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This paper aims to present a comprehensive analysis of conjugate heat transfer phenomena occurring within the developing region of square ducts under both isothermal and isoflux boundary conditions. The study involves a rigorous numerical investigation, using advanced computational methods to simulate the complex heat exchange interactions between solid structures and surrounding fluid flows. The results of this analysis provide valuable insights into the heat transfer characteristics of such systems and contribute to a deeper understanding of fluid–thermal interactions in duct flows.

The manuscript outlines a detailed numerical methodology, combining computational fluid dynamics and finite element analysis, to accurately model the conjugate heat transfer process. This approach ensures both the thermal behaviour of the solid walls and the fluid flow dynamics are well captured.

The results presented in the manuscript reveal significant variations in heat transfer characteristics for isothermal and isoflux boundary conditions. These findings have implications for optimizing heat exchangers and enhancing thermal performance in various engineering applications.

The insights gained from this study have the potential to influence the design and optimization of heat exchange systems, contributing to advancements in energy efficiency and engineering practices.

The research introduces a novel approach to study conjugate heat transfer in square ducts, particularly focusing on the developing region. This unique perspective offers fresh insights into heat transfer mechanisms that were previously not thoroughly explored.

Most of the passive techniques for enhancing heat transfer inside pipes (e.g. rough surfaces, swirl-flow devices and coiled tubes) give origin to an irregular distribution of the heat transfer coefficient at the fluid–wall interface along the wall perimeter. This irregular distribution could be critical in some industrial applications, but most of the available research papers, mainly due to the practical difficulty of local measuring heat flux on the internal wall surface of a pipe, present the results only in terms of Nusselt number averaged along the wall circumference. This paper aims to study the application of inverse problem solution techniques, which could overcome this limitation.

With regard to the estimation of the local convective heat transfer coefficient in coiled tubes, two different inverse heat conduction problem solution techniques were considered and compared both by synthetic and experimental data.

The paper shows the success of two inverse problem solution techniques in the estimation of the local convective heat transfer coefficient in coiled tubes.

This paper fulfills an identified need because most of the available research papers present the results only in terms of average thermal performance, neglecting local behavior.

The knowledge of the heat transfer coefficient is important for the proper design of heat exchangers as well as for the determination of the working medium outlet temperatures. This paper aims to present a method of simultaneous determination of coefficients in correlation formulas for the Nusselt number on both sides of the heat transfer surface.

The idea of the developed method is based on determining such a values of the coefficients in Nusselt number correlations that fulfill the condition of equality between the measured and calculated temperature at the outlet of heat exchanger in terms of least squares method. To test the proposed method, a special experimental installation was built. The heat transfer in helically coiled tube-in-tube heat exchanger was examined for the wide range of temperature changes and volumetric flow rates of working fluid.

The simulation results were validated with an experimental data. The results show that the heat transfer coefficient of the counter-current is higher than the co-current flow in helically coiled heat exchanger. This phenomenon can be beneficial particularly in the laminar flow regime.

The correlation for the Nusselt number as a function of the Reynolds and Prandtl numbers for hot and cold liquid was obtained with the least squares method for the experimental data.

The presented method allows for the simultaneous determination of heat transfer coefficient on both sides of the wall without the necessity of indirect calculation of the overall heat transfer coefficient. The presented method can be used in the thermal design of various type heat exchangers.

This work presents the new methodology of determination correlations for the helically coiled tube-in-tube heat exchanger for co-current and counter-current arrangement, which can be used in thermal design.

The driving force behind this study is the need to learn more about the ways in which green human resource management (GHRM) can impact sustainable corporate performance (SCP), especially in the context of Ho Chi Minh City's manufacturing sector. The primary objective is to analyze the roles of GHRM, green behavior (GBH) and green commitment (GCM) in relation to SCP, as well as identify the mediating roles of green behavior and green commitment in the relationship between GHRM and SCP.

The research design employs a quantitative approach to investigate the nexus of GHRM and SCP, with a focus on the manufacturing sector in Ho Chi Minh City. Methodologically, the study integrates the ability-motivation-opportunity (AMO) and resource-based view (RBV) frameworks to construct a comprehensive theoretical model. Data are gathered from a sample comprising 322 senior managers and directors representing various enterprises. Analysis is conducted utilizing Smart PLS software version 3.3.7, employing partial least squares structural equation modeling (PLS-SEM) to assess both first-level and second-level variables in a two-step process.

The empirical findings underscore significant relationships between GHRM, green behavior, green commitment and SCP. Specifically, the study reveals that GHRM positively influences green behavior, green commitment and SCP. Additionally, both green behavior and green commitment exhibit positive effects on SCP. Furthermore, the research confirms the pivotal mediating roles of green behavior and green commitment in the relationship between GHRM and SCP.

In terms of originality and value, this study makes notable contributions to both theoretical understanding and practical implications in the field of sustainable business management. By delving into the intricate interplay between GHRM, green behavior, green commitment and SCP, this research extends existing knowledge and offers novel insights. Moreover, the identification of the mediating roles of green behavior and green commitment enriches the theoretical frameworks in this domain. The findings provide practical implications for businesses, particularly in Ho Chi Minh City's manufacturing sector, by emphasizing the significance of optimizing human resource practices for achieving sustainable development goals. This research thus contributes to enhancing competitiveness and sustainability in similar industries, offering valuable guidance for strategic decision-making and policy formulation.

Singular perturbation turning point problems (SP-TPPs) involving parabolic convection–diffusion Partial Differential Equations (PDEs) with large spatial delay are studied in this paper. These type of equations are important in various fields of mathematics and sciences such as computational neuroscience and require specialized techniques for their numerical analysis.

We design a numerical method comprising a hybrid finite difference scheme on a layer-adapted mesh for the spatial discretization and an implicit-Euler scheme on a uniform mesh in the temporal variable. A combination of the central difference scheme and the simple upwind scheme is used as the hybrid scheme.

Consistency, stability and convergence are investigated for the proposed scheme. It is established that the present approach has parameter-uniform convergence of OΔτ+K−2(lnK)2, where Δτ and K denote the step size in the time direction and number of mesh-intervals in the space direction.

Parabolic SP-TPPs exhibiting twin boundary layers with large spatial delay have not been studied earlier in the literature. The presence of delay portrays an interior layer in the considered problem’s solution in addition to twin boundary layers. Numerical illustrations are provided to demonstrate the theoretical estimates.

The purpose of this study is to construct and analyze a parameter uniform higher-order scheme for singularly perturbed delay parabolic problem (SPDPP) of convection-diffusion type with a multiple interior turning point.

The authors construct a higher-order numerical method comprised of a hybrid scheme on a generalized Shishkin mesh in space variable and the implicit Euler method on a uniform mesh in the time variable. The hybrid scheme is a combination of simple upwind scheme and the central difference scheme.

The proposed method has a convergence rate of order O(N−2L2+Δt). Further, Richardson extrapolation is used to obtain convergence rate of order two in the time variable. The hybrid scheme accompanied with extrapolation is second-order convergent in time and almost second-order convergent in space up to a logarithmic factor.

A class of SPDPPs of convection-diffusion type with a multiple interior turning point is studied in this paper. The exact solution of the considered class of problems exhibit two exponential boundary layers. The theoretical results are supported via conducting numerical experiments. The results obtained using the proposed scheme are also compared with the simple upwind scheme.

This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and resource management.

The current research was studied through bibliometric review and content analysis, and various contributors and linkages were found. Also, the possible directions and implications of the field were analyzed.

The paper’s key findings include the role of modern computer science in water resource management through sensor technology, big data analytics, IoT, machine learning and cloud computing. This, in turn, helps in understanding future implications of IoT resource management.

A more extensive database can add up to more combinations of linkages and ideas about the future direction. The implications and understanding gained by the research can be used by governments and firms dealing with water management of smart cities. It can also help find ways for optimizing water resources using IoT and modern-day computer science.

This study is one of the very few investigations that highlighted IoT’s role in water supply management. Thus, this study helps to assess the scope and the trend of the case area.

The objective of this study was to evaluate the technical-economic process efficiency of obtaining simultaneous lipo-soluble (LSF) and water-soluble (WSF) fractions from annatto seeds.

The batches of annatto seeds were submitted to the refrigerated solid-liquid extraction process in four stages: pre-extraction, aqueous extraction, separation by decantation and filtration. After that, LSF and WSF from annatto seeds were obtained. The process efficiency and the quality of LSF and WSF were analyzed in terms of average yield and bioactive compounds (bixin, norbixin, phenolics and flavonoids) and their antioxidant and antimicrobial activities. Furthermore, they were economically evaluated in terms of costs of manufacturing and profitability parameters.

The process was efficient in terms of overall average yield (LSF = 8.68% and WSF = 2.76%) (w/w) and in terms of quality, mainly with higher average yields of bixin (82.34% in LSF) and norbixin (29.59% in WSF) (w/w). The concentration of bioactive compounds in the fractions promoted an increase in inhibiting free radicals (DPPH* and ABTS*+) and in the ferric-reducing power (FRAP). LSF showed a minimum inhibitory concentration of 0.06 mg mL-1 for S. aureus and 0.13 mg mL-1 for S. Typhimurium and S. Enteritidis. The lowest manufacturing costs were obtained for the LSF due to its higher extraction yield compared to the WSF. Plants on an industrial scale of 100 and 1000 L were considered economically viable, with a return on investment of 5 and 2 years.

Thus, fractions (WSF and LSF) can be applied as natural additives, as sources of bioactive compounds for nutraceutical and/or pharmaceutical, and in the development of other innovative processes. These results have practical applicability for pharmaceutical and food industry.

1. Green processing of annatto seeds obtains fractions rich in antioxidant compounds.

2. Efficiently presents a high yield of bixin and other bioactive compounds.

3. Effective in concentrating compounds that inhibit microbial growth.

4. Fractions are more accessible sources of bioactive compounds for isolation.

5. Cost of manufacturing (COM) and profitability are studied.

Green processing of annatto seeds obtains fractions rich in antioxidant compounds.

Efficiently presents a high yield of bixin and other bioactive compounds.

Effective in concentrating compounds that inhibit microbial growth.

Fractions are more accessible sources of bioactive compounds for isolation.

Cost of manufacturing (COM) and profitability are studied.

The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance.

In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements.

The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model.

The proposed approach can be applied to any problem as long as experimental/computational results can be obtained and will deliver the best approximation model to the available data set.

The purpose of this paper is to develop and optimize a mathematical model based on a framework that integrates key concepts related to a circular economy (CE) and sharing economy (SE) for a leading manufacturer of laptops in India.

This study mathematically modelled the integration of sharing networks in a circular production system. This is done through an optimization package that deploys a multi-objective mixed-integer linear programming model.

This study evaluated the economic benefit and the environmental impact associated with the aforementioned integration in a production system. This study illustrated the inverse relationship between economic benefit and environmental impact and provided a set of solutions that can be used according to the case organizations goals, capacities and logistical capabilities.

This study will aid similarly structured companies in adopting this approach to integrate sustainable practices in their production system. It also enumerated Industry 4.0 (I4.0) use-cases that can be used to effectively implement this mathematical model. Further research can be conducted using multiple companies in an inter-dependent network to maximize synergy.

This study will help to better understand the role of sharing networks in the circular economy model especially in the consumer electronics industry.

This study is the first of its kind to mathematically model the integration of aspects related to SE and CE. It also validates the aforementioned model using a numerical case-study and offers decision-support to key executives within the case organization.