Evaluation of Martensite Fraction in 1026 Steel by Infrared Thermography Combined with the Koistinen-Marburger Model

2016 ◽  
Vol 869 ◽  
pp. 411-415
Author(s):  
Dimitry V. Bubnoff ◽  
Mariana M.O. Carvalho ◽  
Carlos Roberto Xavier ◽  
Gláucio S. da Fonseca ◽  
José Adilson de Castro
Keyword(s):  
Heat Treatment ◽  
Phase Transformations ◽  
Infrared Thermography ◽  
Martensite Transformation ◽  
Infrared Camera ◽  
Martensite Formation ◽  
Transformation Kinetics ◽  
Temperature Distributions ◽  
Martensite Fraction ◽  
Model Adjustment

In the present work, the martensite formation during heat treatment of 1026 steel was studied in order to acquire process knowledge and reinforce the effectiveness of infrared thermography method to evaluate the temperature distributions. Several tests were carried out and monitored by an infrared camera and thermocouples. Martensite fraction was evaluated with the aid of the Koistinen-Marburger model and adequate parameters describing phase transformations were obtained for 1026 steel samples. This research revealed the need of model adjustment in order to accurately describe the martensite transformation kinetics according to experimental results.

scholarly journals Real-time synchrotron X-ray diffraction study on the isothermal martensite transformation of maraging steel in high magnetic fields

2012 ◽  
Vol 45 (4) ◽  
pp. 748-757 ◽  
Author(s):  
D. San Martin ◽  
E. Jiménez-Melero ◽  
J. A. Duffy ◽  
V. Honkimäki ◽  
S. van der Zwaag ◽  
...  
Keyword(s):  
Maraging Steel ◽  
Martensite Transformation ◽  
Strain Relaxation ◽  
Transformation Strain ◽  
High Energy ◽  
Phase Behaviour ◽  
X Rays ◽  
Martensite Formation ◽  
Transformation Kinetics ◽  
Austenite Grains

The isothermal austenite-to-martensite transformation kinetics in a maraging steel have been studied by time-dependent microbeam diffraction measurements with high-energy X-rays. The transformation kinetics are shown to be accelerated significantly when a magnetic field of 8 T is applied. The average phase behaviour, obtained from a Rietveld refinement of the powder-averaged diffraction data, demonstrates that the martensite formation does not lead to a macroscopic strain in the austenite and martensite phases. An analysis of individual austenite reflections in the microbeam diffraction patterns, however, indicates that within the transforming austenite grains a transformation strain develops as a result of the formed martensite. The development of elastic strains during the transformation is explained by a partial strain confinement within the untransformed part of the austenite grain. The strain relaxation to the surrounding austenite grains is found to be dependent on the austenite volume. For a set of individual austenite grains the martensite nucleation is correlated with the initial austenite volume and the strain developed prior to the transformation as a result of martensite formation in the neighbouring grains.

scholarly journals 3D Thermal Monitoring of Jointed Rock Masses through Infrared Thermography and Photogrammetry

2021 ◽  
Vol 13 (5) ◽  
pp. 957
Author(s):  
Guglielmo Grechi ◽  
Matteo Fiorucci ◽  
Gian Marco Marmoni ◽  
Salvatore Martino
Keyword(s):  
Surface Temperature ◽  
Infrared Thermography ◽  
Point Cloud ◽  
Engineering Geology ◽  
Point Clouds ◽  
Jointed Rock ◽  
Geometric Accuracy ◽  
Rock Masses ◽  
Natural Systems ◽  
Temperature Distributions

The study of strain effects in thermally-forced rock masses has gathered growing interest from engineering geology researchers in the last decade. In this framework, digital photogrammetry and infrared thermography have become two of the most exploited remote surveying techniques in engineering geology applications because they can provide useful information concerning geomechanical and thermal conditions of these complex natural systems where the mechanical role of joints cannot be neglected. In this paper, a methodology is proposed for generating point clouds of rock masses prone to failure, combining the high geometric accuracy of RGB optical images and the thermal information derived by infrared thermography surveys. Multiple 3D thermal point clouds and a high-resolution RGB point cloud were separately generated and co-registered by acquiring thermograms at different times of the day and in different seasons using commercial software for Structure from Motion and point cloud analysis. Temperature attributes of thermal point clouds were merged with the reference high-resolution optical point cloud to obtain a composite 3D model storing accurate geometric information and multitemporal surface temperature distributions. The quality of merged point clouds was evaluated by comparing temperature distributions derived by 2D thermograms and 3D thermal models, with a view to estimating their accuracy in describing surface thermal fields. Moreover, a preliminary attempt was made to test the feasibility of this approach in investigating the thermal behavior of complex natural systems such as jointed rock masses by analyzing the spatial distribution and temporal evolution of surface temperature ranges under different climatic conditions. The obtained results show that despite the low resolution of the IR sensor, the geometric accuracy and the correspondence between 2D and 3D temperature measurements are high enough to consider 3D thermal point clouds suitable to describe surface temperature distributions and adequate for monitoring purposes of jointed rock mass.

scholarly journals A New Systematic Approach Based on Dilatometric Analysis to Track Bainite Transformation Kinetics and the Influence of the Prior Austenite Grain Size

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 324
Author(s):  
David San-Martin ◽  
Matthias Kuntz ◽  
Francisca G. Caballero ◽  
Carlos Garcia-Mateo
Keyword(s):  
Heat Treatment ◽  
Grain Size ◽  
Prior Austenite ◽  
Bainitic Transformation ◽  
Transformation Rate ◽  
Transformation Kinetics ◽  
Austenite Grain Size ◽  
Austenite Grain ◽  
Prior Austenite Grain Size ◽  
Prior Austenite Grain

This investigation explores the influence of the austenitisation heat treatment and thus, of the prior austenite grain size (PAGS), on the kinetics of the bainitic transformation, using as A case study two high-carbon, high-silicon, bainitic steels isothermally transformed (TIso = 250, 300, 350 °C), after being austenised at different temperatures (γTγ = 925–1125 °C). A methodology, based on the three defining dilatometric parameters extracted from the derivative of the relative change in length, was proposed to analyse the transformation kinetics. These parameters are related to the time to start bainitic transformation, the time lapse for most of the transformation to take place and the transformation rate at the end of the transformation. The results show that increasing the PAGS up to 70 µm leads to an increase in the bainite nucleation rate, this effect being more pronounced for the lowest TIso. However, the overall transformation kinetics seems to be weakly affected by the applied heat treatment (γTγ and TIso). In one of the steels, PAGS > 70 µm (γTγ > 1050 °C), which weakly affects the progress of the transformation, except for TIso = 250 °C, for which the enhancement of the autocatalytic effect could be the reason behind an acceleration of the overall transformation.

Characterization of Fouled Flat Sheet Membranes by Infrared Thermography

2014 ◽  
Author(s):  
Kennethrex O. Ndukaife ◽  
George Agbai Nnanna
Keyword(s):  
Surface Temperature ◽  
Infrared Thermography ◽  
Spectral Power ◽  
Membrane Surface ◽  
Infrared Camera ◽  
Feed Solution ◽  
Feed Concentration ◽  
Ir Camera ◽  
Measure Surface Temperature

An Infrared thermography (IRT) technique for characterization of fouling on membrane surface has been developed. The emitted spectral power from the fouled membrane is a function of emissivity and surface morphology. In this work, a FLIR A320 IR camera was used to measure surface temperature and emissivity. The surface temperature and the corresponding emissivity value of various areas on the fouled membrane surface is measured by the infrared camera and recorded alongside its thermogram. Different fouling experiments were performed using different concentrations of aluminum oxide nanoparticle mixed with deionized water as feed solution (333 ppm, 1833 ppm and 3333 ppm) so as to investigate the effect of feed concentration on the degree of fouling and thus its effect on the emissivity values measured on the membrane surfaces. Surface plots in 3D and Line plots are obtained for the measured emissivity values and thickness of the fouling deposit on the membrane surface respectively. The results indicate that the IRT technique is sensitive to changes that occur on the membrane surface due to deposition of contaminants on the membrane surface and that emissivity is a function of temperature, surface roughness and thickness of the specimen under investigation.

Reflection interference removal for infrared thermography images based on GAN

2021 ◽  
Vol 63 (9) ◽  
pp. 529-533
Author(s):  
Jiali Zhang ◽  
Yupeng Tian ◽  
LiPing Ren ◽  
Jiaheng Cheng ◽  
JinChen Shi
Keyword(s):  
Neural Networks ◽  
Infrared Thermography ◽  
Metal Surfaces ◽  
Infrared Image ◽  
Infrared Camera ◽  
Infrared Images ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Continuous Application ◽  
Visible Images

Reflection in images is common and the removal of complex noise such as image reflection is still being explored. The problem is difficult and ill-posed, not only because there is no mixing function but also because there are no constraints in the output space (the processed image). When it comes to detecting defects on metal surfaces using infrared thermography, reflection from smooth metal surfaces can easily affect the final detection results. Therefore, it is essential to remove the reflection interference in infrared images. With the continuous application and expansion of neural networks in the field of image processing, researchers have tried to apply neural networks to remove image reflection. However, they have mainly focused on reflection interference removal in visible images and it is believed that no researchers have applied neural networks to remove reflection interference in infrared images. In this paper, the authors introduce the concept of a conditional generative adversarial network (cGAN) and propose an end-to-end trained network based on this with two types of loss: perceptual loss and adversarial loss. A self-built infrared reflection image dataset from an infrared camera is used. The experimental results demonstrate the effectiveness of this GAN for removing infrared image reflection.

scholarly journals Physical and Numerical Simulations of Closed Die Hot Forging and Heat Treatment of Forged Parts

Materials ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 15
Author(s):  
Łukasz Poloczek ◽  
Łukasz Rauch ◽  
Marek Wilkus ◽  
Daniel Bachniak ◽  
Władysław Zalecki ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Grain Size ◽  
Numerical Simulations ◽  
Phase Transformations ◽  
Hot Forging ◽  
Transformation Model ◽  
Controlled Cooling ◽  
Austenite Grain Size ◽  
Austenite Grain ◽  
Conventional Heat Treatment

The paper describes physical and numerical simulations of a manufacturing process composed of hot forging and controlled cooling, which replace the conventional heat treatment technology. The objective was to investigate possibilities and limitations of the heat treatment with the use of the heat of forging. Three steels used to manufacture automotive parts were investigated. Experiments were composed of two sets of tests. The first were isothermal (TTT) and constant cooling rate (CCT) dilatometric tests, which supplied data for the identification of the numerical phase transformation model. The second was a physical simulation of the sequence forging-cooling on Gleeble 3800, which supplied data for the validation of the models. In the numerical part, a finite element (FE) thermal-mechanical code was combined with metallurgical models describing recrystallization and grain growth during forging and phase transformations during cooling. The FE model predicted distributions of the temperature and the austenite grain size in the forging, which were input data for further simulations of phase transformations during cooling. A modified JMAK equation was used to calculate the kinetics of transformation and volume fraction of microstructural constituents after cooling. Since the dilatometric tests were performed for various austenitization temperatures before cooling, it was possible to include austenite grain size as a variable in the model. An inverse algorithm developed by the authors was applied in the identification procedure. The model with optimal material parameters was used for simulations of hot forging and controlled cooling in one of the forging shops in Poland. Distributions of microstructural constituents in the forging after cooling were calculated. As a consequence, various cooling sequences during heat treatment could be analyzed and compared.

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