Suleiman, Fatima K2025-04-252025-04-252025-04-252025-04-04https://hdl.handle.net/10012/21646Advanced high strength steels (AHSS) play a prominent role in the automotive industry due to their unique combinations of strength and ductility—essential material properties for manufacturing lightweight vehicles that meet global regulations for fuel economy, vehicle emissions, and passenger safety. Precise thermal control during intercritical annealing is crucial to achieving the mechanical properties of AHSS. Unfortunately, steel manufacturers report unacceptably high rejection rates for AHSS due to substandard mechanical properties. This problem is often attributed to temperature excursions during intercritical annealing of the AHSS, which can be caused by errors in the pyrometrically-inferred temperatures used to control the furnaces. Measuring the temperature of the steel strip through pyrometry requires detailed knowledge of the spectral emissivity of the steel strip, which is imperfectly known since it varies with wavelength, direction, temperature, surface roughness, and oxidation, the latter depending on alloy composition and processing conditions. Therefore, wavelength-dependent variations in the spectral emissivity of AHSS lead to errors in pyrometry measurements during intercritical annealing, which in turn affect the mechanical properties of the steel. In pyrometry, a temperature estimate is typically obtained using spectral irradiance measured from the steel strip in combination with an emissivity compensation algorithm that assumes or prescribes an underlying emissivity relationship based on the number of detection wavelengths. While various emissivity compensation approaches have been developed for mitigating pyrometer errors caused by uncertain spectral emissivity, none have been specifically designed for AHSS. Hence, these methods do not adequately capture how the evolving surface state of annealing AHSS affects the spectral emissivity and thus the resulting pyrometrically-inferred measurements. Further, existing pyrometry algorithms only provide a point estimate of the surface temperature, making it impossible to assess the reliability of the estimates. To address these challenges, this dissertation aims to develop robust pyrometry methods for AHSS that provide accurate and precise temperature estimates with its associated uncertainties. This thesis starts by presenting an empirical approach for modelling the spectral emissivity of advanced high strength steel based on response surface methodology (RSM). Using ex situ measurements on annealed dual-phase AHSS samples (DP980), variation in the spectral emissivity with respect to dew point, alloy composition, pre-annealed surface state, and wavelength is analyzed using full factorial designs. The significant main and interaction effects were found to vary across the spectral range, with the ratio of alloy components and pre-annealed surface state dominating at shorter and longer wavelengths, respectively. Furthermore, the factorial design of experiments was used to develop a novel multivariate emissivity model capturing the effects of dew point, alloy composition, pre-annealed surface state, and wavelength on the emissivity of dual-phase AHSS. To extend the investigation to the high-temperature spectral emissivity variations during intercritical annealing, a laboratory-scale annealing simulator representative of the industrial furnace conditions was designed and fabricated to enable in situ pyrometry and emissivity measurements on AHSS samples. With lab-scale experiments that simulate the annealing and temperature control process of an industrial continuous galvanizing line (CGL), the in situ effect of process parameters, such as chemical composition, annealing temperature, and atmosphere dew point, on the radiative properties of AHSS was observed and modelled. Using in situ measurements from DP980 alloys heated in the annealing simulator, the suitability of existing pyrometry models for accurately predicting the surface temperature of AHSS was examined. By comparing the performance of several dual-wavelength (ratio) and multi-wavelength pyrometry algorithms, it was observed that both methods over-predict the surface temperature; however, the predictions of the multi-wavelength algorithm were generally superior. Given that the spectral emissivity varies significantly with the surface properties of the AHSS coil and further evolves with surface oxidation during annealing, this thesis also investigated the effect of the annealing atmosphere on the radiative properties of dual phase AHSS (DP980) using in situ spectral emissivity measurements from samples annealed within a reducing N2-H2 atmosphere at dew points ranging from −45°C to +10°C, with an annealing schedule similar to that of industrial continuous galvanizing lines (CGLs). The analysis further explored the effect of variations in oxidation kinetics by comparing the radiative properties of DP980 replicates annealed with the same heating schedule and dew point. It was also discovered that low-temperature oxidation of the native oxide of AHSS impacts the evolving spectral emissivity during intercritical annealing. In addition, a comparison of evolving spectral emissivity of dual-phase AHSS alloys against that of a standard EDDS grade IF steel showed that in situ emissivity measurements could potentially identify the formation of mixed/ternary oxides during annealing. Furthermore, this thesis also evaluated the ability of ex situ measurements to capture temperature-dependent variations in emissivity due to electron mobility as described by the Drude model and the Hagen-Rubens theory. The ex situ radiative properties were found to underpredict the in situ spectral emissivity, especially at lower temperatures and at shorter wavelengths. This underprediction was also shown to significantly impact the accuracy of pyrometry estimates at those temperatures. The ex situ measurements were also used to validate the annealing simulator against an industry-standard galvanizing simulator. Finally, with the ultimate objective of improving the robustness of pyrometrically-inferred temperature measurements, this dissertation presents a Bayesian pyrometry methodology in which all pyrometry variables including the measured spectral irradiance, spectral emissivity and inferred-temperature are expressed as random variables that obey probability density functions. Additional information about the spectral emissivity from ex situ characterization were first incorporated into the inference through maximum likelihood priors. The prior and measurement densities were propagated through Bayes’ equation to obtain the posterior densities. The posterior densities provide the pyrometrically-inferred temperature and, crucially, its associated uncertainties. Compared to standard pyrometry methods that provide a point estimate of surface temperature, the Bayesian framework infers the measurement uncertainty via the posterior probability density, which will allow galvanizers to better assess the reliability of the pyrometrically-inferred temperature. The credibility interval of the temperature posterior was further narrowed by defining a multivariate in situ emissivity prior conditioned on the annealing dew point and the equivalent blackbody temperature. Overall, by investigating the behaviour of the spectral emissivity of AHSS during processing, specifically how it evolves with material properties and processing parameters, this thesis presents a comprehensive empirical approach to developing emissivity compensation algorithms that improves the accuracy and reliability of pyrometric temperature predictions on AHSS during annealing.enadvanced high strength steelspectral emissivitypyrometrynon-contact thermometryannealing simulationBayesian statisticsuncertainty quantificationresponse surface methodologyDoctoral Thesis