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This study aims to investigate the effect of slanted perforation diameter in tabs for the control of Mach 1.4 underexpanded supersonic jet flow characteristics.

Numerical investigation was carried out for NPR 5 to analyze the effect of slanted perforation diameter in tabs to control the Mach 1.4 jet. Four sets of tabs with slanted circular perforation geometries (Φ_p = 1, 1.5, 2 and 2.5 mm) were considered in this study. The inclination angle of 20° (α_P) with reference to the jet axis was maintained constant for all the four tabs considered.

Determined value indicates there is a 68%, 71%, 73% and 75% drop in supersonic core for the Φ_p = 1, 1.5, 2.0 and 2.5 mm, respectively. The results show that the tabs with 2.5 mm perforation diameter were found to be efficient in reducing the supersonic jet core in comparison with other tab cases. The reduction in supersonic core length is due to the extent of miniscule vortices exuviating from slanted small and large diameter perforation in the tabs.

The concept of slanted perforation can be applied in scramjet combustion, which finds its best application in hypersonic vehicles and in noise suppression in fighter aircraft.

Slanted perforation and circular shapes with different diameters have not been studied in the supersonic regime. Examining the effect of circular diameter in slanted perforation is an innovation in this research paper.

In comparison to a nozzle with a larger/finite separation distance (Thanigaiarasu et al., 2019), a thin-lip nozzle (Srinivasarao et al., 2017) minimizes drag. Coaxial nozzles with thin lips are an appropriate tool for studying high subsonic jets because it does not create a dominant re-circulation zone. This study aims to analyze the characteristic of separation distances, between primary and secondary nozzles, within the range of 0.7–3.2 mm which can be considered a thin lip.

A separation distance of 0.7  (Papamoschou, 2004), 1.7  and 2.65 mm (Lovaraju and Rathakrishnan, 2011) is considered for the present study. The main nozzle exit Mach number is maintained at a subsonic condition of Mach 0.6, and the co-flowing nozzle exit Mach number is varied from 0% (secondary jet stopped/single jet) to 100% (Mach 0.6) in steps of 20% with respect to the main nozzle exit Mach number. A comparison was made between these velocity ratios for all three lip thicknesses in the present study. Design mesh and analysis were done by using Gambit 2.6.4 and Fluent 6.12. Velocity contours and turbulence contours were studied for qualitative analysis.

When lip thickness increases from 0.7 to 2.65 mm, the potential core length (PCL) of the primary jet decreases marginally. Additionally, the PCL of the primary jet elongates significantly as the velocity ratio increases. The primary shear layer is dominant at 20% co-flow (20 PCF), less dominant at 60% co-flow (60 PCF) and almost disappeared at 100% co-flow (100 PCF). Concurrently, the secondary shear layer almost disappeared in 20 PCF, dominant in 60 PCF and more dominant in 100 PCF. Different zones such as initial merging, intermediate and fully merged zones are quantitatively and qualitatively analyzed.

Co-flow nozzle is used in turbofan engine exhaust. The scaled-down model of a turbofan engine has been analyzed. Core length is directly proportional to the jet noise. The PCL signifies the jet noise reduction in a high-speed jet. For a low-velocity ratio, the potential core is reduced and hence can reduce the jet noise. At the same time, as the velocity ratio increases, the mass flow rate of the coaxial increases. The increase in the mass flow increases the thrust of the engine. The aircraft engine designer should analyze the requirement of the aircraft and choose the optimal velocity ratio coaxial nozzle for the engine exhaust (Papamoschou, 2004).

There have been many research studies carried out previously at various lip thickness such as 0.4  (Georgiadis, 2003), 0.7  (Papamoschou, 2004), 1.5  (Srinivasarao et al., 2014a), 1.7  (Sharma et al., 2008), 2  (Naren, Thanigaiarasu and Rathakrishnan, 2016), 2.65  (Lovaraju and Rathakrishnan, 2011), 3  (Inturiet al., 2022) and 3.2 mm (Perumal et al., 2020). However, there is no proper study to vary the lip thickness in this range from 0.7 to 3.2 mm to understand the flow behavior of a co-flowing jet.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

This research explores the antecedents of tourist satisfaction and revisit intention, especially in light of the post-pandemic environment that pushed tourism to the lowest level in the present decade. A comprehensive conceptual model based on the brand equity theory (BET) is developed, and interrelationships between brand heritage, community support and benefits, hedonism, culture, tourist satisfaction and revisit intention.

The data were collected from 670 tourists visiting one of the heritage destinations in southern India (Kanchipuram). After checking the psychometric properties of the survey instrument, the hypotheses were tested using path analysis and Hayes's PROCESS macros.

The results indicate that heritage brand of destination sites is positively associated with (1) tourist satisfaction and (2) tourist revisit intention. The findings also support the positive effect of attractiveness of products is positively related to tourist satisfaction, which in turn, is a significant predictor of tourist revisit intention. The findings also support that community support benefits moderating the relationship between heritage brand and attractiveness of products in heritage destinations tourist satisfaction.

This study has several implications for practicing managers engaged in maintaining heritage destinations. As this research highlights the importance of heritage brands of destinations in influencing tourist satisfaction, local communities and policymakers need to provide the necessary infrastructure and facilities at these destinations. Further, local entrepreneurs are motivated to invest in delivering products that attract tourists.

The conceptual model developed in this study, is first of its kind, to the best of the authors’ knowledge, that investigates the effect of hedonism (second moderator) moderating the relationship between tourist satisfaction and culture (first moderator) in influencing tourists to revisit their intention. In addition to direct relationships, the moderating role of community support and benefits, culture and hedonism makes a unique contribution to the bourgeoning literature on tourism especially in Indian context.

Ensuring the early detection of structural issues in aircraft is crucial for preserving human lives. One effective approach involves identifying cracks in composite structures. This paper employs experimental modal analysis and a multi-variable Gaussian process regression method to detect and locate cracks in glass fiber composite beams.

The present study proposes Gaussian process regression model trained by the first three natural frequencies determined experimentally using a roving impact hammer method with crystal four-channel analyzer, uniaxial accelerometer and experimental modal analysis software. The first three natural frequencies of the cracked composite beams obtained from experimental modal analysis are used to train a multi-variable Gaussian process regression model for crack localization. Radial basis function is used as a kernel function, and hyperparameters are optimized using the negative log marginal likelihood function. Bayesian conditional probability likelihood function is used to estimate the mean and variance for crack localization in composite structures.

The efficiency of Gaussian process regression is improved in the present work with the normalization of input data. The fitted Gaussian process regression model validates with experimental modal analysis for crack localization in composite structures. The discrepancy between predicted and measured values is 1.8%, indicating strong agreement between the experimental modal analysis and Gaussian process regression methods. Compared to other recent methods in the literature, this approach significantly improves efficiency and reduces error from 18.4% to 1.8%. Gaussian process regression is an efficient machine learning algorithm for crack localization in composite structures.

The experimental modal analysis results are first utilized for crack localization in cracked composite structures. Additionally, the input data are normalized and employed in a machine learning algorithm, such as the multi-variable Gaussian process regression method, to efficiently determine the crack location in these structures.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

The purpose of this paper is to consider the simultaneous flow of Casson Williamson non Newtonian fluids in a vertical porous medium under the influence of variable thermos-physical parameters.

The model equations are a set of partial differential equations (PDEs). These PDEs were transformed into a non-dimensionless form using suitable non-dimensional quantities. The transformed equations were solved numerically using an iterative method called spectral relaxation techniques. The spectral relaxation technique is an iterative method that uses the Gauss-Seidel approach in discretizing and linearizing the set of equations.

It was found out in the study that a considerable number of variable viscosity parameter leads to decrease in the velocity and temperature profiles. Increase in the variable thermal conductivity parameter degenerates the velocity as well as temperature profiles. Hence, the variable thermo-physical parameters greatly influence the non-Newtonian fluids flow.

This study considered the simultaneous flow of Casson-Williamson non-Newtonian fluids by considering the fluid thermal properties to vary within the fluid layers. To the best of the author’s knowledge, such study has not been considered in literature.

This will not be an overstatement to state that the micro, small and medium enterprise (MSME) industry is crucial and the vital driver of the world economy. It covers different fields and dimensions such as defense products, electrical components and low-cost products. The sector plays a vital role in rendering work with low capital expenditure and is one of the emerging pillars of the Indian economy. Given the significance of this sector in contributing towards India's gross domestic product (GDP), it becomes appropriate to resolve all the issues related to MSME on a primary basis for ensuring required support. The recent global pandemic of COVID-19 has impacted this sector to a great extent. This research study targets the MSME industry and points out the directly linked enablers adding to improve the sector's resiliency and sustainability. Therefore, identification and the interrelationship between the MSME enablers need to be studied, which helps make a preliminary list that deals with their impedance benefaction towards resiliency increment.

The writers have done a comprehensive literature analysis of the enablers for the MSME sector to enable effectively and efficiently during emergencies and pandemics. An endeavor has been made on the enablers to order them by utilizing the modified Total Interpretative Structure Modelling (m-TISM) technique. Authentication of this research work highlights the significance of enablers and their position in a hierarchical structure. Further, MICMAC investigation on the recognized enablers is performed to arrange them in the four quadrants on their dependence and driving power.

The authors have attempted to predict the significance of the MSME sector and its essential contribution to the development of India's economy. The result of m-TISM in the current research work revealed the essential commitment of a hierarchical design dealing with the MSME considering the viewpoint of future development. The well-planned traditional design in the MSME helps establish better government policies and programs and transport infrastructure.

Every research study has a few restrictions. Likewise, the boundaries of the current study are that inputs collated for fostering the models are from a few specialists that may not mirror the assessment of the whole MSME sector.

The MSME sector is the developing sector in the current day, and it is needed to keep supporting the sector for the country's development. The current study has set out the functional establishment to improve MSME practicality. In addition, the research highlights the accountability of the MSME authorities to go with the identified enablers having solid driving power for successful usage of the available resources. This will help the MSME development and add value to practitioners and policymakers in the future.

The growth of this sector is essential for the development of the economy and the development of a nation. The current study presents a unique structure that gives a superior comprehension of the enablers. It will help play a crucial role in developing the MSME area. The structure model developed with the assistance of m-TISM and MICMAC examine the identified enablers with inputs from experts in the field. The hierarchy developed from the study recognized the enablers located on their commitment of suitability development of the MSME field.

Combustion of fuel with oxidizer inside a combustion chamber of an internal combustion engine forms inevitable oxides of nitrogen (NOx) due to high temperature at different locations of the combustion chamber. This study aims to quantify NOx formed inside the combustion chamber using two fuels, a conventional diesel (n-heptane) and a biodiesel (methyl oleate).

This research uses a computational fluid dynamics simulation of chemically reacting fluid flow to quantify and compare oxides of nitrogen (NOx) in a compression ignition (CI) engine. The study expends species transport model of ANSYS FLUENT. The simulation model has provided the temperature profile inside the combustion chamber, which is subsequently used to calculate NOx using the NOx model. The simulation uses a single component hydrocarbon and oxygenated hydrocarbon to represent fuels; for instance, it uses n-heptane (C₇H₁₆) for diesel and methyl-oleate (C₁₉H₃₆O₂) for biodiesel. A stoichiometric air–fuel mixture is used for both fuels. The simulation runs a single cylinder CI engine of 650 cm³ swept volume with inlet and exhaust valves closed.

The pattern for variation of velocity, an important flow parameter, which affects combustion and subsequently oxides of nitrogen (NOx) formation at different piston locations, is similar for the two fuels. The variations of in-cylinder temperature and NOx formation with crank angles have similar patterns for the fuels, diesel and biodiesel. However, the numerical values of in-cylinder temperature and mass fraction of NOx are different. The volume averaged static peak temperatures are 1,013 K in case of diesel and 1,121 K in case of biodiesel, while the mass averaged mass fractions of NOx are 15 ppm for diesel and 141 ppm for biodiesel. The temperature rise after combustion is more in case of biodiesel, which augments the oxides of nitrogen formation. A new parameter, relative mass fraction of NOx, yields 28% lower value for biodiesel than for diesel.

This work uses a new concept of simulating simple chemical reacting system model to quantify oxides of NOx using single component fuels. Simplification has captured required fluid flow data to analyse NOx emission from CI engine while reducing computational time and expensive experimental tests.