Justin Elsey

In vivo dosimeters for HDR brachytherapy: A comparison of a diamond detector, MOSFET, TLD, and scintillation detector

The large dose gradients in brachytherapy necessitate a detector with a small active volume for accurate dosimetry. The dosimetric performance of a novel scintillation detector (BrachyFOD) is evaluated and compared to three commercially available detectors, a diamond detector, a MOSFET, and LiF TLDs. An 192Ir HDR brachytherapy source is used to measure the depth dependence, angular dependence, and temperature dependence of the detectors. Of the commercially available detectors, the diamond detector was found to be the most accurate, but has a large physical size. The TLDs cannot provide real time readings and have depth dependent sensitivity. The MOSFET used in this study was accurate to within 5% for distances of 20 to 50 mm from the 192Ir source in water but gave errors of 30%-40% for distances greater than 50 mm from the source. The BrachyFOD was found to be accurate to within 3% for distances of 10 to 100 mm from an HDR 192Ir brachytherapy source in water. It has an angular dependence of less than 2% and the background signal created by Cerenkov radiation and fluorescence of the plastic optical fiber is insignificant compared to the signal generated in the scintillator. Of the four detectors compared in this study the BrachyFOD has the most favorable combination of characteristics for dosimetry in HDR brachytherapy.

A plastic scintillation dosimeter for high dose rate brachytherapy.

In vivo dose verification in brachytherapy requires a small insertable dosimeter with a real-time readout capability. Fibre optic scintillation dosimeters, consisting of a plastic scintillator coupled to an optical fibre, are one of the most promising dosimeters for this application. We have developed two sizes of the BrachyFOD scintillation dosimeter which have external diameters of 2.2 mm and 1 mm and have determined their important dosimetric characteristics (depth dose relation, angular dependence, temperature dependence, energy dependence). We have shown that the background signal created by Cerenkov and fibre fluorescence does not significantly affect the performance in most clinical geometries using an (192)Ir source from an HDR brachytherapy unit. The dosimeter design enables readout at less than 0.5 s intervals. The BrachyFOD satisfies the need for a real-time in vivo brachytherapy dosimeter.

Modeling and control of a food extrusion process

This contribution reports on the process systems engineering analysis of a food extrusion process leading towards the development and implementation of an on-line process control scheme. A versatile dynamic model of the process predicting the quality variables product gelatinisation, specific mechanical energy, specific volume and residence time has been developed and fitted to experimental data. The model is used to investigate the practicality of an adaptive inferential estimator (Guilandoust et al., 1987) for predicting infrequently measured quality variables on-line. The simulated performance of simple PI and model predictive control of these quality variables is compared.

Optimal coupling of light from a cylindrical scintillator into an optical fiber.

Radiation dose measurements based on scintillator detection are conveniently made by coupling the light from the scintillator into an optical fiber. The low light levels involved typically require sensitive photodetectors, so it is advantageous to increase the available signal by optimizing the optical coupling efficiency between the scintillator and optical fiber. We model this process using geometric optics and finite-element ray tracing to determine the features that maximize the amount of light coupled to an optical fiber from a cylindrical scintillator. We also address whether the coupling can be improved by using an intermediate optical element such as a lens, and we provide a means for calculating its required optical properties for a given geometry.

Evolving Input-Output Models of Chemical Process Systems Using Genetic Programming

Abstract Complex processes are often modelled using input-output data from experimental tests. Regression and neural network modelling techniques are commonly used for this purpose. Unfortunately, these methods provide minimal structural insight into process characteristics. In this contribution, we propose the use of Genetic Programming (GP) as a method for developing input-output process models from experimental data. GP performs symbolic regression, determining both the structure and the complexity of the model during its evolution. This lias the advantage that no a priori modelling assumptions have to be made. Moreover, the technique can discriminate between relevant and irrelevant process inputs, yielding parsimonious model structures that accurately represent process characteristics. Two examples are used to demonstrate the utility of the GP technique as a process modelling tool.

Acoustics based on-line quality estimation

Abstract One of the major difficulties with developing advanced control strategies for cooking extruders is the lack of cheap, easy to implement, on-line “product quality” estimators. One of the most promising developments in this area is the recent emergence of acoustics based estimation techniques. The basis of this approach relies on the fact that as the extrudate leaves the die, the water content partially flashes causing the extrudate to expand. There are discernible differences in sound as this steam escapes when different products are being extruded. It is the interaction between this expansion, the rheology of the extrudate, and the resultant bubble size distribution that gives the final product many of the qualities that both the manufacturer and the consumer are looking for. This paper outlines the techniques used to analyse experimental acoustic data and develop correlations to predict final extruder product properties.