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At least 793 records · Page 44

Modeling of the Temperature-dependent Spectral Response of In(1-x)Ga(x)Sb Infrared Photodetectors

A model of the spectral responsivity of In(1-x) Ga(x) Sb p-n junction infrared photodetectors has been developed. This model is based on calculations of the photogenerated and diffusion currents in the device. Expressions for the carrier mobilities, absorption coefficient and normal-incidence reflectivity as a function of temperature were derived from extensions made to Adachi and Caughey-Thomas models. Contributions from the Auger recombination mechanism, which increase with a rise in temperature, have also been considered. The responsivity was evaluated for different doping levels, diffusion depths, operating temperatures, and photon energies. Parameters calculated from the model were compared with available experimental data, and good agreement was obtained. These theoretical calculations help to better understand the electro-optical behavior of In(1-x) Ga(x) Sb photodetectors, and can be utilized for performance enhancement through optimization of the device structure.

Gonzalex-Cuevas, Juan A.↗

Modeling of hypersonic reacting flows

The effect of nonequilibrium thermochemical processes on the aerodynamic and heat transfer characteristics of a hypersonic vehicle is illustrated with examples. It is shown that the conventional method of predicting chemical reactions always predict that the flow is closer to equilibrium than it actually is, leading to incorrect predictions of aerodynamic characteristics of a vehicle. A method is presented for predicting chemical processes using a two-temperature kinetic model, which is developed on the basis of combining conservation equations for vibrational energy and for electron electronic energy, which are also derived. The validity of the two-temperature model is proven using two types of experimental data: radiation and shock shapes.

Park, Chul↗

Development of a Pronghorn Model of the High Temperature Engineering Test Reactor: Preliminary Results from Loss of Forced Cooling #3 [Slides]

This presentation contains results from a Pronghorn model of the High Temperature Engineering Test Reactor (HTTR) operated by the Japan Atomic Energy Agency. The model was used to simulate a loss of forced cooling (LOFC) experiment. This presentation contains preliminary results from a standalone thermal hydraulics model of this LOFC test and some discussion of the results compared to data

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

New Insights into Low-Temperature Oxidation of Propane from Synchrotron Photoionization Mass Spectrometry and Multiscale Informatics Modeling

We investigated the low-temperature oxidation of propane at 4 Torr and temperatures of 530, 600, and 670 K. The oxidation is initiated by pulsed laser photolysis of oxalyl chloride, (COCl)2, at 248 nm, which rapidly generates a ~1:1 mixture of 1-propyl (n-propyl) and 2-propyl (i-propyl) radicals via the fast Cl + propane reaction. Reactants, intermediates and products are probed with isomeric selectivity by time-resolved multiplexed photoionization mass spectrometry (MPIMS) with tunable synchrotron vacuum UV radiation as the ionization source. At all three temperatures, the major stable product species is propene, formed in the C3H7 + O2 reactions by direct HO2-elimination from both n- and i-propyl peroxy radicals. The experimentally derived propene yields relative to the initial concentration of Cl atoms are (20 ± 4)% at 530 K, (55 ± 11)% at 600 K, and (86 ± 17)% at 670 K at a reaction time of 20 ms. The lower yield of propene at low temperature reflects substantial formation of propyl peroxy radicals, which do not completely decompose on the experimental time scale. In addition, we detect the C3H6O isomers methyloxirane, oxetane, acetone and propanal as minor products. Our measured yields of oxetane and methyloxirane, which are co-products of OH radicals, suggest a revision of the OH formation pathways in models of low-temperature propane oxidation. The experimental results are modeled and interpreted using a multi-scale informatics approach that is presented in detail in a separate publication (Burke, M. P.; Goldsmith, C. F.; Klippenstein, S. J.; Welz, O.; Huang H.; Antonov I. O.; Savee J. D.; Osborn D. L.; Zádor, J.; Taatjes, C. A.; Sheps, L., Multi-Scale Informatics for Low-Temperature Propane Oxidation: Further Complexities in Studies of Complex Rections, submitted, 2015). The model predicts the time profiles and yields of the experimentally observed primary products well, and shows satisfactory agreement for products formed mostly via secondary radical-radical reactions.

Combustion↗

Improved multiphysics model of the High Temperature Engineering Test Reactor for the simulation of loss-of-forced-cooling experiments

We present a multiphysics model of the High Temperature Engineering Test Reactor for comparison with past and predict future loss-of-forced-cooling (LOFC) experiments. The approach selected combines (1) 3-D full-core superhomogenization-corrected neutronics, (2) 3-D full-core homogenized or semi-heterogeneous heat transfer (macroscale), (3) 2-D axisymmetric fuel rod heat transfer (mesoscale), and (4) 1-D thermal-hydraulics channels. Although large sensitivities remain and the available experimental data are insufficient for use in a rigorous validation exercise, the overall transient behavior is successfully reproduced. The novelty of our work includes (1) a new macroscale-mesoscale heat transfer coupling approach relying on gap conductance to drastically speed up numerical convergence by two orders of magnitude, (2) determination of a radial effective thermal conductivity that yields reasonably close results between the homogenized and semi-heterogeneous macroscale thermal models, and (3) a preliminary study of the reactor's early behavior following a LOFC event, thus enabling further assessment of numerical models against fission power measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling In-Reactor Temperature Gradients in Lithium Aluminate Ceramic Pellets

In reactor thermal performance of lithium aluminate ceramic pellets are calculated to determine operating temperatures if internal components shift during irradiation. A 2D conduction model was setup to model this scenario with additional physics, including thermal expansion of components to reactor temperatures, creep down of the cladding due to differential pressure between the inside of the rod and reactor coolant system, and net radiation exchange between components. The non-linear coupling of the governing equations presented convergence challenges due to the very different effects from a small temperature change on the radiation vs radial and circumferential conduction equations. Initial temperature guesses for the multidimensional solution were provided from conservative 1D models simulating bounding scenarios. Convergence was greatly improved by taking small steps towards the root solutions and averaging with initial guesses. The final method robustly converged all 132 points at an axial plane after a few dozen iterations. The temperature results show that the additional physics have a secondary effect as the dominant heat transfer mechanism is radial conduction across the gas gap followed by circumferential conduction around components. Circumferential conduction in the lithium aluminate pellets is enhanced by the relatively high thermal conductivity of this ceramic.

Carstens, Nathan A.↗

Assessing the Impact of Soil Layer Depth Specification on the Observability of Modeled Soil Moisture and Brightness Temperature

The utility of hydrologic land surface models (LSMs) can be enhanced by using information from observational platforms, but mismatches between the two are common.This study assesses the degree to which model agreement with observations (observability) is affected by two mechanisms in particular: 1) physical incongruities between the support volumes being characterized and 2) inadequateor inconsistent parameterizations of physical processes. The Noah and Noah-MP LSMs by default characterize surface soil moisture (SSM) in the top 10 cm of the soil column. This depth may be reasonable when comparing against soil moisture from in situ probes centered at 5 cm,but it is notably different from the 5 cm (or less) sensing depth of NASA’s Soil Moisture Active Passive (SMAP) satellite mission. These depth inconsistencies are examined by using thinner model layers in the Noah and Noah-MP LSMs and comparing resultant simulations to in situ and SMAP soil moisture. In addition, a forward radiative transfer model to simulate microwave brightness temperatures (Tbs) is used to facilitate direct comparisons of LSM-based and SMAP-based L-band Tb retrievals. Observability is quantified using Kolmogorov-Smirnov distance values, calculated from empirical cumulative distribution functions of SSM and Tb time series. Experiment results depend on the particular subspace being analyzed (SSM or Tb). This study concludes that therole of increasedsoil layer discretizationon LSM observability is secondary to the influence of component parameterizations, the effects of which dominate systematic differences with observations

SMAP↗

Response of U.S. West Coast Mountain Snowpack to Local Sea Surface Temperature Perturbations: Insights from Numerical Modeling and Machine Learning

Sea surface temperature (SST) significantly modulates the precipitation and temperature over land, with important consequences on land surface processes such as snowpack. Compared to the impact of remote SST, the effect of nearshore/local SST is less well understood. In this study, the impact of local SST on the mountain snowpack of the U.S. West Coast is investigated using two 6-km regional climate simulations driven by the same lateral boundary conditions but with time-varying versus time-invariant and warmer local SSTs during 2003–15. Results show that local SST warming leads to warmer winter with more precipitation over the mountains. Meanwhile, the removal of SST temporal variability results in reduced temperature variability but increased precipitation variability. As a result, winter snow accumulation decreases by ~200 mm per season in the Cascade Mountains in the north but increases by ~100 mm per season in the Sierra Nevada in the south. Such a dipole response results from the competing effects of precipitation and temperature change at different elevations and are amplified by the enhanced atmospheric river moisture transport. To further delineate the relative contributions of different meteorological factors to the snowpack response, two neural network models were developed to predict the snow behaviors at seasonal and monthly scales. These models reveal the dominant influence of the total amount and the average temperature of precipitation on the snowpack response. Furthermore, these findings highlight the sensitivity of mountain snowpack to local SST in the western United States and underscore the importance of local SST and atmospheric rives to accurate snowpack estimations for water management.

54 ENVIRONMENTAL SCIENCES↗

Development of a high temperature pyrolysis mechanism for cyclopentanone, a potential biofuel derived from biomass

Cyclopentanone (CPO) is a promising biofuel for spark-ignition engines due to its ring strain and high auto-ignition resistance. The Department of Energy has identified CPO as a potential biofuel candidate because of its unique chemical properties. Understanding CPO decomposition is crucial to building a high-temperature combustion model. In this study, we present a comprehensive kinetic model for high-temperature pyrolysis of CPO with verified results from high-pressure shock tube (HPST) measurements. The time histories of carbon monoxide (CO), ethylene (C2H4), and CPO absorbances over the temperature range of 1156-1416 K and 8.53-10.06 atm were measured. A corresponding kinetic model was generated using the Reaction Mechanism Generator (RMG) with the parameters of dominant pathways from either previous studies or quantum calculation within current work. The final model containing 821 species and 79,859 reactions exhibited a good agreement with the experimental results. In this study, the C2H4/CO ratio was used as an essential factor to validate the model and to prove that radical-involved bimolecular pathways were as significant as unimolecular decomposition of CPO. The rate of production (ROP) analysis showed that H radicals play major roles in both primary reactions and product pyrolysis. The insights from this work can be used to generate a better CPO combustion model and help evaluate CPO as a biofuel. Such understanding can also be helpful when proposing pyrolysis or combustion models for other biofuels.

cyclopentanone, reaction mechanism, pyrolysis, sho↗

The ROSAT All-Sky Survey of active binary coronae. II - Coronal temperatures of the RS Canum Venaticorum systems

We present the results from an analysis of X-ray spectra of 44 RS CVn systems obtained during the ROSAT All-Sky Survey with the Position Sensitive Proportional Counter (PSPC). Thermal plasma models with two temperature components are found to reproduce the observations better than single or continuous temperature models. We typically find that a bimodal distribution of temperatures centered near 2 x 10 exp 6 and 1.6 x 10 exp 7 K fit the data best. We show that the PSPC temperatures agree well with those from similar low-resolution measurements, although differences exist, primarily due to differing detector bandpasses. After comparing coronal (either temperature or emission measure) characteristics with stellar parameters including rotation period and dynamo number, we find no compelling relationship. The height-integrated emission measures of the components in the two-temperature models, including a gravity term, are found to be well correlated with temperature.

Dempsey, Robert C.↗

Modeling of Prismatic High Temperature Reactors in Pronghorn

Pronghorn is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based thermal-hydraulics code developed at Idaho National Laboratory (INL) for advanced reactor analysis. It has been previously applied to model Pebble-Bed High Temperature Reactors (High Temperature Reactor (HTR)s), Liquid-Metal Cooled Reactors, and Molten Salt Reactors, among others. This work applies the coarse-mesh thermal hydraulics capabilities in Pronghorn to model Prismatic-Core HTRs. In particular, the Oregon State University (OSU)’s High Temperature Test Facility (HTTF) is modeled with Pronghorn. The HTTF is a 1:4 height scaled-down facility of General Atomics’ Modular High Temperature Gas-cooled Reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy Scales in X-Ray Microcalorimeters

Microcalorimeter pulse shape characteristics, such as pulse height, decay time and rise time, are dependent on the detector temperature and bias as well as the photon energy and flux. We examine the nature of the temperature dependency by illuminating the ASTRO-E2 X-ray Spectrometer (XRS) microcalorimeter array with X-rays generated by electron impact on a range of foil targets. The resulting pulses are collected for a range of detector temperatures. We observe and model the temperature dependence of the pulse shape characteristics by fitting the data with non-linear pulse models. Our aim is to determine a robust method for correcting the energy scale obtained in ground calibration for slight differences in the operating conditions while in orbit.

Tillotson, W. A.↗

Deterministic Modeling of the High Temperature Test Reactor

Idaho National Laboratory (INL) is tasked with the development of reactor physics analysis capability of the Next Generation Nuclear Power (NGNP) project. In order to examine INL’s current prismatic reactor deterministic analysis tools, the project is conducting a benchmark exercise based on modeling the High Temperature Test Reactor (HTTR). This exercise entails the development of a model for the initial criticality, a 19 column thin annular core, and the fully loaded core critical condition with 30 columns. Special emphasis is devoted to the annular core modeling, which shares more characteristics with the NGNP base design. The DRAGON code is used in this study because it offers significant ease and versatility in modeling prismatic designs. Despite some geometric limitations, the code performs quite well compared to other lattice physics codes. DRAGON can generate transport solutions via collision probability (CP), method of characteristics (MOC), and discrete ordinates (Sn). A fine group cross section library based on the SHEM 281 energy structure is used in the DRAGON calculations. HEXPEDITE is the hexagonal z full core solver used in this study and is based on the Green’s Function solution of the transverse integrated equations. In addition, two Monte Carlo (MC) based codes, MCNP5 and PSG2/SERPENT, provide benchmarking capability for the DRAGON and the nodal diffusion solver codes. The results from this study show a consistent bias of 2–3% for the core multiplication factor. This systematic error has also been observed in other HTTR benchmark efforts and is well documented in the literature. The ENDF/B VII graphite and U235 cross sections appear to be the main source of the error. The isothermal temperature coefficients calculated with the fully loaded core configuration agree well with other benchmark participants but are 40% higher than the experimental values. This discrepancy with the measurement stems from the fact that during the experiments the control rods were adjusted to maintain criticality, whereas in the model, the rod positions were fixed. In addition, this work includes a brief study of a cross section generation approach that seeks to decouple the domain in order to account for neighbor effects. This spectral interpenetration is a dominant effect in annular HTR physics. This analysis methodology should be further explored in order to reduce the error that is systematically propagated in the traditional generation of cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data

Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management. Without accessibility to other data sources, the onsite observed temperatures or the airport temperatures are used in forecast models. In this paper, we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations (PWS) to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework. The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs. Our approach is distinguished from existing literature in various aspects. First, we leverage the crowdsourcing weather data from PWS in addition to public data sources. In this way, the data is at much finer time resolution (e.g., at 5-minute frequency) and spatial resolution (e.g., arbitrary location vs grid). Second, our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance. Here, we demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio, Texas, USA. In general, the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50% compares with persistent model and has 90% chance to outperform airport forecast in short-term forecasting. In a real-time setting, the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon. Moreover, we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance. Finally, we implement our model in other cities such as Syracuse and Chicago to test the model's performance in different landforms and climate types.

54 ENVIRONMENTAL SCIENCES↗

Deterministic Modeling of the High Temperature Test Reactor with DRAGON-HEXPEDITE

The Idaho National Laboratory (INL) is tasked with the development of reactor physics analysis capability of the Next Generation Nuclear Power (NGNP) project. In order to examine the INL’s current prismatic reactor analysis tools, the project is conducting a benchmark exercise based on modeling the High Temperature Test Reactor (HTTR). This exercise entails the development of a model for the initial criticality, a 19 fuel column thin annular core, and the fully loaded core critical condition with 30 fuel columns. Special emphasis is devoted to physical phenomena and artifacts in HTTR that are similar to phenomena and artifacts in the NGNP base design. The DRAGON code is used in this study since it offers significant ease and versatility in modeling prismatic designs. DRAGON can generate transport solutions via Collision Probability (CP), Method of Characteristics (MOC) and Discrete Ordinates (Sn). A fine group cross-section library based on the SHEM 281 energy structure is used in the DRAGON calculations. The results from this study show reasonable agreement in the calculation of the core multiplication factor with the MC methods, but a consistent bias of 2-3% with the experimental values is obtained. This systematic error has also been observed in other HTTR benchmark efforts and is well documented in the literature. The ENDF/B VII graphite and U 235 cross sections appear to be the main source of the error. The isothermal temperature coefficients calculated with the fully loaded core configuration agree well with other benchmark participants but are 40% higher than the experimental values. This discrepancy with the measurement partially stems from the fact that during the experiments the control rods were adjusted to maintain criticality, whereas in the model, the rod positions were fixed. In addition, this work includes a brief study of a cross section generation approach that seeks to decouple the domain in order to account for neighbor effects. This spectral interpenetration is a dominant effect in annular HTR physics. This analysis methodology should be further explored in order to reduce the error that is systematically propagated in the traditional generation of cross sections.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Revealing the critical role of radical-involved pathways in high temperature cyclopentanone pyrolysis

Cyclopentanone (CPO) is a promising biofuel for spark-ignition engines due to its ring strain and high auto-ignition resistance. Understanding CPO decomposition is crucial for building a high-temperature combustion model. Here we present a comprehensive kinetic model for high-temperature pyrolysis of CPO with verified results from high-pressure shock tube (HPST) measurements. The time- histories of carbon monoxide (CO), ethylene (C 2 H 4 ), and CPO absorbances over the temperature range of 1156-1416 K and pressure range of 8.53-10.06 atm were measured during current experiments. A corresponding detailed kinetic model was generated using the Reaction Mechanism Generator (RMG) with dominant unimolecular/radical-involved decomposition pathways from either previous studies or quantum calculations within the current work. The obtained model containing 821 species and 79,859 reactions exhibited a good agreement with the experimental results. In this study, the absorbance ratio between C 2 H 4 and CO was used as an important factor to validate models and to prove that radical-involved bimolecular pathways were as significant as unimolecular decomposition of CPO. The rate of production (ROP) analysis showed H radicals play a major role in the decomposition, and the whole decomposition process could be divided into three stages based on the H radical concentration. Finally, the insights from present work can be used to generate a better CPO combustion model and help evaluate CPO as an advanced biofuel.

09 BIOMASS FUELS↗

Basal melt beneath whillans ice stream and ice streams A and C

We have used a recently derived map of the velocity of Whillans Ice Stream and Ice Streams A and C to help estimate basal melt. Temperature was modeled with a simple vertical advection-diffusion equation, 'tuned' to match temperature profiles. We find that most of the melt occurs beneath the tributaries where larger basal shear stresses and thicker ice favors greater melt (e.g., 10-20 mm/yr). The occurrence of basal freezing is predicted beneath much of the ice plains of Ice Stream C and Whillans Ice Stream. Modelled melt rates for when Ice Stream C was active suggest there was just enough melt water generated in its tributaries to balance basal freezing on its ice plain. Net basal melt for Whillans Ice Stream is positive due to smaller basal temperature gradients. Modelled temperatures on Whillans Ice Stream, however, were constrained by a single temperature profile at UpB. Basal temperature gradients for Whillans B1 and Ice Stream A may have conditions more similar to those beneath Ice Streams C and D, in which case, there may not be sufficient melt to sustain motion. This would be consistent with the steady deceleration of Whillans stream over the last few decades.

glaciers ice sheets↗