105 resultados para linear machine modeling


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The infection of insect cells with baculovirus was described in a mathematical model as a part of the structured dynamic model describing whole animal cell metabolism. The model presented here is capable of simulating cell population dynamics, the concentrations of extracellular and intracellular viral components, and the heterologous product titers. The model describes the whole processes of viral infection and the effect of the infection on the host cell metabolism. Dynamic simulation of the model in batch and fed-batch mode gave good agreement between model predictions and experimental data. Optimum conditions for insect cell culture and viral infection in batch and fed-batch culture were studied using the model.

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Kinematic analysis is conducted to derive the geometric constraints for the geometric design of foldable barrel vaults (FBV) composed of polar or angulated scissor units. Non-linear structural analysis is followed to determine the structural response of FBVs in the fully deployed configuration under static loading. Two load cases are considered: cross wind and longitudinal wind. The effect of varying member sizes, depth-to-span ratio and geometric imperfections is examined. (C) 2000 Elsevier Science Ltd. All rights reserved.

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In order to use the finite element method for solving fluid-rock interaction problems in pore-fluid saturated hydrothermal/sedimentary basins effectively and efficiently, we have presented, in this paper, the new concept and numerical algorithms to deal with the fundamental issues associated with the fluid-rock interaction problems. These fundamental issues are often overlooked by some purely numerical modelers. (1) Since the fluid-rock interaction problem involves heterogeneous chemical reactions between reactive aqueous chemical species in the pore-fluid and solid minerals in the rock masses, it is necessary to develop the new concept of the generalized concentration of a solid mineral, so that two types of reactive mass transport equations, namely, the conventional mass transport equation for the aqueous chemical species in the pore-fluid and the degenerated mass transport equation for the solid minerals in the rock mass, can be solved simultaneously in computation. (2) Since the reaction area between the pore-fluid and mineral surfaces is basically a function of the generalized concentration of the solid mineral, there is a definite need to appropriately consider the dependence of the dissolution rate of a dissolving mineral on its generalized concentration in the numerical analysis. (3) Considering the direct consequence of the porosity evolution with time in the transient analysis of fluid-rock interaction problems; we have proposed the term splitting algorithm and the concept of the equivalent source/sink terms in mass transport equations so that the problem of variable mesh Peclet number and Courant number has been successfully converted into the problem of constant mesh Peclet and Courant numbers. The numerical results from an application example have demonstrated the usefulness of the proposed concepts and the robustness of the proposed numerical algorithms in dealing with fluid-rock interaction problems in pore-fluid saturated hydrothermal/sedimentary basins. (C) 2001 Elsevier Science B.V. All rights reserved.

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Cpfg is a program for simulating and visualizing plant development, based on the theory of L-systems. A special-purpose programming language, used to specify plant models, is an essential feature of cpfg. We review postulates of L-system theory that have influenced the design of this language. We then present the main constructs of this language, and evaluate it from a user's perspective.

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L-studio/cpfg is a plant modeling software system designed for Windows 95/98/NT platforms. Its key components are the L-system-based plant simulator cpfg and the modeling environment called L-studio. We overview version 1.0 of this system from the user's perspective.

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A numerical model of heat transfer in fluidized-bed coating of solid cylinders is presented. By defining suitable dimensionless parameters, the governing equations and its associated initial and boundary conditions are discretized using the method of orthogonal collocation and the resulting ordinary differential equations simultaneously solved for the dimensionless coating thickness and wall temperatures. Parametric Studies showed that the dimensionless coating thickness and wall temperature depend on the relative heat capacities of the polymer powder and object, the latent heat of fusion and the size of the cylinder. Model predictions for the coating thickness and wall temperature compare reasonably well with numerical predictions and experimental coating data in the literature and with our own coating experiments using copper cylinders immersed in nylon-11 and polyethylene powders. (C) 2001 Elsevier Science Ltd. All rights reserved.

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The earth's tectonic plates are strong, viscoelastic shells which make up the outermost part of a thermally convecting, predominantly viscous layer. Brittle failure of the lithosphere occurs when stresses are high. In order to build a realistic simulation of the planet's evolution, the complete viscoelastic/brittle convection system needs to be considered. A particle-in-cell finite element method is demonstrated which can simulate very large deformation viscoelasticity with a strain-dependent yield stress. This is applied to a plate-deformation problem. Numerical accuracy is demonstrated relative to analytic benchmarks, and the characteristics of the method are discussed.

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We present a scheme which offers a significant reduction in the resources required to implement linear optics quantum computing. The scheme is a variation of the proposal of Knill, Laflamme and Milburn, and makes use of an incremental approach to the error encoding to boost probability of success.

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A Cellular-Automaton Finite-Volume-Method (CAFVM) algorithm has been developed, coupling with macroscopic model for heat transfer calculation and microscopic models for nucleation and growth. The solution equations have been solved to determine the time-dependent constitutional undercooling and interface retardation during solidification. The constitutional undercooling is then coupled into the CAFVM algorithm to investigate both the effects of thermal and constitutional undercooling on columnar growth and crystal selection in the columnar zone, and formation of equiaxed crystals in the bulk liquid. The model cannot only simulate microstructures of alloys but also investigates nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies.

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This paper presents a case study that explores how operator digging style juxtaposes with mechanical capability for a class of hydraulic mining excavators. The relationships between actuator and digging forces are developed and these are used to identify the excavator's capability to apply forces in various directions. Two distinct modes of operation are examined to see how they relate to the mechanical capabilities of the linkage and to establish if one has merit over the other. It is found that one of these styles results in lower loading of the machine.

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The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

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The purpose of this study was to investigate the effects of a specific cognitive race plan on 100 m sprint performance, Twelve elite sprinters (11 male and 1 female) performed 100 m time trials under normal (control) conditions and then under experimental conditions (use of race cues). In the experimental condition, participants were asked to think about specific thought content in each of three segments of the 100 m. A multiple baseline design was employed. A mean improvement of 0.26 s was found. Eleven of the 12 participants showed improvement using the specific cognitive race plan (p < .005). Participants also produced more consistent sprint performances when using the cues (p < .01). Subjective evaluations made by the participants unanimously supported the use of the race plan for optimizing sprint performance. Environmental conditions, effort, and practice effects were considered as possible influences on the results.

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The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

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When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.