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The purpose of the paper is to study the effect of elevated temperature on load carrying capacity of reinforced self compacting concrete beams and the performance of deteriorated beams after retrofitting by GFRP sheets. The reinforced beams which were exposed to sustained elevated temperature and tested for flexural load-carrying capacity. Further deteriorated beams (exposed from 500°C to 800°C) were re-strengthened by adopting retrofitting with GFRP sheets.

The investigation includes the concrete specimens, i.e. cubes of 150 mm, cylinders of size 150 mm dia with 300 mm height and beams of 150 × 150 × 1,100 mm, reinforced with minimum tension reinforcement according to IS 456–2000. The specimens were subjected to elevated temperature from 300°C to 800°C with an interval of 100°C for 2 h. The residual compressive strength, modulus of elasticity, load at first crack of beams and load-carrying capacity of beams for 5-mm deflection were measured before and after retrofitting.

The result shows that there is a gain in residual compressive strength at 300°C and beyond which it decreases. The modulus of elasticity, load at first crack and load-carrying capacity of beams reduces continuously with an increase in temperature. The decrease in load-carrying capacity of beams is observed from 27.55% and up to 38.77% between the temperature range of 500°C–800°C and after the retrofitting of distressed beams, the load carrying capacity increases up to 24.48%.

Better performance was observed with retrofitting by GFRP sheets when the specimens were distressed due to elevated temperatures.

The present experimental investigation attempts to study the behaviour of hybrid fibre-reinforced self-compacting concrete (HFSCC) subjected to elevated temperature. The purpose of this study is to find out the performance of hybrid fibres of 0.5 per cent by volume of concrete (out of which 75 per cent are steel fibres and 25 per cent, polypropylene fibres). Reinforced beams were casted and tested for the flexural load-carrying capacity, and comparisons were made with the load-carrying capacity of reinforced beams without the inclusion of fibres.

The study includes 60 concrete cubes of 150 mm and 60 beams of 150 × 150 × 1,100 mm reinforced with minimum tension reinforcement according to IS 456-2000. The specimens were subjected to elevated temperature from 100°C to 500°C with an interval of 100°C for 2 h. The residual compressive strength and the load-carrying capacity of beams for 5-mm deflection were measured. Parameters such as load at first crack, width and length of cracks developed on the beam during the application of load were also studied.

The result shows that for self-compacting concrete without fibres (SCCWOF), there is a gain in compressive strength between 200°C and 300°C, beyond which the strength decreases. For HFSCC, the gain in strength is between 300°C and 400°C, and thereafter the strength gets reduced. The load-carrying capacity of beams reduces with an increase in temperature. An increase in load-carrying capacity (up to 40.7 per cent) for HFSCC beams is observed when compared to SCCWOF beams at 500°C.

Better performance was observed with the usage of fibres when the specimens were subjected to elevated temperatures.

The Reinforced Concrete(RC) elements are known to perform well during exposure to elevated temperatures. Hence, RC elements are widely used to resist the extreme heat developing from accidental fires and other industrial processes. In both of the scenarios, the RC element is exposed to elevated temperatures. However, the primary differences between the fire and processed temperatures are the rate of temperature increase, mode of exposure and exposure durations. In order to determine the effect of two heating modalities, RC beams were exposed to processed temperatures with slow heating rates and fire with fast heating rates.

In the present study, RC beam specimens were exposed to 200 °C, to 800 °C temperature at 200 °C intervals for 2 h' duration by adopting two heating modes; Fire and processed temperatures. An electrical furnace with low-temperature increment and a fire furnace with standard time-temperature increment is adapted to expose the RC elements to elevated temperatures.

It is observed from test results that, the reduction in load-carrying capacity, first crack load, and thermal crack widths of RC beams exposed to 200 °C, and 600 °C temperature at fire is significantly high from the RC beams exposed to the processed temperature having the same maximum temperature. As the exposure temperature increases to 800 °C, the performance of RC beams at all heating modes becomes approximately equal.

In this work, residual performance, and failure modes of RC beams exposed to elevated temperatures were achieved through two different heating modes are presented.

The purpose of this study is to investigate the Cattaneo-Christov double diffusion, multiple slips and Darcy-Forchheimer’s effects on entropy optimized and thermally radiative flow, thermal and mass transport of hybrid nanoliquids past stretched cylinder subject to viscous dissipation and Arrhenius activation energy.

The presented flow problem consists of the flow, heat and mass transportation of hybrid nanofluids. This model is featured with Casson fluid model and Darcy-Forchheimer model. Heat and mass transportations are represented with Cattaneo-Christov double diffusion and viscous dissipation models. Multiple slip (velocity, thermal and solutal) mechanisms are adopted. Arrhenius activation energy is considered. For graphical and numerical data, the bvp4c scheme in MATLAB computational tool along with the shooting method is used.

Amplifying curvature parameter upgrades the fluid velocity while that of porosity parameter and velocity slip parameter whittles down it. Growing mixed convection parameter, curvature parameter, Forchheimer number, thermally stratified parameter intensifies fluid temperature. The rise in curvature parameter and porosity parameter enhances the solutal field distribution. Surface viscous drag gets controlled with the rising of the Casson parameter which justifies the consideration of the Casson model. Entropy generation number and Bejan number upgrades due to growth in diffusion parameter while that enfeeble with a hike in temperature difference parameter.

To the best of the authors’ knowledge, this research study is yet to be available in the existing literature.

This paper aims to develop supply chain strategies for the fashion retail supply chain (FRSC), likely to be disrupted by the current pandemic (COVID-19) under physical and online retail stores. The resilient retail supply chain design is proposed under budget allocation and merchandise capacity constraints.

This paper utilises the theory of constraint (ToC) and goal programming (GP) to address the COVID-19 impact on FRSC. The budgetary and capacity constraints are formulated with a constraint optimisation model and tested with six different priorities to deal with the physical and online stores. Next, all priorities are developed under different FRSC business scenarios. The ToC-GP-based optimisation model is validated with one of the Indian fashion retail supply chains.

The proposed optimisation model presents the optimal retailing strategies for selling fashion goods over physical and online platforms. The multiple scenarios are presented for developing trade-offs among different strategies to maximise the retailer's merchandise performance. This paper also highlighted the strategic movement from high merchandise density stores to low merchandise density stores. This implies a reduction of sales targets and aspiration levels of both online and physical fashion stores.

The proposed model is validated with one of the fashion retailers in India. Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.

This research helps fashion retail supply chain managers deal with consumer demand uncertainty over physical and online stores in pandemic times. Limitation: Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.

This is the first study that considered the impact of COVID-19 on the retail fashion supply chain. The effect of physical and online platforms is mainly discussed from consumer marketing perspectives, but an inventory and resilience perspective is missing in earlier studies. The role of merchandise planning is highlighted in this study.

This study initially aims to identify the barriers to the big data analytics (BDA) initiative and further evaluates the barriers for knowing their interrelations and priority in improving the performance of manufacturing firms.

A total of 15 barriers to BDA adoption were identified through literature review and expert opinions. Data were collected from three types of industries: automotive, machine tools and electronics manufacturers in India. The grey-decision-making trial and evaluation laboratory (DEMATEL) method was employed to explore the cause–effect relationship amongst barriers. Further, the barrier's influences were outranked and cross-validated through analytic network process (ANP).

The results showed that “lack of data storage facility”, “lack of IT infrastructure”, “lack of organisational strategy” and “uncertain about benefits and long terms usage” were most common barriers to adopt BDA practices in all three industries.

The findings of the study can assist service providers, industrial managers and government organisations in understanding the barriers and subsequently evaluating interrelationships and ranks of barriers in the successful adoption of BDA in a manufacturing organisation context.

The paper is one of the initial efforts in evaluating the barriers to BDA in improving the performance of manufacturing firms in India.

During pre-vaccine era, pharmaceutical supplies [self-care essentials (SCEs)] have been proved to be a major deflector, protector and safety guard against novel coronavirus disease (COVID-19). Hence, the objective of the study is to provide a comprehensive socio-technological decision-making framework based on multiple criteria for selecting the suppliers of pharmaceuticals, such as SCEs, by multi-brand enterprises (distributors) in the pandemic environment.

A hybrid methodology of Bayesian best worst method (BWM) and multi-attributive border approximation area comparison (MABAC) method has been applied for carrying out the study. Bayesian BWM has been applied for computing the importance of criteria identified for the selection of SCEs' suppliers during pandemic environment and MABAC method evaluated the suppliers of the SCEs.

In the study, the authors have identified eight criteria such as disinfection and sanitization of vehicles, social conscience of suppliers, brand (Technological recognition) of SCEs and logistics and distribution network, among others, which are critical to the selection of a supplier for the supply of SCEs. The application of the proposed hybrid model revealed that lead time and quality of SCEs are of utmost concern for pharmacies in a pandemic environment. Among the ten suppliers, results showed that Suppliers 2, 4 and 5 have been ranked first for supplying hand wash, hand sanitizer and face mask, respectively.

The proposed model has helped the multi-brand distributors of pharmaceuticals in selecting suppliers during the ongoing crisis of COVID-19. In addition to that, in future the outcomes of the study would be helpful for multi-brand distributors as well as pharmacies and hospitals in selecting the best suppliers. Policy makers will be able to make and revise the policies immediately with the help of the proposed decision-making framework.

The paper makes a novel contribution towards theory with the criteria identified for selecting best suppliers during the pandemic COVID-19. Additionally, the proposed hybrid model helps multi-brand distributors of pharmaceuticals in making decisions that lead to a huge social and economic success in pandemic time.

The study aims to explore the argument of implementing the lean method to part or whole of an operation by examining the moderating impact of varying levels of the extent of implementation of four different lean methods, along with their functionalities, in predicting productivity improvement (PI).

As the focus of understanding the efficacy of lean principles is shifting from process to industry level, this study tried to generalize the approach by gathering data from 132 large Indian auto component manufacturers. This involves an assessing/monitoring approach rather than measurement.

Results highlighted the interdependence or individuality of the extent of implementation of lean methods and their functionalities. Findings revealed a significant moderating effect in improving productivity to a greater extent of 50%.

Adopting an assessment approach to a measurement study provides a noteworthy contribution to bridging theory and practical consequences. The findings can be appropriately extrapolated to medium and small enterprises forming a critical connection in the entire automobile manufacturing ecosystem.

The study showed that even if a lean method is applied to a certain extent of operations the chances of PI are significant. This is important for decision makers as they confront problems of optimum resource allocation.

PI, reduced cost and generalization of results would enable the auto component industry to become more competitive.

The examination of the moderation effect of a lean principle implementation extent, along with that of its functionalities to predict the improvement in productivity from its existing level, is a major outcome of this study.

The purpose of this paper is to study the two-dimensional micropolar fluid flow with conjugate heat transfer and mass transpiration. The considered nanofluid has graphene nanoparticles.

Governing nonlinear partial differential equations are converted to nonlinear ordinary differential equations by similarity transformation. Then, to analyze the flow, the authors derive the dual solutions to the flow problem. Biot number and radiation effect are included in the energy equation. The momentum equation was solved by using boundary conditions, and the temperature equation solved by using hypergeometric series solutions. Nusselt numbers and skin friction coefficients are calculated as functions of the Reynolds number. Further, the problem is governed by other parameters, namely, the magnetic parameter, radiation parameter, Prandtl number and mass transpiration. Graphene nanofluids have shown promising thermal conductivity enhancements due to the high thermal conductivity of graphene and have a wide range of applications affecting the thermal boundary layer and serve as coolants and thermal management systems in electronics or as heat transfer fluids in various industrial processes.

Results show that increasing the magnetic field decreases the momentum and increases thermal radiation. The heat source/sink parameter increases the thermal boundary layer. Increasing the volume fraction decreases the velocity profile and increases the temperature. Increasing the Eringen parameter increases the momentum of the fluid flow. Applications are found in the extrusion of polymer sheets, films and sheets, the manufacturing of plastic wires, the fabrication of fibers and the growth of crystals, among others. Heat sources/sinks are commonly used in electronic devices to transfer the heat generated by high-power semiconductor devices such as power transistors and optoelectronics such as lasers and light-emitting diodes to a fluid medium, thermal radiation on the fluid flow used in spectroscopy to study the properties of materials and also used in thermal imaging to capture and display the infrared radiation emitted by objects.

Micropolar fluid flow across stretching/shrinking surfaces is examined. Biot number and radiation effects are included in the energy equation. An increase in the volume fraction decreases the momentum boundary layer thickness. Nusselt numbers and skin friction coefficients are presented versus Reynolds numbers. A dual solution is obtained for a shrinking surface.

The major goal of this article is to investigate flow and thermal aspects of Oldroyd B with hybrid nanostructure subject to a radially stretched surface under the influence of low and moderate Prandtl numbers.

The non-dimensional governing equations are solved considering BVP4C in MATLAB as instrumental.

Entropy generation effect is analyzed. Radial velocity and entropy generation exhibit opposite effect in response to amplified relaxation and retardation time parameters in case of both low and moderate Prandtl numbers. Augmented relaxation and retardation time parameters controls heat transfer rate.The results show that increasing the aspect ratio increases both the average Nusselt and entropy generation numbers for each value of the Prandtl number, while increasing the prandtl number decreases both. There is also a minimum value for the entropy generation number at a given relaxation and retardation parameter.

Assume that the Oldroyd B fluid is dispersed with hybrid nanostructure in order to ameliorate thermal conductivity of Oldroyd B fluid so as to make it as best coolant.

The low range of Prandtl number comprising particles of air, gas, etc. and moderate range of Prandtl number comprising particles of honey, thin motor oil, or any non-Newtonian liquid. The hybrid nanofluid is radiative in nature. Also, the effects of significant physical parameters on entropy generation are highlighted. The entropy generation number intensifies due to the rise in temperature difference parameter at low/moderate Prandtl number effectively. Entropy minimization can lead to the amelioration of available energy thereby enhances the efficiency of several thermal systems.

This article's primary goal is to investigate the flow and thermal aspects of Oldroyd B with a hybrid nanostructure subject to a radially stretched surface under the influence of low and moderate Prandtl numbers.