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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

MADSpython 1.x

MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data- and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.

O'Malley, Daniel↗
DOE OSTI2025

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization algorithm that requires derivative information. Other UP methods often used for optimization under uncertainty (OUU) can be designed to work within an established constrained optimization framework. Methods of UP are evaluated in this study including iterative sampling approaches, first‐order approximations, and surrogate modeling with machine learning (ML). A method of dimensional reduction based on global sensitivity analysis is introduced to support the UP methods for the large dimensionality of the problem. Analytical UP methods able to achieve similar optimums 10 times faster than the baseline MC approach, and produce 93.9% similar output distributions are reported.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Efficient rolling texture predictions and texture-sensitive properties of α-uranium foils

Here, finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favors one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a final recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of the thermal expansion and elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Weakly supervised anomaly detection for resonant new physics in the dijet final state using proton-proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

An anomaly detection search for narrow-width resonances beyond the Standard Model that decay into a pair of jets is presented. The search is based on 139 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded during 2015–2018 with the ATLAS detector at the Large Hadron Collider. The analysis is optimized without a particular signal model and aims to be sensitive to a broad range of new physics. It uses two different machine learning strategies to estimate the background in different signal regions. In each region, a weakly supervised classifier is trained to distinguish this background model from data. The analysis focuses on events with high transverse momentum jets reconstructed as large-radius jets. The mass and substructure of these jets are used as inputs to the classifiers. After a classifier-based selection, the distribution of the invariant mass of the two jets is used to search for potential local excesses. The model-independent results of both the anomaly detection methods show no signs of significant local excesses. In addition to model-independent results, a representative set of signal models is injected into the data, and the sensitivity of the methods to these scenarios is reported.

Aad, G. [Aix-Marseille Université] (ORCID:00000002↗
DOE OSTI2015

Sensitivity Analysis of OECD Benchmark Tests in BISON

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on sensitivity analysis of a fuels performance benchmark problem. The benchmark problem was defined by the Uncertainty Analysis in Modeling working group of the Nuclear Science Committee, part of the Nuclear Energy Agency of the Organization for Economic Cooperation and Development (OECD ). The benchmark problem involv ed steady - state behavior of a fuel pin in a Pressurized Water Reactor (PWR). The problem was created in the BISON Fuels Performance code. Dakota was used to generate and analyze 300 samples of 17 input parameters defining core boundary conditions, manuf acturing tolerances , and fuel properties. There were 24 responses of interest, including fuel centerline temperatures at a variety of locations and burnup levels, fission gas released, axial elongation of the fuel pin, etc. Pearson and Spearman correlatio n coefficients and Sobol' variance - based indices were used to perform the sensitivity analysis. This report summarizes the process and presents results from this study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Machine Learning-Guided Optimization of SABRE Hyperpolarization for α-Ketoglutarate in Acetone–Water

Signal amplification by reversible exchange (SABRE) is a hyperpolarization method that polarizes target nuclei of metabolites quickly and efficiently. Recent SABRE advances, including Ace-SABRE, yield biocompatible, aqueous solutions of hyperpolarized markers for metabolic monitoring. Building on recent advancements, expanding the substrate scope of Ace-SABRE is desirable. However, SABRE polarization is sensitive to many different parameters; therefore, traditional optimization approaches are experimentally time-consuming. In this proof-of-concept application of machine learning (ML), Bayesian optimization (BO) is used for four important input parameters to model the complex SABRE dynamics while saving experimental time. The presented ML model also provides chemical insights that enable predictions of sample compositions for increased polarization levels. In this paper, we transition from an original average free polarization of p = ∼0.90% to a maximum observed free polarization of p = ∼6.6% for 1- 13 C alpha-ketoglutarate (AKG) with 13 C at natural abundance, utilizing both direct outputs as well as chemical insights revealed by the ML model.

Catalysts↗
DOE OSTI2022

Bounds of linear time‐varying systems with applications to quantify model gap of synchronous generators

Abstract Linear time‐varying (LTV) systems play a key role in many engineering problems, for example, trajectory sensitivity analysis of power systems. Because LTV systems do not generally have closed‐form solutions, estimates of their bounds are crucial to their analysis. In this paper, bounds for LTV systems with known inputs and unknown but bounded inputs are obtained via Grönwall's inequality. The estimated bounds are then used to quantify the gap between synchronous generators and their models in different scenarios through simulation.

42 ENGINEERING↗
DOE OSTI2023

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗
DOE OSTI2024

Infrared-safe energy weighting does not guarantee small nonperturbative effects

Infrared and collinear (IRC) safety has long been used a proxy for robustness when developing new jet substructure observables. This guiding philosophy has been carried into the deep learning era, where IRC-safe neural networks have been used for many jet studies. For graph-based neural networks, the most straightforward way to achieve IRC safety is to weight particle inputs by their energies. However, energy-weighting by itself does not guarantee that perturbative calculations of machine-learned observables will enjoy small nonperturbative corrections. Here, in this paper, we demonstrate the sensitivity of IRC-safe networks to nonperturbative effects, by training an energy flow network (EFN) to maximize its sensitivity to hadronization. We then show how to construct Lipschitz energy flow networks (L-EFNs), which are both IRC safe and relatively insensitive to nonperturbative corrections. We demonstrate the performance of L-EFNs on generated samples of quark and gluon jets, and showcase fascinating differences between the learned latent representations of EFNs and L-EFNs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗
DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗
DOE OSTI2013

Project X: Accelerator Reference Design

Project X is a high-intensity proton facility being developed to support a world-leading program of Intensity Frontier physics over the next two decades at Fermilab. Project X is an integral part of the U.S. Intensity Frontier Roadmap as described in the P5 report of May 2008 [1] and within the Fermilab Strategic Plan of November 2011 [2]. This document represents Part I of the “Project X Book” describing the Project X accelerator facility and the broad range of physics research opportunities enabled by Project X. Parts II and III provide in-depth descriptions of the physics research program, both within and beyond particle physics [3]. The primary elements of the U.S. program to be supported by Project X include: Neutrino Experiments: Experimental studies of neutrino oscillations and neutrino interaction physics with ultra-intense neutrino beams provided by a high-power proton source with energies up to 120 GeV, utilizing near detectors at the Fermilab site and massive detectors at distant underground laboratories. Goal: At least 2 MW of proton beam power at any energy between 60 to 120 GeV; several hundred kW of proton beam power on target at 8 GeV. Kaon, Muon, Nucleon, and Neutron Precision Experiments: World-leading experiments studying ultra-rare kaon decays, searching for muon-to-electron conversion and nuclear electron dipole moments (EDMs), and exploring neutron properties at very high precision. Goal: MW-class proton beams supporting multiple experiments at 1 and 3 GeV, with flexible capability for providing distinct beam formats to concurrent users while allowing simultaneous operations with the neutrino program. Material Science and Nuclear Energy Applications: High-intensity accelerator, spallation, target and transmutation technology demonstrations will provide critical input into the design of future energy systems, including next generation fission reactors, nuclear waste transmutation systems and future thorium fuel-cycle power systems. Possible applications of muon spin rotation techniques provide sensitive probes of the magnetic structure of materials. Goal: Provide MW-class proton beams at 1 GeV, coupled with novel targets required to support a broad range of materials science and energy applications. Platform for Evolution to Future Frontier Facilities: A high-intensity proton source will strengthen and modernize the Fermilab injector complex, providing a robust platform upon which to build future frontier facilities. The Neutrino Factory and Muon Collider are examples that would provide world-leading capabilities at the Intensity and Energy Frontiers for many decades to come. Goal: Provide a straightforward upgrade path for a 4 MW, low-duty-factor source of protons at energies between 5 and 15 GeV. These four elements are expected to form the basis of the Mission Need statement required for the Department of Energy (DOE) Critical Decision 0 (CD-0), and represent the fundamental design criteria for Project X. The following chapters present the Reference Design for the Project X accelerator facility. The Reference Design is based on a continuous wave (CW) superconducting (SC) linac providing up to 1 and 3 MW of beam power at 1 and 3 GeV respectively. A pulsed linac provides acceleration of roughly 4% of the beam delivered from the CW linac to the 8 GeV injection energy of the existing Recycler/Main Injector complex. Upgrades to the Recycler and Main Injector support a factor of three increase, beyond current capabilities, in proton beam power at 60 to 120 GeV. The Reference Design represents a facility that will be unique in the world with unmatched capabilities for the delivery of very high beam power, with flexible beam formats, to multiple users at multiple energies. The utilization of linacs within the Project X facility enables capabilities beyond what is achievable with circular accelerators. It is anticipated that the final configuration and operating parameters of the complex will be further refined through the R&D program in advance of CD-2.

Holmes, Stephen D.↗
DOE OSTI2021

pH Homeostasis and Sodium Ion Pumping by Multiple Resistance and pH Antiporters in Pyrococcus furiosus

Multiple Resistance and pH (Mrp) antiporters are seven-subunit complexes that couple transport of ions across the membrane in response to a proton motive force (PMF) and have various physiological roles, including sodium ion sensing and pH homeostasis. The hyperthermophilic archaeon Pyrococcus furiosus contains three copies of Mrp encoding genes in its genome. Two are found as integral components of two respiratory complexes, membrane bound hydrogenase (MBH) and the membrane bound sulfane sulfur reductase (MBS) that couple redox activity to sodium translocation, while the third copy is a stand-alone Mrp. Sequence alignments show that this Mrp does not contain an energy-input (PMF) module but contains all other predicted functional Mrp domains. The P. furiosus Mrp deletion strain exhibits no significant changes in optimal pH or sodium ion concentration for growth but is more sensitive to medium acidification during growth. Cell suspension hydrogen gas production assays using the deletion strain show that this Mrp uses sodium as the coupling ion. Mrp likely maintains cytoplasmic pH by exchanging protons inside the cell for extracellular sodium ions. Deletion of the MBH sodium-translocating module demonstrates that hydrogen gas production is uncoupled from ion pumping and provides insights into the evolution of this Mrp-containing respiratory complex.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1978

Frequency analysis of 4- to 6-keV electrons associated with an auroral arc

The high time resolution (HTR) experiment considered consists of four sections, including electrostatic deflection plates, electron multiplier, preamplifier-integrator, and frequency analyzer. Electrons in the energy range from 4 to 6 keV electrons are selected by the deflection system, after which they are detected, multiplied, and passed to the charge sensitive preamplifier. The charge pulses are amplified and integrated, and the resulting voltage pulse series is fed to the frequency analyzer. The experiment is essentially a flux detector, so that estimates of the input flux can be made from the mean value of the output spectrum. The results obtained with the HTR in a rocket flight on March 14, 1974, are discussed. The lack of modulation noticed in the high-frequency range indicates that there is insufficient wave energy available in the vicinity of the rocket to produce a wave-particle interaction which the HTR is able to observe. This finding is consistent with the stabilization of the plasma by the low flux of energetic electrons.

Murphree, J. S.↗
NASA NTRS1984

Uniform apparent contrast noise: A picture of the noise of the visual contrast detection system

A picture which is a sample of random contrast noise is generated. The noise amplitude spectrum in each region of the picture is inversely proportional to spatial frequency contrast sensitivity for that region, assuming the observer fixates the center of the picture and is the appropriate distance from it. In this case, the picture appears to have approximately the same contrast everywhere. To the extent that contrast detection thresholds are determined by visual system noise, this picture can be regarded as a picture of the noise of that system. There is evidence that, at different eccentricities, contrast sensitivity functions differ only by a magnification factor. The picture was generated by filtering a sample of white noise with a filter whose frequency response is inversely proportional to foveal contrast sensitivity. It was then stretched by a space-varying magnification function. The picture summmarizes a noise linear model of detection and discrimination of contrast signals by referring the model noise to the input picture domain.

Ahumada, A. J., Jr.↗
NASA NTRS1984

Variable polarity plasma arc welding on the Space Shuttle external tank

Variable polarity plasma arc (VPPA) techniques used at NASA's Marshall Space Flight Center for the fabrication of the Space Shuttle External Tank are presentedd. The high plasma arc jet velocities of 300-2000 m/s are produced by heating the plasma gas as it passes through a constraining orifice, with the plasma arc torch becoming a miniature jet engine. As compared to the GTA jet, the VPPA has the following advantages: (1) less sensitive to contamination, (2) a more symmetrical fusion zone, and (3) greater joint penetration. The VPPA welding system is computerized, operating with a microprocessor, to set welding variables in accordance with set points inputs, including the manipulator and wire feeder, as well as torch control and power supply. Some other VPPA welding technique advantages are: reduction in weld repair costs by elimination of porosity; reduction of joint preparation costs through elimination of the need to scrape or file faying surfaces; reduction in depeaking costs; eventual reduction of the 100 percent-X-ray inspection requirements. The paper includes a series of schematic and block diagrams.

Nunes, A. C., Jr.↗
NASA NTRS1971

The Effects of Parachute System Mass and Suspension-Line Elastic Properties on the LADT #3 Viking Parachute Inflation Load

Analytical calculations have considered the effects of 1) varying parachute system mass, 2) suspension-line damping, and 3) alternate suspension-line force-elongation data on the canopy force history. Results indicate the canopy force on the LADT #3 parachute did not substantially exceed the recorded vehicle force reading and that the above factors can have significant effects on the canopy force history. Analytical calculations have considered the effects of i) varying parachute system mass, 2) suspension line damping, and 3) different suspension-line force-elongation data on the canopy force history. Based on the results of this study the following conclusions are drawn: Specifically, 1. At the LADT #3 failure time of 1.70 seconds, the canopy force ranged anywhere from 15.7% below to 2.4% above the vehicle force depending upon the model and data used. Therefore, the canopy force did not substantially exceed the recorded vehicle force reading. 2. At a predicted full inflation time of 1.80 seconds the canopy force would be greater than the vehicle force by from 1.1% to 10.6%, again depending upon the model and data used. Generally, 3. At low altitudes, enclosed and apparent air mass can significantly effect the canopy force calculated and should, therefore, not be neglected. 4. The canopy force calculations are sensitive to decelerator physical properties. In this case changes in the damping and/or force-elongation characteristics produced significant changes in the canopy force histories. Accurate prediction of canopy force histories requires accurate inputs in these areas.

Talay, Theodore A.↗