David G. Taggart

The effects of system and geometric parameters on abrasive water jet nozzle wear

Nozzle wear dependence on abrasive water jet system parameters and nozzle geometry is experimentally investigated. Experimental procedures for evaluating long term and accelerated nozzle wear are discussed. Accelerated wear tests are conducted to study the effects of nozzle length, inlet angle, diameter, orifice diameter, abrasive flow rate, and water pressure on wear. An empirical model for nozzle weight loss rate is developed and is shown to correlate well with experimental measurements.

A Study of Nozzle Wear in Abrasive Entrained Water Jetting Environment

Parameters that influence nozzle wear in abrasive water jetting environment are identified and classified. Regular and accelerated wear test procedures are developed to study wear under actual and simulated conditions, respectively. In addition to exit diameter growth, nozzle weight loss and bore profiles are shown to better characterize and explain the wear phenomenon. The effect of nozzle geometry on wear is investigated by means of the developed test procedures and measures of wear.

Application of Jetting Technology to Pavement Deicing

Winter maintenance of pavement surfaces consists of plowing and the application of corrosive deicing agents. These chemicals are hazardous to the environment, and thus their use should be minimal. More than 20 years ago, the Connecticut Department of Transportation (ConnDOT) investigated the use of 2.1 MPa (300 psi) pressurized salt brine jets to enhance deicing performance. Despite promising results from several field trials, technical difficulties led to abandonment of this technology in the early 1980s. Recent advances in high-pressure jetting technology suggest that the use of high-pressure jets in conjunction with improved chemical agents for pavement deicing may now be practical. In this study, the application of modern high-pressure jetting technology to deice pavement is explored. The proposed system removes ice and snow through the combined action of mechanical jetting forces and controlled use of deicing chemicals. Appropriate operating parameters and consumption rates are identified and compared with the ConnDOT system developed in the 1970s.

Convergence of a genetic algorithm for estimating cardiac material properties

In this paper we present the results of a detailed study of a systematic numerical scheme for estimating material parameters for ventricular myocardium. The numerical scheme combines a real encoded genetic algorithm with nonlinear finite element analysis. The primary objective of this study was to determine optimal population size for the genetic algorithm so as obtain rapid convergence to actual material parameter values. Optimal parameter settings for the genetic algorithm and interdependencies of material parameters were determined through multiple optimization runs.

Application of the PMR Topology Optimization Scheme to Dual Material Structures

An iterative finite element based topology optimization method based on prescribed material redistribution (PMR) has recently been demonstrated to effectively identify optimal topologies for single material structures. Through the application of a family of Beta probability density and cumulative distribution functions, the method provides a gradual transition from a unimodal distribution of uniform intermediate density to a bimodal distribution of void and fully dense regions. In this paper, the PMR method is extended to dual material structures in which the tensile member strength differs from the compressive member strength. Evolution to topologies which satisfy dual material optimality criteria is ensured through the introduction of local fictitious moduli based on the local stress state. For validation, both analytically derived solutions and a numerical dual material truss optimization procedure are applied. The truss optimization procedure is based on an assumed topology for which the optimal joint coordinates and member cross-sectional areas are determined using a quasi-Newton method and fully stressed design conditions. Validation problems considered include a two-bar dual material cantilever, a dual material truss structure subjected to combined loading, and dual material shear loaded frame structures with pre-existing members. For each case, validation is provided by correlating PMR results with results obtained from the dual material truss optimization procedure. It is demonstrated that for all cases considered, the PMR method provides a reliable tool for the identification of minimum weight dual material structures.Copyright

Use of a genetic algorithm for determining material parameters in ventricular myocardium

The estimation of material parameters in constitutive models for soft biological materials such as myocardium is a challenging problem due to the complex behavior of the material. Here we present a systematic scheme to solve the inverse problem of estimating material parameters from experimentally observed deformation. This scheme couples a genetic algorithm with nonlinear finite element analysis. The approach is very general and can be applied to a wide range of inverse boundary value problems. Effectiveness of this scheme is demonstrated through examples involving two-dimensional and three-dimensional hyperelastic material models. Finally, a problem involving variation of material parameter through the ventricular wall is investigated.