Transformation Diagrams Research Articles

Gas Hydrate Formation and Slurry Flow Characteristics of Gas–Liquid–Solid Multiphase Systems

Hydrate formation, aggregation, and deposition have become major hazards for the safe transportation of oil and gas pipelines. Although there has been a great deal of research into the behavior of particles during hydrate formation and transport, there is less research into the multiphase generation and flow characteristics of hydrate gas and liquids. In this paper, the flow characteristics of hydrate slurry and the flow pattern transition in gas–liquid multiphase system were studied, and the generations of it were compared between a gas–liquid multiphase system and oil–water emulsion system. The results showed that the flow parameters such as pressure, pressure drop, and density fluctuated more drastically in the gas–liquid system than that in the emulsion system, the higher fluctuation meant a higher risk of pipe plugging. At the same time, the influence of pressure and dosage on multiphase flow pattern transformation and boundary change conditions were studied. A gas-slurry flow pattern transformation diagram was drawn based on the defined transformation conditions between flow patterns. The results also indicated that, with the increase of pressure from 5 to 6 MPa, the boundary of slug flow and air mass flow changed to the direction of higher gas and liquid flow velocity. While the boundary of slug flow and wave flow, stratified flow and wave flow changed to the direction of higher gas flow velocity. The boundary of slug flow and air mass flow changed to the direction of lower liquid flow velocity. In contrast, the boundary of slug flow and wave flow, stratified flow and wave flow, slug flow and stratified flow changed to the direction of higher gas flow velocity and lower liquid flow velocity in the 1% inhibitor period compared with that without the inhibitor. This study will provide theoretical references and technological supports for the safety of multiphase transportation pipelines and the safety of deep water production.

Thermokinetic Diagrams of Transformations in Supercooled Austenite in Alloyed Steels

Thermokinetic Diagrams of Transformations in Supercooled Austenite in Alloyed Steels

Improvements in welding continuous cooling transformation diagram of high-strength low-alloy steel weld

The welding continuous cooling transformation (CCT) diagram concerning microstructure evolution in a fine zone of the weld joint provides essential data for microstructure control in practice. In this study, a welding CCT diagram was improved to be elaborate by using the expanded lever rule. Processes for obtaining pieces of phase information are explained in detail. Improvements are: (i) phase areas are clearly presented, (ii) phase volume percentages are given, and (iii) overlapped phase areas are revealed. To meet high-strength requirement, a heat input of 21 kJ cm−1 was referenced from the welding CCT diagram, for achieving acicular ferrite and lath-like martensite. Transformed phase volume fractions are estimated and high strength and good toughness are obtained due to the elaborate phase information.

Gradient Boosted Regression Trees for Modelling Onset of Austenite Decomposition During Cooling of Steels

Continuous cooling transformation (CCT) diagrams can be constructed by empirical methods, which is expensive and time consuming, or by fitting a model to available experimental data. Examples of data-driven models implemented so far include regression models, artificial neural networks, k-Nearest Neighbours and Random Forest. Gradient boosting machine (GBM) has been succesfully used in many machine learning applications, but has not been used before in modelling CCT-diagrams. This article presents a novel way of predicting ferrite start temperatures for low alloyed steels using gradient boosting. First, transformation onset temperatures are predicted over a grid of values with a trained GBM-model after which a physically-based model is fitted to the piecewise constant curve obtained as output from the model. Predictability of the GBM-model is tested with two sets of CCT-diagrams and compared to Random Forest and JMatPro software. GBM outperforms its competitors under all tested model performance metrics: e.g.R2 for test data is 0.92, 0.87 and 0.70 for GBM, Random Forest and JMatPro respectively. Output from the GBM-model is used for fitting a physically based model, which enables the estimation of transformation start for any linear or nonlinear cooling path. This can be further converted to Time-Temperature-Transformation (TTT) diagram.

Impact toughness improvement of high boron-chromium steel by different isothermal heat treatment durations

Abstract This research investigates the improvement of impact toughness by changing isothermal heat treatment time for an alloy having high boron/chromium constituents. Different boron contents (0.5–5.00 wt% B) were added into high chromium steel by sand casting. Along with JMatPro program, dilatometry used to calculate critical temperatures and transformation diagrams as well. After austenization at 1050 °C for an hour, at 390 °C high B/Cr alloys isothermally heat treated for three different time intervals (24, 96, and 168 h). According to experimental findings, isothermal heat treatment enhanced hardness and impact toughness of the alloys (excluding 3.10 and 4.75 wt% boron containing alloys) due to the elimination of microsegregations and lowering carboboride sharpness. However, for every alloy wear resistance was not affected by isothermal heat treatment because carbide/boride fraction controls wear properties of the high B/Cr alloys. According to scanning electron microscope microstructures, cleavage fracture, and plowing were observed in isothermally heat treated specimens. It is noted that, isothermal heat treatment time showed no effect in mechanical properties of the high B/Cr alloys because the large amount of alloying elements shifted the phase transformation curve longer times which was more than JMatPro estimations.

Investigation on residual stress of EQ56 high strength steel butt weld

In the welding process of high-strength steel (HSS), the intense temperature change in joints induces the formation of welding residual stress (WRS), which increases the fatigue crack growth rate. Developing an effective finite element (FE) model for accurately predicting the WRS distribution is critical to improve the quality of welded structures. Experimental tests and numerical simulations were carried out to investigate the WRS distribution of EQ56 HSS. The thermal expansion curves at various heating and cooling rates were measured through thermal simulation experiments for achieving the continuous cooling transformation (CCT) diagram of EQ56 HSS. Based on the CCT diagram, the thermo-metallurgical-mechanical (TMM) FE model was developed to consider the influence of solid-state phase transformation (SSPT) on distribution and magnitude of WRS for welded EQ56 HSS joints, as well as material hardening law. Comparison of predicted WRS distribution and experimental data shows that plastic hardening laws of materials significantly affect the precision of WRS distribution, and combined hardening law gives most reliable prediction. The FE model considering SSPT behavior provides more accurate estimation of WRS distribution than those without considering SSPT behavior.

Experimental characterization and numerical modeling of a viscoelastic expandable epoxy foam: Time–temperature transformation and time–temperature equivalence diagrams

AbstractAn expandable and Fire, Smoke, and Toxicity (FST) compliant epoxy foam is proposed as an interesting alternative to Nomex® honeycomb cores for the development of Multi‐Functional Structures (MFS). The paper first analyzes the processing conditions using several experimental techniques as differential scanning calorimetry (DSC), rheology, and expansion in a closed volume in order to evaluate the reaction kinetics, the chemorheological behavior, and the expansion kinetics of the material. The experimental data are used to identify several empirical models describing the material processing behavior and finally plotting the isothermal time–temperature transformation (TTT) diagram. A typical curing cycle for the foam is used to describe the evolution of the material parameters during the curing process. The fully cured foam is then characterized using optical and laser microscopy in order to identify its cell size distribution and density. Quasi‐static and dynamic machines are used to evaluate its mechanical and dynamical properties. The time–temperature equivalence is finally used to plot the master's curves of the material, representing the evolution of the material viscoelastic properties as a function of the frequency.

A Parameterized Leblond-Devaux Equation for Predicting Phase Evolution during Welding E36 and E36Nb Marine Steels.

High heat input welding can improve welding efficiency, but the impact toughness of the heat-affected zone (HAZ) deteriorates significantly. Thermal evolution in HAZ during welding is the key factor affecting welded joints' microstructures and mechanical properties. In this study, the Leblond-Devaux equation for predicting phase evolution during the welding of marine steels was parameterized. In experiments, E36 and E36Nb samples were cooled down at different rates from 0.5 to 75 °C/s; the obtained thermal and phase evolution data were used to construct continuous cooling transformation diagrams, which were used to derive the temperature-dependent parameters in the Leblond-Devaux equation. The equation was then used to predict phase evolution during the welding of E36 and E36Nb; the quantitative experimental phase fractions of the coarse grain zone were compared with simulated results to verify the prediction results, which are in good agreement. When heat input is 100 kJ/cm, phases in the HAZ of E36Nb are primarily granular bainite, whereas for E36, the phases are mainly bainite with acicular ferrite. When heat input increases to 250 kJ/cm, ferrite and pearlite form in both steels. The predictions agree with experimental observations.

Decomposition of γ-Fe in 0.4C–1.8Si-2.8Mn-0.5Al steel during a continuous cooling process: A comparative study using in-situ HT-LSCM, DSC and dilatometry

Continuous cooling transformation (CCT) diagrams represent roadmaps for producing all heat-treatable steels. CCT curves provide valuable information on the solid-state phase transformation sequence, depending on the defined cooling strategies, the alloying concept of the steel and previous processing steps. The experimental characterization of CCT diagrams is usually done on a laboratory scale applying thermal analysis of dilatometry. In current research studies, however, also other in-situ methods such as high-temperature laser scanning confocal microscopy (HT-LSCM) or differential scanning calorimetry (DSC) are frequently used to investigate phase transformations during thermal cycling. In the present study, HT-LSCM observations and DSC analysis are critically compared with dilatometry results by investigating the CCT diagram of a 0.4%C-1.8%Si-2.8%Mn-0.5%Al (in mass pct.) advanced steel grade. Furthermore, classical examinations by optical microscopy and hardness measurements were performed to support the analysis. In general, very good consistencies between all experimental techniques were identified in determining the transformation start temperature for pearlite, bainite and martensite. The optical microscopy confirmed the observed phase transformations and the results correlated with the measured hardness response. Based on the results, coupling of HT-LSCM and DSC is considered as a valuable novel approach to plot CCT diagrams in future research.

Controlling the Thermal Stability of a Bainitic Structure by Alloy Design and Isothermal Heat Treatment.

The aim of this work was to develop a novel bainitic steel that will be specifically dedicated to achieving a high degree of refinement (nano- or submicron scale) along with increased thermal stability of the structure at elevated temperatures. The material was characterized by improved in-use properties, expressed as the thermal stability of the structure, compared to nanocrystalline bainitic steels with a limited fraction of carbide precipitations. Assumed criteria for the expected low martensite start temperature, bainitic hardenability level, and thermal stability are specified. The steel design process and complete characteristics of the novel steel including continuous cooling transformation and time-temperature-transformation diagrams based on dilatometry are presented. Moreover, the influence of bainite transformation temperature on the degree of structure refinement and dimensions of austenite blocks was also determined. It was assessed whether, in medium-carbon steels, it is possible to achieve a nanoscale bainitic structure. Finally, the effectiveness of the applied strategy for enhancing thermal stability at elevated temperatures was analyzed.

A Methodology for Predicting the Phase Fraction and Microhardness of Welded Joints Using Integrated Models

Understanding the phase transformation and fraction affected by thermal changes is imperative for ensuring the safety of a welded joint. This study proposes a methodology for predicting the phase transformation and fraction of a welded joint using an integrated model. The integrated model includes a heat transfer model and procedures for predicting phase fraction and microhardness. The heat transfer model was developed to simulate the heat transfer in a welded joint and obtain the thermal cycles. The procedure consists of obtaining the peak temperature, austenite fraction, prior austenite grain size (PAGS), and t8/5 (the cooling time between 800 and 500 °C). A database was constructed based on the continuous cooling transformation (CCT) diagram using PAGS and t8/5 as the variables. The phase fraction was then predicted by considering the PAGS with t8/5 from the database. The predicted phase fraction and microhardness were in good agreement with those determined experimentally, demonstrating the reliability of the methodology. This methodology provides a more realistic understanding of phase transformation and facilitates the prediction of the phase fraction and microhardness under various welding conditions that have experimental limitations.

Machine learning study on time–temperature–transformation diagram of carbon and low-alloy steel

Machine learning study on time–temperature–transformation diagram of carbon and low-alloy steel

Prediction of continuous cooling transformation diagrams in steels using light gradient boosting and rule-based optimization

ABSTRACT Continuous cooling transformation (CCT) diagram is an indispensable tool for new product development in the steel industry and it is traditionally plotted via extensive thermomechanical studies. To reduce the cycle time of product development, a machine-learning model to predict the CCT of a new grade (chemistry and processing parameters) has been developed in this work. The idea is to have a holistic predictive model suitable for integrated steel manufacturing plant, instead of having many models for different class of material compositions. A wide range of data set is prepared to this effect and explored with multiple regression-based machine-learning models. Light Gradient Boosting Machine (LGBM) demonstrates exceptional results amongst the rest, and it is topped off with a metallurgical constraint/correction-factor to obtain the final model. The model is validated against test data as well as against some well-established metallurgical correlations and is found to perform fairly well.

Iterative transformations for deeper exploration during concept generation

Engineering designers often generate multiple concepts to increase novelty and diversity among early solution candidates. Many past studies have focused on creating new concepts “from scratch;” however, designers at every level become fixated on their initial designs and struggle to generate different ideas. In line with prior work on design transformations, we propose a concept generation process of iterative transformation to create new ideas by intentionally introducing major changes in form, nature, or function to an existing concept. A study of this concept generation process recruited beginning engineering students likely to benefit from an alternative to "blank slate" generation. Working alone in a single test session, students generated an initial concept for a presented design problem. Then, they were instructed to generate another concept by transforming their initial design into a new concept and repeated this process to create three more concepts. In a second design round, students were asked to consider 7 Design Heuristics strategies to prompt possible transformations for their concepts. Beginning again with their initial concept, each student generated another set of four transformed concepts using iterative transformation. The analysis considered 60 initial concepts and 476 transformed concepts with and without the use of Design Heuristics. We created Design Transformation Diagrams to observe links (sequential, non-sequential, or both) between transformed concepts within each set of four concepts and between the two sets. Three patterns across the diagrams were identified: Fully Sequential, Sequential with Deviation, and Divergent. When aided by Design Heuristics, transformations included more non-sequential links, suggesting synthesis, refinement, and extension of other prior concepts, and resulting in more varied and distinct transformations. This iterative transformation process may support more diversity in concepts generated through a deeper exploration of related concepts without requiring an escape from the influence of existing concepts. Concept generation strategies like Design Heuristics may support engineering students as they learn to expand their early exploration of design concepts.

In-situ characterization of silicate slag crystallization by electrical impedance spectroscopy: Construction of continuous cooling transformation diagram

In-situ characterization of silicate slag crystallization by electrical impedance spectroscopy: Construction of continuous cooling transformation diagram

Development of a machine learning model for prediction of continuous cooling transformation diagrams in welding heat-affected zone

Development of a machine learning model for prediction of continuous cooling transformation diagrams in welding heat-affected zone

Usage of continuous cooling transformation (CCT) diagrams for laser and small-scale induction hardening

Using standard continuous cooling transform (CCT) diagrams for finding hardness of surfaces obtained by laser or small-size induction hardening is discussed. Their misuse may lead to differences between the values obtained from the model and experimental data because unlike hardening of large surfaces, the produced heat is mostly transferred away not by convection to the environment, but mainly by conduction to the interior of the metal material at a very high rate (at the level of many hundred Kelvins per second). The paper explains the details and offers a methodology of suppressing errors based on a combination of theoretical and experimental approaches. The methodology is illustrated with an example.

Application of time–temperature–transformation and time–pressure–transformation diagrams for cooling- and decompression-induced crystallization to estimate the critical cooling rate required to form glassy obsidian

The formation of glass from silicic magmas during eruption is an enigmatic process. To understand the formation of obsidian, we used time–temperature–transformation (TTT) and time–pressure–transformation (TPT) diagrams to estimate the critical cooling and decompression rates needed to form glassy obsidian. The TTT diagram is a contour map of the crystallized volume fraction as a function of the crystallization temperature and time. A contour line for a given crystal fraction in a time versus temperature diagram has a cone shape, with the “nose” of the curve corresponding to the minimum time and corresponding temperature required to generate a specific crystal fraction. We also present a TPT diagram, based on the TTT diagram, and liquidus curve for decompression-induced crystallization. We applied the TTT diagram to the Tokachi–Ishizawa obsidian from Shirataki, Hokkaido, Japan, and used it to estimate the critical cooling rate that would have been required to form its glassy texture by cooling-induced crystallization during eruption. For decompression-induced crystallization, we used the TPT diagram to estimate the critical decompression rate needed to form glassy obsidian. Based on our calculation results, the critical cooling and decompression rates are highly dependent on the interfacial energy between crystals and melt. We compared the estimated critical cooling and decompression rates with those estimated from microlite number density and a one-dimensional solution of the heat conduction equation. Our calculation results reveal that glassy obsidian can be formed during an eruption, particularly under conditions of high interfacial energy.

Influence of Preheating Temperature on Microstructure Evolution and Hardness of High‐Speed Steel AISI M50 Processed by Laser Powder Bed Fusion

The laser powder bed fusion (LPBF) technology has been involved in the tooling industry to produce tools with complex geometry and integrated functions. However, tool steels with high carbon content tend to crack due to the thermal stresses during the LPBF process. One solution is increasing the powder bed temperature to avoid large thermal gradients. In the present study, the influence of the preheating temperature on microstructure and corresponding hardness is systematically investigated. With the help of time–temperature–transformation diagram, the phase evolution during the LPBF process is systematically explained. AISI M50 samples are produced by LPBF from room temperature to a preheating temperature of 650 °C. Higher preheating temperatures shift the optimal laser parameter window to lower volume energy densities. A cellular/dendritic microstructure formed during the rapid solidification with retained austenite is located at the interdendritic regions. Moreover, a high preheating temperature reduces the retained austenite fraction, specifically from 39% without preheating to 7.6% at 650 °C preheating temperature.

Microstructure estimation and validation of ER110S-G steel structures produced by wire and arc additive manufacturing

Wire and Arc Additive Manufacturing (WAAM) emerged as a manufacturing process for large scale structures with extensive form and design freedom. WAAM can be fully exploited once the relation between the transient thermal history and its relation to microstructure development and resultant mechanical properties is established. This relation can be further used for computational design tools such as Topology Optimization. This paper presents a model to predict the relation between the thermal history and solid-state phase transformations in a widely applicable High Strength Low Alloy steel ER110S-G. The transient thermal history of parts manufactured by WAAM is modelled using finite element analysis. The modelled thermal history is validated with thermocouple measurements. Our results show that a critical cooling cycle is responsible for the solid-state phase transformation in an AM part. The cooling rate of this particular cooling cycle is superimposed onto an experimentally constructed Continuous Cooling Transformation (CCT) diagram to determine the local solid-state phase fractions. The predicted phase fractions in three wall samples with different design and processing conditions of AM parts are used to predict the hardness. The predicted hardness is 10% higher than the measured hardness of AM samples. The effect of tempering is also considered in the model through JMAK equation. The results show that the tempering is caused in regions with high martensite content and it lowers the hardness by 8 − 10%. The micrographs of the AM parts show that the microstructural features are same for the AM parts with similar critical cooling rates.