The performance of NIF target designs is simulated in three dimensions using the HYDRA multiphysics radiation hydrodynamics code. In simulations of a cylindrical NIF hohlraum that include an imploding capsule, the motion of the wall material inside the hohlraum shows a high degree of axisymmetry. Laser radiation is able to propagate through the entrance hole for the required duration of the pulse. Gross hohlraum energetics in the simulation mirror the results from an axisymmetric simulation. A simulation of a copper-doped beryllium ablator NIF capsule carried out over large solid angle resolved the full spectrum of the most dangerous modes that grow from surface roughness. Hydrodynamic instabilities evolve into the weakly nonlinear regime. There is no evidence of low mode jetting driven by nonlinear mode coupling.

The thermal-hydrologic (TH) and coupled process models describe the evolution of a potential geologic repository as heat is released from emplaced waste. The evolution (thermal, hydrologic, chemical, and mechanical) of the engineered barrier and geologic systems is heavily dependent on the heat released by the waste packages and how the heat is transferred from the emplaced wastes through the drifts and through the repository host rock. The essential elements of this process are extracted (or abstracted) from the process-level models that incorporate the basic energy and mass conservation principles and applied to the total system models used to describe the overall performance of the potential repository. The process of total system performance assessment (TSPA) abstraction is the following. First is a description of the parameter inputs used in the process-level models. A brief description is given hereof past inputs for the viability assessment (e.g., for TSPA-VA) and current inputs for the site recommendation (TSPA-SR). This is followed by a highlight of the process-level models from which the abstractions are made. These include descriptions of TH, thermal-hydrologic-chemical (THC), and thermal-mechanical (TM) processes used to describe the performance of individual waste packages and waste emplacement drifts as well as the repository as …

Jefferson Lab, Hampton University and the Riverside Regional Medical Center are collaborating in a clinical study employing a dual modality imaging system utilizing scintimammography and digital radiography. The purpose of the study is to obtain clinical data on the reliability of scintimammography in predicting the malignancy of suspected breast lesions with the ultimate goal to reduce the number of false positives associated with conventional x-ray mammography. The scintimammography gamma camera is a custom built mini gamma camera with an active area of 5.3 cm x 5.3 cm based on a 2x2 array of Hamamatsu R7600-C8 position sensitive photomultiplier tubes. The spatial resolution of the gamma camera at the collimator surface is <4 mm FWHM and the sensitivity is 4000 cps/mCi. Preliminary results are that of the six cases that indicated a lesion with high uptake of MiraLuma ({sup 99m}Tc-sestamibi) five were positive for cancer. Out of a total of 25 patients in the study, all cases negative for MiraLuma uptake were confirmed negative via the biopsy pathology. The scintimammography results indicate that the lesions become visible with the mini gamma camera within 3 minutes post injection of MiraLuma.

This article describes the design rationale, a C implementation, and conformance testing of a subset of the new Standard for the BLAS (Basic Linear Algebra Subroutines): Extended and Mixed Precision BLAS. Permitting higher internal precision and mixed input/output types and precisions allows us to implement some algorithms that are simpler, more accurate, and sometimes faster than possible without these features. The new BLAS are challenging to implement and test because there are many more subroutines than in the existing Standard, and because we must be able to assess whether a higher precision is used for internal computations than is used for either input or output variables. We have therefore developed an automated process of generating and systematically testing these routines. Our methodology is applicable to languages besides C. In particular, our algorithms used in the testing code will be valuable to all other BLAS implementors. Our extra precision routines achieve excellent performance--close to half of the machine peak Megaflop rate even for the Level 2 BLAS, when the data access is stride one.

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In this paper a two pronged approach is taken to investigating the energy required for ignition of inertial confinement fusion capsules. A series of one dimensional LASNEX simulations is performed to create a database of barely ignited capsules that span the parameter regime Of interest. This database is used to develop scaling laws for the ignition energy in terms of both the stagnated capsule parameters and the inflight capsule parameters, and explore the connection between these two parameter sets. The second part of this paper examines how much extra energy is required to overcome the effect of the inevitable surface imperfections that are amplified during the implosion process and can lead to capsule break up in flight or to mix of cold fuel into the hotspot, both of which can cause the capsule to fail to ignite. By means of an example, the optimization of a capsule with fixed adiibat, drive pressure, and absorbed energy is performed; the capsule that is maximally robust to these failure modes is found.

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For many nuclei beyond the proton drip line in the Z>72, N>82 region, both proton and a emission are energetically allowed. In the case of some proton emitters, there are {alpha}-decay chains emanating from both parent and daughter nuclei. This means that if the mass excess of one member of an {alpha}-decay chain is known, then the mass excesses for all members of both chains can be obtained. In addition, proton separation energies may be derived for nuclei in the {alpha}-decay chain of the proton emitter. The method of time- and space-correlations also allows the identification of isomeric states in these nuclei. As an example, a large number of mass excesses and proton separation energies for ground and metastable states have been derived from Q{sub a} and Q{sub p} values obtained from the proton emitters {sup 165,166,167}Ir, {sup 171}Au, {sup 177}Tl, and their daughters.

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In this paper an optimization-based method of drift prevention is presented for learning control of underdetermined linear and weakly nonlinear time-varying dynamic systems. By defining a fictitious cost function and the associated model-based sub-optimality conditions, a new set of equations results, whose solution is unique, thus preventing large drifts from the initial input. Moreover, in the limiting case where the modeling error approaches zero, the input that the proposed method converges to is the unique feasible (zero error) input that minimizes the fictitious cost function, in the linear case, and locally minimizes it in the (weakly) nonlinear case. Otherwise, under mild restrictions on the modeling error, the method converges to a feasible sub-optimal input.

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Monte Carlo is an extremely powerful method of simulating complex, three dimensional environments without excessive problem simplification. However, it is often time consuming to simulate models in which the source can be highly varied. Similarly difficult are optimization studies involving sources in which many input parameters are variable, such as particle energy, angle, and spatial distribution. Such studies are often approached using brute force methods or intelligent guesswork. One field in which these problems are often encountered is accelerator-driven Boron Neutron Capture Therapy (BNCT) for the treatment of cancers. Solving the reverse problem of determining the best neutron source for optimal BNCT treatment can be accomplished by separating the time-consuming particle-tracking process of a full Monte Carlo simulation from the calculation of the source weighting factors which is typically performed at the beginning of a Monte Carlo simulation. By post-processing these weighting factors on a recorded file of individual particle tally information, the effect of changing source variables can be realized in a matter of seconds, instead of requiring hours or days for additional complete simulations. By intelligent source biasing, any number of different source distributions can be calculated quickly from a single Monte Carlo simulation. The source description can …

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