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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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At least 325 records · Page 18

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.

60 APPLIED LIFE SCIENCES↗

Experience with abstract notation one

The development of computer science has produced a vast number of machine architectures, programming languages, and compiler technologies. The cross product of these three characteristics defines the spectrum of previous and present data representation methodologies. With regard to computer networks, the uniqueness of these methodologies presents an obstacle when disparate host environments are to be interconnected. Interoperability within a heterogeneous network relies upon the establishment of data representation commonality. The International Standards Organization (ISO) is currently developing the abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively address this problem. When used within the presentation layer of the open systems interconnection reference model, these two standards provide the data representation commonality required to facilitate interoperability. The details of a compiler that was built to automate the use of ASN.1 and BER are described. From this experience, insights into both standards are given and potential problems relating to this development effort are discussed.

Harvey, James D.↗

Improved Results for Route Planning in Stochastic Transportation Networks

In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random. the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variable,. we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.

Boyan, Justin↗

Analysis of nonlinear structures via mode synthesis

An effective procedure for NASTRAN was developed that permits any number of substructures of any size to be synthesized for the purpose of developing normal modes of vibration of the complete structural system. The technique is extended to permit modal transient analysis of the subdivided system. This latter procedure permits the use of NASTRAN's ability to include nonlinear forces in the problem. The five-phase process is accomplished using standard NASTRAN rigid formats with problem-independent alter packages and DMAP sequences.

Gieseke, R. K.↗

A covariance analysis algorithm for interconnected systems

A covariance analysis algorithm for propagation of signal statistics in arbitrarily interconnected nonlinear systems is presented which is applied to six-degree-of-freedom systems. The algorithm uses statistical linearization theory to linearize the nonlinear subsystems, and the resulting linearized subsystems are considered in the original interconnection framework for propagation of the signal statistics. Some nonlinearities commonly encountered in six-degree-of-freedom space-vehicle models are referred to in order to illustrate the limitations of this method, along with problems not encountered in standard deterministic simulation analysis. Moreover, the performance of the algorithm shall be numerically exhibited by comparing results using such techniques to Monte Carlo analysis results, both applied to a simple two-dimensional space-intercept problem.

Cheng, Victor H. L.↗

On non-autonomous dynamical systems

In usual realistic classical dynamical systems, the Hamiltonian depends explicitly on time. In this work, a class of classical systems with time dependent nonlinear Hamiltonians is analyzed. This type of problems allows to find invariants by a family of Veronese maps. The motivation to develop this method results from the observation that the Poisson-Lie algebra of monomials in the coordinates and momenta is clearly defined in terms of its brackets and leads naturally to an infinite linear set of differential equations, under certain circumstances. To perform explicit analytic and numerical calculations, two examples are presented to estimate the trajectories, the first given by a nonlinear problem and the second by a quadratic Hamiltonian with three time dependent parameters. In the nonlinear problem, the Veronese approach using jets is shown to be equivalent to a direct procedure using elliptic functions identities, and linear invariants are constructed. For the second example, linear and quadratic invariants as well as stability conditions are given. Explicit solutions are also obtained for stepwise constant forces. For the quadratic Hamiltonian, an appropriated set of coordinates relates the geometric setting to that of the three dimensional manifold of central conic sections. It is shown further that the quantum mechanical problem of scattering in a superlattice leads to mathematically equivalent equations for the wave function, if the classical time is replaced by the space coordinate along a superlattice. The mathematical method used to compute the trajectories for stepwise constant parameters can be applied to both problems. It is the standard method in quantum scattering calculations, as known for locally periodic systems including a space dependent effective mass.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multiobjective Dynamic Optimization for Optimal Load-Following of Natural Gas Combined Cycle Power Plants under Stress Constraints

With the increasing penetration of intermittent renewable energy sources into the electric grid, there is an associated need for conventional thermal power plants that are designed to operate at base-load conditions to cycle their load rapidly and frequently and operate under low-load conditions. Fast load-following operations lead to plant efficiency loss and the reduction of equipment life. A high-fidelity dynamic model of a natural gas combined cycle power plant, with rigorous equipment level submodels, is developed to capture the plant transient performance and the thermomechanical stress evolution at the high-pressure drum is computed to assess the drum life consumption. Stress evolution is modeled for the location of the edge at the drum/downcomer junction that experiences high circumferential stress amplitude during the fast load-following operation, leading to higher fatigue damage than locations considered under existing design standards. A dynamic optimization problem is solved for optimal load-following operation. Depending on the value of the stress constraint and the desired ramp rate, satisfying the desired stress constraint may be infeasible without relaxing the ramp rate. A multiobjective dynamic optimization problem is solved using a lexicographic approach that minimizes ramp rate relaxation and maximizes efficiency while satisfying stress constraints, avoiding spraying to saturation, and maintaining main steam and reheat steam temperature within bounds. It was observed that the optimal ramp rate can be highly nonlinear as opposed to the industry-standard linear ramp rate. Nonlinear optimal ramp-rate profiles not only help to avoid stress constraints that may be unavoidable by using the linear profile but also result in higher efficiency than the linear profile. Furthermore, the study shows that there is a strong tradeoff between the relaxation in the plant ramp rate and the time-average thermal efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Standard and goal-oriented adaptive mesh refinement applied to radiation transport on 2D unstructured triangular meshes

Standard and goal-oriented adaptive mesh refinement (AMR) techniques are presented for the linear Boltzmann transport equation. A posteriori error estimates are employed to drive the AMR process and are based on angular-moment information rather than on directional information, leading to direction-independent adapted meshes. An error estimate based on a two-mesh approach and a jump-based error indicator are compared for various test problems. In addition to the standard AMR approach, where the global error in the solution is diminished, a goal-oriented AMR procedure is devised and aims at reducing the error in user-specified quantities of interest. The quantities of interest are functionals of the solution and may include, for instance, point-wise flux values or average reaction rates in a subdomain. A high-order (up to order 4) Discontinuous Galerkin technique with standard upwinding is employed for the spatial discretization; the discrete ordinates method is used to treat the angular variable.

97 MATHEMATICS AND COMPUTING↗

Optimal fixed-finite-dimensional compensator for Burgers' equation with unbounded input/output operators

The problem of using reduced order dynamic compensators to control a class of nonlinear parabolic distributed parameter systems was considered. Concentration was on a system with unbounded input and output operators governed by Burgers' equation. A linearized model was used to compute low-order-finite-dimensional control laws by minimizing certain energy functionals. Then these laws were applied to the nonlinear model. Standard approaches to this problem employ model/controller reduction techniques in conjunction with linear quadratic Gaussian (LQG) theory. The approach used is based on the finite dimensional Bernstein/Hyland optimal projection theory which yields a fixed-finite-order controller.

Burns, John A.↗

Adaptive Reweighted Variance Estimation for Monte Carlo Eigenvalue Simulations

Monte Carlo (MC) simulation is used to solve the eigenvalue form of the Boltzmann transport equation to estimate various parameters such as fuel pin flux distributions that are crucial for the safe and efficient operation of nuclear systems (e.g., a nuclear reactor). Monte Carlo eigenvalue simulation uses a sample mean over many stationary cycles (iterations) to estimate various parameters important to nuclear systems. A variance estimate of the sample mean is often used for calculating the confidence intervals. However, MC eigenvalue simulation variance estimators that ignore the intercycle correlation underestimate the true variance of the estimated quantity. This paper presents novel data-adaptive approaches based on a simple autoregressive (AR) model and sigmoid functions to improve MC variance estimation. The standard MC sample-based variance estimator (or naïve estimator) and the spectral density–based MC variance estimator are enhanced by adding data-adaptive components that reduce their bias and improve performance. By investigating the frequency pattern of the AR(1) (order 1) model, two adaptive spectral estimators and one adaptive naïve estimator are proposed. The proposed estimators manifest superior performance when applied to three test problems compared to the standard spectral density–based estimator previously introduced by the authors. In conclusion, these new estimators are straightforward, as they use online algorithms and do not require storage of tallies from all active cycles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A realistic renormalizable supersymmetric E₆ model

A complete realistic model based on the supersymmetric version of E₆ is presented. It consists of three copies of matter 27, and a Higgs sector made of 2×(27+27⁻)+351´+351´⁻ representations. An analytic solution to the equations of motion is found which spontaneously breaks the gauge group into the Standard Model. The light fermion mass matrices are written down explicitly as non-linear functions of three Yukawa matrices. This contribution is based on Ref. [1].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Telescope beam-profile diagnostics and the solar limb

The basic method is described for determining the solar limb brightness profile properly corrected for spurious limb darkening caused by the far wings of the resolving beams encountered in large far-infrared and radio telescopes. When the far wings of the beam can be independently measured this problem is usually amenable to standard deconvolution procedures. Under a broad range of well-defined cases, solutions to the deconvolution problem are unique to within the discrimination provided by the core of the beam profile. The theory is applied to solar limb scans made recently on the James Clerk Maxwell Telscope to show solar limb brightening in 850 micron radiation.

Lindsey, Charles A.↗

An Assessment of the Scientific Basis Behind Global Environmental Concerns in the 21st Century

The notion that human activities may endanger the earth's environment has emerged as a leading societal concern in the post industrial era. Under the ever increasing pressures of population growth and industrialization, the problems of local air pollution have now become matters of both local and global concern. Smog, toxic chemicals, acid rain, ozone depletion, and climate change have become household words and an intense public policy debate about the cost and benefits of environmental protection continues. There is a growing realization that the consequences of air pollution can be felt in unpredictable ways in near and far away places. Unpopulated regions of the world such as the arctic now suffer from arctic haze and ozone depletions are the largest in the Antarctic stratosphere. In the last4ol three decades many countries have instituted ambient air quality standards designed to mitigate problems of health and welfare associated with the release of chemicals. Global agreements to prevent the depletion of ozone layer and to slow down climatic warming are being actively debated and formulated. In parallel there has been an intense exploration of the science of air pollution all over the world. The scientific basis behind environmental concerns is imperfect and is central to this debate. I will review our current scientific understanding of some of the major environmental concerns. An assessment of the forthcoming efforts to put this science on a more solid footing will be provided.

Singh, Hanwant B.↗

Plasma equilibrium with fast ion orbit width, pressure anisotropy, and toroidal flow effects

Here, we formulate the problem of tokamak plasma equilibrium including the toroidal flow and fast ion (or energetic particle, EP) pressure anisotropy and the finite drift orbit width (FOW) effects. The problem is formulated via the standard Grad-Shafranov equation (GShE) amended by the solvability condition which imposes physical constraints on allowed spacial dependencies of the anisotropic pressure. The GShE problem employs the pressure coupling scheme and includes the dominant diagonal terms and non-diagonal corrections to the standard pressure tensor. The anisotropic tensor elements are obtained via the distribution function represented in the factorized form via the constants of motion. Considered effects on the plasma equilibrium are estimated analytically, if possible, to understand their importance for GShE tokamak plasma problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rotating unconstrained modes - A more appropriate dynamic analysis of flexible spinning spacecraft

The objective of the paper is a formation of vehicle modes for gyroscopic space structures through a continuum formulation. This requires examination of adjointness of the associated eigenvalue problems. It is shown that standard conditions of self-adjointness are inadequate even for nongyroscopic structures; modifications required depend on the problem under study. On one hand, in the nongyroscopic case the frequencies appear only quadratically and it is relatively easy to devise the corresponding vehicle modes and the self-adjoint operators. On the other hand in the case of the gyroscopic structures the frequencies appear quadratically as well as linearly; this takes the vehicle mode from a configuration space to a phase space, that is, a Hilbert space in the present case. Four elastic systems of increasing complexity typifying nonspinning and spinning elastic spacecraft are investigated in detail.

Hablani, H. B.↗

Model independent tests of the standard cosmological model

The dark energy problem has led to speculation that not only may {Lambda}CDM be wrong, but that the Friedmann-Lemaitre-Robertson-Walker models themselves may not even provide the correct family of background models. We discuss how direct measurements of H(z) can be used to formulate tests of the standard paradigm in cosmology. On their own, such measurements can be used to test for deviations from flat {Lambda}CDM. When combined with supernovae distances, Hubble rate measurements provide a test of the Copernican principle and the homogeneity assumption of the standard model, which is independent of dark energy or a metric based the theory of gravity. A modification of this test also provides a model independent observable for flatness which decorrelates curvature determination from dark energy. We investigate these tests using Hubble rate measurements from age data, as well as from a Hubble rate inferred from recent measurements of the baryon acoustic oscillations. While the current data are too weak to say anything significant, these tests are exciting prospects for the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Random Matrix Approach to Quantum Adiabatic Evolution Algorithms

We analyze the power of quantum adiabatic evolution algorithms (Q-QA) for solving random NP-hard optimization problems within a theoretical framework based on the random matrix theory (RMT). We present two types of the driven RMT models. In the first model, the driving Hamiltonian is represented by Brownian motion in the matrix space. We use the Brownian motion model to obtain a description of multiple avoided crossing phenomena. We show that the failure mechanism of the QAA is due to the interaction of the ground state with the "cloud" formed by all the excited states, confirming that in the driven RMT models. the Landau-Zener mechanism of dissipation is not important. We show that the QAEA has a finite probability of success in a certain range of parameters. implying the polynomial complexity of the algorithm. The second model corresponds to the standard QAEA with the problem Hamiltonian taken from the Gaussian Unitary RMT ensemble (GUE). We show that the level dynamics in this model can be mapped onto the dynamics in the Brownian motion model. However, the driven RMT model always leads to the exponential complexity of the algorithm due to the presence of the long-range intertemporal correlations of the eigenvalues. Our results indicate that the weakness of effective transitions is the leading effect that can make the Markovian type QAEA successful.

Boulatov, Alexei↗

A standardized approach to PV system performance model validation.

PV performance models are used to predict how much energy a PV system will produce at a given location and subject to prescribed weather conditions. These models are commonly used by project developers to choose between module technologies and array designs (e.g., fixed tilt vs. tracking) for a given site or to choose between different geographic locations, and are used by the financial community to establish project viability. Available models can differ significantly in their underlying mathematical formulations and assumptions and in the options available to the analyst for setting up a simulation. Some models lack complete documentation and transparency, which can result in confusion on how to properly set up, run, and document a simulation. Furthermore, the quality and associated uncertainty of the available data upon which these models rely (e.g., irradiance, module parameters, etc.) is often quite variable and frequently undefined. For these reasons, many project developers and other industry users of these simulation tools have expressed concerns related to the confidence they place in PV performance model results. To address this problem, we propose a standardized method for the validation of PV system-level performance models and a set of guidelines for setting up these models and reporting results. This paper describes the basic elements for a standardized model validation process adapted especially for PV performance models, suggests a framework to implement the process, and presents an example of its application to a number of available PV performance models.

14 SOLAR ENERGY↗