NASA Earth Observing system (EOS) Program is now collecting unprecedented volumes of data (nearly one petabyte/year) to aid the nation in its understanding of the Earth near and long-term climate processes. these data...
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NASA Earth Observing system (EOS) Program is now collecting unprecedented volumes of data (nearly one petabyte/year) to aid the nation in its understanding of the Earth near and long-term climate processes. these data are a national resource that must be carefully preserved to maximize the nations return on the EOS Program. To address this need NASA has initiated the development of a Remote Data Store (RDS) backup and recovery capability that will operate independent of but closely allied to, the current Distributed Active Archive Centers (DAACs). this paper outlines the following: the evolutionary technology paththat will ultimately provide automated, secure, seamless and efficient remote on-line redundant storage; and the recovery and access of operational EOS mission data products. Significant factors that affect the total cost of operations are discussed, as well as emerging technologies and standards. Preliminary modeling points to the operational staffing levels as a dominant cost component. If on-line storage management techniques cannot improve to the point where a small staff can manage petabytes of data, the viability of disk-based storage solutions for large scientific data repositories is unlikely.
A quasi-monochromatic X-ray computed mammotomograph (XCT) system is under development. the importance of a near-monochromatic X-ray beam is that tissues of close attenuation coefficients are expected to be more easily...
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A quasi-monochromatic X-ray computed mammotomograph (XCT) system is under development. the importance of a near-monochromatic X-ray beam is that tissues of close attenuation coefficients are expected to be more easily separable compared withthose from a standard filtered beam. Understanding the behavior of beam hardening, lesion contrast (enhancement), and exposure efficiency for the complete range of breast compositions allows assessment of the feasibility of such an XCT system. In this study, investigated design parameters include tube operating potential and filtration under various combinations of uncompressed breast and lesion thicknesses and breast compositions in order to optimize performance. the simulated X-ray beam was generated from a tungsten target using cone beam imaging geometry. Simulations were run for 10-20% incremental breast compositions of adipose and glandular breast tissue for 8-16 cm thick uncompressed breasts with 1 -10 mm thick soft lesions. For 60-70 kVp tube potentials (corresponding to 35-40 keV mean energy) with /spl sim/500/sup th/ value attenuating layer of Ce filtration, minimal beam hardening was <5%, optimal lesion contrast enhancement was 5-10% for 12 and 16 cm breasts of all compositions and lesion sizes. Beyond 60% adipose tissue composition, heavy filtration decreases lesion contrast for the thinnest breast. Optimal exposure efficiency was also seen in this operating range, with better absolute values obtained for thinner breasts of all compositions and thicker lesions in this mammotomographic application. thus, development of a suitable quasi-monochromatic X-ray beam is possible with commercially available equipment and high-Z K-edge filtration, and can yield optimal characteristics for dedicated mammotomography.
this paper studies fault detection problems for sampled-data (SD) systems. At first a discrete-time residual generator is constructed in two steps. Withthe help of introduced operators, the residual is analyzed quant...
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ISBN:
(纸本)0780372980
this paper studies fault detection problems for sampled-data (SD) systems. At first a discrete-time residual generator is constructed in two steps. Withthe help of introduced operators, the residual is analyzed quantitatively. Following the principle of integrated design, the design of fault detection system is then formulated as an optimization problem. Finally, two design procedures using H-infinity optimization technique are provided and full decoupling problem is discussed.
An approach is presented which allows to incorporate constraints on the system dynamics into the optimization based design of nonlinear systems. In this approach, boundaries in the parameter space of the nonlinear sys...
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ISBN:
(纸本)0780372980
An approach is presented which allows to incorporate constraints on the system dynamics into the optimization based design of nonlinear systems. In this approach, boundaries in the parameter space of the nonlinear system are taken into account, at which desired dynamics characteristics of the system are lost. these boundaries can be defined, for example, by a critical value of the real part of the leading eigenvalue of the linearized system, or by a restriction of eigenvalues to an angular sector in the complex plane. We stress that even though linearizations may be involved when defining the boundaries of interest, the boundaries themselves apply to the nonlinear system. Parametric robustness is guaranteed by staying off the boundaries at a user specified distance in the parameter space. this ensures that the desired dynamics characteristics will be met despite of parametric uncertainty or parameter drift. the proposed method can be applied both to system and controller parameters, thus allowing for an optimization based integrated system and controller design. We illustrate the approach by an application to a simple model of a continuous fermentation process.
the implementation of displacement mapping on subdivision surfaces is discussed in this paper the subdivision surface has recently drawn a lot of attention in the area of geometric modeling, multiresolution surface re...
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the use of measurements to compensate for model uncertainty and disturbances has received increasing attention in the context of process optimization. the standard procedure consists of iteratively using the measureme...
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ISBN:
(纸本)0780372980
the use of measurements to compensate for model uncertainty and disturbances has received increasing attention in the context of process optimization. the standard procedure consists of iteratively using the measurements for identifying the model parameters and the updated model for optimization. However, in the presence of model mismatch, this scheme suffers from lack of synergy between the identification and optimization problems. this paper investigates the performance of run-to-run optimization schemes and proposes to modify the objective function of the identification problem so as to include the cost function and the constraints of the optimization problem. the weights of the various terms in the extended objective function are based on Lagrange multipliers. the performance improvement obtained withthe proposed methodology is illustrated via the simulation of a semi-batch reaction system.
Internal thermally Coupled Distillation Column (ITCDIC) is the frontier of energy saving distillation research. In this paper, an evaluation method on operating cost and its saving in the ITCDIC processes of ideal mix...
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ISBN:
(纸本)0780372980
Internal thermally Coupled Distillation Column (ITCDIC) is the frontier of energy saving distillation research. In this paper, an evaluation method on operating cost and its saving in the ITCDIC processes of ideal mixtures is presented. A mathematical model for optimization is first derived. the benzene-toluene system is studied as an illustrative example. the optimization results show that the energy cost saving potential is close to 40% and annual energy cost saving is about 0.3 million dollars compared withthe operating cost of a conventional distillation column operated at the minimum reflux ratio. the process analysis is also carried out. the optimal operating conditions and some useful results are obtained. these pave the way for the smooth operation and the further optimal design of ideal ITCDIC processes.
Projection to Latent Structures (PLS a.k.a. Partial Least Squares) is a multivariate statistical (MVS) technology that can be applied in inferential / predictive control strategies. Dofasco has used MVS as the basis f...
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ISBN:
(纸本)0780372980
Projection to Latent Structures (PLS a.k.a. Partial Least Squares) is a multivariate statistical (MVS) technology that can be applied in inferential / predictive control strategies. Dofasco has used MVS as the basis for an on-line, adaptive PLS prediction system, which is used to control its desulphurization facility. this paper will introduce the reader to the basic process of steel desulphurization and the motivation for the MVS modeling in this application. As well, the paper examines the PLS and associated adaptation algorithm used. Comments regarding online experiences and operational results are also given.
In this contribution, a global optimization technique using interval analysis applied to the simulation of an antilocking control system with possible sensor tolerances is presented. the antilocking system and the veh...
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ISBN:
(纸本)0780372980
In this contribution, a global optimization technique using interval analysis applied to the simulation of an antilocking control system with possible sensor tolerances is presented. the antilocking system and the vehicle are described as an uncertain discrete time system with nonsmooth nonlinearities. Sensor tolerances can be modeled in a natural way by means of interval arithmetics which helps to achieve reliable results in the simulation. However, a simulation approach using merely natural interval extensions leads to overestimations rendering the result useless. therefore, we employ a global optimization algorithm which allows the inclusion of the actual dynamic system behavior with a predefined and guaranteed overestimation limit. All algorithms are implemented in MATLAB.
the focus of this paper is on the design of robust controllers based on the range of expected variation of uncertain parameters from their nominal values. A minimax optimization problem is formulated withthe objectiv...
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ISBN:
(纸本)0780372980
the focus of this paper is on the design of robust controllers based on the range of expected variation of uncertain parameters from their nominal values. A minimax optimization problem is formulated withthe objective of minimizing the maximum value of the cost function over the range of the uncertain parameter. To expedite the optimization process, equations are derived for the gradient of the cost and constraint functions with respect to the parameters of the controller. the proposed technique is illustrated on two examples. the first is a spring-mass-dashpot and the second is;a two-mass-spring benchmark problem.
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