Elaine P. Scott

Thermal Detection of Embedded Tumors using Infrared Imaging

Breast cancer is the most common cancer among women. Thermography, also known as thermal or infrared imaging, is a procedure to determine if an abnormality is present in the breast tissue temperature distribution. This abnormality in temperature distribution might indicate the presence of an embedded tumor. Although thermography is currently used to indicate the presence of an abnormality, there are no standard procedures to interpret these and determine the location of an embedded tumor. This research is a first step towards this direction. It explores the relationship between the characteristics (location and power) of an embedded heat source and the resulting temperature distribution on the surface. Experiments were conducted using a resistance heater that was embedded in agar in order to simulate the heat produced by a tumor in the biological tissue. The resulting temperature distribution on the surface was imaged using an infrared camera. In order to estimate the location and heat generation rate of the source from these temperature distributions, a genetic algorithm was used as the estimation method. The genetic algorithm utilizes a finite difference scheme for the direct solution of the Pennes bioheat equation. It was determined that a genetic algorithm based approach is well suited for the estimation problem since both the depth and the heat generation rate of the heat source were accurately predicted.

USE OF GENETIC ALGORITHMS IN THERMAL PROPERTY ESTIMATION: PART II - SIMULTANEOUS ESTIMATION OF THERMAL PROPERTIES

This two-part study is on the use of genetic algorithms (GAs) to design experiments and develop estimation methodologies for the determination of thermal properties; Part I is focused on the development of an improved GA, called an extended elitist genetic algorithm (EEGA), and on the implementation of this algorithm to optimize experimental designs used in thermal property estimation, while Part II is directed toward the application of this algorithm to the simultaneous estimation of thermal properties. In Part II the EEGA is used to minimize a least squares objective function containing calculated and measured temperatures. While the EEGA was shown to be an effective strategy for the optimization of experiments in Part I, its potential for use in the estimation of thermal properties is shown here in Part II through the use of case studies. In addition, the effect of the choice of the criterion used to optimize the experimental designs on the accuracy of the property estimates was analyzed for one of the...

Integrated packaging of a 1 kW switching module using a novel planar integration technology

A metal-oxide-semiconductor field-effect transistor (MOSFET) (rating at 500 V/24 A) half-bridge power switching subassembly with gate drivers has been fabricated, employing a planar integration technology, in which an integrated power chips stage is built by embedding chips in a coplanar ceramic substrate with a metallization thin-film interconnection built up onto it. This deposited metallization not only bonds the power chips, but also provides the second-level interconnect wiring. The associated components are mounted on top of the integrated power stage. This packaging scheme results in a three-dimensional (3-D) multiple chips/components assembly with the capability of functional integration. In this paper, the electrical and thermal parameters of this packaged module have been experimentally and theoretically characterized. The procedures adopted for the defined fabrication processes are presented. In addition to the characteristics of the planar integration process, the improved electrical and thermal performance has been demonstrated.

Thermal dose optimization in hyperthermia treatments by using the conjugate gradient method

In the treatment of cancerous tumors, the thermal dose is the time temperature history required to treat or destroy the undesirable tissue. The aim of this article is to calculate the optimum history of the heat source that, in the one-dimensional bioheat transfer model, results in the desired thermal dose. The time dependent strength of this source defines the accumulated energy at the end of a single heat treatment period. First the optimum control problem is formulated in infinite-dimensional form. The associated adjoint problem is obtained using the calculus of variations and an analytical formula is derived for the gradient of the functional of interest. Then a parametric representation of the control parameter is developed and the adjoint state approach is performed in conjugation with the conjugate gradient method for the solution of this control problem in finite-dimensional form. A one-dimensional numerical case is analyzed and discussed to demonstrate the performance and the robustness of the present method.

The Question of Thermal Waves in Heterogeneous and Biological Materials

In the 1990s, there were two experimental studies that sparked a renewed interest in thermal wave behavior at the macroscale level. Both reported thermal relaxation times of 10 s or higher. However, no further experimental evidence of this behavior has been reported. Due to the extreme significance of these findings, the objectives of this study were to try to reproduce these earlier studies and offer an explanation for the outcome. These two previous studies, one using heterogeneous materials and one using bologna, were repeated following the experimental protocol provided in the studies as closely and as practically as possible. In both cases, the temperature response to a specified boundary condition was recorded. The results from the first set of experiments suggested that the thermal relaxation times presented in the previous study were actually the thermal lag expected from applying Fouriers law, taking into account the uncertainty of the temperature sensor. In the second set of experiments, unlike the distinct jumps in temperature found previously, no indication of wave behavior was found. Here, the explanation for the previous results was more difficult to ascertain. Possible explanations include problems with either the experimental protocol or the temperature sensors used.

Development of methodologies for the estimation of blood perfusion using a minimally invasive thermal probe

Parameter estimation techniques have been utilized in the development of methodologies for the noninvasive determination of blood perfusion using measurements from a new thermal surface probe. The basic concept behind this work is that heat flux and temperature measurements from the probe are combined with results from a mathematical model of the probe and tissue in an estimation procedure for the determination of the blood perfusion. The key element of the probe is a thin sensor, which is placed in contact with the tissue and provides time-resolved signals representing heat flux and temperature while the probe is cooled by air jets. This probe has been newly modified to enhance performance. Parameter estimation techniques were developed which incorporate measured heat flux and/or temperature data and corresponding calculated data from the model to estimate blood perfusion and also the thermal contact resistance between the probe and the tissue. The sensitivity coefficients associated with heat flux were found to be much higher than those associated with temperature such that the heat flux measurements were the most influential in the estimation of the parameters. Simultaneous estimates of blood perfusion and contact resistance were successfully obtained using the Gauss minimization method. The resulting estimates of blood perfusion were consistent with the range of values found in the literature.

USE OF GENETIC ALGORITHMS IN THERMAL PROPERTY ESTIMATION: PART I - EXPERIMENTAL DESIGN OPTIMIZATION

This two-part study is on the use of genetic algorithms (GAs) to design experiments and develop estimation methodologies for the determination of thermal properties; Part I is focused on the development of an improved GA and the implementation of this algorithm to optimize experimental designs for the estimation of thermal properties, while Part II is directed toward the use of this algorithm in the estimation of thermal properties. In Part I the methodology used in the improved GA, called the extended elitist genetic algorithm (EEGA), is presented, and results from two optimization test problems are compared with those obtained previously from a basic elitist genetic algorithm (BEGA) and a parametric study. GAs are based on the genetic and selection mechanisms of nature, and the EEGA improves on the BEGA by enhancing the Darwinian principle of the “survival of the fittest. ” In the test problems, several key parameters in two experimental designs used for the simultaneous estimation of thermal properties...

Electrical and thermal layout design considerations for integrated power electronics modules

A methodology was developed to optimize the 3D geometrical design layout of an active integrated power electronics module (IPEM) by considering both electrical and thermal performance. This paper is focused on the electrical analysis, including the parasitic extraction done by the Maxwell Q3D Extractor. A parametric study was conducted to determine the common model EMI noise of several different layouts. The final design layout was achieved after tradeoff between electrical and thermal performance.

Electrical and Thermal Layout Design and Optimization Considerations for DPS Active IPEM

A methodology was developed to optimize the 3D geometrical design layout of an active integrated power electronics module (IPEM) by considering both electrical and thermal performance. This paper is focused on the thermal analysis, which was performed using 3D finite element and computational fluid dynamic (CFD) analyses. A parametric study was conducted to determine the thermal performance of several different design layouts. A sensitivity analysis was performed to determine the overall uncertainty of the predicted simulations. The final design, Gen-II.C, provided a 70% reduction in the common mode current, a 4% reduction in the size of the geometric footprint, and a 3°C reduction in the maximum temperature over Gen-II.A, thus providing an increase in the overall performance.Copyright

Estimation of temperature dependent thermal properties of basic food solutions during freezing

Abstract The thermal properties of food materials exhibit substantial changes with temperature during the freezing process. The estimation of these properties is very important in simulating freezing and in determining the freezing time of foods. Mathematical modeling of thermal properties of foods has been an appealing alternative to experimental methods. These models are generally based on the assumption that food materials are ideal binary solutions. The goal of this research study is to estimate thermal properties, namely the thermal conductivity and apparent volumetric specific heat, of aqueous solutions of basic food substances (sucrose, methylcellulose and wheat gluten) during freezing. Temperature data from transient one-dimensional freezing experiments were used to estimate the temperature dependent thermal properties of these materials during freezing using the Box-Kanemasu estimation method. The estimated thermal properties were then compared with values obtained from models found in the literature. Generally, the predicted thermal conductivities using the models were close to those estimated using the experimental measurements for low concentration sucrose solutions. The predicted apparent volumetric specific heats exhibited larger discrepancies with the estimated values at all sucrose concentrations. Furthermore, the predicted thermal properties of methylcellulose and wheat gluten did not agree well with the estimated thermal properties due to their complex molecular structures and non-ideal characteristics of their aqueous solutions.