The theoretical methodology, conceptual demonstration, and validation of a fully automated computer program for the inverse design and optimization of internal convectively cooled three-dimensional axial gas turbine b...
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The theoretical methodology, conceptual demonstration, and validation of a fully automated computer program for the inverse design and optimization of internal convectively cooled three-dimensional axial gas turbine blades is presented. A parametric computer model of the three-dimensional internal cooling network was developed, including the automatic generation of computational grids. A boundary element computer program was written to solve the steady-state, nonlinear heat conduction equation inside the internally cooled and thermal barrier coated turbine blade. A finite element algorithm was written to model an arbitrary network of internal coolant passages for the calculation of the internal pressure losses, How rates, effects of centrifugal pumping, heating of the coolant fluid, and heat transfer coefficients from the thermal model of the solid to the coolant fluid. The heat conduction and internal flow analyses were strongly and iteratively coupled to account for the heat balance between the blade and the coolant fluid. A system of evolutionary optimization algorithms was used to modify the internal cooling configuration and internal heat transfer enhancements (boundary-layer trip strips and pedestals) to achieve the objectives of increased cooling effectiveness and greater durability against oxidation, corrosion, and creep. The computer-automated design and optimization system was demonstrated on the second high-pressure turbine blade row of the Pratt and Whitney F100 engine. The internal cooling optimization on the product definition of this blade yielded a 5% increase in average cooling effectiveness, with only a marginal increase in coolant flow rate, in addition to having the same corrosion life and a doubling of the creep life.
This paper explores the use of topological optimization to systematically design suspensions for hard disk drives (HDD). The design problem is posed as a material distribution problem, which varies spatial thickness o...
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This paper explores the use of topological optimization to systematically design suspensions for hard disk drives (HDD). The design problem is posed as a material distribution problem, which varies spatial thickness of suspensions so as to enhance their dynamic performance. Due to the requirements for specific motion characteristics, suspensions are designed to have higher torsional and lateral frequencies while maintaining an adequate but not too high frequency for transverse bending. The torsional and lateral frequencies are generally higher in order than the transverse frequencies. Due to their non-convex nature, the optimizations of higher-order frequencies were proven to be more difficult than that of the fundamental frequency. To tackle the problem, present work adopted mode-tracking techniques, and attempted two different optimization algorithms to solve the design problem. With reference to the topological results obtained, it is found that the implementation based on sequential quadratic programming (SQP) performed better than that based on optimal criteria (OC). It was also found that the present design method could tremendously improve the dynamic performance of suspensions.
In target tracking systems measurements are typically collected in "scans" or "frames" and then they are transmitted to a processing center. In multisensor tracking systems that operate in a centra...
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In target tracking systems measurements are typically collected in "scans" or "frames" and then they are transmitted to a processing center. In multisensor tracking systems that operate in a centralized manner, there are usually different time delays in transmitting the scans or frames from the various sensors to the center. This can lead to situations where measurements from the same target arrive out of sequence. Such "out-of-sequence" measurement (OOSM) arrivals can occur even in the absence of scan/frame communication time delays. The resulting "negative-time measurement update" problem, which is quite common in real multisensor systems, was solved previously only approximately in the literature. The exact state update equation, for such a problem is presented. The optimal and two suboptimal algorithms are compared on a number of realistic examples, including a GMTI (ground moving target indicator) radar case.
Multivariate optical elements (MOEs) are multilayer optical interference coatings with arbitrary spectral profiles that are used in multivariate pattern recognition to perform the task of projecting magnitudes of spec...
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Multivariate optical elements (MOEs) are multilayer optical interference coatings with arbitrary spectral profiles that are used in multivariate pattern recognition to perform the task of projecting magnitudes of special basis functions (regression vectors) out of optical spectra. Because MOEs depend on optical interference effects, their performance is sensitive to the angle of incidence of incident light. This angle dependence complicates their use in imaging applications. We report a method for the design of angle-insensitive MOEs based on modification of a previously described nonlinear optimization algorithm. This algorithm operates when the effects of deviant angles of incidence are simulated prior to optimization, which treats the angular deviation as an interferent in the measurement. To demonstrate the algorithm, a 13-layer imaging MOE (IMOE, with alternating layers of high-index Nb2O6 and low-index SiO2) for the determination of Bismarck Brown dye in mixtures of Bismarck Brown and Crystal Violet, was designed and its performance simulated. For angles of incidence that range from 42 to 48, the IMOE has an average standard error of prediction (SEP) of 0.55 muM for Bismarck Brown. This compares with a SEP of 2.8 muM for a MOE designed by a fixed-angle algorithm.
An algorithmic method for the analysis of X-ray line spectra using genetic algorithms is presented. This technique permits the extraction of diagnostic information on the emitting medium from the spectral data. As an ...
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An algorithmic method for the analysis of X-ray line spectra using genetic algorithms is presented. This technique permits the extraction of diagnostic information on the emitting medium from the spectral data. As an example of the method, plasma electron number density and temperature are extracted from the analysis of X-ray spectral data recorded in an Ar-doped inertial-confinement-fusion core. For the study of a sequence of gradually changing spectra, a combination of genetic algorithms and case-based reasoning that learns from experience is used to accelerate the analysis. The technique is general and can be applied to other plasma spectroscopy studies including analysis of spatially and temporally resolved line absorption or emission data. (C) 2002 Elsevier Science Ltd. All rights reserved.
An implementation of the genetic algorithin in a design support tool for (large) solar hot water systems is described. The tool calculates the yield and the costs of solar hot water systems based on technical and fina...
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An implementation of the genetic algorithin in a design support tool for (large) solar hot water systems is described. The tool calculates the yield and the costs of solar hot water systems based on technical and financial data of the system components. The genetic algorithm allows for optimisation of separate variables such as the collector type, the number of collectors, the heat storage mass and the collector heat exchanger area. Optimisation can be focussed on, for example, payback time and CO2 emission reduction. Constraints such as maximum initial costs and installation space are taken into account. The applicability of the genetic algorithm was tested for optimisation of large solar hot water systems. Among others, the sensitivity of the optimum system design to the tap water draw-off and the draw-off pattern has been determined using the optimisation algorithm. As the genetic algorithm is a discrete optimisation tool and is implemented in the design tool through the use of databases, the number of variables in principle is free of choice. (C) 2002 Elsevier Science Ltd. All rights reserved.
We propose a method for the improvement and optimization of the algorithm of finding a function whose Laplace transform is known with the help of a numerical-analytic method based on the representation of the original...
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We propose a method for the improvement and optimization of the algorithm of finding a function whose Laplace transform is known with the help of a numerical-analytic method based on the representation of the original function in the form of Fourier series. The relations obtained by the method of boundary elements are used to determine three-dimensional nonstationary temperature fields in bodies with cavities. As an example, we consider a problem of nonstationary heat conduction for a half space z > 0 containing an ellipsoidal cavity heated by a concentrated heat source with intensity Q. The process of heat exchange between the body and media washing the plane boundary and filling the cavity obeys the Newton law.
The authors discuss the optimal allocation of wavelength converters in shared-per-link structure in WDM networks. In particular, they consider the following two cases: given the total number of converters available in...
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The authors discuss the optimal allocation of wavelength converters in shared-per-link structure in WDM networks. In particular, they consider the following two cases: given the total number of converters available in the system, or given the number of converters available at each node in the system, allocate them properly at the outgoing links of the nodes, such that the total sum of traffic of connections getting through the system is maximised. An optimisation algorithm is proposed to solve the first case, and a heuristic algorithm is developed to find an approximate solution for the second case. Simulation results have shown the effectiveness of the solutions.
In this paper we discuss the optimal design of logical topologies in wavelength-routed IP over WDM networks supporting both unicast and multicast transfer of IP datagrams under deterministic and stochastic traffic pat...
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In this paper we discuss the optimal design of logical topologies in wavelength-routed IP over WDM networks supporting both unicast and multicast transfer of IP datagrams under deterministic and stochastic traffic patterns. The paper brings mainly three original contributions: (i) it provides a MILP formalization of the optimal logical topology design (LTD) problem in presence of multicast traffic under a perfectly known (deterministic) traffic pattern and proposes sub-optimal greedy and metaheuristic algorithms for its solution;(ii) it derives novel, tight optimistic bounds that allow the assessment of the performance of the proposed algorithms;(iii) it investigates the optimal logical topology design problem, when traffic patterns are known with a certain degree of uncertainty, hence characterized with a stochastic description, and it presents approaches for the sub-optimal solution of the problem. Focusing on the current nternet routing algorithms, we explicitly consider the routing of multi-hop flows over the logical topology as an input to the problem, not an optimization target.
In this paper the voltage regulation of a Flyback converter under load transient conditions is investigated. First, the best regulation is found with an optimization algorithm which uses a cycle-by-cycle model. The pr...
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ISBN:
(纸本)0780373693
In this paper the voltage regulation of a Flyback converter under load transient conditions is investigated. First, the best regulation is found with an optimization algorithm which uses a cycle-by-cycle model. The predictions are then compared with the performance given by an optimized peak current-mode controlled converter. Simulation results are then provided to highlight the two different output voltage dynamics during load transients.
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