John Wilson

The continuous annealing process is widely used in the production of advanced high-strength steels. However, to tightly regulate the mechanical properties of the steel, precise control of processing parameters is needed. Although some techniques are available to monitor the mechanical properties of the steel on entry and exit to the furnace, monitoring the evolving microstructure of the steel through installation of sensors in the annealing line is extremely challenging due to the high temperature, high speed of the steel strip and limited space in the furnace. This study presents the development and validation of a multifrequency electromagnetic sensor system for real-time monitoring of microstructural transformations in steel during thermal cycling, intended for deployment in a continuous annealing line. Experiments were conducted on austenitic stainless steel to study the signal response to an increase in resistivity without a change in magnetic permeability. Pure nickel was tested to investigate the response to a change in magnetic permeability and the ferromagnetic-to-paramagnetic transition at its Curie temperature. A ferritic stainless steel was also tested to assess the performance of the system for high-temperature ferromagnetic materials and a higher-temperature ferromagnetic-to-paramagnetic transition. The tests indicate a strong response to material resistivity and permeability changes, with complementary information from different frequencies. Test results are supplemented by a finite element modelling study into the effect of a change in frequency and permeability on sensor response, with a discussion on the implications of experimental and modelling results for future applications. The results show that the developed system has the potential to characterise thermally induced changes in steels, establishing proof of concept for non-destructive, high-temperature electromagnetic sensing in steel processing and setting the foundation for further industrial deployment in phase and recrystallisation monitoring.

The Jiles–Atherton (J–A) model has seen extensive use for modelling the hysteresis behaviour of ferromagnetic materials due to its computational efficiency, simplicity of use, and small number of physically related parameters. However, in this work, the application of the J–A model to hysteresis curves obtained from experimental measurements for as-quenched and quenched-and-tempered engineering steels is considered. It has been demonstrated that the current form of the J–A model is not capable of representing certain observed features in the obtained hysteresis curves of these steels, in particular, the rapid narrowing of the loops seen for as-quenched steels and the sharp corners seen for quenched-and-tempered steels. This work has shown that a superior fit to the major loops for such steels can be obtained by applying Gaussian variations with respect to the applied magnetic field to the model parameters. The findings are supported by experimental results from engineering steels used in the oil and gas industry.

Although much information can be gained about thermally induced microstructural changes in metals through the measurement of their thermophysical properties using a differential scanning calorimeter (DSC), due to competing influences on the signal, not all microstructural changes can be fully characterised this way. For example, accurate characterisation of recrystallisation, tempering, and changes in retained delta ferrite in alloyed steels becomes complex due to additional signal changes due to the Curie point, oxidation, and the rate (and therefore the magnitude) of transformation. However, these types of microstructural changes have been shown to invoke strong magnetic and electromagnetic (EM) responses; therefore, simultaneous EM measurements can provide additional complementary data which can help to emphasise or deconvolute these complex signals and develop a more complete understanding of certain metallurgical phenomena. This paper discusses how a DSC machine has been modified to incorporate an EM sensor consisting of two copper coils printed onto either side of a ceramic substrate, with one coil acting as a transmitter and the other as a receiver. The coil is interfaced with a custom-built data acquisition system, which provides current to the transmit coil, records signals from the receive coil, and is controlled by a graphical user interface which allows the user to select multiple excitation frequencies. The equipment has a useable frequency range of approximately 1–100 kHz and outputs phase and magnitude readings at a rate of approximately 50 samples per second. Simultaneous DSC-EM measurements were performed on a nickel sample up to a temperature of 600 °C, with the reversable ferromagnetic to paramagnetic transition in the nickel sample invoking a clear EM response. The results show that the combined DSC-EM apparatus has the potential to provide a powerful tool for the analysis of thermally induced microstructural changes in metals, feeding into research on steel production, development of magnetic and conductive materials, and many more areas.

Coagulation of particles occurs when two particles collide and stick together. In the Martian atmosphere, dust coagulation would increase the effective particle size, as small particles accrete to larger particles. Murphy et al. (1990) showed that Brownian coagulation of dust in the Martian atmosphere was not significant, due to the low dust particle mixing ratios, while Montmessin et al. (2002) and Fedorova et al. (2014) showed that it mostly involves particle radii smaller than 0.1 um. However, the effects of coagulation have never been explored in 3D, during a global dust storm, i.e. in presence of larger numbers of small particles. Here we revisit this issue by using the NASA Ames Mars Global Climate Model (MGCM) to investigate the temporal and spatial changes in dust particle sizes during the 2018 global storm due to coagulation and the overall impact of these processes on Mars' climate. Our parameterization for coagulation includes the effect of Brownian motion, Brownian diffusion enhancement, and gravitational collection. We show that Brownian motion and Brownian diffusion enhancement dominate gravitational collection. The impact of coagulation is significant during the storm, with coagulation rates increased by a factor of 10 compared to non-storm conditions. The effective particle radius can be increased by a factor of 2 due to coagulation, leading to a 20K colder atmosphere above 30 km altitude. Overall, our parameterization improves the representation of the decay phase of the storm relative to observations. The process remains significant outside the storm period if large numbers of submicron-sized particles are involved. It may be possible, in GCMs, to lift larger amounts of submicron-sized particles from the surface without excess dust buildup in the atmosphere, thus improving the agreement with some of the observations without diverging from the observed column opacities.

Electromagnetic non-destructive testing techniques provide an attractive solution to the problem of monitoring microstructural changes in steels undergoing heat treatment as they are non-contact, have a short response time and are relatively inexpensive. However, to take full advantage of these techniques it is necessary to be able accurately measure the magnetisation characteristics of the materials of interest at temperatures up to the Curie point. This paper details the development of a novel high temperature Epstein frame for installation in a furnace with the design informed and results validated by finite element modelling. Hysteresis loop characteristics are successfully measured for a dual phase steel up to the Curie point for heating and cooling. Results show the developed system has the potential to provide valuable data to inform online electromagnetic monitoring systems.

Iron-rich meteorites are significantly underrepresented in collection statistics from Antarctica. This has led to a hypothesis that there is a sparse layer of iron-rich meteorites hidden below the surface of the ice, thereby explaining the apparent shortfall. As standard Antarctic meteorite collecting techniques rely upon a visual surface search approach, the need has thus arisen to develop a system that can detect iron objects under a few tens of centimetres of ice, where the expected number density is of the order one per square kilometre. To help answer this hypothesis, a large-scale pulse induction metal detector array has been constructed for deployment in Antarctica. The metal detector array is 6 m wide, able to travel at 15 km h^-1 and can scan 1 km² in ~11 hours. This paper details the construction of the metal detector system with respect to design criteria, notably the ruggedization of the system for Antarctic deployment. Some preliminary results from UK and Antarctic testing are presented. We show that the system performs as specified and should reach the pre-agreed target of the detection of a 100 g iron meteorite at 300 mm when deployed in Antarctica.

This paper elaborates the sample preparation protocols required to obtain optimal domain patterns using the Bitter method, focusing on the extra steps compared to standard metallographic sample preparation procedures. The paper proposes a novel bespoke rig for dynamic domain imaging with in situ BH (magnetic hysteresis) measurements and elaborates the protocols for the sensor preparation and the use of the rig to ensure accurate BH measurement. The protocols for static and ordinary dynamic domain imaging (without in situ BH measurements) are also presented. The reported method takes advantage of the convenience and high sensitivity of the traditional Bitter method and enables in situ BH measurement without interrupting or interfering with the domain wall movement processes. This facilitates establishing a direct and quantitative link between the domain wall movement processes–microstructural feature interactions in ferritic steels with their BH loops. This method is anticipated to become a useful tool for the fundamental study of microstructure–magnetic property relationships in steels and to help interpret the electromagnetic sensor signals for non-destructive evaluation of steel microstructures.