T. S. Prasanna Kumar

Influence of Steel Grade on Surface Cooling Rates and Heat Flux during Quenching

Immersion quenching is one of the most widely used processes for achieving martensitic and bainitic steels. The efficiency and quality of quenching are generally tested using standard quench probes for obtaining the cooling curves. A host of parameters like quenchant type, steel grade, bath agitation, section thickness, etc., affect the cooling curves. Cooling curve analyses covered under ASTM standards cannot be used to assess the performance of a quenchant for different grades of steel, as they use a common material for the probe. This article reports the development of equipment, which, in conjunction with mathematical models, can be used for obtaining cooling curves for a specific steel/quenchant combination. The mathematical models couple nonlinear transient inverse heat transfer with phase transformation, resulting in cooling curves specific to the steel grade-quenchant combination. The austenite decomposition models were based on an approach consistent with both the TTT diagram of the steel and Fe-C equilibrium phase diagrams. The TTT diagrams for the specific chemistry of the specimens and the thermophysical properties of the individual phases as functions of temperature were obtained using JMatPro software. Experiments were conducted in the laboratory for computing surface temperature and heat flux at the mid-section of a 25-mm diameter by 100-mm-long cylindrical specimen of two types of steels in two different quenchants. A low alloy steel (EN19) and a plain carbon steel (C45) were used for bringing out the influence of austenite transformation on surface cooling rates and heat flux. Two types of industrial quenchants (i) a mineral oil, and (ii) an aqueous solution of polymer were used. The results showed that the cooling curves, cooling rate curves, and the surface heat flux depended on the steel grade with the quenchant remaining the same.

Optimum CNT Concentration and Bath Temperature for Maximum Heat Transfer Rate during Quenching in CNT Nanofluids

This paper utilizes the experimental and numerical results obtained during quenching of stainless steel (SS) probes in carbon nanotube (CNT) nanofluids to arrive at an optimum CNT concentration and bath temperature for maximum quenching heat transfer rate. The individual effect of CNT concentration and bath temperature on the quenching heat transfer rate has recently been published by the authors. The objective of this work is to study the combined effect of CNT concentration and bath temperature on the heat transfer rate during quenching. For this purpose, CNT nanofluids were prepared by suspending chemically treated CNTs in de-ionized (DI) water without any surfactant at 0.50 and 0.75 wt. % of CNTs. Cylindrical quench probes made of SS 304L with a diameter of 20 mm and an aspect ratio of 2.5 were quenched in the CNT nanofluids by maintaining at 30, 40, and 50°C using an external water bath. The recorded time-temperature data during quenching were used as input and the heat flux and temperature at the quenched surface were estimated based on the inverse heat conduction (IHC) method. The computed boiling curves during quenching were used in conjunction with the boiling curves published in literature to arrive at an optimum CNT concentration and bath temperature for maximum heat transfer rates. The computational results showed that the peak heat flux during quenching of SS probes in CNT nanofluids increased when the CNT nanofluid was maintained at 40 than at 30°C and it started decreasing with further increase in the bath temperature irrespective of the CNT concentration. The enhanced heat transfer performance of CNT nanofluid at a slightly higher temperature during quenching is attributed to the enhanced Brownian motion of CNTs in nanofluid.

A Framework for Adaptive Online Thickness Control at Plate Mill of Bhilai Steel Plant

The Plate Mill at Bhilai Steel Plant (BSP) has two reversing stands, one functioning as the roughing mill, and the other as the finishing mill. The nominal thickness of the slab is 245 mm, which is reduced to about 40 mm as thick plates in the roughing mill and the thinner plates are processed further in the finishing mill. The Plate Mill is now undergoing a major revamp with the main component being the hydraulic automation gap control (HAGC) and the supporting automation systems. The HAGC is backed up by proper sensors, instrumentation, microprocessor-based control equipment working in real time. The installation of the HAGC provides for controlling thickness variations due to process variables like plate temperature, mill spring, and so on. Mathematical models for both off-line simulation and adaptive mill setup have been developed indigenously for automatic control of plate thickness in the revamped Plate Mill. The control of thickness of the plate from head to tail is envisaged as a two-step process, viz., (i) a Level II Adaptive Algorithm, where an optimum drafting schedule generated “on the fly” is downloaded as reference points for the Level 1 automation and (ii) a Level 1 Feedback Controller for applying the necessary correction in the roll gap, for process deviations during rolling. The off-line mathematical models have been validated with extensive data collected from the mill. Once they are implemented online, it is anticipated that continuous updating will improve its performance and will reach international levels of performance guarantee.

Coupled Analysis of Surface Heat Flux, Microstructure Evolution, and Hardness during Immersion Quenching of a Medium Carbon Steel in Plant Conditions

Immersion quenching is one of the most widely used processes for achieving martensitic and bainitic steels. A comprehensive modeling treatment of quenching requires a description of the surface heat flux or heat transfer coefficient. Generally, the heat transfer coefficients obtained during the quenching of a material not undergoing a phase change, such as austenitic stainless steel, are used for calculating the phase change in an alloy steel also. In order to accurately model phase transformation, one must characterize the heat transfer process specific to the quenchant–steel combination in question. This work reports the development of numerical models for the simultaneous estimation of surface heat flux, austenite decomposition, and hardness during the immersion quenching of carbon and alloy steels in plant conditions. The algorithm couples non-linear transient inverse heat transfer with phase transformation, resulting in heat flux values specific to the steel grade–quenchant combination in actual practice. The effects of the soaking temperature, component surface conditions, quenchant conditions, plant operating practices, and so on can be addressed satisfactorily with this method. The austenite decomposition models use a unique approach consistent with both the time–temperature–transformation diagram of the steel and Fe-C equilibrium phase diagrams. Portable and self-contained handheld equipment was designed for testing in the plant. The equipment was used for computing the surface heat flux at the mid-section of a cylindrical specimen of medium carbon 1050 grade steel (25 mm in diameter by 100 mm in length) quenched in an aqueous solution of a polymer. Using the transient heat flux values, the microstructure evolution and hardness across the cross section of the specimen were simultaneously computed. The hardness profile and the microstructure distribution across the specimen section are presented and are corroborated by laboratory measurements. It was found that in this specific case of polymer quenching, the surface hardness was lower than the core hardness due to an anomalous heat transfer condition, which is explained via the use of the models developed in this article.

“Reference QuenchProbe”—An Alternative Probe Design for In-Situ Estimation of Cooling Rates, Heat Flux, and Hardenability During Immersion Quenching of Hardenable Steels

This article reviews some of the limitations of the standard cooling curve analysis and the Jominy hardenability test in extending the results to actual quenching in industrial setups and reports the development of a new portable tool—Reference QuenchProbe—for estimating cooling rates, hardness, and microstructure distributions in hardenable steel grades during immersion quenching, which can be used by the heat treater in the plant. The specimen is made of the same grade of steel as the quenched component with section thickness matching that of the component, which is a departure from standard laboratory tests. The test is carried out in the plant under actual conditions dispensing the need to correlate the standard cooling curve data and end quench hardenability tests done in the laboratory to industrial practice. To test the suite of mathematical models associated with the Reference QuenchProbe hardware and software, specimens of different grades of steels were instrumented with a single thermocouple near the surface of the specimen. Using the cooling data at the point of measurement, the cooling rates, microstructure, and hardness at other critical locations were computed. An enthalpy-based non-linear inverse heat conduction model was coupled with austenite decomposition models for handling the latent heat liberated during quenching. Several steels ranging from low carbon to medium alloy steels were both end-quenched by water and immersion quenched in several industrial quenchants. The computed hardness of end quenched and immersion quenched specimens were shown to be in good agreement with the measured values. The Reference QuenchProbe is thus shown to generate data needed for heat treatment process design including quenchant selection, which can be directly used in practice.

Casting Simulation Methods

Metal casting has grown from an art several thousand years back to a technology a few hundred years to an applied science since a few 10 of years. The science of alloy solidification has seen rapid strides in the recent past through the development of mathematical models and verification under controlled, observable experimental conditions. However, the extension of these models to practical metal casting simulation has not kept pace with it. Full-scale simulation for industrial castings requires an understanding of metal-mold interface heat transfer and the capability to handle multi-scale phenomena involved in industrial metal casting. In spite of the developments in computational technologies so far, it may take a couple of decades for simulation of real castings is made available to industries. This chapter is an attempt to summarize the important developments in alloy solidification modeling and casting simulation methods.

Effect of Mold Filling on the Formation of Air Gap Along the Vertical Mold Wall During Solidification of Al-Cu Alloy

The accuracy of the numerical simulation of casting solidification largely depends on the selection of appropriate thermal boundary conditions. The estimation of heat flux at the metal-mold interface becomes difficult due to the formation of spatially and temporally varying air gap in gravity die-casting. However, the spatial variation in the formation of air gap is often neglected in most of the previous research work. In this paper, an experimental setup that involved mold filling was devised In order to study the spatial variation of air gap and its effect on the heat flux at the metal-mold interface. A Serial-IHCP (inverse heat conduction problem) algorithm was used to estimate the multiple heat flux transients along the metal-mold interface. The estimated heat fluxes at the metal-mold interface have considerable variation during the initial stages of solidification. Further, the analysis indicates that the non-conformal contact between metal and mold begins at the bottom. However, the formation of clearance gap at the metal-mold interface follows a reverse trend as it starts from the top of the vertical mold wall and progresses towards the bottom.Copyright