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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-JeP4-02: An Investigation of Respiratory Surrogate Motion Data Requirements for Multiple-Step Ahead Prediction

Purpose: Respiratory-gated radiotherapy and dynamic tracking employ real-time imaging and surrogate motion-monitoring methods with tumor motion prediction in advance of real-time. This study investigated respiratory motion data length on prediction accuracy of tumor motion. Methods: Predictions generated from the algorithm are validated against a one-dimensional surrogate signal of amplitude versus time. Prediction consists of three major components: extracting top-ranked subcomponents from training data matching the last respiratory cycle; calculating weighting factors from best-matched subcomponents; fusing data proceeding best-matched subcomponents with respective weighting factors to form predictions. Predictions for one respiratory cycle (∼3-6seconds) were assessed using 351 patient data from the respiratory management device. Performance was evaluated for correlation coefficient and root mean square error (RMSE) between prediction and final respiratory cycle. Results: Respiratory prediction results fell into two classes, where best predictions for 70 cycles or less performed using relative prediction and greater than 70 cycles are predicted similarly using relative and derivative relative. For 70 respiratory cycles or less, the average correlation between prediction and final respiratory cycle was 0.9999±0.0001, 0.9999±0.0001, 0.9988±0.0003, 0.9985±0.0023, and 0.9981±0.0023 with RMSE values of 0.0091±0.0030, 0.0091±0.0030, 0.0305±0.0051, 0.0299±0.0259, and 0.0299±0.0259 for equal, relative, pattern, derivative equal and derivative relative weighting methods, respectively. Respectively, the total best prediction for each method was 37, 65, 20, 22, and 22. For data with greater than 70 cycles average correlation was 0.9999±0.0001, 0.9999±0.0001, 0.9988±0.0004, 0.9988±0.0020, and 0.9988±0.0020 with RMSE values of 0.0081±0.0031, 0.0082±0.0033, 0.0306±0.0056, 0.0218±0.0222, and 0.0218±0.0222 for equal, relative, pattern, derivative equal and derivative relative weighting methods, respectively. Respectively, the total best prediction for each method was 24, 44, 42, 30, and 45. Conclusion: The prediction algorithms are effective in estimating surrogate motion in advance. These results indicate an advantage in using relative prediction for shorter data and either relative or derivative relative prediction for longer data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Tulane virus protease as a structural surrogate for inhibitor screening of human norovirus proteases

Human norovirus (HuNoV) is a significant cause of gastroenteritis worldwide, affecting people of all age groups. There are currently no vaccines or drugs available, leaving susceptible populations vulnerable to severe or protracted illness. A HuNoV cultivation system is pivotal for screening norovirus antivirals. While the human intestinal enteroid cultivation system allows robust replication of multiple HuNoV strains, it presents technical and cost barriers. Tulane virus (TV), a surrogate for HuNoV, replicates well in monkey kidney cell lines and is closely related to norovirus in cellular biology. Here, we determined the structures of TV protease (TV-Pro) alone and in complex with rupintrivir, a picornavirus inhibitor that also inhibits HuNoV proteases (HuNoV-Pro). Our data validate TV as an efficient surrogate system for rapid screening of HuNoV protease inhibitors. The TV protease structure exhibits significant backbone similarity to the GI.1 HuNoV protease in the substrate-binding domain, with the BII-CII loop in an open conformation stabilized by hydrogen bonds as present in the GI.1 protease. Structural differences in the S2 pocket and two amino acid changes in the S4 pocket result in slightly altered P2 and P4 substrate and inhibitor conformations. Despite these differences, we confirm previous findings that the TV protease can cleave the GI.1 and GII HuNoV polyprotein substrates with high and moderate efficiency, respectively. We found that rupintrivir efficiently inhibits TV protease in vitro and inhibits TV replication in cell culture with similar efficacy in combination with P-glycoprotein efflux pump inhibitors. We conclude that TV is a valuable surrogate for HuNoV protease inhibitor screening and outline strategies to improve its compatibility as such.

crystal structures↗
DOE OSTI2025

Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems

Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known to be effective in handling high-dimensional computational problems, providing high-quality empirical performance as well as strong probabilistic guarantees. However, their practical application is complicated by the fact that the user needs to set various algorithm-specific tuning parameters which are different from those used in traditional NLA. This paper demonstrates how a surrogate-based autotuning approach can be used to address fundamental problems of parameter selection in RandNLA algorithms. In particular, we provide a detailed investigation of surrogate-based autotuning for sketch-and-precondition (SAP)-based randomized least squares methods, which have been one of the great success stories in modern RandNLA. Empirical results show that our surrogate-based autotuning approach can achieve near-optimal performance with much less tuning cost than a random search (up to about 7.6x fewer trials of different parameter configurations). Moreover, while our experiments focus on least squares, our results demonstrate a general-purpose autotuning pipeline applicable to any kind of RandNLA algorithm.

Cho, Younghyun↗
DOE OSTI2019

The neutron within the deuteron as a surrogate for neutron-induced reactions

We propose the use of neutron poisons in reactions induced by radioactive beams as a test of theoretical models aiming to relate neutron capture in nuclei with neutron surrogate reactions such as ([Formula: see text]) reactions. We exploit the approximations necessary to obtain a direct relation between the two reactions: surrogate versus neutron capture. We also show how this is intimately related to the momentum distribution of the neutron within the deuteron. The models we use are based on the theory of inclusive breakup reactions commonly employed in the treatment of incomplete fusion and surrogate method. Such theories were developed in the 1980s by Ichimura, Austern and Vincent [Phys. Rev. C 32 (1985) 431], Udagawa and Tamura [Phys. Rev. C 24 (1981) 1348] and Hussein and McVoy [Nucl. Phys. A 445 (1985) 124]. We use these theories to derive an expression for the proton yield in the reaction [Formula: see text]. The capture reaction [Formula: see text] is then extracted using reasonable approximations. By recalling an old method proposed by Serber [Phys. Rev. 80 (1950) 1098; Proc. Roy. Soc. A 208 (1951) 559] we explain how the momentum distribution of neutrons within the deuteron will depend on the short-range dependence of the nucleon–nucleon force. The relevance of our work to nucleosynthesis in the rapid neutron capture process is emphasized.

Physics↗
DOE OSTI2023

Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates

Optimal sub-sampling of large datasets from fluid dynamics simulations is essential for training reduced-order machine learned models. A method using Shannon entropy was developed to weight flow features according to their level of information content, such that the most informative features can be extracted and used for training a surrogate model. The method is demonstrated in the canonical flow over a cylinder problem simulated with OpenFOAM. Both time-independent predictions and temporal forecasting were investigated as well as two types of prediction targets: local per-grid-point predictions and global per-time-step predictions. When tested on training a surrogate model, results indicate that our entropy-based sampling method typically outperforms random sampling and yields more reproducible results in less iterations. Finally, the method was used to train a surrogate model for modeling turbulence in magnetohydrodynamic flows, which revealed various challenges and opportunities for future research.

Brewer, Wes↗
DOE OSTI2024

Helium as a Surrogate for Deuterium in LPI Studies

Helium or neopentane can be used as surrogate gas fill for deuterium (D2) or deuterium-tritium (DT) in laser-plasma interaction studies. Surrogates are convenient to avoid flammability hazards or the integration of cryogenics in an experiment. To test the degree of equivalency between deuterium and helium, experiments were conducted in the Pecos target chamber at Sandia National Laboratories. Observables such as laser propagation and signatures of laser-plasma instabilities (LPI) were recorded for multiple laser and target configurations. It was found that some observables can differ significantly despite the apparent similarity of the gases with respect to molecular charge and weight. While a qualitative behaviour of the interaction may very well be studied by finding a suitable compromise of laser absorption, electron density, and LPI cross sections, a quantitative investigation of expected values for deuterium fills at high laser intensities is not likely to succeed with surrogate gases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of the calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C μ , C ε2 , C ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal values of the turbulence model parameters, was parametric uncertainty, which was rectified by calibration. Post-calibration, the dominant contribution to model inaccuraries are due to the structural errors in RANS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluating the Potential for Marine and Hydrokinetic Devices to Act as Artificial Reefs or Fish Aggregating Devices. Based on Analysis of Surrogates in Tropical, Subtropical, and Temperate U.S. West Coast and Hawaiian Coastal Waters

Wave energy converters (WECs) and tidal energy converters (TECs) are only beginning to be deployed along the U.S. West Coast and in Hawai‘i, and a better understanding of their ecological effects on fish, particularly on special-status fish (e.g., threatened and endangered) is needed to facilitate project design and environmental permitting. The structures of WECs and TECs placed on to the seabed, such as anchors and foundations, may function as artificial reefs that attract reef-associated fishes, while the midwater and surface structures, such as mooring lines, buoys, and wave or tidal power devices, may function as fish aggregating devices (FADs), forming the nuclei for groups of fishes. Little is known about the potential for WECs and TECs to function as artificial reefs and FADs in coastal waters of the U.S. West Coast and Hawai‘i. We evaluated these potential ecological interactions by reviewing relevant information about fish associations with surrogate structures, such as artificial reefs, natural reefs, kelps, floating debris, oil and gas platforms, marine debris, anchored FADs deployed to enhance fishing opportunities, net-cages used for mariculture, and piers and docks. Based on our review, we postulate that the structures of WECs and TECs placed on or near the seabed in coastal waters of the U.S. West Coast and Hawai‘i likely will function as small-scale artificial reefs and attract potentially high densities of reef-associated fishes (including special-status rockfish species [Sebastes spp.] along the mainland), and that the midwater and surface structures of WECs placed in the tropical waters of Hawai‘i likely will function as de facto FADs with species assemblages varying by distance from shore and deployment depth. Along the U.S. West Coast, frequent associations with midwater and surface structures may be less likely: juvenile, semipelagic, kelp-associated rockfishes may occur at midwater and surface structures of WECs in coastal waters of southern California to Washington, and occasional, seasonal, or transitory associations of coastal pelagic fishes such as jack mackerel (Trachurus symmetricus) may also occur at WECs in these waters. Importantly, our review indicated that negative effects of WEC structures on special-status fish species, such as increased predation of juvenile salmonids or rockfishes, are not likely. In addition, WECs installed in coastal California, especially in southern California waters, have the potential to attract high densities of reef-associated fishes and may even contribute to rockfish productivity, if fish respond to the WECs similarly to oil and gas platforms, which have some of the highest secondary production per unit area of seafloor of any marine habitat studied globally (Claisse et al. 2014). We encountered some information gaps, owing to the paucity or lack, in key locations, of comparable surrogate structures in which fish assemblages and ecological interactions were studied. TECs are most likely to be used in the Puget Sound area, but suitable surrogates are lacking there. However, in similarly cold-temperate waters of Europe and Maine, benthopelagic fish occurred around tidal turbines during lower tidal velocities, and this type of interaction may be expected by similar species at TECs in Puget Sound. To address information gaps in the near term, such as whether WECs would function as FADs in temperate waters, studies of navigation buoys using hydroacoustics are recommended.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Compaction Behavior of Surrogate Degraded Emplaced WIPP Waste

The present study results are focused on laboratory testing of surrogate waste materials. The surrogate wastes correspond to a conservative estimate of degraded Waste Isolation Pilot Plant (WIPP) containers and TRU waste materials at the end of the 10,000 year regulatory period. Testing consists of hydrostatic, triaxial, and uniaxial strain tests performed on surrogate waste recipes that were previously developed by Hansen et al. (1997). These recipes can be divided into materials that simulate 50% and 100% degraded waste by weight. The percent degradation indicates the anticipated amount of iron corrosion, as well as the decomposition of cellulosics, plastics, and rubbers (CPR). Axial, lateral, and volumetric strain and axial, lateral, and pore stress measurements were made. Two unique testing techniques were developed during the course of the experimental program. The first involves the use of dilatometry to measure sample volumetric strain under a hydrostatic condition. Bulk moduli of the samples measured using this technique were consistent with those measured using more conventional methods. The second technique involved performing triaxial tests under lateral strain control. By limiting the lateral strain to zero by controlling the applied confining pressure while loading the specimen axially in compression, one can maintain a right-circular cylindrical geometry even under large deformations. This technique is preferred over standard triaxial testing methods which result in inhomogeneous deformation or “barreling”. Manifestations of the inhomogeneous deformation included non-uniform stress states, as well as unrealistic Poisson’s ratios (> 0.5) or those that vary significantly along the length of the specimen. Zero lateral strain controlled tests yield a more uniform stress state, and admissible and uniform values of Poisson’s ratio.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

PLAN-TA9-2443(U), Rev. B Remediated Nitrate Salt (RNS) Surrogate Formulation and Testing Standard Procedure

This document identifies scope and some general procedural steps for performing Remediated Nitrate Salt (RNS) Surrogate Formulation and Testing. This Test Plan describes the requirements, responsibilities, and process for preparing and testing a range of chemical surrogates intended to mimic the energetic response of waste created during processing of legacy nitrate salts. The surrogates developed are expected to bound1 the thermal and mechanical sensitivity of such waste, allowing for the development of process parameters required to minimize the risk to worker and public when processing this waste. Such parameters will be based on the worst-case kinetic parameters as derived from APTAC measurements as well as the development of controls to mitigate sensitivities that may exist due to friction, impact, and spark. This Test Plan will define the scope and technical approach for activities that implement Quality Assurance requirements relevant to formulation and testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Results from Second Round of Remediated Nitrate Salt Surrogate Formulation and Testing

High Explosives and Technology (M-7) completed the second round of formulation and testing of Remediated Nitrate Salt (RNS) surrogates on March 17, 2016. This report summarizes the results of the work and also includes additional documentation required under test plan PLAN-TA9-2443 Rev B, "Remediated Nitrate Salt (RNS) Surrogate Formulation and Testing Standard Procedure", released February 16, 2016. All formulation and testing was carried out according to PLAN-TA9-2443 Rev B. Results from the first round of formulation and testing were documented in memorandum M7-16-6042, "Results from First Round of Remediated Nitrate Salt Surrogate Formulation and Testing."

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Fabrication and Characterization of Surrogate TRISO Particles Using 800μm ZrO 2 Kernels

In support of fully ceramic microencapsulated (FCM) fuel development, coating development work is ongoing at Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with both UN kernels and surrogate (uranium-free) kernels. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere. The surrogate TRISO particles are necessary for separate effects testing and for utilization in the consolidation process development. This report focuses on the fabrication and characterization of surrogate TRISO particles which use 800μm in diameter ZrO 2 microspheres as the kernel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Surrogate Measurements of Actinide (n,2n) Cross Sections with NeutronSTARS

Directly measuring (n,2n) cross sections on short-lived actinides presents a number of experimental challenges. The surrogate reaction technique is an experimental method for measuring cross sections on short-­lived isotopes, and it provides a unique solution for measuring (n,2n) cross sections. This technique involves measuring a charged-­particle reaction cross section, where the reaction populates the same compound nucleus as the reaction of interest. To perform these surrogate (n,2n) cross section measurements, a silicon telescope array has been placed along a beam line at the Texas A&M University Cyclotron Institute, which is surrounded by a large tank of gadolinium-doped liquid scintillator, which acts as a neutron detector. The combination of the charge-particle and neutron-detector arrays is referred to as NeutronSTARS. In the analysis procedure for calculating the (n,2n) cross section, the neutron detection efficiency and time structure plays an important role. Due to the lack of availability of isotropic, mono-energetic neutron sources, modeling is an important component in establishing this efficiency and time structure. This report describes the NeutronSTARS array, which was designed and commissioned during this project. It also describes the surrogate reaction technique, specifically referencing a 235 U(n,2n) commissioning measurement that was fielded during the past year. Advanced multiplicity analysis techniques have been developed for this work, which should allow for efficient analysis of 241 Pu(n,2n) and 239 Pu(n,2n) cross section measurements

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

System Reliability Analysis Capability and Surrogate Model Application in RAVEN

This report collect the effort performed to improve the reliability analysis capabilities of the RAVEN code and explore new opportunity in the usage of surrogate model by extending the current RAVEN capabilities to multi physics surrogate models and construction of surrogate models for high dimensionality fields.

31274↗
DOE OSTI2017

L2 Milestone: Neutron Capture Cross Sections from Surrogate (p, d) Measurements: Determination of the Unknown 87 Y(n, g) Cross Section and Assessment of the Method Via the 90 Zr(n, g) Benchmark Case: Theory Report

Cross sections for compound-nuclear reactions involving unstable targets are important for many applications, but can often not be measured directly. Here we describe a method for extracting cross sections for neutron-capture on unstable isotopes from indirect (surrogate) measurements. The surrogate reaction, which produces the compound nucleus of interest, has to be described and the decay of the nucleus has to be modeled. We outline the approach for one-neutron pickup and report on the determination of the 90 Zr(n, γ ) reaction from surrogate 92 Zr(p,d) data, which is compared to the directly-measured capture cross section and thus provides a benchmark for the method. We then apply the method to determine the 87 Y(n, γ ) cross section, which has not been measured directly. The work was carried out in the context of an LLNL L2 Milestone. This report addresses the theory aspects of the milestone. A complementary document summarizes the experimental efforts [1].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Aluminum Clad Spent Nuclear Fuel Task 6: Surrogate Sample Preparation and Validation Experiment Test Plan

This document presents the experimental test plan for Task 6: Surrogate Preparation and Validation. Task 6 will produce and validate surrogate oxyhydroxide materials used in other experimental tasks within the larger Aluminum Clad Spent Nuclear Fuel Long Term Dry Storage Project. Task 6 includes both the preparation and characterization of surrogate oxyhydroxide materials as well as the analysis of oxide/oxyhydroxide layers on Savannah River Site Spent Nuclear Fuel Materials. This test plan provides experimental design details and the task’s overall quality assurance approach.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Effluent Management Facility Stack Monitor Qualification: Assessment with Surrogate Stacks

Sampling and monitoring at the Waste Treatment and Immobilization Plant (WTP) Effluent Management Facility (EMF) exhaust is required to meet the regulatory criteria that governs stacks that may exceed the 0.1-millirem per year threshold limit given in Title 40 of the Code of Federal Regulations, Part 61, National Emissions Standards for Hazardous Air Pollutants, Subpart H, National Emission Standard for Emissions of Radionuclides other than Radon from Department of Energy Facilities. As a result, the flow conditions and probe location must be within certain bounds as prescribed by the American National Standards Institute/Health Physics Society (ANSI/HPS) standard N13.1-1999. Compliance with the standard may be demonstrated by tests on the stack itself, or with a surrogate stack (i.e., a scale model or other geometrically similar stack). Pacific Northwest National Laboratory (PNNL) has performed scale model stack tests for 11 of the 20 emission points that are planned for the WTP. Additionally, PNNL has full scale stack results from Idaho National Laboratory and PNNL facility stacks to use as references. One or more WTP scale model stack results were expected to be appropriate as a surrogate stack to the EMF. This report describes the EMF stack monitoring location as well as an assessment of existing surrogate stacks used to qualify the EMF stack sampling location.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Time Series Dimension Reduction for Surrogate Models of Port Scanning Cyber Emulations

Surrogate model development is a key resource in the scientific modeling community for providing computational expedience when simulating complex systems without loss of great fidelity. The initial step to development of a surrogate model is identification of the primary governing components of the system. Principal component analysis (PCA) is a widely used data science technique that provides inspection of such driving factors, when the objective for modeling is to capture the greatest sources of variance inherent to a dataset. Although an efficient linear dimension reduction tool, PCA makes the fundamental assumption that the data is continuous and normally distributed. Thus, it provides ideal performance when these conditions are met. In the case for which cyber emulations provide realizations of a port scanning scenario, the data to be modeled follows a discrete time series function comprised of monotonically increasing piece-wise constant steps. The sources of variance are related to the timing and magnitude of these steps. Therefore, we consider using XPCA, an extension to PCA for continuous and discrete random variates. This report provides the documentation of the trade-offs between the PCA and XPCA linear dimension reduction algorithms, for the intended purpose to identify key components of greatest variance in our time series data. These components will ultimately provide the basis for future surrogate models of port scanning cyber emulations.

97 MATHEMATICS AND COMPUTING↗