Study on the Multi-wavelength Emissivity of GCr15 Steel and its Application on Temperature Measurement for Continuous Casting Billets

A method for measuring the multi-wavelength emissivity of a steel surface is proposed, and an applicable experimental apparatus is designed. Multi-wavelength radiant energy emitted from a sample was measured using a fiber-optic spectrometer and its temperature measured using a NiCrSi/NiSiMg thermocouple. Utilizing the unique vacuum control and background noise-shielding systems, we investigated the multi-wavelength emissivity of GCr15 steel at three different degrees of surface oxidation at temperatures ranging from 1000 \(^{\circ }\)C to \(1100\,^{\circ }\)C. The experimental results show that the multi-wavelength (0.7 \(\upmu \)m–0.9 \(\upmu \)m) emissivity increased substantially, from 0.409–0.565 to 0.609–0.702, once the steel was oxidized. In addition, the emissivity increased slightly with increasing temperature, but the trends for emissivity and wavelength were similar. To measure the surface temperature of casting billets based on multi-wavelength thermometry, the functional relationships between emissivity and wavelength at different extents of oxidation were determined. Temperature measurements based on our technique were compared with those from common colorimetric thermometry. Our approach reduced the temperature fluctuation from \(\pm 23\,^{\circ }\)C to \(\pm 3.5\,^{\circ }\)C, indicating that a reliable measurement of the multi-wavelength emissivity of GCr15 steel is obtained using this experimental apparatus.     

An efficient hybrid reliability analysis method with random and interval variables

Random and interval variables often coexist. Interval variables make reliability analysis much more computationally intensive. This work develops a new hybrid reliability analysis method so that the probability analysis (PA) loop and interval analysis (IA) loop are decomposed into two separate loops. An efficient PA algorithm is employed, and a new efficient IA method is developed. The new IA method consists of two stages. The first stage is for monotonic limit-state functions. If the limit-state function is not monotonic, the second stage is triggered. In the second stage, the limit-state function is sequentially approximated with a second order form, and the gradient projection method is applied to solve the extreme responses of the limit-state function with respect to the interval variables. The efficiency and accuracy of the proposed method are demonstrated by three examples.