Browsing by Subject "Temperature control"

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Computational modeling and real-time control of patient-specific laser treatment of prostate cancer
(2008-05) Fuentes, David Thomas A., 1981-; Oden, J. Tinsley (John Tinsley), 1936-
Hyperthermia based cancer treatments delivered under various modalities have the potential to become an effective option to eradicate the disease, maintain functionality of infected organs, and minimize complications and relapse. Moreover, hyperthermia therapies are a form of minimally invasive cancer treatment which are key to improving the quality of life post-treatment. Many modalities are available for delivering the heat source. However, the ability to control the energy deposition to prevent damage to adjacent healthy tissue is a limiting factor in all forms of thermal therapies, including cryotherapy, microwave, radio-frequency, ultrasound, and laser. The application of a laser heat source under the guidance of real-time treatment data has the potential to provide unprecedented control over the temperature field induced within the biological domain. The computational infrastructure developed in this work combines a computational model of bioheat transfer based on a nonlinear version of the Pennes equation for heterogeneous media with the precise timing and orchestration of the real-time solutions to the problems of calibration, optimal control, data transfer, registration, finite element mesh refinement, cellular damage prediction, and laser control; it is an example of Dynamic-Data-Driven Applications System (DDDAS) in which simulation models interact with measurement devices and assimilates data over a computational grid for the purpose of producing high-fidelity predictions of physical events. The tool controls the thermal source, provides a prediction of the entire outcome of the treatment and, using intra-operative data, updates itself to increase the accuracy of the prediction. A precise mathematical framework for the real-time finite element solution of the problems of calibration, optimal heat source control, and goal-oriented error estimation applied to the equations of bioheat transfer is presented. It is demonstrated that current finite element technology, parallel computer architecture, data transfer infrastructure, and thermal imaging modalities are capable of inducing a precise computer controlled temperature field within a biological domain. The project thus addresses a set of problems falling in the intersection of applied mathematics, imaging physics, computational science, computer science and visualizations, biomedical engineering, and medical science. The work involves contributions in the three component areas of the CAM program; A, Applicable Mathematics; B, Numerical Analysis and Scientific Computing; and C, Mathematical modeling and Applications. The ultimate goal of this research is to provide the medical community a minimally invasive clinical tool that uses predictive computational techniques to provide the optimal hyperthermia laser treatment procedure given real-time, patient specific data.
Temperature control and modeling of rapid thermal processing
(2005) Cho, Wonhui; Edgar, Thomas F.
A Rapid Thermal Processing (RTP) chamber capable of plasma-enhanced CVD was built with associated computer control system. The RTP chamber can handle up to a 6 inch wafer and is equipped with 37 tungsten halogen lamps positioned in three concentric zones to radiatively heat the wafer. Thermocouple instrumented wafers with K-type thermocouple junctions embedded at the proper temperature measurement positions acquired the temperature responses from center, middle and edge regions of the wafer. Two narrow band gap infrared pyrometers (λ = 3.3µm) were installed at the top of the lamp housing with water circulating light pipes accessing the wafer temperature signal points. In RTP, accurate temperature control during ramp and hold with fast ramp rate and good uniformity is necessary. The RTP chamber showed ill-conditioned behavior for a 3 x 3 lamp power and wafer temperature multivariable system, showing relatively large interactions between controlled variables, which yielded significant temperature differences across the wafer. A baffle ring was tested to obtain an improved condition number and uniformity of ±1◦C among three measured temperatures. Wafer effective emissivity and view factors were estimated from closed-loop identification of process parameters. Through the on-line estimation of the above parameters and simple closed-loop identification of the process parameters, such as time constants and process gains, one can detect wafer temperature variation from recipe set values when there is a unwanted deposition at the measurement side of the wafer. To accurately identify the ill-conditioned system, an iterative identification method was developed and effects of element uncertainties to control an ill-conditioned system was investigated. Furthermore, a multiloop control strategy was also developed. Finally, an iterative technique was introduced that allows a recipe-driven SISO(Single Input Single output) controlled system to automatically optimize the process recipe for optimal power ratios of each lamp zone.