Mark Deinert

UTEX modeling of radioxenon isotopic fractionation resulting from subsurface transport

The underground transport of environmental xenon (UTEX) model is a finite-difference code that was developed at the University of Texas at Austin to simulate the transport of radioxenon from an underground nuclear detonation to the surface. UTEX handles a time dependent source term and includes the effects of radioactive decay to determine isotopic signatures of the various radioxenon species as a function of release time. The model shows that significant perturbations in the isotopic signatures are possible under some geologic conditions. Transport of radioxenon gas in UTEX is driven in large part by atmospheric pumping. A study was undertaken to characterize the dependence of resulting isotopic signatures on the various geologic and physical parameters that define the system model. Additionally, the model was used to roughly simulate isotopic measurements at various depths and position; the potential dependence of isotopic radioxenon fractionation on sampling depth and lateral position between fractures was examined.

Non-invasive material discrimination using spectral x-ray radiography

Current radiographic methods are limited in their ability to determine the presence of nuclear materials in containers or composite objects. A central problem is the inability to distinguish the attenuation pattern of high-density metals from those with a greater thickness of a less dense material. Here, we show that spectrally sensitive detectors can be used to discriminate plutonium from multiple layers of other materials using a single-view radiograph. An inverse algorithm with adaptive regularization is used. The algorithm can determine the presence of plutonium in simulated radiographs with a mass resolution per unit area of at least 0.07 g cm−2.

Potential for rooftop photovoltaics in Tokyo to replace nuclear capacity

In 2010, nuclear power accounted for 27% of electricity production in Japan. The March 2011 disaster at the Fukushima Daiichi power station resulted in the closure of all of Japan’s nuclear power plants and it remains an open question as to how many will reopen. Even before the loss of nuclear capacity, there were efforts in Japan to foster the use of renewable energy, including large scale solar power. Nuclear power plants in Japan provided more than just base-load by storing energy in large scale pumped hydroelectric storage systems, which was then released to provide some peaking capacity. If this storage were instead coupled to current generation rooftop solar systems in Tokyo, the combined system could help to meet peak requirements while at the same time providing 26.5% of the electricity Tokyo used to get from nuclear output, and do so 91% of the time. Data from a study of rooftop space and a 34 yr data set of average daily irradiance in the Tokyo metropolitan area were used. Using pumped hydroelectric storage with 5.6 times this rooftop area could completely provide for TEPCO’s nuclear capacity.

Performance and calibration of a neutron image intensifier tube based real-time radiography system

Image calibration is central to extending the capabilities of neutron radiography beyond mere visualization. However, the effects of scattered neutrons and variations in background image intensity adversely affect quantitative radiography. We describe the calibration of a real-time neutron radiography system that limits these effects and which is applicable to systems with variable digitizer gain and offset. A neutron image intensifier tube coupled to a vidicon camera with a capture rate of 30 frames/s was used. The system could account for 10 ml of water entering the field of view to within 2% and could measure the variation in thickness of a graphite wedge to within 2.3%. The spatial resolution was 450 /spl mu/m for a field of view of 410 cm/sup 2/. The image persistence half life was /spl sim/0.3 s and the system was functional for quantitative radiography with neutron fluxes above /spl sim/5*10/sup 5/n/cm/sup 2//s.

A model for the latent heat of melting in free standing metal nanoparticles

Nanoparticles of many metals are known to exhibit scale dependent latent heats of melting. Analytical models for this phenomenon have so far failed to completely capture the observed phenomena. Here we present a thermodynamic analysis for the melting of metal nanoparticles in terms of their internal energy and a scale dependent surface tension proposed by Tolman. The resulting model predicts the scale dependence of the latent heat of melting and is confirmed using published data for tin and aluminum.

Propagation of a solitary fission wave

Reaction-diffusion phenomena are encountered in an astonishing array of natural systems. Under the right conditions, self stabilizing reaction waves can arise that will propagate at constant velocity. Numerical studies have shown that fission waves of this type are also possible and that they exhibit soliton like properties. Here, we derive the conditions required for a solitary fission wave to propagate at constant velocity. The results place strict conditions on the shapes of the flux, diffusive, and reactive profiles that would be required for such a phenomenon to persist, and this condition would apply to other reaction diffusion phenomena as well. Numerical simulations are used to confirm the results and show that solitary fission waves fall into a bistable class of reaction diffusion phenomena.

Scale effects in the latent heat of melting in nanopores.

The curvature of a liquid vapor interface has long been known to change the equilibrium vapor pressure. It has also been shown that a capillary structure will affect the temperature at which both freezing and vaporization of a substance will occur. However, describing interfacial effects on the latent heat of a phase change has proven more difficult. Here, we present a classical thermodynamic model for how the latent heat of melting changes as the size of the particles undergoing the transition decreases. The scale dependence for the surface tension is taken into consideration using a Tolman length correction. The resulting model is tested by fitting to published experimental data for the latent heat of melting for benzene, heptane, naphthalene, and water contained in nano-porous glass. In all cases the model fits the data with a R(2) ≥ 0.94.

Comparison of Numerically Stable Methods for Implementation of a Double Porosity Model with First-Order Reaction Terms

The influence of barometric cycling on gas transport through complex media can be described using a double porosity model. Here vertical channels simulate the effect of cracks that pass through homogeneous regions of media. The cracks are coupled to the atmosphere and act as boundaries for the sections of homogeneous media. Convection–diffusion models are then used to simulate gas transport through the coupled system. This approach has been used to model soil aeration, subsurface movement of volatile compounds, and the migration of gases to the surface after below ground nuclear detonations. In the present work, we describe four stable numerical methods that can be used to implement the double porosity model when first-order reactions produce and consume the gaseous species of interest. We find that all four methods satisfy analytical crosschecks and agree to at least seven digits of precision. An iterative solver based on Newton’s method is found to be optimal as it is easily scalable to 3-D models and to multithreaded execution.

A Rapid Computational Method for Reducing the Search Space Required in Nuclear Reactor Optimization

Reactor optimization is central to increasing the efficiency of nuclear fuel cycles and critical for making meaningful comparisons between different design options. Optimization algorithms work by generating trial parameter sets which can be used as inputs to reactor physics models. Unfortunately, many reactor physics codes require substantial CPU time, making optimization of large parameter sets impractical. We have developed a method for finding optima within an N-dimensional parameter space using a fast, flexible reactor physics model that is capable of performing fuel burnup calculations on the order of once per second. Global optima found in this way can then be verified using a high fidelity reactor physics code. We demonstrate our approach by considering a simple fuel pin pitch optimization for a light-water reactor, and we find our code executes in 5 minutes. Repeating this approach using a high-fidelity Monte Carlo simulation requires approximately 15 days of runtime by contrast.Copyright