Heat transfer in lattice BGK modeled fluid

The thermal lattice BGK model is a recently suggested numerical tool aiming at solving problems of thermohydrodynamics. The quality of the lattice BGK simulation is checked in this paper by calculating temperature profiles in the Couette flow under different Eckert and Mach numbers. A revised lower order model is proposed to improve the accuracy and the higher order model is proved to be advantageous in this respect, especially in the flow regime with a higher Mach number.     

Exact ground state of the generalized three-dimensional Shastry-Sutherland model

We generalize the Shastry-Sutherland model to three dimensions. By representing the model as a sum of the semidefinite positive projection operators, we exactly prove that the model has exact dimer ground state. Several schemes for constructing the three-dimensional Shastry-Sutherland model are proposed. Received 20 February 2002 / Received in final form 27 May 2002 Published online 17 September 2002     

Multibody dynamics of aircraft occupants seated behind interior walls

To improve aircraft crash safety, conditions critical to occupants survival during a crash must be known. In view of the importance of this problem, studies of post-crash dynamic behavior of victims are necessary in order to reduce severe injuries. In this study, crash dynamics program SOM-LA/TA, incorporating a dynamic model of the human body with a finite element model of the seat structure was used. Modifications were performed in the program for reconstruction of an occupant's head impact with the interior walls or bulkhead. A viscoelastic-type contact force model was used to represent the compliance characteristics of the bulkhead. Correlated studies of analytical simulations with impact sled test results were accomplished. A parametric study of the coefficients in the contact force model was then performed in order to obtain the correlations between the coefficients and the Head Injury Criteria. A measure of optimal values for the bulkhead compliance and displacement requirements was thus achieved in order to keep the possibility of a head injury as little as possible. This information could in turn be used in the selection of suitable materials for the bulkhead, instrument panel, or interior walls of an aircraft.     

M/G/1/N vacation model with varying E-limited service discipline

We define and analyze anM/G/1/N vacation model that uses a service discipline that we call theE-limited with limit variation discipline. According to this discipline, the server provides service until either the system is emptied (i.e. exhausted) or a randomly chosen limit ofl customers has been served. The server then goes on a vacation before returning to service the queue again. The queue length distribution and the Laplace-Stieltjes transforms of the waiting time, busy period and cycle time distributions are found. Further, an expression for the mean waiting time is developed. Several previously analyzed service disciplines, including Bernoulli scheduling, nonexhaustive service and limited service, are special cases of the general varying limit discipline that is analyzed in this paper.     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Some properties of the bilevel programming problem

The purpose of this paper is to elaborate on the difficulties accompanying the development of efficient algorithms for solving the bilevel programming problem (BLPP). We begin with a pair of examples showing that, even under the best of circumstances, solutions may not exist. This is followed by a proof that the BLPP is NP-hard.This work was partially supported by a grant from the Advanced Research Program of the Texas Higher Education Coordinating Board.     

A Partial Differential Inequality in Geological Models

Sedimentation and erosion processes in sedimentary basins can be modeled by a parabolic equation with a limiter on the fluxes and a constraint on the time variation.This limiter happens to satisfy a stationary scalar hyperbolic inequality,within a constraint,for which the authors prove the existence and the uniqueness of the solution.Actually,this solution is shown to be the maximal element of a convenient convex set of functions.The existence proof is obtained thanks to the use of a numerical scheme.     

Practical aspects associated with location planning for maternal and perinatal assistance in Brazil

A study has been carried out aimed at reducing perinatal mortality in the municipality of Rio de Janeiro through a better distribution of health care facilities. The algorithmic aspects are detailed elsewhere and here the emphasis is on practical issues and difficulties encountered. A 3-level hierarchical model was developed. Both uncapacitated and capacitated versions are briefly described together with some results based on actual data. The project brought to light many contradictions between OR theory and practice in developing countries and, unfortunately, the models developed were not implemented by the municipality health authorities. Possible reasons for this outcome are analysed.     

Portfolio optimization in stochastic markets

We consider a multiperiod mean-variance model where the model parameters change according to a stochastic market. The mean vector and covariance matrix of the random returns of risky assets all depend on the state of the market during any period where the market process is assumed to follow a Markov chain. Dynamic programming is used to solve an auxiliary problem which, in turn, gives the efficient frontier of the mean-variance formulation. An explicit expression is obtained for the efficient frontier and an illustrative example is given to demonstrate the application of the procedure.