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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China

Increasing roof albedo (using a “cool” roof) and night ventilation are passive cooling technologies that can reduce the cooling loads in buildings, but existing studies have not comprehensively explored the potential benefits of integrating these two technologies. This study combines an experiment in the summer and transition seasons with an annual simulation so as to evaluate the thermal performance, energy savings and thermal comfort improvement that could be obtained by coupling a cool roof with night ventilation. A holistic approach integrating sensitivity analysis and multi-objective optimization is developed to explore key design parameters (roof albedo, night ventilation air change rate, roof insulation level and internal thermal mass level) and optimal design options for the combined application of the cool roof and night ventilation. The proposed approach is validated and demonstrated through studies on a six-storey office building in Xiamen, a cooling-dominated city in southeast China. Simulations show that combining a cool roof with night ventilation can significantly decrease the annual cooling energy consumption by 27% compared to using a black roof without night ventilation and by 13% compared to using a cool roof without night ventilation. Roof albedo is the most influential parameter for both building energy performance and indoor thermal comfort. Optimal use of the cool roof and night ventilation can reduce the annual cooling energy use by 28% during occupied hours when air-conditioners are on and reduce the uncomfortable time slightly during occupied hours when air-conditioners are off.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Interpretation of thermoreflectance measurements with a two-temperature model including non-surface heat deposition

We develop a solution to the two-temperature diffusion equation in axisymmetric cylindrical coordinates to model heat transport in thermoreflectance experiments. Our solution builds upon prior solutions that account for two-channel diffusion in each layer of an N-layered geometry, but adds the ability to deposit heat at any location within each layer. We use this solution to account for non-surface heating in the transducer layer of thermoreflectance experiments that challenge the timescales of electron-phonon coupling. A sensitivity analysis is performed to identify important parameters in the solution and to establish a guideline for when to use the two-temperature model to interpret thermoreflectance data. We then fit broadband frequency domain thermoreflectance (BB-FDTR) measurements of SiO{sub 2} and platinum at a temperature of 300 K with our two-temperature solution to parameterize the gold/chromium transducer layer. We then refit BB-FDTR measurements of silicon and find that accounting for non-equilibrium between electrons and phonons in the gold layer does lessen the previously observed heating frequency dependence reported in Regner et al. [Nat. Commun. 4, 1640 (2013)] but does not completely eliminate it. We perform BB-FDTR experiments on silicon with an aluminum transducer and find limited heating frequency dependence, in agreement with time domain thermoreflectance results. We hypothesize that the discrepancy between thermoreflectance measurements with different transducers results in part from spectrally dependent phonon transmission at the transducer/silicon interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Nested polynomial trends for the improvement of Gaussian process-based predictors

The role of simulation keeps increasing for the sensitivity analysis and the uncertainty quantification of complex systems. Such numerical procedures are generally based on the processing of a huge amount of code evaluations. When the computational cost associated with one particular evaluation of the code is high, such direct approaches based on the computer code only, are not affordable. Surrogate models have therefore to be introduced to interpolate the information given by a fixed set of code evaluations to the whole input space. When confronted to deterministic mappings, the Gaussian process regression (GPR), or kriging, presents a good compromise between complexity, efficiency and error control. Such a method considers the quantity of interest of the system as a particular realization of a Gaussian stochastic process, whose mean and covariance functions have to be identified from the available code evaluations. In this context, this work proposes an innovative parametrization of this mean function, which is based on the composition of two polynomials. This approach is particularly relevant for the approximation of strongly non linear quantities of interest from very little information. After presenting the theoretical basis of this method, this work compares its efficiency to alternative approaches on a series of examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Adaptive polynomial chaos techniques for uncertainty quantification of a gas cooled fast reactor transient

Uncertainty quantification plays an increasingly important role in the nuclear community, especially with the rise of Best Estimate Plus Uncertainty methodologies. Sensitivity analysis, surrogate models, Monte Carlo sampling and several other techniques can be used to propagate input uncertainties. In recent years however polynomial chaos expansion has become a popular alternative providing high accuracy at affordable computational cost. This paper presents such polynomial chaos (PC) methods using adaptive sparse grids and adaptive basis set construction, together with an application to a Gas Cooled Fast Reactor transient. Comparison is made between a new sparse grid algorithm and the traditionally used technique proposed by Gerstner. An adaptive basis construction method is also introduced and is proved to be advantageous both from an accuracy and a computational point of view. As a demonstration the uncertainty quantification of a 50% loss of flow transient in the GFR2400 Gas Cooled Fast Reactor design was performed using the CATHARE code system. The results are compared to direct Monte Carlo sampling and show the superior convergence and high accuracy of the polynomial chaos expansion. Since PC techniques are easy to implement, they can offer an attractive alternative to traditional techniques for the uncertainty quantification of large scale problems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

THREE-DIMENSIONAL THERMAL MODELING ANALYSIS OF CST MEDIA FOR THE SMALL ION EXCHANGE PROJECT

The Small Column Ion Exchange (SCIX) project is designed to accelerate closure of High Level Waste (HLW) tanks at the Savannah River Site (SRS). The SRS tanks store HLW in three forms: sludge, saltcake, and supernate. An in-tank ion exchange process is being designed to treat supernate and dissolved saltcake waste. Through this process, radioactive cesium from the salt solution is adsorbed into Crystalline Silicotitanate (CST) ion exchange media packed within a flow-through column. A packed column loaded with radioactive cesium generates significant heat from radiolytic decay. The waste supernate solution within the ion exchange bed will boil around 120 C. Solution superheating above the boiling point within the column could lead to violent hazardous energy releases. System heating from loaded CST is also of concern in other process modules, such as the waste tank. Due to tank structural integrity concerns, the wall temperature limit for the SRS waste tanks is 100 C. The transfer of cesium-loaded CST to the tank could result in localized hot spots on the tank floor and walls which may exceed this limit. As a result, thermal modeling calculations have been conducted to predict the maximum temperatures achievable both in the column and in the waste tank. As specified in the associated Technical Task Plan, one objective of the present work was to compute temperature distributions within the ion exchange column module under accident scenarios including loss of salt solution flow through the bed and loss of coolant system flow. The column modeling domain and the scope of the calculations in this case were broadened relative to previous two-dimensional calculations to include vertical temperature distributions within the packed bed of ion exchange media as well as the upper column plenum region containing only fluid. The baseline design conditions and in-column modeling domain for the ion-exchange column module are shown in Figure 1. These evaluations assumed the maximum bounding cesium loading considered possible based on current knowledge regarding CST media and the anticipated feed compositions. Since this cesium loading was considerably higher than the nominal loading conditions in SRS waste, cases with lower loading were also evaluated. Modeling parameters were the same as those used previously unless otherwise indicated. The current model does not capture multi-phase cooling mechanisms operative when solution boiling occurs. This feature is conservative in the sense that it does not account for the large cooling effects associated with phase transfer. However, the potential transfer of heat to the plenum region associated with vertical bubble ascension through the column during boiling is also neglected. Thermal modeling calculations were also performed for the entire waste storage tank for the case where loaded and ground CST was transferred to the tank. The modeling domain used for the in-tank calculations is provided in Figure 2. The in-tank domain is based on SRS Tank 41, which is a Type-IIIA tank. Temperature distributions were evaluated for cylindrical, ground CST mounds located on the tank floor. Media grinding is required prior to vitrification processing of the CST in the SRS Defense Waste Processing Facility (DWPF). The location of the heat source region on the tank floor due to the accumulation of CST material was assumed to be just under the grinder. The shape of the CST mound was assumed to be cylindrical. This shape is believed to be most representative of the actual mound shape formed in the tank, given that submersible mixing pumps will be available for media dispersion. Alternative configurations involving other geometrical shapes for the CST mound were evaluated in the previous work. Sensitivity analysis for the in-tank region was performed for different amounts of CST media. As was the case for the in-column model, the in-tank model does not include multi-phase cooling mechanisms operative when solution boiling occurs. The in-column and the in-tank evaluations incorporated recently updated maximum cesium loading levels calculated using the current SCIX feed compositions, which resulted in significantly higher cesium loading than previously calculated. The calculations were conducted to ensure conservative predictions for the maximum temperatures achievable using the current baseline design. The degree of conservatism was reduced for in-column calculations relative to the previous work by using a three-dimensional modeling approach and selecting parameters which were nearer to expected conditions. The degree of conservatism for the in-tank calculations was also reduced by lowering the soil penetration depth below the tank from 150 to 20 feet. The primary goals of the extended thermal modeling effort were to determine whether fluid boiling or superheating are possible within the column module and to determine the maximum floor temperatures within the tank loaded with spent CST.

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

Inverse Uncertainty Quantification of Reactor Simulation with Polynomial Chaos Surrogate Model

Reliable uncertainty quantification (UQ) and sensitivity analysis (SA) is significant part of modelling and simulation. This is particularly important in the nuclear community due to the fact that the licensing of nuclear installations has shifted from conservative to Best Estimate plus Uncertainty (BEPU) methodologies. UQ can be broadly classified as forward UQ and inverse UQ. Forward UQ is the process of quantifying the uncertainties in simulation outputs by propagating the uncertainties in input parameters. It requires knowledge in the input uncertainty, which is often specified by ad-hoc expert judgment which lacks mathematical rigor. The inverse UQ is the process to determine the uncertainty in input parameters given observations of the output. The purpose of this paper is to replace such ad-hoc expert judgment of the statistical properties of input model parameters in nuclear reactor simulation. This summary presents work on inverse UQ of a nonlinear Point Reactor Kinetics Equations - lumped thermal-hydraulics parameter coupled problem. Bayesian inference and Markov Chain Monte Carlo (MCMC) are used for the inverse UQ. Because MCMC requires a large number of simulations which is impractical for models that are computationally expensive, surrogate models is constructed by generalized Polynomial Chaos (PC) expansion technique. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

A simplified approach to characterizing a kilovoltage source spectrum for accurate dose computation

Purpose: To investigate and validate the clinical feasibility of using half-value layer (HVL) and peak tube potential (kVp) for characterizing a kilovoltage (kV) source spectrum for the purpose of computing kV x-ray dose accrued from imaging procedures. To use this approach to characterize a Varian Registered-Sign On-Board Imager Registered-Sign (OBI) source and perform experimental validation of a novel in-house hybrid dose computation algorithm for kV x-rays. Methods: We characterized the spectrum of an imaging kV x-ray source using the HVL and the kVp as the sole beam quality identifiers using third-party freeware Spektr to generate the spectra. We studied the sensitivity of our dose computation algorithm to uncertainties in the beam's HVL and kVp by systematically varying these spectral parameters. To validate our approach experimentally, we characterized the spectrum of a Varian Registered-Sign OBI system by measuring the HVL using a Farmer-type Capintec ion chamber (0.06 cc) in air and compared dose calculations using our computationally validated in-house kV dose calculation code to measured percent depth-dose and transverse dose profiles for 80, 100, and 125 kVp open beams in a homogeneous phantom and a heterogeneous phantom comprising tissue, lung, and bone equivalent materials. Results: The sensitivity analysis of the beam quality parameters (i.e., HVL, kVp, and field size) on dose computation accuracy shows that typical measurement uncertainties in the HVL and kVp ({+-}0.2 mm Al and {+-}2 kVp, respectively) source characterization parameters lead to dose computation errors of less than 2%. Furthermore, for an open beam with no added filtration, HVL variations affect dose computation accuracy by less than 1% for a 125 kVp beam when field size is varied from 5 Multiplication-Sign 5 cm{sup 2} to 40 Multiplication-Sign 40 cm{sup 2}. The central axis depth dose calculations and experimental measurements for the 80, 100, and 125 kVp energies agreed within 2% for the homogeneous and heterogeneous block phantoms, and agreement for the transverse dose profiles was within 6%. Conclusions: The HVL and kVp are sufficient for characterizing a kV x-ray source spectrum for accurate dose computation. As these parameters can be easily and accurately measured, they provide for a clinically feasible approach to characterizing a kV energy spectrum to be used for patient specific x-ray dose computations. Furthermore, these results provide experimental validation of our novel hybrid dose computation algorithm.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2012

Comparisons of four categories of waste recycling in China's paper industry based on physical input-output life-cycle assessment model

Highlights: Black-Right-Pointing-Pointer Using crop straws and wood wastes for paper production should be promoted. Black-Right-Pointing-Pointer Bagasse and textile waste recycling should be properly limited. Black-Right-Pointing-Pointer Imports of scrap paper should be encouraged. Black-Right-Pointing-Pointer Sensitivity analysis, uncertainties and policy implications are discussed. - Abstract: Waste recycling for paper production is an important component of waste management. This study constructs a physical input-output life-cycle assessment (PIO-LCA) model. The PIO-LCA model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper. Crop straw recycling and wood utilization for paper production have small total intensity of environmental impacts. Moreover, environmental impacts reduction of crop straw recycling and wood utilization benefits the most from technology development. Thus, using crop straws and wood (including wood wastes) for paper production should be promoted. Technology development has small effects on environmental impacts reduction of bagasse recycling, textile waste recycling and scrap paper recycling. In addition, bagasse recycling and textile waste recycling have big total intensity of environmental impacts. Thus, the development of bagasse recycling and textile waste recycling should be properly limited. Other pathways for reusing bagasse and textile wastes should be explored and evaluated. Moreover, imports of scrap paper should be encouraged to reduce large indirect impacts of scrap paper recycling on domestic environment.

09 BIOMASS FUELS↗
NASA NTRS1992

Integrating aerodynamics and structures in the minimum weight design of a supersonic transport wing

An approach is presented for determining the minimum weight design of aircraft wing models which takes into consideration aerodynamics-structure coupling when calculating both zeroth order information needed for analysis and first order information needed for optimization. When performing sensitivity analysis, coupling is accounted for by using a generalized sensitivity formulation. The results presented show that the aeroelastic effects are calculated properly and noticeably reduce constraint approximation errors. However, for the particular example selected, the error introduced by ignoring aeroelastic effects are not sufficient to significantly affect the convergence of the optimization process. Trade studies are reported that consider different structural materials, internal spar layouts, and panel buckling lengths. For the formulation, model and materials used in this study, an advanced aluminum material produced the lightest design while satisfying the problem constraints. Also, shorter panel buckling lengths resulted in lower weights by permitting smaller panel thicknesses and generally, by unloading the wing skins and loading the spar caps. Finally, straight spars required slightly lower wing weights than angled spars.

Barthelemy, Jean-Francois M.↗
DOE OSTI2012

An EPGPT-based approach for uncertainty quantification

Generalized Perturbation Theory (GPT) has been widely used by many scientific disciplines to perform sensitivity analysis and uncertainty quantification. This manuscript employs recent developments in GPT theory, collectively referred to as Exact-to-Precision Generalized Perturbation Theory (EPGPT), to enable uncertainty quantification for computationally challenging models, e.g. nonlinear models associated with many input parameters and many output responses and with general non-Gaussian parameters distributions. The core difference between EPGPT and existing GPT is in the way the problem is formulated. GPT formulates an adjoint problem that is dependent on the response of interest. It tries to capture via the adjoint solution the relationship between the response of interest and the constraints on the state variations. EPGPT recasts the problem in terms of a smaller set of what is referred to as the 'active' responses which are solely dependent on the physics model and the boundary and initial conditions rather than on the responses of interest. The objective of this work is to apply an EPGPT methodology to propagate cross-sections variations in typical reactor design calculations. The goal is to illustrate its use and the associated impact for situations where the typical Gaussian assumption for parameters uncertainties is not valid and when nonlinear behavior must be considered. To allow this demonstration, exaggerated variations will be employed to stimulate nonlinear behavior in simple prototypical neutronics models. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

In vivo dosimetry for gynaecological brachytherapy using a novel position sensitive radiation detector: Feasibility study

Purpose: In gynecological radiotherapy with high dose rate (HDR){sup 192}Ir brachytherapy, the treatment complexity has increased due to improved optimization techniques and dose constraints. As a consequence, it has become more important to verify the dose delivery to the target and also to the organs at risk (e.g., the bladder). In vivo dosimetry, where dosimeters are placed in or on the patient, is one way of verifying the dose but until recently this was hampered by motion of the radiation detectors with respect to the source. The authors present a novel dosimetry method using a position sensitive radiation detector. Methods: The prototype RADPOS system (Best Medical Canada) consists of a metal oxide field effect transistor (MOSFET) dosimeter coupled to a position-sensor, which deduces its 3D position in a magnetic field. To assess the feasibility of in vivo dosimetry based on the RADPOS system, different characteristics of the detector need to be investigated. Using a PMMA phantom, the positioning accuracy of the RADPOS system was quantified by comparing position readouts with the known position of the detector along the x and y-axes. RADPOS dose measurements were performed at various distances from a Nucletron{sup 192}Ir source in a PMMA phantom to evaluate the energy dependence of the MOSFET. A sensitivity analysis was performed by calculating the dose after varying (1) the position of the RADPOS detector to simulate organ motion and (2) the position of the first dwell position to simulate errors in delivery. The authors also performed an uncertainty analysis to determine the action level (AL) that should be used during in vivo dosimetry. Results: Positioning accuracy is found to be within 1 mm in the 1-10 cm range from the origin along the x-axis (away from the transmitter), meeting the requirements for in vivo dosimetry. Similar results are obtained for the other axes. The ALs are chosen to take into account the total uncertainty on the measurements. As a consequence for in vivo dosimetry, it is determined that the RADPOS sensor, if placed, for example, in the bladder Foley balloon, would detect a 2 mm motion of the bladder, at a 5% chance of a false positive, with an AL limit of 9% of the dose delivered. The authors found that source position errors, caused by, e.g., a wrong first dwell position, are more difficult to detect; indeed, with our single RADPOS detector, positioned in the bladder, dwell position errors below 5 mm and resulting in a dose error within 10%, could be detected in the tandem but not in the colpostats. A possible solution to improve error detection is to use multiple MOSFETs to obtain multiple dose values. Conclusions: In this study, the authors proposed a dosimetry procedure, based on the novel RADPOS system, to accurately determine the position of the radiation dosimeter with respect to the applicator. The authors found that it is possible to monitor the delivered dose in a point and compare it to the predetermined dose. This allows in principle the detection of problems such as bladder motion/filling or source mispositioning. Further clinical investigation is warranted.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Subcritical Copper-Reflected-α-phase Plutonium (SCRαP) Integral Experiment Design

A Subcritical Copper-Reflected α-phase Plutonium (SCRαP) integral benchmark experiment is proposed where multiplication will be approximated using correlated neutron data from a detector system consisting of {sup 3}He tubes inside polyethylene. Measurements will be performed on various subcritical experimental configurations consisting of a weapons-grade plutonium sphere surrounded by different Cu thicknesses. In addition to the proposed base experimental configurations with Cu, additional configurations are planned with the plutonium ball nested in various thicknesses of interleaved polyethylene spherical shells mixed in with the Cu shells. The polyethylene is intended to provide fast neutron moderation and reflection, resulting in additional measurements with differing multiplication, spectra, and nuclear data sensitivity. The proposed experiments will performed at the National Criticality Experiments Research Center (NCERC). NCERC is home to a 4.5-kg α-phase stainless steel clad plutonium sphere that is referred to as the BeRP (Beryllium-Reflected Plutonium) ball due to its historical use in a beryllium-reflected critical experiment. In 2014, similar subcritical measurements were performed with the BeRP ball surrounded by nickel and tungsten. The nickel-reflected measurements were documented as a benchmark evaluation which was accepted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Similar to past measurements, the proposed work will help both identify deficiencies and quantify uncertainties in nuclear data and validate computational methods related to neutron multiplication inference for subcritical benchmark evaluations. Monte Carlo simulations were performed for the preliminary design of a subcritical Copper-Reflected - phase Plutonium (SCRP) integral benchmark experiment. Specifically, MCNP{sup R} version 6 was used to determine the k{sub eff} and associated nuclear data sensitivities for different preliminary configurations (reflector thickness, material type). The final experimental design process will include continuous-energy nuclear data sensitivity analysis. This will help assess the potential impact of this integral measurement as it relates to international efforts to continuously improve current libraries (ENDF, JEFF, JENDL etc) that still tend to over/under-estimate the measured results of integral experiments, sometimes significantly. Deficiencies in underlying nuclear data quantities such as Nubar have been shown to have an effect on inferred values from subcritical measurements as well. The proposed experiments and subsequent computational validation will help identify such deficiencies. It will also help validate new nuclear data evaluations, including one for Cu that was recently performed in the resolved region up to 100 MeV for {sup 65}Cu and {sup 63}Cu which is expected to improve Cu-related benchmark simulation performance. The final experimental design phase will also include simulation results that will incorporate the detectors that will be used for the subcritical measurements. For the benchmark portion of the measurements, the main detectors that are being considered are portable neutron multiplicity counters made up of {sup 3}He tubes embedded in polyethylene and lined with cadmium. These detectors employ a data acquisition system that produces list-mode data (correlated information where each event is listed sequentially) that can be analyzed using the Feynman variance-to-mean method. Other detector systems including SNAP (single {sup 3}He tube embedded in polyethylene), and a high-purity germanium (HPGe) detector are being considered for supplementary measurements only and are not intended to be used for the final benchmark measurements. Decoupling the supplementary detectors from the system eliminates any contribution to the total system multiplication, and greatly simplifies the final computational benchmark model. Therefore, an optimization of the portable neutron multiplicity counter placement in the benchmark measurements will be performed to ensure that there is minimal contribution to the total system multiplication. In addition, new temperature measurement techniques and hardware will be explored. (authors)

42 ENGINEERING↗
DOE OSTI2016

Emulation of dynamic simulators with application to hydrology

Many simulation-intensive tasks in the applied sciences, such as sensitivity analysis, parameter inference or real time control, are hampered by slow simulators. Emulators provide the opportunity of speeding up simulations at the cost of introducing some inaccuracy. An emulator is a fast approximation to a simulator that interpolates between design input–output pairs of the simulator. Increasing the number of design data sets is a computationally demanding way of improving the accuracy of emulation. We investigate the complementary approach of increasing emulation accuracy by including knowledge about the mechanisms of the simulator into the formulation of the emulator. To approximately reproduce the output of dynamic simulators, we consider emulators that are based on a system of linear, ordinary or partial stochastic differential equations with a noise term formulated as a Gaussian process of the parameters to be emulated. This stochastic model is then conditioned to the design data so that it mimics the behavior of the nonlinear simulator as a function of the parameters. The drift terms of the linear model are designed to provide a simplified description of the simulator as a function of its key parameters so that the required corrections by the conditioned Gaussian process noise are as small as possible. The goal of this paper is to compare the gain in accuracy of these emulators by enlarging the design data set and by varying the degree of simplification of the linear model. We apply this framework to a simulator for the shallow water equations in a channel and compare emulation accuracy for emulators based on different spatial discretization levels of the channel and for a standard non-mechanistic emulator. Our results indicate that we have a large gain in accuracy already when using the simplest mechanistic description by a single linear reservoir to formulate the drift term of the linear model. Adding some more reservoirs does not lead to a significant improvement in accuracy. However, the transition to a spatially continuous linear model leads again to a similarly large gain in accuracy as the transition from the non-mechanistic emulator to that based on one reservoir.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Radiation Transport in Random Media With Large Fluctuations

Strongly heterogeneous media arise in several applications that include radiation shields, nuclear fuel, BWR moderators, clouds, planetary and stellar atmospheres, turbulent gases and plasmas. Neutral and charged particle transport computations in such media have relied heavily on formulating transport equations with spatially random coefficients (physical data) and developing solution methods to deal with the additional stochastic dimensions. Attempts at developing approximate closures that yield only low order statistical information (e.g., mean and variance of the flux) have proved to be highly restrictive under real physics conditions or rely on techniques that require fluctuation amplitudes to be small for robustness. Recently, stochastic spectral methods such as polynomial chaos and stochastic collocation have been developed for aleatoric uncertainty quantification and sensitivity analysis, and successfully applied in radiation transport work. Advances in UQ techniques have tended to focus on efficiently handling large numbers of uncertain variables but the rigorous stochastic basis of the approach also promotes its use in situations where stochasticity is due to spatial heterogeneity and the associated uncertainty is large. Here we apply these techniques to radiation transport in media with spatially randomly varying cross sections without restriction on fluctuation amplitudes. Specifically, we represent the cross sections as a lognormal spatial random process with specified mean, variance and covariance function and use a Karhunen-Loeve (KL) decomposition to generate cross section realizations that are strictly positive. Woodcock Monte Carlo (WMC) is then used to simulate transport using random sampling of cross sections and deterministic sampling based on a stochastic collocation technique. Numerical results for the mean and variance in the scalar flux and leakage currents are obtained for weak and strong random variations. We focus in this work on demonstrating the approach and defer application to specific problems to a future investigation. We have demonstrated that a combination of stochastic spectral representation and Woodcock Monte Carlo simulation allows efficient computation of radiation transport in strongly random media. The use of a lognormal distribution to represent the fluctuations in medium properties facilitates enforcement of strict positivity of cross section realizations, a condition that has challenged standard approaches that assume Gaussian fluctuations. The fact that the lognormal random process is a memoryless nonlinear transformation of a Gaussian process further enables efficient and accurate reconstruction of the random cross section realizations using a Karhunen-Loeve representation of the cross section. Finally, the robustness of this model enables fluctuations of arbitrarily large amplitude to be studied, using both random sampling Monte Carlo and more efficient stochastic collocation techniques. The present work is being extended to allow reconstruction of probability density functions of output variables using polynomial chaos representation, and to accommodate general cross section covariance functions. Also, techniques are being explored to more judiciously select ceiling cross sections to enhance the efficiency of Woodcock Monte Carlo for transport in random media. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Nuclear Data Uncertainty Quantification for Adjoint-Weighted Quantities via XGPT in Monte Carlo Codes

The Total Monte Carlo method (TMC) is an innovative approach to nuclear data uncertainty propagation. In TMC, a large number of independent ENDF files are randomly generated starting from nuclear models parameters and their uncertainties. These files are then processed with NJOY or similar codes to produce a set of formatted continuous-energy cross sections (i.e., ACE files), and independent Monte Carlo neutron transport simulations are run with these different ACE files as input. Finally the distributions of the considered response functions are obtained directly from the results of the Monte Carlo runs. Despite several improvements of the TMC method, this approach is often considered an inefficient way of propagating nuclear data uncertainties, as it requires several computationally expensive Monte Carlo runs. Covariance-based methods present important advantages for several applications, especially when different sources of uncertainties are to be investigated. For this reason, sensitivity analysis and uncertainty quantification capabilities are being implemented in several Monte Carlo neutron transport codes. On the other hand, the fact that no artificial multi-group covariance matrices are required and that higher moments of the responses distributions can be easily obtained, are definite advantages of the TMC method. In an effort to overcome the limitations of both approaches, a new method, called eXtended Generalized Perturbation Theory (XGPT) is under development. When performing nuclear data uncertainty propagation, such XGPT approach does not require generating discretized (i.e., multigroup) covariance matrices, and allows to estimate higher moments of the response probability distributions, via linear perturbation theory. One of the promising applications of the XGPT method involves its adoption in conjunction with the Proper Orthogonal Decomposition (POD) of nuclear data, to build a Reduced Order Model (ROM) for the approximation of thousands of independent TMC results in a single criticality source simulation. In the present work, this approach is employed for the first time to evaluate the impact of uncertainty in nuclear data on adjoint-weighted quantities. The method has been implemented in an extended version of the Serpent-2.1.24 Monte Carlo code and is demonstrated on two fast spectrum benchmarks, focusing on {sup 208}Pb nuclear data. A new method for propagating nuclear data uncertainties in criticality source Monte Carlo simulations has been developed. This eXtended Generalized Perturbation Theory (XGPT) approach allows to accurately reproduce reference Total Monte Carlo (TMC) uncertainty estimates in a single criticality source simulation. The present work aims to demonstrate that the proposed method can quantify nuclear data uncertainty based on adjoint-weighted quantities. The XGPT approach was applied to evaluate the impact of {sup 208}Pb nuclear data uncertainties on the effective prompt neutron lifetime (l{sub eff}) in two fast spectrum systems. The obtained XGPT results show a good agreement with the reference TMC results, obtained from independent Monte Carlo runs with {sup 208}Pb nuclear data from random TENDL-2013 evaluations. The XGPT method, implemented in a extended version of the Serpent Monte Carlo code and adopted along with the Proper Orthogonal Decomposition (POD) of the nuclear data, is able to provide an accurate reduced order model to approximate thousands TMC results within a single run, ensuring a large saving in computational requirements. The effect of {sup 208}Pb nuclear data uncertainties appears to be rather large. This is consistent with previous studies that adopted the same input random evaluations data from TENDL. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Effects of radiative heat loss on extinction limits of counterflow premixed ammonia-air flames

The effect of radiative heat loss on counterflow premixed ammonia-air flames has been investigated as a function of equivalence ratio and system pressure. Non-adiabatic counterflow premixed flame simulations incorporating detailed chemistry, transport, and radiative heat transfer in the optically thin limit have been employed to elucidate important underlying physics and extinction characteristics. Similar to methane-air flame systems, non-adiabatic counterflow premixed computations show that the combined effects of positive flame stretch, sub-unity Lewis number, and radiative heat loss lead to the extension of the lean flammability limit for ammonia-air flames, revealing a C-shaped curve near the lean flammability limit that exhibits both radiation-induced and stretch-induced extinction states. Here, the computations compare favorably with the experimentally determined extinction stretch rate values for the stretch-induced extinction states over a wide range of equivalence ratios at different pressures up to 5 atm. A novel feature sensitivity analysis has also been developed to highlight important sensitive reactions for the stretch- and radiation-induced extinction states. Furthermore, the controlling chemistry at the dual-extinction states and at varying pressures are compared and discussed.

10 SYNTHETIC FUELS↗
DOE OSTI2012

Utility of Bromide and Heat Tracers for Aquifer Characterization Affected by Highly Transient Flow Conditions

A tracer test using both bromide and heat tracers conducted at the Integrated Field Research Challenge site in Hanford 300 Area (300A), Washington, provided an instrument for evaluating the utility of bromide and heat tracers for aquifer characterization. The bromide tracer data were critical to improving the calibration of the flow model complicated by the highly dynamic nature of the flow field. However, most bromide concentrations were obtained from fully screened observation wells, lacking depth-specific resolution for vertical characterization. On the other hand, depth-specific temperature data were relatively simple and inexpensive to acquire. However, temperature-driven fluid density effects influenced heat plume movement. Moreover, the temperature data contained “noise” caused by heating during fluid injection and sampling events. Using the hydraulic conductivity distribution obtained from the calibration of the bromide transport model, the temperature depth profiles and arrival times of temperature peaks simulated by the heat transport model were in reasonable agreement with observations. This suggested that heat can be used as a cost-effective proxy for solute tracers for calibration of the hydraulic conductivity distribution, especially in the vertical direction. However, a heat tracer test must be carefully designed and executed to minimize fluid density effects and sources of noise in temperature data. A sensitivity analysis also revealed that heat transport was most sensitive to hydraulic conductivity and porosity, less sensitive to thermal distribution factor, and least sensitive to thermal dispersion and heat conduction. This indicated that the hydraulic conductivity remains the primary calibration parameter for heat transport.

Ma, Rui↗