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An investigation of the temperature response and corresponding lesion growth resulting from in vivo interstitial laser photocoagulation was performed in order to test the applicability of Arrhenius theory. The irradiations were performed in vivo in rabbit muscle for various exposures at 1.0W using an 805 nm diode laser source coupled to an optical fibre with a pre-charred tip, thereby forcing it to function as a point heat source. Temperature responses were measured using a five-microthermocouple array along a range of radial distances from the point heat source. Each temperature profile was fitted with a curve predicted by the Weinbaum-Jiji bioheat transfer equation. The lesions were resected 48 hours after irradiation and the boundary of thermal damage resulting in necrosis was determined histologically. Numerical integration of the Arrhenius integral using temperature-time data at the lesion boundary produced corresponding activation energy and pre-exponential factor pairs (Ea , a) consistent with reported values for various other endpoints and tissue types. As well, theoretical predictions of the lesion growth from Arrhenius theory agreed well with experimental results. However, the thermal parameters, which are generally assumed to be constant when solving the bioheat transfer equation, were found to vary with radial distance from the source, presumably due to a dependence on temperature. / Thesis / Master of Science (MS)

Heat treatment for the purpose of material strengthening is accompanied by residual stresses and distortion. During these processing steps, steel alloys experience a phase change that in turn modify their overall mechanical response. To properly account for the cumulative composite behavior, the mechanical response, transformation kinetics and subsequent interaction of each phase have to be properly accounted for. Of interest to material designers and fabricators is modeling and simulating the evolutionary process a part undergoes for the sake of capturing the observable residual stress states and geometric distortion accumulated after processing. In an attempt to capture the aforementioned physical phenomena, this investigation is premised upon a consistent thermodynamic framework. Following this, the single phase Evolving Microstructural Model of Inelasticity state variable model is extended to accommodate the occurrence of multiphases, affirming that the interaction between coexisting phases is through an interfacial stress. Since the efficacy of a multiphase model is dependent on its ability to capture the behavior of constituents phases and their subsequent interaction, we introduce a physically based self-consistent strain partitioning algorithm. With synthesis of the aforementioned ideas, the additional transformation induced plasticity is numerically accounted for by modifying each phase’s flowrule to accommodate an interfacial stress. In addition, for simulating the cohabitation of two phases, the mechanical multiphase model equations is coupled with a previously developed non-diffusional phase transformation kinetics model. A qualitative assessment of the material response based on a Taylor, Sachs and self-consistent polycrystalline approximation is carried out. Further analysis of the multiphase model and its interaction with transformation kinetics is evaluated.

For years, heart rate (HR) kinetics have been used as an indicator of training status and fatigue. Slowed kinetics indicate poor fitness and/or fatigue. In this study it was determined that HR kinetics can be reliably estimated during modeled, quasi-binary, and dynamic exercise using cross-correlation analysis of HR and external work rate. Heart rate and running speed were cross-correlated yielding a cross-correlation function (CCF) and analyzed for its peak (CCFmax) and time delay (CCFlag). Modeled exercise data where the time constants for HR (τ) increased from 2-120 sec. yielded linear decreases in CCFmax (r2 = 0.9949) and linear increases in CCFlag (r2=0.9996). A strong linear relationship existed between CCFmax and CCFlag (r2=0.9989). Steady-state exercise data produced strong relationships between the calculated τ and CCFmax (r2=0.8736) and CCFlag (r2=0.9061), and CCFmax and CCFlag showed a positive relationship (r2=0.7753). CCFmax between repeated sprint trials (R2=0.9123) and super set trails (R2=0.9227) were very similar. These results suggest good repeatability for both quasi-binary activity and random activity. To assess validity, CCFmax values during the sprint trials were compared to two standard field tests of fitness (Beep and Man U tests). There were strong relationships between CCFmax and distances covered during the Beep (r2=0.7911) and Mann U tests (r2=0.7770). Lastly, the applicability of the CCF method was applied to dynamic exercise, using data collected from competitive soccer matches. For the field players, significant reductions in CCFmax occurred during the first and second periods of the match. There was a significant relationship between the total distance covered during the match and the decline in CCFmax (r=-0.4297, p<0.05). Larger declines in CCFmax during the last 15 min of the match were also seen in the second match of a multiple match week compared to the first match. Tis later finding suggests that CCFmax may be a use tool to evaluate "fatigue" during dynamic exercise. Overall, cross-correlation of HR and running speed appears to be a reliable, valid and applicable approach to evaluate HR kinetics during exercise. As such, it may be beneficial for evaluating player fitness and readiness for competition. / Doctor of Philosophy / Exercise physiologists and sports professionals are continually in search of novel techniques which would assess training effectiveness and performance on the field. However, it is of paramount importance that any field-based data collection method must be noninvasive as to not interfere with the athlete's ability to perform in sport. Currently, heart rate (HR) is the most readily accessible and commonly used variable to estimate cardiovascular response to exercise. Heart rate kinetics have proven to be a powerful indicator of training status as HR responses to changes in exercise intensity are accelerated following exercise training. In this study we were able to determine that HR kinetics can be reliably estimated during modeled, quasi-binary, and dynamic exercise using cross-correlation analysis of HR and external work rate. Heart Rate and running speed were cross-correlated yielding a cross-correlation function (CCF). That function was then analyzed for its peak (CCFmax) and time delay (CCFlag). Modeled exercise data yielded linear decreases in CCFmax and linear increases in CCFlag. Also, CCFmax and CCFlag were correlated to each other. Steady-state exercise data produced the same linear relationships observed for the modeled data for CCFmax and CCFlag. CCFmax between repeated sprint trials were found to be highly reliable which suggest good repeatability for both quasi-binary activity and random activity. CCFmax was also found to be highly valid when comparing sprint values to validated fitness test values. Additionally, good relationships were found between CCFmax derived during fitness tests and distances covered on the fitness tests. As HR kinetics are linked to fitness, these results suggest that CCFmax values are valid. There was a significant relationship between the total distance covered during a full soccer match and the decline in CCFmax in field players that were not seen in the goalkeeper. Lastly, CCFmax declined during the last 15 minutes of the match compared to the start of the match. These results demonstrate CCF derived HR kinetics appear to be reliable and valid metrics for evaluating soccer fitness and "fatigue". This method may prove to be a strong indicator of fitness in other high activity sports as well.

Please read the abstract in the dissertation. Copyright / Dissertation (MEng)--University of Pretoria, 2011. / Chemical Engineering / unrestricted

Fatigue cracking is one primary distress in asphalt pavements, dominant especially in later years of service. Prediction of mixture fatigue resistance is critical for various applications, e.g., pavement design and preventative maintenance. The goal of this work was to develop a tool for prediction of binder aging level and mixture fatigue life in pavement from unaged binder/mixture properties. To fulfill this goal, binder oxidation during the early fast-rate period must be understood. In addition, a better hourly air temperature model is required to provide accurate input for the pavement temperature prediction model. Furthermore, a user-friendly software needs to be developed to incorporate these findings. Experiments were conducted to study the carbonyl group formation in one unmodified binder (SEM 64-22) and one polymer-modified binder (SEM 70-22), aged at five elevated temperatures. Data of SEM 64-22, especially at low temperatures, showed support for a parallel-reaction model, one first order reaction and one zero order reaction. The model did not fit data of SEM 70-22. The polymer modification of SEM 70-22 might be responsible for this discrepancy. Nonetheless, more data are required to draw a conclusion. Binder oxidation rate is highly temperature dependent. Hourly air temperature data are required as input for the pavement temperature prediction model. Herein a new pattern-based air temperature model was developed to estimate hourly data from daily data. The pattern is obtained from time series analysis of measured data. The new model yields consistently better results than the conventional sinusoidal model. The pavement aging and fatigue analysis (PAFA) software developed herein synthesizes new findings from this work and constant-rate binder oxidation and hardening kinetics and calibrated mechanistic approach with surface energy (CMSE) fatigue analysis algorithm from literature. Input data include reaction kinetics parameters, mixture test results, and pavement temperature. Carbonyl area growth, dynamic shear rheometer (DSR) function hardening, and mixture fatigue life decline are predicted as function of time. Results are plotted and saved in spreadsheets.