Simulation and Modeling of Return Waveforms from a Ladar Beam Footprint in USU LadarSIM

Ladar systems are an emerging technology with applications in many fields. Consequently, simulations for these systems have become a valuable tool in the improvement of existing systems and the development of new ones. This paper discusses the theory and issues involved in reliably modeling the return waveform of a ladar beam footprint in the Utah State University LadarSIM simulation software. Emphasis is placed on modeling system-level effects that allow an investigation of engineering tradeoffs in preliminary designs, and validation of behaviors in fabricated designs. Efforts have been made to decrease the necessary computation time while still maintaining a usable model. A full waveform simulation is implemented that models optical signals received on detector followed by electronic signals and discriminators commonly encountered in contemporary direct-detection ladar systems. Waveforms are modeled using a novel hexagonal sampling process applied across the ladar beam footprint. Each sample is weighted using a Gaussian spatial profile for a well formed laser footprint. Model fidelity is also improved by using a bidirectional reflectance distribution function (BRDF) for target reflectance. Once photons are converted to electrons, waveform processing is used to detect first, last or multiple return pulses. The detection methods discussed in this paper are a threshold detection method, a constant fraction method, and a derivative zero-crossing method. Various detection phenomena, such as range error, walk error, drop outs and false alarms, can be studied using these detection methods

Modeling overland flow and soil erosion on nonuniform hillslopes: a finite volume scheme.

This paper presents a finite volume scheme for coupling the St. Venant equations with the multi- particle size class Hairsine-Rose soil erosion model. A well-balanced MUSCL-Hancock scheme is proposed to minimize spurious waves in the solution arising from an imbalance between the flux gradient and the source terms in the momentum equation. Additional criteria for numerical stability when dealing with very shallow flows and wet-dry fronts are highlighted. Numerical tests show that the scheme performs well in terms of accuracy and robustness for both the water and sediment transport equations. The proposed scheme facilitates the application of the Hairsine-Rose model to complex scenarios of soil erosion with concurrent interacting erosion processes over a non-uniform topography

Pippi - painless parsing, post-processing and plotting of posterior and likelihood samples

Interpreting samples from likelihood or posterior probability density functions is rarely as straightforward as it seems it should be. Producing publication-quality graphics of these distributions is often similarly painful. In this short note I describe pippi, a simple, publicly-available package for parsing and post-processing such samples, as well as generating high-quality PDF graphics of the results. Pippi is easily and extensively configurable and customisable, both in its options for parsing and post-processing samples, and in the visual aspects of the figures it produces. I illustrate some of these using an existing supersymmetric global fit, performed in the context of a gamma-ray search for dark matter. Pippi can be downloaded and followed at http://github.com/patscott/pippi .Comment: 4 pages, 1 figure. v3: Updated for pippi 2.0. New features include hdf5 support, out-of-core processing, inline post-processing with arbitrary Python code in the input file, and observable-specific data cuts. Pippi can be downloaded from http://github.com/patscott/pipp

Near-Earth asteroid sample return missions

The rate of discovery of new NEAs and the success of D-S 1 and NEAR-Shoemaker, suggest that sample return from NEAs is now technically feasible. Here we present a summary of a recent workshop on the topic

The Abundance of New Kind of Dark Matter Structures

A new kind of dark matter structures, ultracompact minihalos (UCMHs) was proposed recently. They would be formed during the radiation dominated epoch if the large density perturbations are existent. Moreover, if the dark matter is made up of weakly interacting massive particles, the UCMHs can have effect on cosmological evolution because of the high density and dark matter annihilation within them. In this paper, one new parameter is introduced to consider the contributions of UCMHs due to the dark matter annihilation to the evolution of cosmology, and we use the current and future CMB observations to obtain the constraint on the new parameter and then the abundance of UCMHs. The final results are applicable for a wider range of dark matter parametersComment: 4 pages, 1 tabl

Modeling the dynamics of soil erosion and size-selective sediment transport over nonuniform topography in flume-scale experiments

Soil erosion and the associated nutrient fluxes can lead to severe degradation of surface waters. Given that both sediment transport and nutrient sorption are size selective, it is important to predict the particle size distribution (PSD) as well as the total amount of sediment being eroded. In this paper, a finite volume implementation of the Hairsine-Rose soil erosion model is used to simulate flume-scale experiments with detailed observations of soil erosion and sediment transport dynamics. The numerical implementation allows us to account for the effects of soil surface microtopography (measured using close range photogrammetry) on soil erosion. An in-depth discussion of the model parameters and the constraints is presented. The model reproduces the dynamics of sediment concentration and PSD well, although some discrepancies can be observed. The calibrated parameters are also consistent with independent data in the literature and physical reason. Spatial variations in the suspended and deposited sediment and an analysis of model sensitivity highlight the value of collecting distributed data for a more robust validation of the model and to enhance parametric determinacy. The related issues of spatial resolution and scale in erosion prediction are briefly discussed

Statistical coverage for supersymmetric parameter estimation: a case study with direct detection of dark matter

Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the employed statistical framework and scanning algorithm. In frequentist parameter estimation, a central requirement for properly constructed confidence intervals is that they cover true parameter values, preferably at exactly the stated confidence level when experiments are repeated infinitely many times. Since most widely-used scanning techniques are optimised for Bayesian statistics, one needs to assess their abilities in providing correct confidence intervals in terms of the statistical coverage. Here we investigate this for the Constrained Minimal Supersymmetric Standard Model (CMSSM) when only constrained by data from direct searches for dark matter. We construct confidence intervals from one-dimensional profile likelihoods and study the coverage by generating several pseudo-experiments for a few benchmark sets of pseudo-true parameters. We use nested sampling to scan the parameter space and evaluate the coverage for the benchmarks when either flat or logarithmic priors are imposed on gaugino and scalar mass parameters. The sampling algorithm has been used in the configuration usually adopted for exploration of the Bayesian posterior. We observe both under- and over-coverage, which in some cases vary quite dramatically when benchmarks or priors are modified. We show how most of the variation can be explained as the impact of explicit priors as well as sampling effects, where the latter are indirectly imposed by physicality conditions. For comparison, we also evaluate the coverage for Bayesian credible intervals, and observe significant under-coverage in those cases.Comment: 30 pages, 5 figures; v2 includes major updates in response to referee's comments; extra scans and tables added, discussion expanded, typos corrected; matches published versio

Mathematical Model of the Oxidation of a Uranium Carbide Fuel Pellet Including an Adherent Product Layer

Uranium carbide is a candidate fuel for Generation IV nuclear reactors. However, like any candidate fuel, a reprocessing route should be established before implementation. One proposed method involves a pre-oxidation step, where the carbide fuel is oxidised to an oxide and then reprocessed as normal. A mathematical model has been developed to simulate such an oxidation using finite difference approximations of the heat and mass transfer processes occurring. Available literature was consulted to provide coefficients for the reaction rates and importantly the diffusion of oxygen through the adherent oxide layer that forms on the carbide: the rate limiting step. The transient temperature, oxygen and carbon monoxide distributions through the system are modelled in order to predict oxidation completion times and the temperatures reached. It was found that for a spherical pellet of radius 0.935cm, the oxidation can take between 1 h to 19 h depending on the oxidation conditions and reach temperatures of up to 1556°C. A robust model results that offers increased understanding of a process crucial to the sustainable use of carbide fuels in energy generation