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In this communication, a theoretical simulation is aimed to characterize the Darcy–Forchheimer flow of a magneto-couple stress fluid over an inclined exponentially stretching sheet. Stokes’ couple stress model is deployed to simulate non-Newtonian microstructural characteristics. Two different kinds of thermal boundary conditions, namely, the prescribed exponential order surface temperature (PEST) and prescribed exponential order heat flux, are considered in the heat transfer analysis. Joule heating (Ohmic dissipation), viscous dissipation and heat source/sink impacts are also included in the energy equation because these phenomena arise frequently in magnetic materials processing.

The governing partial differential equations are transformed into nonlinear ordinary differential equations (ODEs) by adopting suitable similar transformations. The resulting system of nonlinear ODEs is tackled numerically by using the Runge–Kutta fourth (RK4)-order numerical integration scheme based on the shooting technique. The impacts of sundry parameters on stream function, velocity and temperature profiles are viewed with the help of graphical illustrations. For engineering interests, the physical implication of the said parameters on skin friction coefficient, Nussult number and surface temperature are discussed numerically through tables.

As a key outcome, it is noted that the augmented Chandrasekhar number, porosity parameter and Forchhemeir parameter diminish the stream function as well as the velocity profile. The behavior of the Darcian drag force is similar to the magnetic field on fluid flow. Temperature profiles are generally upsurged with the greater magnetic field, couple stress parameter and porosity parameter, and are consistently higher for the PEST case.

The findings obtained from this analysis can be applied in magnetic material processing, metallurgy, casting, filtration of liquid metals, gas-cleaning filtration, cooling of metallic sheets, petroleum industries, geothermal operations, boundary layer resistors in aerodynamics, etc.

From the literature review, it has been found that the Darcy–Forchheimer flow of a magneto-couple stress fluid over an inclined exponentially stretching surface with heat flux conditions is still scarce. The numerical data of the present results are validated with the already existing studies under limited cases and inferred to have good concord.

The purpose of this paper is to compare the evaporative resistance and thermal insulation of clothing measured by thermal manikin “Walter” using uniform and non-uniform skin.

The non-uniform skin with different perspiration rates was made by laminating a silicone layer on the inner side of a uniform skin. The thermal manikin was then covered with prepared non-uniform skin as well as uniform one. Four types of clothing ensembles were tested.

The relative intensity of perspiration rate was realized in different part of “Walter” skin, which was close to the perspiration rate of human being. There was a strong correlation between uniform skin and non-uniform skin. The thermal insulation and evaporative resistance of clothing measured on the non-uniform skin were higher than the ones determined on the uniform skin. However, their moisture permeability index showed the reversed tendency.

The implication of the research is to investigate the differences between uniform skin and non-uniform skin for manikin “Walter.” This is possibly useful in correcting and predicting more accurate thermal insulation and evaporative resistance of clothing measured by “Walter” with a uniform skin in future.

It was more accurate using non-uniform skin in evaluating thermal and wet comfort comparing to uniform skin.

The effective implementation of the six sigma strategy within UK manufacturing industries, in particular SMEs, can be considered to be poor. SMEs cite high costs and complexity of implementation as being the major limiting factors as to its widespread use. This paper aims to describe the application of six sigma in an SME and to show how the company applied a cost‐effective six sigma methodology to eradicate a critical to quality (CTQ) issue. The paper seeks to conclude by developing a strategic framework for the widespread use of six sigma in SMEs.

This paper applies the six sigma strategy in an SME in order to eradicate a major CTQ issue. It identifies the approach employed, the tools and techniques used and shows the savings that were made through the structured application of the DMAIC procedure, which is at the heart of the six sigma approach.

Through the correct application of experimental design approaches, this paper identifies the optimum parameter settings that enabled the company to eradicate the CTQ issue and achieve significant improvements in quality and cost from a modest financial outlay.

The design and implementation of an SME‐specific six sigma strategy and its application to a real engineering problem will enable companies to apply the techniques and to attain improvements in terms of cost and quality.

The application of the six sigma strategy and the resulting conclusions as to its effectiveness for industry are the real value of this paper. This paper will be valuable for quality professionals, design engineers and manufacturing specialists in a wide range of industries.

The purpose of this paper is to measure the thermal insulation of protective clothing with multilayer gaps in low-level heat exposures.

Nine different combinations of protective clothing systems with multiple air gaps are used to measure the thermal insulation by a self-designed bench-scale test apparatus in different levels of an external thermal radiation of 2-10 kW/m2. The outside and inside surface temperatures of each fabric layer are also measured to calculate the local thermal insulation of each fabric layer and each air gap.

The results show that the total thermal insulation of protective clothing under thermal radiation is less than that in normal environments, and the exposed thermal radiation will worsen the total thermal insulation of the multilayer fabric systems. Air gap plays a positive role in the total thermal insulation, and thus provides the enhanced thermal protection. It is also suggested that the local resistance of the air gap closer to the external thermal radiation is more easily affected by the thermal radiation, due to the different heat transfer ways in the fabric system and the external thermal radiation.

Effects of air gap on the thermal insulation of protective clothing, and contribution of the local thermal resistance of each fabric layer and each air gap to the total thermal insulation.

The purpose of this study is to predict the thermal protective performance (TPP) of flame-retardant fabric more economically using machine learning and analyze the factors affecting the TPP using model visualization.

A total of 13 machine learning models were trained by collecting 414 datasets of typical flame-retardant fabric from current literature. The optimal performance model was used for feature importance ranking and correlation variable analysis through model visualization.

Five models with better performance were screened, all of which showed R2 greater than 0.96 and root mean squared error less than 3.0. Heat map results revealed that the TPP of fabrics differed significantly under different types of thermal exposure. The effect of fabric weight was more apparent in the flame or low thermal radiation environment. The increase in fabric weight, fabric thickness, air gap width and relative humidity of the air gap improved the TPP of the fabric.

The findings suggested that the visual analysis method of machine learning can intuitively understand the change trend and range of second-degree burn time under the influence of multiple variables. The established models can be used to predict the TPP of fabrics, providing a reference for researchers to carry out relevant research.

The findings of this study contribute directional insights for optimizing the structure of thermal protective clothing, and introduce innovative perspectives and methodologies for advancing heat transfer modeling in thermal protective clothing.

Communication of an impending hazard to people in near real time is critical. The purpose of this paper is to develop an internet‐SMS based geo‐hazard warning communication system.

A warning system based on an internet‐resident concept and the available cellular mobile infrastructure is proposed in this study. The functionality of the system is modular in architecture.

The messages have been transmitted in a set of 20 SMSs six times, to locally‐owned mobile numbers, resulting in a total number of 120. It has been found that 58 messages got delivered within ten seconds, the rest within 40 more seconds. The threat messages reached the impending threat areas within acceptable time delay.

The paper describes the implementation of a novel and stand‐alone system for dynamic hazard warning. Cellular or mobile phone, a gadget used by common man, is expected to be the best proposition to effectively warn people individually and to propagate hazard messages to users in large regions ubiquitously. The concept allows pervasiveness and redundancy, important to withstanding hazards and bringing several original elements through the development of this “fast warning system”, as current warning strategies do not include such solutions.

The purpose of this paper is to capture the evolution and status of utilization of the Six Sigma philosophy in the development of small to medium‐sized enterprises (SMEs), as well as to document prominent development of practices through a systematic literature review.

The methodology adopted for this study used the principles of content analysis and deductive reasoning vis‐à‐vis various sub domains of Six Sigma methodology pertaining to industries in general and SMEs in particular.

The literature revealed that: Management's commitment is most important in SME Six sigma implementation. Benefits of Six Sigma have been enjoyed largely by the bigger industrial units and to a relatively lesser extent by the smaller units, i.e. SMEs. Quality management culture has largely been ignored or given less importance in the SME sector, which is evident from the meagre literature. There is a dearth of clear and SME‐specific methodologies (for Six Sigma approach) for quality improvement and there are far fewer models for quality improvement in the SME sector.

It has been found, on the basis of a systematic literature review approach (used in this paper), that quality management and development in SMEs needs to be done in a planned manner using Six Sigma roadmap.

The advancements in the cloud computing has gained the attention of several researchers to provide on-demand network access to users with shared resources. Cloud computing is important a research direction that can provide platforms and softwares to clients using internet. However, handling huge number of tasks in cloud infrastructure is a complicated task. Thus, it needs a load balancing (LB) method for allocating tasks to virtual machines (VMs) without influencing system performance. This paper aims to develop a technique for LB in cloud using optimization algorithms.

This paper proposes a hybrid optimization technique, named elephant herding-based grey wolf optimizer (EHGWO), in the cloud computing model for LB by determining the optimal VMs for executing the reallocated tasks. The proposed EHGWO is derived by incorporating elephant herding optimization (EHO) in grey wolf optimizer (GWO) such that the tasks are allocated to the VM by eliminating the tasks from overloaded VM by maintaining the system performance. Here, the load of physical machine (PM), capacity and load of VM is computed for deciding whether the LB has to be done or not. Moreover, two pick factors, namely, task pick factor (TPF) and VM pick factor (VPF), are considered for choosing the tasks for reallocating them from overloaded VM to underloaded VM. The proposed EHGWO decides the task to be allocated in the VM based on the newly derived fitness functions.

The minimum load and makespan obtained in the existing methods, constraint measure based LB (CMLB), fractional dragonfly based LB algorithm (FDLA), EHO, GWO and proposed EHGWO for the maximum number of VMs is illustrated. The proposed EHGWO attained minimum makespan with value 814,264 ns and minimum load with value 0.0221, respectively. Meanwhile, the makespan values attained by existing CMLB, FDLA, EHO, GWO, are 318,6896 ns, 230,9140 ns, 1,804,851 ns and 1,073,863 ns, respectively. The minimum load values computed by existing methods, CMLB, FDLA, EHO, GWO, are 0.0587, 0.026, 0.0248 and 0.0234. On the other hand, the proposed EHGWO with minimum load value is 0.0221. Hence, the proposed EHGWO attains maximum performance as compared to the existing technique.

This paper illustrates the proposed LB algorithm using EHGWO in a cloud computing model using two pitch factors, named TPF and VPF. For initiating LB, the tasks assigned to the overloaded VM are reallocated to under loaded VMs. Here, the proposed LB algorithm adapts capacity and loads for the reallocation. Based on TPF and VPF, the tasks are reallocated from VMs using the proposed EHGWO. The proposed EHGWO is developed by integrating EHO and GWO algorithm using a new fitness function formulated by load of VM, migration cost, load of VM, capacity of VM and makespan. The proposed EHGWO is analyzed based on load and makespan.

This study aims to analyze the two-dimensional ferrofluid flow in porous media. The effects of changes in parameters such as permeability parameter, buoyancy parameter, Reynolds and Prandtl numbers, radiation parameter, velocity slip parameter, energy dissipation parameter and viscosity parameter on the velocity and temperature profile are displayed numerically and graphically.

By using simplification, nonlinear differential equations are converted into ordinary nonlinear equations. Modeling is done in the Cartesian coordinate system. The finite element method (FEM) and the Akbari-Ganji method (AGM) are used to solve the present problem. The finite element model determines each parameter’s effect on the fluid’s velocity and temperature.

The results show that if the viscosity parameter increases, the temperature of the fluid increases, but the velocity of the fluid decreases. As can be seen in the figures, by increasing the permeability parameter, a reduction in velocity and an enhancement in fluid temperature are observed. When the Reynolds number increases, an increase in fluid velocity and temperature is observed. If the speed slip parameter increases, the speed decreases, and as the energy dissipation parameter increases, the temperature also increases.

When considering factors like thermal conductivity and variable viscosity in this context, they can significantly impact velocity slippage conditions. The primary objective of the present study is to assess the influence of thermal conductivity parameters and variable viscosity within a porous medium on ferrofluid behavior. This particular flow configuration is chosen due to the essential role of ferrofluids and their extensive use in engineering, industry and medicine.

The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units.

The proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique.

The proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization.

To validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.