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The purpose of this research paper is to find the optimum parameters, namely, the sliding speed, applied load and percentage of silicon carbide particles (SiCp), under which AlSi10Mg/SiCp composites experience minimum wear.

Wear rate (WR) of AlSi10Mg, AlSi10Mg/10SiC and AlSi10Mg/20SiC was measured using pin-on-disk equipment according to ASTM G99 standards. Response surface method was used to design the experiments, model and analyze the tribological behaviour. Tests were conducted as per Box–Beheken design of experiments. The wear mechanisms were observed using scanning electron microscope. Genetic algorithm was used to find the optimum parameters for minimum WR.

Wear mechanisms underwent changes with variation in applied load, sliding speed and per cent SiCp. An optimum wear condition was obtained when the process parameters, namely, the sliding speed, applied load and percentage of SiCp, were at 4 m/s, 10 N and 20 per cent, respectively. Combined GA-RSM approach was successfully used to predict the minimum WR condition of AlSi10Mg/SiCp composites with an accuracy of 94 per cent.

The tribological behaviour of AlSi10Mg/SiCp composites has been investigated in detail. A statistical WR model is proposed. This paper provides an optimum condition to design the tribo contact between steel and AlSi10Mg/SiCp composites.

Previous research assumes that economic development is the key to increasing the food supply and alleviating child malnutrition. However, economic development alone does not promise that income is distributed fairly, nor does it guarantee that other human needs will be fulfilled. What has been missing from cross-national research is an analysis of how gender inequality shapes women’s abilities to effectively maintain food security. The current study contributes to this literature by exploring the multidimensional effects of women’s empowerment on child stunting and wasting.

Pooling data from the Demographic and Health Surveys and the World Bank, the analysis estimates a series of multi-level models that examine the country-level influences on malnutrition, while also accounting for household and maternal characteristics that affect food security at the individual level.

Results suggest that improvements in women’s education, control over reproduction, representation in national politics, and life expectancy correspond to improvements in child malnutrition. Notably, the effects of gender inequality are comparable to or larger than those of economic development. The multi-level modeling technique illustrates how social forces that are larger than the individual shape the chances of experiencing food insecurity.

Cross-national data are limited in scope and cannot prove causality. Further research is also needed to better understand the process by which women wield advances in rights and empowerment to affect food security.

If policymakers want to facilitate food security in poor countries, they should not disregard the potential of policies that will promote more equitable rights for women.

The paper aims to describe the Taguchi design method-based abrasive wear modeling of in situ AlB2 flake reinforced Al-4Cu matrix alloy composites.

The abrasive wear behaviors of the composite samples were investigated using pin-on-disk method where the samples slid against different sizes of SiC abrasive grits under various testing conditions. The orthogonal array, signal-to-noise (S/N) ratio and analysis of variance were used to study the optimal testing parameters on composite samples.

The weight loss of composites decreased with increasing grit size and percentage reinforcement and increased with increasing sliding speed. The optimum test condition, at which the minimum weight loss is obtained, has been determined to be A3B3C1 levels of the control factors. Deviations between the actual and the predicted S/N ratios for abrasive weight losses are negligibly small with 99.5 per cent confidence level.

This paper fulfils an identification of Taguchi method-based abrasive wear behavior of AlB2/Al-4Cu metal matrix composites produced by squeeze casting under various testing conditions.

Aluminium and its alloys are the most preferred material in aerospace and automotive industries because of their high strength-to-weight ratio. However, these alloys are found to be low wear resistance. Hence, the incorporation of ceramic particles with the aluminium alloy may be enhanced the mechanical and tribological properties. The purpose of this study is to optimize the specific wear rate and friction coefficient of titanium dioxide (TiO₂) reinforced AA7075 matrix composites. The four wear control factors are considered, i.e. reinforcement (Wt.%), applied load (N), sliding velocity (m/s) and sliding distance (m).

The composites were fabricated through stir casting route with varying weight percentages (0, 5, 10 and 15 Wt.%) of TiO₂ particulates. The mechanical properties of the composites were studied. The specific wear rate and friction coefficient of the newly prepared composites was determined by using a pin-on-disc apparatus under dry sliding conditions. Experiments were planned as per Taguchi’s L16 orthogonal design. Signal-to-noise ratio analysis was used to find the optimal combination of parameters.

The mechanical properties such as yield strength, tensile strength and hardness of the composites significantly improved with the addition of TiO₂ particles. The analysis of variance result shows that the applied load and reinforcement Wt.% are the most influencing parameters on specific wear rate and friction coefficient during dry sliding conditions. The scanning electron microscope morphology of the worn surface shows that TiO₂ particles protect the matrix from more removal of material at all conditions.

This paper provides a solution for optimal parameters on specific wear rate and friction coefficient of aluminium matrix composites (AMCs) using Taguchi methodology. The obtained results are useful in improving the wear resistance of the AA7075-TiO₂ composites.

Designing new aircraft that are state-of-the-art and beyond always requires the development of new technologies. This paper aims to present lessons learned while designing, building and testing new UAVs in the configuration of the flying wing. The UAV contains a number of aerodynamic devices that are not obvious solutions and use the latest manufacturing technology achievements, such as 3D printing.

The design solutions were applied on an airworthy aircraft and checked during test flights. The process was first conducted on the smaller UAV, and based on the test outcomes, improvements were made and then applied on the larger version of the UAV, where they were verified.

A number of practical findings were identified. For example, the use of 3D printing technology for manufacturing integrated pressure ports, investigation of the adverse yaw effect on the flying wing configuration and the effectiveness of winglet rudders in producing yawing moment.

All designed devices were tested in practice on the flying aircraft. It allowed for improved aircraft performance and handling characteristics. Several of the technologies used improved the speed and quality of aerodynamic device design and manufacturing, which also influences the reliability of the aircraft.

The paper presents how 3D printing technology can be utilized for manufacturing of aerodynamic devices. Specially developed techniques for control surface design, which can affect adverse yaw problem and aircraft handling characteristics, were described.

Since, wear is the one of the most commonly encountered industrial problems leading to frequent replacement of components there is a need to develop metal matrix composites (MMCs) for achieving better wear properties. The purpose of this paper is to fabricate aluminum MMCs to improve the dry sliding wear characteristics. An effective multi-response optimization approach called the principal component analysis (PCA) was used to identify the sets of optimal parameters in dry sliding wear process.

The present work investigates the dry sliding wear behavior of graphite reinforced aluminum composites produced by the molten metal mixing method by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried on graphite reinforced MMCs and its matrix alloy sliding against a steel counter face. Different contact stress, reinforcement percentage, sliding distance and sliding velocity were selected as the control variables and the response selected was wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Optimization of dry sliding performance of the graphite reinforced MMCs was performed using PCA.

Based on the PCA, the optimum level parameters for overall principal component (PC) of WVL and COF have been identified. Moreover, analysis of variance was performed to know the impact of individual factors on overall PC of WVL and COF. The results indicated that the reinforcement percentage was found to be most effective factor among the other control parameters on dry sliding wear followed by sliding distance, sliding velocity and contact stress. Finally the wear surface morphology of the composites has been investigated using scanning electron microscopy.

Various manufacturing techniques are available for processing of MMCs. Each technique has its own advantages and disadvantages. In particular, some techniques are significantly expensive compared to others. Generally the manufacturer prefers the low cost technique. Therefore stir casting technique which was used in this paper for manufacturing of Aluminum MMCs is the best alternative for processing of MMCs in the present commercial sectors. Since the most important criteria of a dry sliding wear behavior is to provide lower WVL and COF, this study has intended to prove the application of PCA technique for solving multi objective optimization problem in wear applications like piston rings, piston rods, cylinder heads and brake rotors, etc.

Application of multi-response optimization technique for evaluation of tribological characteristics for Aluminum MMCs made up of graphite particulates is a first-of-its-kind approach in literature. Hence PCA method can be successfully used for multi-response optimization of dry sliding wear process.

This study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.

This study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.

This study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.

The government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.

This study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.

Aluminium is the most preferred material in engineering structural components because of its excellent properties. Furthermore, the properties of aluminium may be enhanced through metal matrix composites and an in-depth investigation on the evolved properties is needed in view of metallurgical, mechanical and tribological aspects. The purpose of this study is to explore the effect of TiC addition on the tribological behavior of aluminium composites.

Aluminium metal matrix composites at different weight percentage of titanium carbide were produced through powder metallurgy. Produced composites were subjected to sliding wear test under dry condition through Taguchi’s L9 orthogonal design.

Optimal process condition to achieve the minimum wear rate was identified though the main effect plot. Sliding velocity was identified as the most dominating factor in the wear resistance.

The production of components with improved properties is promoted efficiently and economically by synthesizing the composite via powder metallurgy.

Though the investigations on the wear behavior of aluminium composites are analyzed, reinforcement types and the mode of fabrication have their significance in the metallurgical and mechanical properties. Thus, the produced component needs an in-detail study on the property evolution.

This research aims to describe the influence of weight per cent of graphite (Gr), applied load and sliding speed on the wear behavior of aluminum (Al) alloy A356 reinforced with silicon carbide (SiC) (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) particles. The objective is to analyze the effect of the aforementioned parameters on a specific wear rate.

These hybrid composites are obtained by means of the compo-casting process. Tribological analyses were conducted on block-on-disc tribometer at three different loads (10, 20 and 30 N) and three different sliding speeds (0.25, 0.5 and 1 m/s), at the sliding distance of 900 m, in dry sliding wear conditions. Optimization of the tribological behavior was conducted via the Taguchi method, and ANOVA was used for the analysis of the specific wear rate. Confirmation tests are used to foresee and check the experimental results. Examined samples were analyzed via a scanning electron microscope (SEM). Regression models for predicting specific wear rate were developed with Taguchi and ANN (artificial neural network) methods.

The biggest impact on value of specific wear rate has the load (43.006%), while the impact of Wt.% Gr (31.514%) was less. After comparison of the results, i.e. regression models, for predicting the specific wear rate, it was observed that ANN was more efficient than the Taguchi method. The specific wear rate of Al alloy A356 with SiC (10 Wt.%) and Gr (1 Wt.% and 5 Wt.%) decreases with a decrease in the load and weight per cent of Gr-reinforcing material, as well as with a decrease in sliding speed.

The results obtained in this paper using the Taguchi method and the ANN method are useful for improving and further investigating the wear behavior of the SiC- and Gr-reinforced Al alloy A356.

Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA).

Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically.

The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established.

Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution.

The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible.

As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact.

In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.