<div>The objective of this doctoral research was to develop a versatile inverse heat transfer approach, that would enable the solution of small scale problems present in microelectronics, as well as the analysis of the complex heat flux in turbines. An inverse method is a mathematical approach which allows the resolution of problems starting from the solution. In a direct problem, the boundary conditions are given, and using the governing physics principles and equations you can calculate the solution or physical effect. In an inverse method, the solution is provided and through the physical equations, the boundary conditions can be determined. Therefore, the inverse method applied to heat transfer means that we know the variation of temperature (effect) over time and space. With the temperature input, the geometry, thermal properties of the test article and the heat diffusion equation, we can compute the spatially- and temporally-varying heat flux that generated the temperature map.</div><div><br></div><div>This doctoral dissertation develops two inverse methodologies: (1) an optimization methodology based on the conjugate gradient method and (2) a function specification method combined with a regularization technique, which is less robust but much faster. We implement these methodologies with commercial codes for solving conductive heat transfer with COMSOL and for conjugate heat transfer with ANSYS Fluent.</div><div><br></div><div>The goal is not only the development of the methods but also the validation of the techniques in two different fields with a common purpose: quantifying heat dissipation. The inverse methods were applied in the micro-scale to the dissipation of heat in microelectronics and in the macro-scale to the gas turbine engines.<br></div><div><br></div><div>In microelectronics, we performed numerical and experimental studies of the two developed inverse methodologies. The intent was to predict where heat is being dissipated and localized hot spots inside of the chip from limited measurements of the temperature outside of the chip. Here, infrared thermography of the chip surface is the input to the inverse methods leveraging thermal model of the chip. Furthermore, we combined the inverse methodology with a Kriging interpolation technique with genetic algorithm optimization to optimize the location and number of the temperature sensors inside of the chip required to accurately predict the thermal behavior of the microchip at each moment of time and everywhere.<br></div><div><br></div><div>In the application for gas turbine engines, the inverse method can be useful to detect or predict the conditions inside of the turbine by taking measurements in the outer casing. Therefore, the objective is the experimental validation of the technique in a wind tunnel especially designed with optical access for non-contact measurement techniques. We measured the temperature of the outer casing of the turbine rotor with an infrared camera and surface temperature sensors and this information is the input of the two methodologies developed in order to predict which the heat flux through the turbine casing. A new facility, specifically, an annular turbine cascade, was designed to be able to measure the relative frame of the rotor from the absolute frame. In order to get valuable data of the heat flux in a real engine, we need to replicate the Mach, Reynolds, and temperature ratios between fluid and solid. Therefore, the facility can reproduce a large range of pressures and flow temperatures. Because some regions of interest are not accessible, this researchprovides a significant benefit for understanding the system performance from limited data. With inverse methods, we can measure the outside of objects and provide an accurate prediction of the behavior of the complete system. This information is relevant not only for new designs of gas turbines or microchips, but also for old designs where due to lack of prevision there are not enough sensors to monitor the thermal behavior of the studied system.<br></div><div><br></div>

Sensors have become essential elements in human life for safe and comfortable existence in the ever demanding world. Various technologies over decades have contributed in their own way fulfilling innumerable sensing requirements. The discovery of optical sensor technologies has revolutionized the sensing field due to their inherent advantages. Among the large number of fiber optic sensor technologies, FBG based sensors have become widely known and popular within and outside the photonics community and has seen a prominent rise in their utilization. This thesis explores the use of FBG sensors for a wide range of applications scanning across a variety of engineering and medical applications, in the areas of civil engineering, biomechanical engineering, aerospace engineering, geoengineering, etc. It also deals with newer methods of packaging FBG sensors for the measurement of specific engineering parameters like strain, temperature, pressure, displacement and vibration. In the field of civil engineering, FBG sensors are employed for strain sensing on a prism and furthermore tested on a full size brick wallet. During this study, emphasis is made on substituting traditional sensors by specially packaged FBG sensors with the intent of either enhancing the sensing system’s performance or in merging/uniting the inherent advantages of FBG sensors. In the area of biomechanics, a novel sensor methodology using FBG sensors, for measuring surface strains generated on the skin of the calf muscle during various leg exercises is proposed. This methodology is used to address one of the most critical and life threatening issues in long distance air travel, namely the Deep Vein Thrombosis. Further, a FBG sensor based plantar sensing plate, is designed and developed, to measure plantar strain distribution in foot and also to analyze the postural stability. In the field of aerospace engineering, FBG sensors are used for addressing two of the most vital issues; Structural Health Monitoring (SHM) and direct measurement of pressure and temperature on the surface of an aircraft under hypersonic wind flow. Carbon Fiber Composite coupon level testing is carried out to obtain a generic strain calibration factor for the FBG sensor. Further, FBG sensors are exploited for the direct measurement of absolute temperature and pressure on the leeward surface of blunt cone at hypersonic wind speeds. In the domain of geoengineering, the feasibility studies have been undertaken to use a FBG as a seismic sensor and as a bore-well characterizing sensor. A novel FBG seismic sensor package is developed using a single FBG sensor to pick up the seismic waves propagating through the ground generated from earthquakes and ground tremors. Further, FBG sensors are used for measurement of temperature profiles in a bore-well to delineate and characterize the behavior of fractures during seasonal climatic changes. To summarize, the present thesis demonstrates a comprehensive experimental study which bring out the utility of FBG sensors in a variety of challenging applications.