Novel method for refinement of retained austenite in micro/nano-structured bainitic steels

A comparative study was conducted to assess the effects of two different heat treatments on the amount and morphology of the retained austenite in a micro/nano-structured bainitic steel. The heat treatments used in this work were two-stage bainitic transformation and bainitic-partitioning transformation. Both methods resulted in the generation of a multi-phase microstructure containing nanoscale bainitic ferrite, and/or fresh martensitic phases and much finer retained austenite. Both heat treatments were verified to be effective in refining the retained austenite in micro/nano-structured bainite and increasing the hardness. However, the bainitic transformation followed by partitioning cycle was proved to be a more viable approach than the two-stage bainitic transformation due to much shorter processing time, i.e. ∼2 h compared to ∼4 day, respectively

Developing a framework for improvement of building thermal performance modeling under urban microclimate interactions

Coupled models developed from the building energy simulation (BES) and computational fluid dynamics (CFD) methods are occasionally used for analyzing the buildings thermal performance. Nevertheless, the large uncertainty in the input parameters of BES models and values of the closure coefficients of Reynolds-averaged Navier-Stokes (RANS) turbulence models restrict the accuracy of coupled BES-CFD models for thermal performance prediction in highly dense urban areas.Thus, a systematic framework for improving the accuracy of the coupled BES-CFD models is proposed in this study, consisting of an approximation technique and a stochastic optimization approach. In this framework, at first, a CFD model is improved with a closure coefficients optimization procedure using experimental data. In the second step, the improved CFD model is utilized to conduct a series of CFD simulations for real-geometry buildings in order to calibrate the BES model with the alteration of parameters such as the adaptive discharge coefficient, local wind profile, and convective heat transfer coefficients over the building façades.The developed framework is then applied to a small cross-ventilated office building surrounded by neighboring buildings. Deviations up to 60% are found in the prediction of the energy saving potential of cross-ventilation strategy by the default and calibrated BES models

Influence of Co and Al on pearlitic transformation in superbainitic steels

The effect of cobalt and aluminium on the austenite-to-pearlite transformation in a super-bainitic steel was investigated. The experimental work showed that the transformation rate of pearlitic and the volume fraction of pearlite both were increased by adding about 4 wt. % Co and 1.5 wt. % Al to the parent super-bainitic steel. The addition of cobalt and aluminium to super-bainitic steels desirably accelerated the growth rate of pearlitic microstructure, and undesirably reduced the interlamellar spacing of pearlite; resulting in a hardness higher than that of the parent steel in the pearlitic condition. Nevertheless, the accelerated pearlitic reaction, as a softening process of the super-bainitic steels prior to machining/forming, may make the commercial use of these steels more viable

Experimental and Steady-RANS CFD Modelling of Cross-ventilation in Moderately-dense Urban Areas

Computational fluid dynamics (CFD) models based on the steady Reynolds-averaged Navier Stokes (SRANS) equations are vastly used for calculation of airflow field inside and around cross-ventilated buildings. However, most of the developed CFD guidelines ignore CFD challenges related to cross-ventilation modeling in terms of flow unsteadiness, high level of gradients of airflow parameters, and complex interactions between the indoor and outdoor flows.Hence, a systematic parametric study was performed in this study for a generic cross-ventilated building model with a planar area ratio of 0.25 against different wind angles while effects of different CFD parameters, including advection and diffusion terms discretization methods, mesh generation techniques, and turbulence models on prediction accuracy and convergence behavior of CFD solver were comprehensively studied.Results show that a particularly generated unstructured tetrahedral mesh configuration with significantly lower mesh numbers can provide comparable results with structured hexahedral mesh configuration. Furthermore, second-order discretization scheme for advection terms encounters convergence issues against the normal wind angle, but generally presents more accurate results against oblique wind angles. Moreover, two-equation turbulence models showed very low accuracy in the case of normal wind angle, but acceptable results were found for oblique wind angles

Development of Auto Ejection Melt Spinning (AEMS) and its application in fabrication of cobalt-based ribbons

Auto Ejection Melt Spinning (AEMS) is a new variant of melt spinning processes in which spontaneous ejection of the alloy occurs as soon as it is fully melted. Unlike the conventional laboratory melt spinning processes, there is no need for a skilled operator to monitor the melt temperature and/or manually release the ejection gas at the right moment. This new process substantially reduces the uncertainties associated with temperature measurement and human errors. On the request of the authors, the capability of the new process was independently tested and verified by the design engineers of a renowned manufacture of laboratory melt spinners in Germany [Edmund Bühler GmbH]. The application of the new process for fabrication of high melting point cobalt-based ribbons is also described and the key findings are outlined

Measurement of residual stresses in dissimilar friction stir-welded aluminium and copper plates using the contour method

The longitudinal residual stresses in the friction stir-welded plates of 5A06 aluminium and pure copper were determined using the contour method. The results revealed the presence of high tensile and compressive residual stresses on the aluminium and copper sides, respectively. The residual stresses were detected on the weld zone as well as the thermo-mechanically affected zone (TMAZ) of the aluminium plate. In contrast, the compressive residual stresses in the copper plate had a much narrower width along the weld line. Peak tensile stresses up to 240 MPa were found in the TMAZ of the aluminium plate

Combined effect of stress and strain on crystallographic orientation of bainite

Experiments have been conducted to see whether specific crystallographic variants of bainite form in polycrystalline steel when transformation occurs from plastically deformed austenite which is otherwise free from externally applied stress. It is demonstrated by studying both overall and microtexture that there is no perceptible variant selection as bainite forms. Indeed, the texture is found to weaken on transformation

Predicting sustainable arsenic mitigation using machine learning techniques.

This study evaluates state-of-the-art machine learning models in predicting the most sustainable arsenic mitigation preference. A Gaussian distribution-based Naïve Bayes (NB) classifier scored the highest Area Under the Curve (AUC) of the Receiver Operating Characteristic curve (0.82), followed by Nu Support Vector Classification (0.80), and K-Neighbors (0.79). Ensemble classifiers scored higher than 70% AUC, with Random Forest being the top performer (0.77), and Decision Tree model ranked fourth with an AUC of 0.77. The multilayer perceptron model also achieved high performance (AUC=0.75). Most linear classifiers underperformed, with the Ridge classifier at the top (AUC=0.73) and perceptron at the bottom (AUC=0.57). A Bernoulli distribution-based Naïve Bayes classifier was the poorest model (AUC=0.50). The Gaussian NB was also the most robust ML model with the slightest variation of Kappa score on training (0.58) and test data (0.64). The results suggest that nonlinear or ensemble classifiers could more accurately understand the complex relationships of socio-environmental data and help develop accurate and robust prediction models of sustainable arsenic mitigation. Furthermore, Gaussian NB is the best option when data is scarce

Microstructure and Interfacial Reactions During Vacuum Brazing of Stainless Steel to Titanium Using Ag-28 pct Cu Alloy

Microstructural evolution and interfacial reactions during vacuum brazing of grade-2 Ti and 304L-type stainless steel (SS) using eutectic alloy Ag-28 wt pct Cu were investigated. A thin Ni-depleted zone of α -Fe(Cr, Ni) solid solution formed on the SS-side of the braze zone (BZ). Cu from the braze alloy, in combination with the dissolved Fe and Ti from the base materials, formed a layer of ternary compound τ2, adjacent to Ti in the BZ. In addition, four binary intermetallic compounds, Cu3Ti2, Cu4Ti3, CuTi and CuTi2 formed as parallel contiguous layers in the BZ. The unreacted Ag solidified as islands within the layers of Cu3Ti2 and Cu4Ti3. Formation of an amorphous phase at certain locations in the BZ could be revealed. The β -Ti(Cu) layer, formed due to diffusion of Cu into Ti-based material, transformed to an α -Ti + CuTi2eutectoid with lamellar morphology. Tensile test showed that the brazed joints had strength of 112 MPa and failed at the BZ. The possible sequence of events that led to the final microstructure and the mode of failure of these joints were delineated