The relationship between explosive yield and seismic magnitude has been extensively studied for underground nuclear tests larger than about 1 kt. For monitoring smaller tests over local ranges (within 200 km), we need to know whether the available formulas can be extrapolated to much lower yields. Here, we review published information on amplitude decay with distance, and on the seismic magnitudes of industrial blasts and refraction explosions in the western U. S. Next we measure the magnitudes of some similar shots in the northeast. We find that local magnitudes ML of small, contained explosions are reasonably consistent with the magnitude-yield formulas developed for nuclear tests. These results are useful for estimating the detection performance of proposed local seismic networks.
In many parts of the United States, as well as other regions of the world, competing demands for fresh water or water suitable for desalination are outstripping sustainable supplies. In these areas, new water supplies are necessary to sustain economic development and agricultural uses, as well as support expanding populations, particularly in the Southwestern United States. Increasing the supply of water will more than likely come through desalinization of water reservoirs that are not suitable for present use. Surface-deployed seismic and electromagnetic (EM) methods have the potential for addressing these critical issues within large volumes of an aquifer at a lower cost than drilling and sampling. However, for detailed analysis of the water quality, some sampling utilizing boreholes would be required with geophysical methods being employed to extrapolate these sampled results to non-sampled regions of the aquifer. The research in this report addresses using seismic and EM methods in two complimentary ways to aid in the identification of water reservoirs that are suitable for desalinization. The first method uses the seismic data to constrain the earth structure so that detailed EM modeling can estimate the pore water conductivity, and hence the salinity. The second method utilizes the coupling of seismic and EM waves through the seismo-electric (conversion of seismic energy to electrical energy) and the electro-seismic (conversion of electrical energy to seismic energy) to estimate the salinity of the target aquifer. Analytic 1D solutions to coupled pressure and electric wave propagation demonstrate the types of waves one expects when using a seismic or electric source. A 2D seismo-electric/electro-seismic is developed to demonstrate the coupled seismic and EM system. For finite-difference modeling, the seismic and EM wave propagation algorithms are on different spatial and temporal scales. We present a method to solve multiple, finite-difference physics problems that has application beyond the present use. A limited field experiment was conducted to assess the seismo-electric effect. Due to a variety of problems, the observation of the electric field due to a seismic source is not definitive.
We investigate the potential for neutron generation using the 1 MeV RHEPP-1 intense pulsed ion beam facility at Sandia National Laboratories for a number of emerging applications. Among these are interrogation of cargo for detection of special nuclear materials (SNM). Ions from single-stage sources driven by pulsed power represent a potential source of significant neutron bursts. While a number of applications require higher ion energies (e.g. tens of MeV) than that provided by RHEPP-1, its ability to generate deuterium beams allow for neutron generation at and below 1 MeV. This report details the successful generation and characterization of deuterium ion beams, and their use in generating up to 3 x 10{sup 10} neutrons into 4{pi} per 5kA ion pulse.
This paper has three goals. The first is to review Shannon's theory of information and the subsequent advances leading to today's statistics-based text analysis algorithms, showing that the semantics of the text is neglected. The second goal is to propose an extension of Shannon's original model that can take into account semantics, where the 'semantics' of a message is understood in terms of the intended or actual changes on the recipient of a message. The third goal is to propose several lines of research that naturally fall out of the proposed model. Each computational approach to solving some problem rests on an underlying model or set of models that describe how key phenomena in the real world are represented and how they are manipulated. These models are both liberating and constraining. They are liberating in that they suggest a path of development for new tools and algorithms. They are constraining in that they intentionally ignore other potential paths of development. Modern statistical-based text analysis algorithms have a specific intellectual history and set of underlying models rooted in Shannon's theory of communication. For Shannon, language is treated as a stochastic generator of symbol sequences. Shannon himself, subsequently Weaver, and at least one of his predecessors are all explicit in their decision to exclude semantics from their models. This rejection of semantics as 'irrelevant to the engineering problem' is elegant and combined with developments particularly by Salton and subsequently by Latent Semantic Analysis, has led to a whole collection of powerful algorithms and an industry for data mining technologies. However, the kinds of problems currently facing us go beyond what can be accounted for by this stochastic model. Today's problems increasingly focus on the semantics of specific pieces of information. And although progress is being made with the old models, it seems natural to develop or extend information theory to account for semantics. By developing such theory, we can improve the quality of the next generation analytical tools. Far from being a mere intellectual curiosity, a new theory can provide the means for us to take into account information that has been to date ignored by the algorithms and technologies we develop. This paper will begin with an examination of Shannon's theory of communication, discussing the contributions and the limitations of the theory and how that theory gets expanded into today's statistical text analysis algorithms. Next, we will expand Shannon's model. We'll suggest a transactional definition of semantics that focuses on the intended and actual change that messages are intended to have on the recipient. Finally, we will examine implications of the model for algorithm development.
An initial version of a Systems Dynamics (SD) modeling framework was developed for the analysis of a broad range of energy technology and policy questions. The specific question selected to demonstrate this process was 'what would be the carbon and import implications of expanding nuclear electric capacity to provide power for plug in hybrid vehicles?' Fifteen SNL SD energy models were reviewed and the US Energy and Greenhouse gas model (USEGM) and the Global Nuclear Futures model (GEFM) were identified as the basis for an initial modeling framework. A basic U.S. Transportation model was created to model U.S. fleet changes. The results of the rapid adoption scenario result in almost 40% of light duty vehicles being PHEV by 2040 which requires about 37 GWy/y of additional electricity demand, equivalent to about 25 new 1.4 GWe nuclear plants. The adoption rate of PHEVs would likely be the controlling factor in achieving the associated reduction in carbon emissions and imports.
The density of molten nitrate salts was measured to determine the effects of the constituents on the density of multi-component mixtures. The molten salts consisted of various proportions of the nitrates of potassium, sodium, lithium and calcium. Density measurements ere performed using an Archimedean method and the results were compared to data reported in the literature for the individual constituent salts or simple combinations, such as the binary Solar Salt mixture of NaNO3 and KNO3. The addition of calcium nitrate generally ncreased density, relative to potassium nitrate or sodium nitrate, while lithium nitrate decreased density. The temperature dependence of density is described by a linear equation regardless of composition. The molar volume, and thereby, density of multi-component mixtures an be calculated as a function of temperature using a linear additivity rule based on the properties of the individual constituents.
This report documents the various photovoltaic (PV) performance models and software developed and utilized by researchers at Sandia National Laboratories (SNL) in support of the Photovoltaics and Grid Integration Department. In addition to PV performance models, hybrid system and battery storage models are discussed. A hybrid system using other distributed sources and energy storage can help reduce the variability inherent in PV generation, and due to the complexity of combining multiple generation sources and system loads, these models are invaluable for system design and optimization. Energy storage plays an important role in reducing PV intermittency and battery storage models are used to understand the best configurations and technologies to store PV generated electricity. Other researcher's models used by SNL are discussed including some widely known models that incorporate algorithms developed at SNL. There are other models included in the discussion that are not used by or were not adopted from SNL research but may provide some benefit to researchers working on PV array performance, hybrid system models and energy storage. The paper is organized into three sections to describe the different software models as applied to photovoltaic performance, hybrid systems, and battery storage. For each model, there is a description which includes where to find the model, whether it is currently maintained and any references that may be available. Modeling improvements underway at SNL include quantifying the uncertainty of individual system components, the overall uncertainty in modeled vs. measured results and modeling large PV systems. SNL is also conducting research into the overall reliability of PV systems.
Longcope Jr., Donald B.; Warren, Thomas L.; Duong, Henry
In this paper we develop an aft-body loading function for penetration simulations that is based on the spherical cavity-expansion approximation. This loading function assumes that there is a preexisting cavity of radius a{sub o} before the expansion occurs. This causes the radial stress on the cavity surface to be less than what is obtained if the cavity is opened from a zero initial radius. This in turn causes less resistance on the aft body as it penetrates the target which allows for greater rotation of the penetrator. Results from simulations are compared with experimental results for oblique penetration into a concrete target with an unconfined compressive strength of 23 MPa.
Biofouling, the unwanted growth of biofilms on a surface, of water-treatment membranes negatively impacts in desalination and water treatment. With biofouling there is a decrease in permeate production, degradation of permeate water quality, and an increase in energy expenditure due to increased cross-flow pressure needed. To date, a universal successful and cost-effect method for controlling biofouling has not been implemented. The overall goal of the work described in this report was to use high-performance computing to direct polymer, material, and biological research to create the next generation of water-treatment membranes. Both physical (micromixers - UV-curable epoxy traces printed on the surface of a water-treatment membrane that promote chaotic mixing) and chemical (quaternary ammonium groups) modifications of the membranes for the purpose of increasing resistance to biofouling were evaluated. Creation of low-cost, efficient water-treatment membranes helps assure the availability of fresh water for human use, a growing need in both the U. S. and the world.