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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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This paper summarizes the progress in the use of non-invasive methods for measuring liquid level in small modular nuclear reactors. High precision gravimeters are used to measure changes in liquid level in a test facility environment, and results are compared to simulations. Possible configurations for the meters use in the NuScale SMR are also discussed. (authors)
Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. One limitation of the DDET driver codes developed to date (namely ADAPT, ADS, and MCDET ) is that the tree is driven by a single simulator. The goal of this work is a general multi-simulator driver. This limits the parameter space that may be explored in a single DDET to that which may be covered by a single simulator. In this work, the Analysis of Dynamic Accident Progression Trees (ADAPT) code is extended to support multiple arbitrary simulators. This capability will increase the depth and breadth of phenomena that may be analyzed in a single DDET. For example, a large-scale system code may pass the analysis to a more detailed code if certain conditions are met, in order to capture relevant phenomena that would be lost if only the system code were to be used. In addition, the time required to cover a given uncertainty space may be reduced by dynamically identifying and running only the situations that are appropriate given the plant conditions in each simulator. The use of multiple simulators is expected to further reduce subjectivity in PRA by enabling high fidelity modeling of reality. (authors)
The quasi-differential neutron induced neutron emission reaction measurement (QD-NINE) method provides an additional benchmark which constrains cross-section evaluations and provides a measure of verification for existing evaluations. Experiments are preformed using an array of EJ-309 liquid scintillators at a variety of angles measuring the neutron scattering response from a sample.. An MCNP simulation is then compared to this experimental data and is run using various sets of evaluated nuclear data. Since the isotopes of interest for this measurement, {sup 235}U and {sup 239}Pu, are difficult to obtain, the WNR facility at LANL was chosen to perform the measurements utilizing the chi-nu detector array. A measurement of carbon has been performed and the high energy cutoff has been extended from 20 to 60 MeV compared with previous measurements using this method. An early stage simulation was compared to the experimental data and the results show good agreement. (authors)
In the safety analysis of loss-of-coolant-accident (LOCA) and steam generator tube rupture (SGTR) scenarios of light water reactors, a modeling of a break is very important to predict the accident's result. For example, the design of a break simulator to simulate a LOCA in light water reactors requires accurate knowledge of the leakage flow through the break, whose shape can be assumed as an orifice or a nozzle according to the characteristics of the break shape. In the case of a small-break LOCA (SBLOCA) scenario, the critical flow mostly occurs by sub-cooled and saturated liquid water including a two-phase water flow at relatively high-pressure conditions. Among previous critical flow maps, Moody's maps are well known for their critical flow rate and pressure of a single component and two-phase mixture with respect to the upstream enthalpy and pressure. In Moody's model, a slip ratio defined by maximizing the critical flow rate with respect to the slip ratio was introduced, and thus its predictions tended to be too conservative. Later, Moody suggested other maps based on a homogeneous equilibrium model (HEM), and they were useful to predict a choked condition for a given upstream condition. However, their predictions of the critical flow rate seemed to show quite an underestimation compared to various test data. The author suggested more practicable critical flow maps for a critical mass flux and pressure of a steam-water flow with respect to the upstream stagnation conditions using an extended Henry-Fauske model. From a comparison with the selected test data, suggested maps showed conservative predictions within reasonable ranges. In this report, a new correlation for the critical flow rate was developed to simulate the suggested critical flow maps within a reasonable range of error. (authors)
License applications for sodium fast reactors will include sodium fire analysis and subsequent mitigation strategies. Sodium leaks or ruptures from piping and support systems can lead to significant fires due to the reactive nature of sodium with air and water. Understanding the behavior of sodium fires is crucial for modeling and predicting accidents in sodium fast reactors. This paper describes the initial results of a control volume code, CONTAIN-LMR (CLMR), modeling effort for a sodium spray fire experiment conducted at Sandia National Laboratories (SNL) in Albuquerque, New Mexico in 2010. Additional sodium spray and pool fire tests were conducted at SNL in 2009 and 2010 and will be compared to CLMR results in future papers. The purpose of this analysis was extract information from the evolution of the SNL tests to better understand how to use CLMR in future sodium fire analysis. Thus the following CLMR simulations were not completely the result of blind benchmarking study. (authors)
A recent international inter-code comparison exercise for criticality excursion analysis demonstrated that the transient criticality codes participating the exercise are showed to reproduce well the initial peak power compared with measurements performed with TRACY and SILENE reactors. However the oscillatory behavior after peak power is less well reproduced. The integrated behavior in term of energy release is quite well reproduced. The recent experiments performed with TRACY JAEA's reactor and the analytic interpretation of void clustering during prompt critical have suggested a simplified vibration model of a damped oscillator. Finally a recent ICNC paper by present authors offered a perfect correlation between peak pressure and peak power. Owing to these three facts the present paper aims at proposing a new system of equations for the dynamic of a critical excursion taking into account gas bubble generation after exceeding the solubility threshold of dissolved radiolytic gas. The model explains why the simple vibration model of the JAEA school fairly represent pressure dynamic records at moderate peak pressure as measured with SILENE reactor. Also, an important parameter of the proposed model, namely the rate of transfer from dissolved gas to gas bubbles, is fixed by the correlation between peak pressure and peak power. Thus the model has one less tunable parameter and can predict a large range of critical low pressure excursions. After presentation of the model and discussion of some of its important features, some numerical simulations are made based upon SILENE and TRACY transient experiments ranging from tenths of kPa to several bars and comparisons are presented between calculated results and experimentally recorded one's. (authors)
The magnetohydrodynamic (MHD) kinematics model describes the electromagnetic behavior of an electrically conducting fluid when its hydrodynamic properties are assumed to be known. In particular, the MHD kinematics equations can be used to simulate the magnetic field induced by a given velocity field. While prescribing the velocity field leads to a simpler model than the fully coupled MHD system, this may introduce some epistemic uncertainty into the model. If the velocity of a physical system is not known with certainty, the magnetic field obtained from the model may not be reflective of the magnetic field seen in experiments. Additionally, uncertainty in physical parameters such as the magnetic resistivity may affect the reliability of predictions obtained from this model. By modeling the velocity and the resistivity as random variables in the MHD kinematics model, we seek to quantify the effects of uncertainty in these fields on the induced magnetic field. We develop stochastic expressions for these quantities and investigate their impact within a finite element discretization of the kinematics equations. We obtain mean and variance data through Monte Carlo simulation for several test problems. Toward this end, we develop and test an efficient block preconditioner for the linear systems arising from the discretized equations.
Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.
The P2 experiment at the MESA facility in Mainz aims to make a high precision measurement of the weak charge of the proton, and a suitable experimental setup is currently being designed [1]. As high precision measurements of the weak charges of different particles and nuclei are differently sensitive to physics beyond the Standard Model in the form of new quantum loop correction parameters, experiments with a range of different target materials are complementary. We introduce first feasibility considerations for the determination of the Weak Mixing Angle via the scattering of electrons from carbon nuclei in a graphite target with the P2 detector setup. In order to make an estimate of the achievable precision we present analytic calculations as well as Monte-Carlo simulations. The results of Geant4 simulations of proposed experimental setups are included.
An all-optical pump-probe technique has been employed to investigate the nonlinear magnetization dynamics of a 10 nm Fe/MgO(001) thin film in time domain. The magnetization precession was excited by pump-laser pulses and modulated by laser fluence variations. With increasing the laser fluence up to 7.1 mJ/cm{sup 2}, in addition to the uniform precession mode, a second harmonic signal was detected. The time evolution of the second harmonic signal was obtained in time-frequency domain. Based on the Landau-Lifshitz-Gilbert equation, the numerical simulation was performed to reproduce the observed the frequency doubling behaviors in Fe/MgO(001) film.
In order to investigate the intense laser propagation and channel formation in dense plasma, we conducted an experiment with proton deflectometry on the OMEGA EP Laser facility. The proton image was analyzed by tracing the trajectory of mono-energetic protons, which provides understanding the electric and magnetic fields that were generated around the channel. The estimated field strengths (E ∼ 10{sup 11} V/m and B ∼ 10{sup 8} G) agree with the predictions from 2D-Particle-in-cell (PIC) simulations, indicating the feasibility of the proton deflectometry technique for over-critical density plasma.
Presented study concerns numerical simulation of Physical Vapor Transport (PVT) growth of bulk Silicon Carbide (SiC) crystals. Silicon Carbide is a wide band gap semiconductor, with numerous applications due to its unique properties. Wider application of SiC is limited by high price and insufficient quality of the product. Those problems can be overcame by optimizing SiC production methods. Experimental optimization of SiC production is expensive because it is time consuming and requires large amounts of energy. Numerical modeling allows to learn more about conditions inside the reactor and helps to optimize the process at much lower cost. In this study several simulations of processes with different reactor geometries were presented along with discussion of reactor geometry influence on obtained monocrystal shape and size.
The turbulence observed in the scrape-off-layer of a tokamak is often characterized by intermittent events of bursty nature, a feature which raises concerns about the prediction of heat loads on the physical boundaries of the device. It appears thus necessary to delve into the statistical properties of turbulent physical fields such as density, electrostatic potential, and temperature, focusing on the mathematical expression of tails of the probability distribution functions. The method followed here is to generate statistical information from time-traces of the plasma density stemming from Braginskii-type fluid simulations and check this against a first-principles theoretical model. The analysis of the numerical simulations indicates that the probability distribution function of the intermittent process contains strong exponential tails, as predicted by the analytical theory.
Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was used in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.
Applied and material physics studies with positron beams of Fermi–surfaces, defects, interfaces etc. offer excellent diagnostics tools. At ELI-NP, an intense γ beam of about 10{sup 11} photons/s with energies up to 3.5 MeV will be used to generate a positron beam via pair production in a tungsten converter target. To obtain a high intensity beam of moderated positrons the design of the positron source is of high importance. The design of a dedicated positron source at ELI–NP is being investigated based on extensive GEANT4 simulations. The goal of the simulations is to optimize the geometry of the target and the gamma beam collimation. We present here the characteristics of the positron beam obtained for different geometries of the converter target.
Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but also make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.
In the present paper, a design methodology of the gyroklystron amplifier has been described and subsequently used for the design of a typically selected 200 kW, Ka-band, four-cavity gyroklystron amplifier. This conceptual device design has been validated through the 3D particle-in-cell (PIC) simulation and nonlinear analysis. Commercially available PIC simulation code “MAGIC” has been used for the electromagnetic study at the different location of the device RF interaction structure for the beam-absent case, i.e., eigenmode study as well as for the electron beam and RF wave interaction behaviour study in the beam present case of the gyroklystron. In addition, a practical problem of misalignment of the RF cavities with drift tubes within the tube has been also investigated and its effect on device performance studied. The analytical and simulation results confirmed the validity of the gyroklystron device design. The PIC simulation results of the present gyroklystron produced a stable RF output power of ∼218 kW for 0% velocity spread at 35 GHz, with ∼45 dB gain, 37% efficiency, and a bandwidth of 0.3% for a 70 kV, 8.2 A gyrating electron beam. The simulated values of RF output power have been found in agreement with the nonlinear analysis results within ∼5%. Further, the PIC simulation has been extended to study a practical problem of misalignment of the cavities axis and drift tube axis of the gyroklystron amplifier and found that the RF output power is more sensitive to misalignments in comparison to the device bandwidth. The present paper, gyroklystron device design, nonlinear analysis, and 3D PIC simulation using commercially available code had been systematically described would be of use to the high-power gyro-amplifier tube designers and research scientists.
In conventional nuclear magnetic resonance (NMR) diffusion measurements a significant amount of experimental time is used up by magnetization recovery, serving to prevent the formation of the steady state, as in the latter case the manifestation of diffusion is modulated by multiple applications of the pulse sequence and conventional diffusion coefficient inference procedures are generally not applicable. Here, an analytical expression for diffusion-related effects in a two-pulse NMR experiment (e.g., pulsed-gradient spin echo) in the steady state mode (with repetition times less than the longitudinal relaxation time of the sample) is derived by employing a Fourier series expansion within the solution of the Bloch-Torrey equations. Considerations are given for the transition conditions between the full relaxation and the steady state experiment description. The diffusion coefficient of a polymer solution (polyethylene glycol) is measured by a two-pulse sequence in the full relaxation mode and for a range of repetition times, approaching the rapid steady state experiment. The precision of the fitting employing the presented steady state solution by far exceeds that of the conventional fitting. Additionally, numerical simulations are performed yielding results strongly supporting the proposed description of the NMR diffusion measurements in the steady state.