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At least 1,657 records · Page 92

MCNP Simulation of the SFRC and Minimum Detection Threshold Determination (Rev. 1)

In this report the Minimum Detection Threshold (MDT) for the Spent Fuel Rod Counter (SFRC) was determined using Monte Carlo N-Particle transport computer code (MCNP). A model of the SFRC was simulated in addition to a fuel transport pipe and spent Magnox fuel at descending positions down the pipe. The neutron MDT for Magnox fuel free-falling along a discharge pipe was calculated to be equal to 4080 n/s. The gamma MDT for the same free falling fuel as measured by the SFRC’s ionization chamber was determined to be 455 γ/s. These values were determined to be a conservative value to use when the instrument is deployed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Randomization of dust-ejecta motions and the observed morphology of cometary heads

The computer code that has been used over years to study the dust-coma morphology of comets and to generate their synthetic images is upgraded by introducing two categories of random perturbations into the motions of dust particles ejected from discrete sources of activity on the nucleus surface. The new technique is applied to three types of morphological features: multiple concentric halos, a system of spiral jets, and a sunward fan-shaped coma. The results indicate that inclusion of random perturbations substantially enhances the capability for generating synthetic images that faithfully simulate the observed appearance of dust comets. By increasing the magnitude of perturbations in the synthetic images beyond a certain limit, it is possible to 'erase' morphological features characteristic of the ejection process. This implies that the lack of distinct morphology in the head of a comet cannot be interpreted as the absence of discrete sources of activity on the nucleus surface. The effects of varying random perturbations on the appearance of the computer-generated images are investigated in detail and the suspected major role that imperfect flow collimation (or flow divergence) in dust jets plays with regard to the observed coma morphology is discussed.

Sekanina, Zdenek↗

HTR-Proteus Pebble Bed Experimental Program Cores 9 & 10: Columnar Hexagonal Point-on-Point Packing with a 1:1 Moderator-to-Fuel Pebble Ratio

PROTEUS is a zero-power research reactor based on a cylindrical graphite annulus with a central cylindrical cavity. The graphite annulus remains basically the same for all experimental programs, but the contents of the central cavity are changed according to the type of reactor being investigated. Through most of its service history, PROTEUS has represented light-water reactors, but from 1992 to 1996 PROTEUS was configured as a pebble-bed reactor (PBR) critical facility and designated as HTR-PROTEUS. The nomenclature was used to indicate that this series consisted of High Temperature Reactor experiments performed in the PROTEUS assembly. During this period, seventeen critical configurations were assembled and various reactor physics experiments were conducted. These experiments included measurements of criticality, differential and integral control rod and safety rod worths, kinetics, reaction rates, water ingress effects, and small sample reactivity effects (Ref. 3). HTR-PROTEUS was constructed, and the experimental program was conducted, for the purpose of providing experimental benchmark data for assessment of reactor physics computer codes. Considerable effort was devoted to benchmark calculations as a part of the HTR-PROTEUS program. References 1 and 2 provide detailed data for use in constructing models for codes to be assessed. Reference 3 is a comprehensive summary of the HTR-PROTEUS experiments and the associated benchmark program. This document draws freely from these references. Only Cores 9 and 10 are evaluated in this benchmark report due to similarities in their construction. The other core configurations of the HTR-PROTEUS program are evaluated in their respective reports as outlined in Section 1.0. Cores 9 and 10 were evaluated and determined to be acceptable benchmark experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

HTR-Proteus Pebble Bed Experimental Program Cores 5, 6, 7, & 8: Columnar Hexagonal Point-on-Point Packing with a 1:2 Moderator-to-Fuel Pebble Ratio

PROTEUS is a zero-power research reactor based on a cylindrical graphite annulus with a central cylindrical cavity. The graphite annulus remains basically the same for all experimental programs, but the contents of the central cavity are changed according to the type of reactor being investigated. Through most of its service history, PROTEUS has represented light-water reactors, but from 1992 to 1996 PROTEUS was configured as a pebble-bed reactor (PBR) critical facility and designated as HTR-PROTEUS. The nomenclature was used to indicate that this series consisted of High Temperature Reactor experiments performed in the PROTEUS assembly. During this period, seventeen critical configurations were assembled and various reactor physics experiments were conducted. These experiments included measurements of criticality, differential and integral control rod and safety rod worths, kinetics, reaction rates, water ingress effects, and small sample reactivity effects (Ref. 3). HTR-PROTEUS was constructed, and the experimental program was conducted, for the purpose of providing experimental benchmark data for assessment of reactor physics computer codes. Considerable effort was devoted to benchmark calculations as a part of the HTR-PROTEUS program. References 1 and 2 provide detailed data for use in constructing models for codes to be assessed. Reference 3 is a comprehensive summary of the HTR-PROTEUS experiments and the associated benchmark program. This document draws freely from these references. Only Cores 9 and 10 are evaluated in this benchmark report due to similarities in their construction. The other core configurations of the HTR-PROTEUS program are evaluated in their respective reports as outlined in Section 1.0. Cores 9 and 10 were evaluated and determined to be acceptable benchmark experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

HTR-Proteus Pebble Bed Experimental Program Cores 5,6,7,&8: Columnar Hexagonal Point-on-Point Packing with a 1:2 Moderator-to-Fuel Pebble Ratio

PROTEUS is a zero-power research reactor based on a cylindrical graphite annulus with a central cylindrical cavity. The graphite annulus remains basically the same for all experimental programs, but the contents of the central cavity are changed according to the type of reactor being investigated. Through most of its service history, PROTEUS has represented light-water reactors, but from 1992 to 1996 PROTEUS was configured as a pebble-bed reactor (PBR) critical facility and designated as HTR-PROTEUS. The nomenclature was used to indicate that this series consisted of High Temperature Reactor experiments performed in the PROTEUS assembly. During this period, seventeen critical configurations were assembled and various reactor physics experiments were conducted. These experiments included measurements of criticality, differential and integral control rod and safety rod worths, kinetics, reaction rates, water ingress effects, and small sample reactivity effects (Ref. 3). HTR-PROTEUS was constructed, and the experimental program was conducted, for the purpose of providing experimental benchmark data for assessment of reactor physics computer codes. Considerable effort was devoted to benchmark calculations as a part of the HTR-PROTEUS program. References 1 and 2 provide detailed data for use in constructing models for codes to be assessed. Reference 3 is a comprehensive summary of the HTR-PROTEUS experiments and the associated benchmark program. This document draws freely from these references. Only Cores 9 and 10 are evaluated in this benchmark report due to similarities in their construction. The other core configurations of the HTR-PROTEUS program are evaluated in their respective reports as outlined in Section 1.0. Cores 9 and 10 were evaluated and determined to be acceptable benchmark experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Right Time at the Right Places

In my undergraduate studies at the Massachusetts Institute of Technology (MIT), the short-lived chemical physics major allowed me to evade a number of courses required for chemistry majors. Thus, it was possible to take many physics courses and most of the advanced PhD-level courses in physical chemistry. I also took the introductory electrical engineering course in computer programming. The latter allowed me to write lots of computer code as a part of my (passing, but largely unsuccessful) senior thesis directed graciously by Professor Walter Thorson. As recommended by MIT Professor John C. Slater, I moved to Stanford University with Professor Frank Harris as my PhD supervisor. Frank was the perfect advisor for me, providing very close direction during the first year, and then allowing me to develop more and more independently. Within a few days of my twenty-fifth birthday, I became an assistant professor of chemistry at the University of California, Berkeley. Eighteen years later, I moved to the University of Georgia as director of a new research institute.

autobiography↗

MELCOR

MELCOR is a fully integrated, engineering-level computer code for modeling the progression of severe accidents in light water reactors (LWR) at nuclear power plants and nuclear fuel cycle facilities. Originally developed to assess severe accidents following Three Mile Island, MELCOR’s flexible modeling framework has enabled it to be applied to safety assessments of a much broader range of nuclear power reactor designs and other types of nuclear facilities processing radioactive material. Further, MELCOR can model a broad spectrum of severe accident phenomena such as thermal-hydraulic response in a reactor coolant system; core heat-up, degradation, and relocation; and transport behavior in both boiling water and pressurized water reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Status of HEU-Pb in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the average neutron energy the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. The lack of integral measurements to determine errors in Pb cross-section data has caused the latest nuclear cross-section libraries to over/underestimate k eff compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fast-Spectrum Critical Assemblies with a Pb-HEU Core Surrounded by a Copper Reflector

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These M&S tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to accurately model systems of interest, the industry must improve key nuclear data measurements and our confidence of how well we understand the data. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles benchmark experiment data in a handbook that can be used by criticality safety engineers to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the neutron energy within the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. This has caused the latest nuclear cross-section libraries to over/underestimate changes in the neutron population compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Need for Uncertainty Quantification in Predictions [Slides]

Natural and engineered systems are often modeled through mathematical equations using computer codes. Finite resources, inability to accurately control experimental conditions, encounter, or explore the entire parameter space of interest are a few reasons that scientists and engineers rely on numerical simulations for predictive capability. Associated with every prediction is an uncertainty, since our ability to simulate a physical process is limited by our knowledge of the physics, and the parameters. In the last two decades, the need for Uncertainty Quantification (UQ) has been recognized in several fields and we often ask questions about the risk or uncertainty associated with events and make decisions accordingly. In this talk, I will illustrate the effects of model and parametric uncertainties and the need to include them in our predictive capabilities.

97 MATHEMATICS AND COMPUTING↗

DYNGEN: A program for calculating steady-state and transient performance of turbojet and turbofan engines

The DYNGEN, a digital computer program for analyzing the steady state and transient performance of turbojet and turbofan engines, is described. The DYNGEN is based on earlier computer codes (SMOTE, GENENG, and GENENG 2) which are capable of calculating the steady state performance of turbojet and turbofan engines at design and off-design operating conditions. The DYNGEN has the combined capabilities of GENENG and GENENG 2 for calculating steady state performance; to these the further capability for calculating transient performance was added. The DYNGEN can be used to analyze one- and two-spool turbojet engines or two- and three-spool turbofan engines without modification to the basic program. A modified Euler method is used by DYNGEN to solve the differential equations which model the dynamics of the engine. This new method frees the programmer from having to minimize the number of equations which require iterative solution. As a result, some of the approximations normally used in transient engine simulations can be eliminated. This tends to produce better agreement when answers are compared with those from purely steady state simulations. The modified Euler method also permits the user to specify large time steps (about 0.10 sec) to be used in the solution of the differential equations. This saves computer execution time when long transients are run. Examples of the use of the program are included, and program results are compared with those from an existing hybrid-computer simulation of a two-spool turbofan.

Sellers, J. F.↗

Artificial Neural Network Representation of Dynamic Criticality Excursion Experiment Data

This paper outlines time dependent considerations in applying the artificial neural network (ANN) paradigm to dynamic nuclear criticality excursion experiment data. The ANN amongst a variety of uses, can apply to function fitting of multiple input-multiple output data sets, pattern recognition, cluster analysis, and time series prediction. The ANN is a component of Machine Learning (ML) data analysis. The practical application of ML to criticality safety has been funded through the Y-12 Plant Directed Research and Demonstration (PDRD) program to support criticality safety and emergency planning efforts. The initial effort considered function fitting of criticality excursion data. Recent efforts successfully extended the ANN to criticality safety code validation. The initial ANN work applied to criticality excursions centered around multivariate function fitting of static (tabular) data taken from the French Consequences Radiologiques d'un Accident de Criticite (CRAC) and SILENE reactor campaigns. The former report (LeCorche) summarized important tabular data for the first 44 CRAC experiments. The initial ANN was trained to specific time-independent inputs, then applied to predict peak fission rate and total fissions for a wide variety of fissile solutions process conditions. This work extends that effort to apply the ANN paradigm to dynamic prediction of time-dependent criticality excursion experiment data. A dynamic criticality excursion in fissile solution represents a complex multiphysics phenomenon. Factors include among other things, coupled neutronic, multiphase fluid flow, temperature, pressure, acoustic shock, boiling heat transfer, reactivity feedback, and radiolytic gas considerations. There have been many efforts to model (over time) as coupled ordinary and (space) as partial differential equations (ODE, PDE). The ANN representation noted here does not rely on solving explicit ODE or PDEs. Rather the intent is to demonstrate that as a time series, the criticality excursion can be predicted by training specific ANN architectures to experimental input and output time series exclusively. The rationale for extending this work to the time-dependent regime is important in developing a 'criticality excursion emulator' solely on the basis of learning characteristics from experiment dynamic data. An emulator is different than a computer code simulator driven by the solution of ODEs and PDEs given select 'tuning parameters' that match outputs to experiments. A criticality excursion emulator, derived exclusively from an ANN or ML, could predict most likely excursion characteristics, trained from historic dynamic experiment data, presented with input values within the range of those experiments. The work noted shows that generic time-series ANN architectures can be satisfactorily applied to the prediction of dynamic, extremely chaotic criticality excursion power given an initial time dependent input series. In reality, an excursion emulator could be driven by user-supplied initial (t=0), time independent or constant values to generate time dependent outputs. Thus ongoing work includes developing a custom ANN such that initial dynamic conditions would be predicted. Those results then serve as inputs to a customized ANN architecture currently in development. (author)

42 ENGINEERING↗

Predicting Flutter and Forced Response in Turbomachinery

TURBO-AE is a computer code that enables detailed, high-fidelity modeling of aeroelastic and unsteady aerodynamic characteristics for prediction of flutter, forced response, and blade-row interaction effects in turbomachinery. Flow regimes that can be modeled include subsonic, transonic, and supersonic, with attached and/or separated flow fields. The three-dimensional Reynolds-averaged Navier-Stokes equations are solved numerically to obtain extremely accurate descriptions of unsteady flow fields in multistage turbomachinery configurations. Blade vibration is simulated by use of a dynamic-grid-deformation technique to calculate the energy exchange for determining the aerodynamic damping of vibrations of blades. The aerodynamic damping can be used to assess the stability of a blade row. TURBO-AE also calculates the unsteady blade loading attributable to such external sources of excitation as incoming gusts and blade-row interactions. These blade loadings, along with aerodynamic damping, are used to calculate the forced responses of blades to predict their fatigue lives. Phase-lagged boundary conditions based on the direct-store method are used to calculate nonzero interblade phase-angle oscillations; this practice eliminates the need to model multiple blade passages, and, hence, enables large savings in computational resources.

VanZante, Dale E.↗

A Spreadsheet for the Mixing of a Row of Jets with a Confined Crossflow

An interactive computer code, written with a readily available software program, Microsoft Excel (Microsoft Corporation, Redmond, WA) is presented which displays 3 D oblique plots of a conserved scalar distribution downstream of jets mixing with a confined crossflow, for a single row, double rows, or opposed rows of jets with or without flow area convergence and/or a non-uniform crossflow scalar distribution. This project used a previously developed empirical model of jets mixing in a confined crossflow to create an Microsoft Excel spreadsheet that can output the profiles of a conserved scalar for jets injected into a confined crossflow given several input variables. The program uses multiple spreadsheets in a single Microsoft Excel notebook to carry out the modeling. The first sheet contains the main program, controls for the type of problem to be solved, and convergence criteria. The first sheet also provides for input of the specific geometry and flow conditions. The second sheet presents the results calculated with this routine to show the effects on the mixing of varying flow and geometric parameters. Comparisons are also made between results from the version of the empirical correlations implemented in the spreadsheet and the versions originally written in Applesoft BASIC (Apple Computer, Cupertino, CA) in the 1980's.

J D Holderman↗

A Spreadsheet for the Mixing of a Row of Jets with a Confined Crossflow

An interactive computer code, written with a readily available software program, Microsoft Excel (Microsoft Corporation, Redmond, WA) is presented which displays 3 D oblique plots of a conserved scalar distribution downstream of jets mixing with a confined crossflow, for a single row, double rows, or opposed rows of jets with or without flow area convergence and/or a non-uniform crossflow scalar distribution. This project used a previously developed empirical model of jets mixing in a confined crossflow to create an Microsoft Excel spreadsheet that can output the profiles of a conserved scalar for jets injected into a confined crossflow given several input variables. The program uses multiple spreadsheets in a single Microsoft Excel notebook to carry out the modeling. The first sheet contains the main program, controls for the type of problem to be solved, and convergence criteria. The first sheet also provides for input of the specific geometry and flow conditions. The second sheet presents the results calculated with this routine to show the effects on the mixing of varying flow and geometric parameters. Comparisons are also made between results from the version of the empirical correlations implemented in the spreadsheet and the versions originally written in Applesoft BASIC (Apple Computer, Cupertino, CA) in the 1980's.

J D Holderman↗

Prediction Uncertainties beyond the Range of Experience: A Case Study in Inertial Confinement Fusion Implosion Experiments

Scientists often predict physical outcomes, e.g., experimental results, with the assistance of computer codes that, at their best, only coarsely approximate reality. Coarse predictions are challenging in critical part due to the multitude of seemingly arbitrary yet consequential decisions that must be made such as choice of relevant data, calibration of code parameters, and construction of empirical discrepancy forms. In this paper, we present a case study in the context of inertial confinement fusion (ICF) implosion experiments where extrapolative predictions are needed with quantified uncertainties. The purpose of this case study is to reflect relevant statistical methods, as applied to ICF model fitting and prediction, to document the numerous decisions that must be made in the prediction pipeline, to extend a complex example in extrapolation to the uncertainty quantification (UQ) community, and to reflect on the challenges we encountered supporting extrapolations with imperfect models and thereby recommend several future research directions. We conclude with a discussion about the UQ community's role in less than ideal predictive scenarios like our ICF exercise.

97 MATHEMATICS AND COMPUTING↗

Ground Source Heat Pump Computational Results

This data submission includes simulation results for ground loop heat pump systems located in 6 different cities across the United States. The cities are Boston, MA, Dayton, OH, Omaha, NE, Orlando, FL, Sacramento, CA, and St. Paul, MN. These results were obtained from the two-dimensional geothermal computer code called GEO2D. GEO2D was written as part of this DOE funded grant. The results included in this submission for each of the 6 cities listed above are: 1) specific information on the building being heated or cooled by the ground loop geothermal system, 2) some extreme values for the building heating and cooling loads during the year, 3) the inputs required to carry out the simulation, 4) a plot of the hourly building heating and cooling loads throughout the year, 5) a plot of the fluid temperature exiting the ground loop for a 20 year period, 6) a plot of the heat exchange between the ground loop and the ground for a 20 year period, and 7) ground and ground loop temperature contour plots at different times of the year for the 20 year period.

15 GEOTHERMAL ENERGY↗