In this paper a parallel computing based software demonstrator for the simulation and leakage minimization of water networks is presented. This demonstrator, based on the EPANET package, tackles three different types ...
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In this paper a parallel computing based software demonstrator for the simulation and leakage minimization of water networks is presented. This demonstrator, based on the EPANET package, tackles three different types of problems making use of parallel computing. First, the solution of the hydraulic problem is treated by means of the gradient method. The key point in the parallelization of the method is the solution of the underlying linear systems, which is carried out by means of a multifrontal Choleski method. Second, the water quality simulation problem is approached by using the discrete volume element method. The application of parallel computing is based on dividing the water network in several parts using the multilevel recursive bisection graph partitioning algorithm. Finally, the problem of leakage minimization using pressure reducing valves is approached. This results in the formulation of an optimization problem for each time step, which is solved by means of sequential quadratic programming. Because these subproblems are independent of each other, they can be solved in parallel.
Studies the effect of both ply angle variation and the position of lumped massed on flutter speed for uniform thickness wind-tunnel models. Parametric study for uniform thickness beam; Optimization of nonuniform thick...
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Studies the effect of both ply angle variation and the position of lumped massed on flutter speed for uniform thickness wind-tunnel models. Parametric study for uniform thickness beam; Optimization of nonuniform thickness beam.
作者:
Celi, RUniv Maryland
Alfred Gessow Rotorcraft Ctr Dept Aerosp Engn College Pk MD 20742 USA
An inverse simulation methodology based on numerical optimization is presented. The methodology is applied to a simplified version of the slalom maneuver in the ADS-33D helicopter handling qualities specification. The...
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An inverse simulation methodology based on numerical optimization is presented. The methodology is applied to a simplified version of the slalom maneuver in the ADS-33D helicopter handling qualities specification. The inverse simulation is formulated as an optimization problem with trajectory. and dynamic constraints, pilot inputs as design variables, and an objective function that depends on the specific problem being solved. A maximum speed solution is described. The results show that numerical optimization is a reliable and flexible tool for inverse simulation, both when the required trajectory is prescribed explicitly and when it is defined indirectly through geometric and dynamic constraints. When the trajectory is defined indirectly, there is not a single acceptable trajectory but rather an entire family with noticeable differences in the helicopter dynamics and in the required pilot inputs. Even when the trajectory is prescribed explicitly, multiple solutions exist. For handling qualities studies, the multiple solutions may provide an indication of tbe amount of scatter in pilot ratings to be expected for a given aircraft and a given maneuver. However, if the inverse simulation is used for simulation validation, then additional constraints may have to be placed on the solution to make it unique.
Two variants of the BLISS method are proposed for multidisciplinary design optimization (MDO). These variants utilize experimental design methods and response surfaces to reduce the number of expensive system analysis...
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Two variants of the BLISS method are proposed for multidisciplinary design optimization (MDO). These variants utilize experimental design methods and response surfaces to reduce the number of expensive system analysis required for solution of the MDO problem. BLISS is an MDO method for decomposition-based optimization of engineering systems that involves system optimization with a relatively small number of design variables and a number of subsystem optimizations that could each have a large number of local variables. In BLISS, the optimum sensitivity analysis data are used to relate the subsystem optimization solutions with the system optimizations. Instead, with the proposed variants, polynomial response surface approximations using either the system analysis or the subsystem optimization results are used. Additionally, the response surface construction process is well suited for computing in a concurrent processing environment. The proposed variants are implemented and evaluated on a conceptual-level aircraft and ship design problem.
A novel methodology is developed to integrate state-of-the-art computational fluid dynamics analysis, NURBS, and optimization theory to reduce total pressure distortion and sustain total pressure recovery within a cur...
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A novel methodology is developed to integrate state-of-the-art computational fluid dynamics analysis, NURBS, and optimization theory to reduce total pressure distortion and sustain total pressure recovery within a curved three-dimensional subsonic S-duct diffuser by automated redesign of the diffuser shape. Two independent design variables are used. The change of the surface shape is assumed to be Gaussian. GASP with the modified Baldwin-Lomax turbulence model (Baldwin, B. S., and Lomax, ii., "Thin Layer Approximation and Algebraic Model for Separated Turbulent Flows," AIAA Paper 78-257, 1978) is employed for the flowfield prediction and proved to give good agreement with the experimental surface pressure for the baseline S-duct diffuser geometry. The automated design optimization is performed with a gradient-based method to minimize the total pressure distortion based on the two design variables. The best configuration obtained reduced distortion by typically 70% while keeping the total recovery essentially the same. The results indicate that the mechanism responsible for improved diffuser performance is the suppression of detrimental secondary Rows by changing the surface shape to redirect the flow.
A new computational decomposition scheme is applied to a pursuit-evasion game that describes the visual identification of a foreign intruder aircraft in three dimensions. The intruder is assumed to minimize its distan...
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A new computational decomposition scheme is applied to a pursuit-evasion game that describes the visual identification of a foreign intruder aircraft in three dimensions. The intruder is assumed to minimize its distance to the state border at the time of identification, whereas the identifying aircraft wishes to intercept the intruder as far away inland as possible. The identification occurs when the identifier reaches the intruder's velocity and attitude within a given distance from it. The computational scheme decomposes the minimaximization of the payoff into two sequences of optimal control problems that can be solved using discretization and nonlinear programming techniques.
The inverse problem of estimating the open-channel flow roughness is solved using an embedded optimization model. Measurement data for flow depths and discharges at several locations and times are used as inputs to th...
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The inverse problem of estimating the open-channel flow roughness is solved using an embedded optimization model. Measurement data for flow depths and discharges at several locations and times are used as inputs to the optimization model. The nonlinear optimization model embeds the finite-difference approximations of the governing equations for unsteady flow in an open channel as equality constraints. The sequential quadratic programming Algorithm is used to solve the optimization model. The performance of the proposed parameter estimation model is evaluated for different scenarios of data availability and noise in flow measurement data. Solution results for illustrative problems indicate the potential applicability of the proposed model.
In an abstract framework, we study local convergence properties of Newton's method for a sequence of generalized equations which models a discretized variational inequality. We identify conditions under which the ...
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In an abstract framework, we study local convergence properties of Newton's method for a sequence of generalized equations which models a discretized variational inequality. We identify conditions under which the method is locally quadratically convergent, uniformly in the discretization. Moreover, we show that the distance between the Newton sequence for the continuous problem and the Newton sequence for the discretized problem is bounded by the norm of a residual. As an application, we present mesh-independence results for an optimal control problem with control constraints.
In the past few Sears there has been interest in using response surface techniques to create surrogates to computer simulations. Response surface techniques allow detection and correction of errors as well as filterin...
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In the past few Sears there has been interest in using response surface techniques to create surrogates to computer simulations. Response surface techniques allow detection and correction of errors as well as filtering out numerical noise, but these techniques introduce additional modeling errors. Methods of reducing both noise and modeling errors are explored. It is also demonstrated that repairing designs with large errors is preferable to eliminating these designs from consideration. Response surface approximations for a high-speed civil transport wing weight equation created from the results of a large number of structural optimizations are used for demonstration. It is shown that the statistical tools available for response surface techniques are effective for error detection and for filtering out noise. Once the noise is reduced, modeling errors can also be reduced by increasing the order of the approximation.
We show that the quadratic growth condition and the Mangasarian-Fromovitz constraint qualification (MFCQ) imply that local minima of nonlinear programs are isolated stationary points. As a result, when started suffici...
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We show that the quadratic growth condition and the Mangasarian-Fromovitz constraint qualification (MFCQ) imply that local minima of nonlinear programs are isolated stationary points. As a result, when started sufficiently close to such points, an L-infinity exact penalty sequential quadratic programming algorithm will induce at least R-linear convergence of the iterates to such a local minimum. We construct an example of a degenerate nonlinear program with a unique local minimum satisfying the quadratic growth and the MFCQ but for which no positive semidefinite augmented Lagrangian exists. We present numerical results obtained using several nonlinear programming packages on this example and discuss its implications for some algorithms.
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