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The main aim of this paper is to investigate key challenges that hinder sustainable and resilient green supply chain (GSC) building in small and medium-sized enterprises (SMEs) with respect to how they interact after the COVID era.

Using a questionnaire, policymakers and industry managers from SMEs identify the main obstacles that will affect their resilience. These issues are then discussed with 50 experienced professionals from the top management field and further divided into sustainability and gresilience challenges. The Grey-DEMATEL (Grey sets and Decision-Making Trial and Evaluation Laboratory) has been employed to assess the significance of challenges to SMEs' development of green resilience. Overall, the paper aims to build up a novel decision-making technology for the interconnectedness of green and resilience in the post-pandemic supply chain world.

The 12 sustainability and gresilience challenges highlighted by experts in the sector were analyzed. Insufficient government assistance and the handling of resources are the most significant challenges to developing a sustainable and gresilient value chain system, according to the study. The study highlights supply chain restructuring, waste reduction management, shortages of skilled manpower and insufficient knowledge of digitalization as key challenges for SMEs to prioritize.

The outcomes of this research are crucial for SMEs building resilient supply networks through the green concept. Policymakers may utilize the data to pinpoint shortcomings in the supply chain for tactical as well as strategic development and improvement.

When it comes to building green resilience and sustainability in an unpredictable business climate, the outcomes of this research will be significant for SMEs.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlets of a six strand billet caster tundish. The numerical prediction of the tracer concentration has been made with six different turbulence models (the standard k‐ε, the k‐ε RNG, the Low Re number Lam‐Bremhorst model, the Chen‐Kim high Re number model (CK), the Chen‐Kim low Re number model (CKL) and the simplest constant effective viscosity model (CEV)) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of the k‐ε model, the RNG, the Lam‐Bremhorst and the CK model is much better than the CKL model and the CEV model as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. However, the k‐ε model predicts the closest value to the experimental observation compared to all other models. The prediction of the transient behavior of the tracer is best done by the Lam‐Bremhorst model and then by the RNG model, but these models do not predict the gross quantities that accurately like the k‐ε model for a single strand bare tundish. With the help of the above six turbulence models mixing parameters such as the ratio of mix to dead volume and the mean residence time were computed for the six strand tundish for different outlet positions, height of advanced pouring box (APB) and shroud immersion depth. It was found that three turbulence models show a peak value in the ratio of mix to dead volume when the outlets were placed at 200 mm away from the wall. An APB was put on the bottom of the tundish surrounding the inlet jet when the outlets were kept at 200 mm away from the wall. It was also found that there exists an optimum height of the APB where the ratio of mix to dead volume and the mean residence time attain further peak values signifying better mixing in the tundish. At this optimum height of the APB, the shroud immersion depth was made to change from 0 to 400 mm. It was also observed that there exists an optimum immersion depth of the shroud where the ratio of mix to dead volume still attains another peak signifying still better mixing. However, all the turbulence models do not predict the same optimum height of the APB and the same shroud immersion depth as the optimum depth. The optimum height of the APB and the shroud immersion depth were decided when two or more turbulence models predict the same values.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of a single strand bare tundish. The numerical prediction of the tracer concentration has been made with three different turbulence models; (a standard k‐ε, a k‐ε RNG and a Low Re number Lam‐Bremhorst model) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of k‐ε model with that of the experiment is better than the other two turbulence models as far as gross quantities like mean residence time and ratio of mixed to dead volume are concerned. However, it has been found that the initial transient development of the tracer concentration is best predicted by the Lam‐Bremhorst model and then by the RNG model. The k‐ε model predicts the tracer concentration much better than the other two models after the initial transience (t>40 per cent of mean residence time) and the RNG model lies in between the k‐ε and the Lam‐Bremhorst one. The numerical study has been extended to a multi strand tundish (having 6 outlets) where the effect of outlet positions on the ratio of mix to dead volume has been studied with the help of the above three turbulence models. It has been found that all the three turbulence models show a peak value for the ratio of mix to dead volume (a mixing parameter) when the outlets are placed 200 mm away from the wall (position‐2) thus signifying an optimum location for the outlets to get highest mixing in a given multi strand tundish.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a single strand bare tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of the tundish. The numerical prediction of the tracer concentration has been made with nine different turbulence models and has been compared with the experimental observation for the tundish. It has been found that the prediction from the standard k‐ε model, the k‐ε Chen‐Kim (ck) and the standard k‐ε with Yap correction (k‐ε Yap), matches well with that of the experiment compared to the other turbulence models as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. It has been found that the initial transient development of the tracer concentration is best predicted by the low Reynolds number Lam‐Bremhorst model (LB model) and then by the k‐ε RNG model, while these two models under predict the mean residence time as well as the ratio of mixed to dead volume. The Chen‐Kim low Reynolds number (CK low Re) model (with and without Yap correction) as well as the constant effective viscosity model over predict the mixing parameters, i.e. the mean residence time and the ratio of mixed to dead volume. Taking the solution of the k‐ε model as a starting guess for the large eddy simulation (LES), a solution for the LES could be arrived after adopting a local refinement of the cells twice so that the near wall y⁺ could be set lower than 1. Such a refined grid gave a time‐independent solution for the LES which was used to solve the species continuity equation. The LES solution slightly over predicted the mean residence time but could predict fairly well the mixed volume. However, the LES could not predict both the peaks in the tracer concentration like the k‐ε, RNG and the Lam‐Bremhorst model. An analysis of the tracer concentration on the bottom plane of the tundish could help to understand the presence of plug and mixed flow in it.

Two‐dimensional numerical simulations have been performed using a finite volume method that employs unstructured grids with cell‐wise local refinement and an interface‐capturing scheme to predict the shape of the free surface, thus simulating the surface wave that is created in a mold due to the flow from the submerged entry nozzle (SEN). Simulation has been done for 1:6.25 aspect ratio of the mold having a height of 2 m with parallel rectangular ports as well as 15° upward and downward ports. It has been found that for low inlet velocity of the SEN (<1 m/s) the maximum wave amplitude of the surface remains below 12 mm and no outside air is entrapped by the wave to form a bubble. However, for high inlet velocity (2 m/s or more) there is considerable fluctuations on the free surface and the maximum wave amplitude shoot up beyond 70 mm at the start up and slowly falls to about 30 mm entrapping air bubbles from the surroundings. The movement of the air bubble within the mold and its rise to the free surface where it subsequently collapses has been captured well in the numerical simulation. The overall shape of the free surface matches well, excepting the initial transience, with that of the experimentally observed free surface, although the free surface never attains a perfect steady shape neither in the experiment nor in the numerical simulation due to its continuous oscillation and breaking.

The purpose of this article is to numerically investigate the effect of casting speed on the fluid flow, solidification and inclusion motion under the influence of electromagnetic stirring (EMS) in the bloom caster mold with bifurcated submerged entry nozzle (SEN).

The electromagnetic field obtained by solving Maxwell’s equation is coupled with the fluid flow, solidification and discrete phase model using the in-house user-defined functions. An enthalpy porosity approach and Lagrangian approach are applied for the solidification analysis and non-metallic inclusions motion tracking, respectively.

Investigation shows that the casting speed and EMS significantly affect the steel flow, solidification and inclusion behavior inside the mold. Investigations are being conducted into the complex interplay between the induced flow and the SEN’s inertial impinging jet. In low and medium casting speeds, the application of EMS significantly increases the inclusion removal rate. Inclusion removal is studied for its different size and density and further effect of EMS is also reported on cluster formation and distribution of inclusion in the domain.

The model may be used to optimize the process parameter (casting speed and EMS) to improve the casting quality of steel by removing the impurities.

The effect of casting speed on the solidification and inclusion behavior under the influence of time-varying EMS in bloom caster mold with bifurcated nozzle has not been investigated yet. The findings may assist the steelmakers in improving the casting quality.

The purpose of this study is to explore how a time-varying electromagnetic stirring (EMS) affects the fluid flow and solidification behavior in a slab caster continuous casting mold. Further, the study of inclusion movements in the mold is carried out under the effect of a time-varying electromagnetic field.

A three-dimensional coupled numerical model of solidification and magnetohydrodynamics has been developed for slab caster mold to investigate the inclusions transport by discrete phase model with the use of user-defined functions. Enthalpy porosity and the Lagrangian approach are applied to analyze the behavior of solidification and inclusion.

The study shows that the magnetic field density distribution has a radial symmetry in relation to the stirrer’s center. As the EMS current intensity increases, the strength of the lower recirculation zone gradually decreases and nearly disappears at higher intensities. Additionally, the area of localized remelting zone expands in the solidification front with rising current intensity. The morphology of inclusions and EMS current intensity have a significant impact on the behavior and movement of inclusions within the molten steel.

By using the model, one can optimize the EMS parameter to enhance the quality of steel casting through the elimination of impurities and by improving the microstructure of cast that mainly depend on solidification and flow patterns of molten steel.

Until now, the use of time-varying EMS in the slab caster mold to study solidification and inclusion behavior has not been explored.

This investigation aims to analyze the steel-flux interface level fluctuation because of electromagnetic stirring and its process parameters in a continuous casting billet mold.

An un-coupled numerical model for electromagnetic field generation and a coupled numerical model of electromagnetic field and two-phase fluid flow have been developed. The two-phase fluid flow has been modeled using volume of fluid method, in which externally generated time-varying electromagnetic field is coupled and analyzed using magnetohydrodynamic method. Top surface standing wave stability criteria are used to study the criticality of interface stability.

Results show that application electromagnetic field for stirring increases the interface level fluctuation, specifically at the mold corners and near the submerged entry nozzle. The increase in current intensity and stirrer width barely affect the interface level. However, interface level fluctuation increases considerably with increase in frequency. Using stability criteria, it is found that at 20 Hz frequency, the ratio of height to wavelength of interface wave increases much above the critical value. The iso-surface of the interface level shows that at 20 Hz frequency, mold flux gets entrapped into the liquid steel.

The model may be used during optimization of in-mold electromagnetic stirrer to avoid mold flux entrapment and control the cast quality.

The study of mold level fluctuation in the presence of in-mold electromagnetic stirrer has rarely been reported. The criticality of stirrer process parameters on level fluctuation has not been yet reported. This study lacks in experimental validation; however, the findings will be much useful for the steelmakers to reduce the casting defects.

The purpose of present investigation is to analyze the in-mold electromagnetic stirring (M-EMS) process and the effect of stirrer frequency on fluid flow and solidification in a continuous casting billet caster mold.

A hybrid approach involving finite element and finite volume method has been used for the study. Finite element model is used to calculate time variable magnetic field, which is further coupled with fluid flow and solidification equations for magneto-hydrodynamic analysis with finite volume model.

Results show that though superheat given to steel before its entry into the mold is quickly removed, solid shell formation is delayed by the use of M-EMS. Final solid shell thickness, however, is slightly reduced. Increase in frequency is found to increase the magnetic flux density and tangential velocity of liquid steel and decrease in diameter of liquid core.

The work is of great industrial relevance. The model may be used to design industrial setup of in-mold electromagnetic stirrer and process could be analyzed and optimized numerically.

The paper evaluates the influence of M-EMS and its frequency on solidification and flow behavior in the continuous casting mold. The iso-surface temperatures from pouring temperature to liquidus temperature inside the mold have been shown. The findings may be useful for the steelmakers to reduce the defect in continuous casting.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.