. A new, coupled neutron and gamma heating calculation procedure has been developed based on VARIANT transport calculations. In the new heating calculation procedure, the neutron flux distribution is first determined by solving an eigenvalue transport problem using the VARIANT transport code. Using the calculated neutron flux, the intra-nodal gamma source distributions are calculated to be consistent with the neutron flux distribution with the GAMSOR code. For this, the GAMSOR code has been updated to generate the intra-nodal gamma source distributions in the form of the VARSRC dataset of VARIANT. With this gamma source distribution, the gamma flux distribution is determined by solving a fixed source gamma transport problem using VARIANT again. With the neutron and gamma flux distributions, the heat generation rates are evaluated at individual fuel pins and assembly duct walls, without assuming separable axial and radial profiles for the intra-assembly power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Large-Scale Inference of Multivariate Regression for Heavy-Tailed and Asymmetric Data

Large-scale multivariate regression is a fundamental statistical tool with a wide range of applications. Here, this study considers the problem of simultaneously testing a large number of general linear hypotheses, encompassing covariate-effect analysis, analysis of variance, and model comparisons. The challenge that accompanies a large number of tests is the ubiquitous presence of heavy-tailed and/or highly skewed measurement noise, which is the main reason for the failure of conventional least squares-based methods. For large-scale multivariate regression, we develop a set of robust inference methods to explore data features such as heavy tailedness and skewness, which are not visible to least squares methods. The new testing procedure is based on the data-adaptive Huber regression and a new covariance estimator of regression estimates. Under mild conditions, we show that our methods produce consistent estimates of the false discovery proportion. Extensive numerical experiments and an empirical study on quantitative linguistics demonstrate the advantage of the proposed method over many state-of-the-art methods when the data are generated from heavy-tailed and/or skewed distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-100: Development and Implementation of a Treatment Planning Tracking System Into the Radiation Oncology Clinic

Purpose: With increasing numbers of cancer patients being diagnosed and the complexity of radiotherapy treatments rising it’s paramount that patient plan development continues to stay fluid within the clinic. In order to maintain a high standard of care and clinical efficiency the establishment of a tracking system for patient plan development allows healthcare providers to view real time plan progression and drive clinical workflow. In addition, it provides statistical datasets which can further identify inefficiencies within the clinic. Methods: An application was developed utilizing Microsoft’s ODBC SQL database engine to track patient plan status throughout the treatment planning process while also managing key factors pertaining to the patient’s treatment. Pertinent information is accessible to staff in many locations, including tracking monitors within dosimetry, the clinic network for both computers and handheld devices, and through email notifications. Plans are initiated with a CT and continually tracked through planning stages until final approval by staff. Patient’s status is dynamically updated by the physicians, dosimetrists, and medical physicists based on the stage of the patient’s plan. Results: Our application has been running over a six month period with all patients being processed through the system. Modifications have been made to allow for new features to be implemented along with additional tracking parameters. Based on in-house feedback, the application has been supportive in streamlining patient plans through the treatment planning process and data has been accumulating to further improve procedures within the clinic. Conclusion: Over time the clinic will continue to track data with this application. As data accumulates the clinic will be able to highlight inefficiencies within the workflow and adapt accordingly. We will add in new features to help support the treatment planning process in the future.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

The reliability of computational fluid dynamics (CFD) codes is checked by comparing simulations with experimental data. A typical data set consists chiefly of velocity and temperature readings, both ideally having high spatial and temporal resolution to facilitate rigorous code validation. While high resolution velocity data is readily obtained through optical measurement techniques such as particle image velocimetry, it has proven difficult to obtain temperature data with similar resolution. Traditional sensors such as thermocouples cannot fill this role, but the recent development of distributed sensing based on Rayleigh scattering and swept-wave interferometry offers resolution suitable for CFD code validation work. Thousands of temperature measurements can be generated along a single thin optical fiber at hundreds of Hertz. Sensors function over large temperature ranges and within opaque fluids where optical techniques are unsuitable. But this type of sensor is sensitive to strain and humidity as well as temperature and so accuracy is affected by handling, vibration, and shifts in relative humidity. Such behavior is quite unlike traditional sensors and so unconventional installation and operating procedures are necessary to ensure accurate measurements. This paper demonstrates implementation of a Rayleigh scattering-type distributed temperature sensor in a thermal mixing experiment involving two air jets at 25 and 45 °C. We present criteria to guide selection of optical fiber for the sensor and describe installation setup for a jet mixing experiment. We illustrate sensor baselining, which links readings to an absolute temperature standard, and discuss practical issues such as errors due to flow-induced vibration. This material can aid those interested in temperature measurements having high data density and bandwidth for fluid dynamics experiments and similar applications. We highlight pitfalls specific to these sensors for consideration in experiment design and operation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Status of the data acquisition, trigger, and slow control systems of the Mu2e experiment at Fermilab

The Mu2e experiment at the Fermilab will search for a coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. In this work, the Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq framework as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates several framework components — an artdaq-based DAQ, an art-based event processing, and an EPICS-based detector control system (DCS), and provides a uniform multi-user interface to its components through a web browser. Data streams from the Mu2e tracker and calorimeter are handled by the artdaq-based DAQ and processed by a one-level software trigger implemented within the art framework. Events accepted by the trigger have their data combined, post-trigger, with the separately read out data from the Mu2e Cosmic Ray Veto system. Foundation of the Mu2e DCS, EPICS – an Experimental Physics and Industrial Control System – is an open-source platform for monitoring, controlling, alarming, and archiving. A prototype of the TDAQ and the DCS systems has been built and tested over the last three years at Fermilab’s Feynman Computing Center, and now the production system installation is underway. This work presents their status and focus on the installation plans and procedures for racks, workstations, network switches, gateway computers, DAQ hardware, slow controls implementation, and testing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Mechanisms of sequential particle transfer and characteristics of light neutron-excess and oriented nuclei

The procedure for evaluating the second-order corrections to the matrix elements of the reaction A(x, y)B, which are obtained using the method of distorted waves with a finite radius of intercluster interaction (DWBAFR), is developed. It is based on the assumption of a virtual cluster structure of light nuclei and uses integral equations for a four-body problem in the Alt-Grassberger-Sandhas formalism. These corrections are related with the mechanisms of sequential particles transfer. The latter are represented by the quadrangle diagrams. Their matrix elements are summed up coherently with those given by the pole and triangle diagrams which were calculated by using DWBAFR. The computer code QUADRO is written for the numerical implementation of the method proposed. The statistical tensors of nucleus B formed in the reaction A(x, y)B at incident particle energies of about 10 MeV/nucleon in the center of mass frame are determined. Specific calculations allowed for description of both the experimental cross sections (0-rank statistical tensors) of various reactions (including those where nucleus B has some excess neutrons) and polarized characteristics of nucleus B* (in the case of the latter produced in the exited state). A two-neutron periphery of nuclei {sup 6}He, {sup 10}Be, {sup 12}B (both in dineutron and cigarlike configurations) is restored by analyzing the differential cross sections of elastic alpha-6He-scattering and {sup 9}Be(d, p){sup 10}Be and {sup 10}B(t, p){sup 12}B reactions. It is shown that the structure of neutron peripheries is fundamentally different for these nuclei and its feature depends on the way those neutron-excess nuclei are formed: in {sup 6}He both configurations contribute to a two-neutron halo, while in {sup 10}Be there is a barely noticeable one-neutron halo, and in {sup 12}B there is a “dineutron skin”. Orientation characteristics of nuclei B* are calculated. Their comparison with experimental data made it possible to draw important conclusions about a contribution to the statistical tensors of nucleus B* coming from the two-step mechanisms and its impact on the properties of oriented light nuclei, including their polarization. Finally, a simplified method for calculating the matrix elements of mechanisms, which take into account sequential particle transfer, is proposed. It is demonstrated to be correct by evaluating a contribution of the corresponding corrections to the total amplitude of the reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Symmetry reduction of tensor networks in many-body theory: I. Automated symbolic evaluation of SU(2) algebra

Abstract The ongoing progress in (nuclear) many-body theory is accompanied by an ever-rising increase in complexity of the underlying formalisms used to solve the stationary Schrödinger equation. The associated working equations at play in state-of-the-art ab initio nuclear many-body methods can be analytically reduced with respect to angular-momentum, i.e. SU (2), quantum numbers whenever they are effectively employed in a symmetry-restricted context. The corresponding procedure constitutes a tedious and error-prone but yet an integral part of the implementation of those many-body frameworks. Indeed, this symmetry reduction is a key step to advance modern simulations to higher accuracy since the use of symmetry-adapted tensors can decrease the computational complexity by orders of magnitude. While attempts have been made in the past to automate the (anti-) commutation rules linked to Fermionic and Bosonic algebras at play in the derivation of the working equations, there is no systematic account to achieve the same goal for their symmetry reduction. In this work, the first version of an automated tool performing graph-theory-based angular-momentum reduction is presented. Taking the symmetry-unrestricted expressions of a generic tensor network as an input, the code provides their angular-momentum-reduced form in an error-safe way in a matter of seconds. Several state-of-the-art many-body methods serve as examples to demonstrate the generality of the approach and to highlight the potential impact on the many-body community.

Tichai, A.↗
DOE OSTI2012

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for path way and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Development of a New 47-Group Library for the CASL Neutronics Simulators

The CASL core simulator MPACT is under development for the neutronics and thermal-hydraulics coupled simulation for the pressurized light water reactors. The key characteristics of the MPACT code include a subgroup method for resonance self-shielding, and a whole core solver with a 1D/2D synthesis method. The ORNL AMPX/SCALE code packages have been significantly improved to support various intermediate resonance self-shielding approximations such as the subgroup and embedded self-shielding methods. New 47-group AMPX and MPACT libraries based on ENDF/B-VII.0 have been generated for the CASL core simulator MPACT of which group structure comes from the HELIOS library. The new 47-group MPACT library includes all nuclear data required for static and transient core simulations. This study discusses a detailed procedure to generate the 47-group AMPX and MPACT libraries and benchmark results for the VERA progression problems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Core loading pattern optimization of thorium fueled heavy water breeder reactor using genetic algorithm

In this work genetic algorithm was proposed to solve fuel loading pattern optimization problem in thorium fueled heavy water reactor. The objective function of optimization was to maximize the conversion ratio and minimize power peaking factor. Those objectives were simultaneously optimized using non-dominated Pareto-based population ranking optimal method. Members of non-dominated population were assigned selection probabilities based on their rankings in a manner similar to Baker's single criterion ranking selection procedure. A selected non-dominated member was bred through simple mutation or one-point crossover process to produce a new member. The genetic algorithm program was developed in FORTRAN 90 while neutronic calculation and analysis was done by COREBN code, a module of core burn-up calculation for SRAC. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Autonomous and dynamic precursor selection for solid-state materials synthesis

Abstract Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and conditions to be tested. Here we introduce an algorithm (ARROWS 3 ) designed to automate the selection of optimal precursors for solid-state materials synthesis. This algorithm actively learns from experimental outcomes to determine which precursors lead to unfavorable reactions that form highly stable intermediates, preventing the target material’s formation. Based on this information, ARROWS 3 proposes new experiments using precursors it predicts to avoid such intermediates, thereby retaining a larger thermodynamic driving force to form the target. We validate this approach on three experimental datasets, containing results from over 200 synthesis procedures. In comparison to black-box optimization, ARROWS 3 identifies effective precursor sets for each target while requiring substantially fewer experimental iterations. These findings highlight the importance of domain knowledge in optimization algorithms for materials synthesis, which are critical for the development of fully autonomous research platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Prediction of atomization energy using graph kernel and active learning

Data-driven prediction of molecular properties presents unique challenges to the design of machine learning methods concerning data structure/dimensionality, symmetry adaption, and confidence management. In this paper, we present a kernel-based pipeline that can learn and predict the atomization energy of molecules with high accuracy. The framework employs Gaussian process regression to perform predictions based on the similarity between molecules, which is computed using the marginalized graph kernel. To apply the marginalized graph kernel, a spatial adjacency rule is first employed to convert molecules into graphs whose vertices and edges are labeled by elements and interatomic distances, respectively. We then derive formulas for the efficient evaluation of the kernel. Specific functional components for the marginalized graph kernel are proposed, while the effects of the associated hyperparameters on accuracy and predictive confidence are examined. We show that the graph kernel is particularly suitable for predicting extensive properties because its convolutional structure coincides with that of the covariance formula between sums of random variables. Using an active learning procedure, we demonstrate that the proposed method can achieve a mean absolute error of 0.62 ± 0.01 kcal/mol using as few as 2000 training samples on the QM7 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

STAR-CCM+ Verification and Validation Plan

The commercial Computational Fluid Dynamics (CFD) code STAR-CCM+ provides general purpose finite volume method solutions for fluid dynamics and energy transport. This document defines plans for verification and validation (V&V) of the base code and models implemented within the code by the Consortium for Advanced Simulation of Light water reactors (CASL). The software quality assurance activities described herein are port of the overall software life cycle defined in the CASL Software Quality Assurance (SQA) Plan [Sieger, 2015]. STAR-CCM+ serves as the principal foundation for development of an advanced predictive multi-phase boiling simulation capability within CASL. The CASL Thermal Hydraulics Methods (THM) team develops advanced closure models required to describe the subgrid-resolution behavior of secondary fluids or fluid phases in multiphase boiling flows within the Eulerian-Eulerian framework of the code. These include wall heat partitioning models that describe the formation of vapor on the surface and the forces the define bubble/droplet dynamic motion. The CASL models are implemented as user coding or field functions within the general framework of the code. This report defines procedures and requirements for V&V of the multi-phase CFD capability developed by CASL THM. Results of V&V evaluations will be documented in a separate STAR-CCM+ V&V assessment report. This report is expected to be a living document and will be updated as additional validation cases are identified and adopted as part of the CASL THM V&V suite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Application Note: Mixed Signal Simulation with Xyce™ 7.1

This application note describes how Release 7.1 of the Xyce circuit simulator can be coupled with external simulators via either a Python-based interface that leverages the Python ctypes foreign function library or via the Verilog Procedural Interface (VPI). It also documents the usage of these interfaces on RHEL7 with Python 2.6 or 2.7. These interfaces are still under development and may change in the future. So, a key purpose of this application note is to solicit feedback on these interfaces from both internal Sandia Xyce users and other performers on the DARPA Posh Open Source Hardware (POSH) program.

97 MATHEMATICS AND COMPUTING↗