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The capability of steel columns to support their design loads is highly affected by the time of exposure and temperature magnitude, which causes deterioration of mechanical properties of steel under fire conditions. It is known that structural steel loses strength and stiffness as temperature increases, particularly above 400 °C. The duration of time in which steel is exposed to high temperatures also has an impact on how much strength it loses. The time-dependent response of steel is critical when estimating load carrying capacity of steel columns exposed to fire. Thus, investigating the structural response of cold-formed steel (CFS) columns is gaining more interest due to the nature of such structural elements.

In this study, experiments were conducted on two CFS configurations: back-to-back (B-B) channel and toe-to-toe (T-T) channel sections. All CFS column specimens were exposed to different temperatures following the standard fire curve and cooled by air or water. A total of 14 tests were conducted to evaluate the capacity of the CFS sections. The axial resistance and yield deformation were noted for both section types at elevated temperatures. The CFS column sections were modelled to simulate the section's behaviour under various temperature exposures using the general-purpose finite element (FE) program ABAQUS. The results from FE modelling agreed well with the experimental results. Ultimate load of experiment and finite element model (FEM) are compared with each other. The difference in percentage and ratio between both are presented.

The results showed that B-B configuration showed better performance for all the investigated parameters than T-T sections. A noticeable loss in the ultimate strength of 34.5 and 65.6% was observed at 90 min (986℃) for B-B specimens cooled using air and water, respectively. However, the reduction was 29.9 and 46% in the T-T configuration, respectively.

This research paper focusses on assessing the buckling strength of heated CFS sections to analyse the mode of failure of CFS sections with B-B and T-T design configurations under the effect of elevated temperature.

This paper aims to propose a new hydrostatic squeeze film damper compensated with electrorheological valve restrictors to control the nonlinear dynamic behavior of a rigid rotor caused by high unbalance eccentricity ratio. To investigate the effect of electrorheological valve restrictors on the dynamic behavior of a rigid rotor, a nonlinear model is developed and presented.

The nonlinear results are compared with those obtained from a linear approach. The results show good agreement between the linear and nonlinear methods when the unbalanced force is small. The effects of unbalance eccentricity ratio and electric field on the vibration response and the bearing transmitted force are investigated using the nonlinear models.

The results of simulation performed that the harmonics generated by high unbalance eccentricities can be reduced by using hydrostatic squeeze film damper compensated with electrorheological valve restrictors.

The numerical results demonstrate that this type of smart hydrostatic squeeze film damper provides to hydrostatic designers a new bearing configuration suitable to control rotor vibrations and bearing transmitted forces, especially for high speed.

This study aims to the service life of TA15 alloy by solving the problem of the binding force between the matrix and AlTiSiN coating. The effect of a plasma nitriding (PN) interlayer on the magnetron-sputtered AlTiSiN coating was also investigated in detail.

The double-glow plasma alloying (DGPA) and magnetron sputtering (MS) techniques were combined as a new approach to realize a bilayer on TA15 consisting of an AlTiSiN layer with a PN interlayer. A TiN interlayer was formed via co-diffusion during the PN conducted at 1050°C for 3 h.

The PN interlayer can effectively improve the adhesion between coating and matrix; the PN/AlTiSiN coating presented excellent adhesion (80.1 N) and anti-wear property with a nano-hardness of 18.62 GPa. The resulting three-dimensional wear-track morphology exhibited a shallow depth and a narrow width.

The novel combination of the DGPA and MS technologies, using an infiltration layer rather than a coating one as the intermediate layer, can effectively enhance the adhesion between AlTiSiN coating and TA15 matrix. Meanwhile, the gradient layer can effectively improve both surface bearing and wear resistance.

Simulation-based optimization is a decision-making tool for identifying an optimal design of a system. Here, optimal design means a smart system with sensing, computing and control capabilities with improved efficiency. As compared to testing the physical prototype, computer-based simulation provides much cheaper, faster and lesser time-and resource-consuming solutions. In this work, a comparative analysis of heuristic simulation optimization methods (genetic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed.

In this work, a comparative analysis of heuristic simulation optimization methods (genertic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed. Further, a novel simulation annealing-based heuristic approach is proposed for critical infrastructure.

A small scale network of 50–100 nodes shows that genetic simulation optimization with multi-criteria and multi-dimensional features performs better as compared to other simulation optimization approaches. Further, a minimum of 3.4 percent and maximum of 16.2 percent improvement is observed in faster route identification for small scale Internet-of-things (IoT) networks with simulation optimization constraints integrated model as compared to the traditional method.

In this work, simulation optimization techniques are applied for identifying optimized Quality of service (QoS) parameters for critical infrastructure which in turn helps in improving the network performance. In order to identify optimized parameters, Tabu search and ant-inspired heuristic optimization techniques are applied over QoS parameters. These optimized values are compared with every monitoring sensor point in the network. This comparative analysis helps in identifying underperforming and outperforming monitoring points. Further, QoS of these points can be improved by identifying their local optimum values which in turn increases the performance of overall network. In continuation, a simulation model of bus transport is taken for analysis. Bus transport system is a critical infrastructure for Dehradun. In this work, feasibility of electric recharging units alongside roads under different traffic conditions is checked using simulation. The simulation study is performed over five bus routes in a small scale IoT network.

Today, a firm’s major concern is to know the way in which an innovation is adopted in the marketplace. The purpose of this paper is to focus on the two-stage nature of diffusion process in which the time lag between people being informed and their act of making final purchase is considered.

The paper discusses an approach based on the time lag for modeling awareness and adoption process as two separate and yet connected processes. Varying forms of time lag (constant, deterministic or random) have been considered while modeling the required framework. Furthermore, an equivalence approach has been shown between the present framework and the two well-known and established approaches of infinite queuing theory and hazard rate function.

The results are verified on sales data of two different consumer durables and it show good prediction capability of proposed models in capturing the real-life scenario. Further, the equivalence approach helps us to quantify such scenarios which were difficult to be modeled with any one particular approach. Further, the possibility of capturing different market scenarios by studying various distribution functions has been identified.

The proposed methodology is based on a two-stage adoption process. The same can be extended to a multi-stage adoption process as in today’s competitive environment. “Motivation” is one such factor that is highly important which can be considered in some later studies. In future, the authors wish to study the multi-stage adoption process considering the different forms of time lag function.

The equivalence approach discussed in the paper can help to cater the possibility of capturing different market scenarios by studying various distribution functions.

The proposed approach helps to cater the time lag between awareness and adoption process and develop different mean value functions to account for the manner in which sales are happening under different circumstances. The proposed methodical approach can also help decision makers in managing their available resources in a prudent manner.

In the current market scenario, software upgrades and updates have proved to be very handy in improving the reliability of the software in its operational phase. Software upgrades help in reinventing working software through major changes, like functionality addition, feature enhancement, structural changes, etc. In software updates, minor changes are undertaken which help in improving software performance by fixing bugs and security issues in the current version of the software. Through the current proposal, the authors wish to highlight the economic benefits of the combined use of upgrade and update service. A cost analysis model has been proposed for the same.

The article discusses a cost analysis model highlighting the distinction between launch time and time to end the testing process. The number of bugs which have to be catered in each release has been determined which also consists of the count of latent bugs of previous version. Convolution theory has been utilized to incorporate the joint role of tester and user in bug detection into the model. The cost incurred in debugging process was determined. An optimization model was designed which considers the reliability and budget constraints while minimizing the total debugging cost. This optimization was used to determine the release time and testing stop time.

The proposal is backed by real-life software bug dataset consisting of four releases. The model was able to successfully determine the ideal software release time and the testing stop time. An increased profit is generated by releasing the software earlier and continues testing long after its release.

The work contributes positively to the field by providing an effective optimization model, which was able to determine the economic benefit of the combined use of upgrade and update service. The model can be used by management to determine their timelines and cost that will be incurred depending on their product and available resources.

Gated communities, residential enclaves that offer upscale housing and a variety of recreational and communal facilities within a walled area with controlled entrances, are proliferating in many of India's large metropolitan cities. In this paper, we analyze the images of place and identity that are evoked in online advertisements for gated communities in the city of Bangalore in southern India. Since the 1990s, Bangalore has become known as India's premier information technology (IT) hub and a magnet for multinational corporations and high-skill personnel. The latter include Non-Resident Indians (NRIs) who lived and worked abroad for several years and have returned to partake of new opportunities offered in the country. We explore the intersection of notions of identity, home and community in a globalised world through an examination of the graphic and textual images encoded in the advertisements of thirteen prominent developers in Bangalore whose upscale gated developments cater to NRIs. The advertisements depict high-end gated communities as places of luxury, exclusiveness, high security and convenience which also offer a range of recreational facilities for individuals and families. Additionally, those who live in the gated enclaves are portrayed as persons of distinction and class who are global and cosmopolitan in their outlook and identity.

Purpose: The purpose of this study is to examine how leading a childhood characterized by transnational mobility affects youths’ understanding of and relationship to their ethnic identity.

Study approach: This study examines the effects of transnational mobility on ethnic identity by focusing on the specific case of Indian Americans who grew up in the USA and Bangalore, a city in southwest India, before relocating to the USA for college. The analysis for this chapter comes from semi-structured, in-depth interviews with 20 transnational Indian American youth.

Findings: The data analysis reveals that by spending part of their childhood in India, transnational Indian American youth were able to learn more about their Indian ethnic identity, which helped them resolve issues related to their status as an ethnic minority in the USA, reframe how they define their ethnic identity, and reevaluate the status of their ethnic identity relative to their counterparts in the USA.

Originality: This study focuses on the unique case of Indian American youth who had a childhood characterized by transnational mobility. As such, this work contributes to the literature on children and youths’ transnational mobility through its focus on the migration patterns of relatively elite and socially privileged children and youth. Additionally, it adds to our understanding of the effects of migration between the USA and India by addressing how these processes affect children and youth. Last, it adds to the literature on Indian Americans by focusing on an understudied subpopulation within this group. The study motivates future research on the diversity that exists among transnationally mobile Indian American children and youth.

The purpose of the present work is to mathematically model the reliability growth of a multi-version software system that is affected by infected patches.

The work presents a mathematical model that studies the reliability change due to the insertion of an infected patch in multi-version software. Various distribution functions have been considered to highlight the varied aspects of the model. Furthermore, weighted criteria approach has been discussed to facilitate the choice of the model.

The model presented here is able to quantify the effect of an infected patch on multi-version software. The model captures the hike in bug content due to an infected patch.

Multi-version systems have been studied widely, but the role of an infected patch has not been yet explored. The effect of an infected patch has been quantified by modeling the extra bugs generated in the system. This bug count would prove helpful in further studies for optimal resource allocation and testing effort allocation.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.