Optimization Of Various Processes Research Articles

Dynamic Interactions: Non-Integer-Order Heat-Mass Transfer in Magnetohydrodynamic Flow of Non-Newtonian Fluid over Inclined Plates

The heat and mass transfer phenomenon in the presence of a moving magnetic field has a wide range of applications, spanning from industrial processes to environmental engineering and energy conversion technologies. Understanding these interactions enables the optimization of various processes and the development of innovative technologies. This manuscript is about a non-integer-order heat-mass transfer model for Maxwell fluid over an inclined plate in a porous medium. The MHD flow of non-Newtonian fluid over the plate due to the natural convection of the symmetric temperature field and general motion of the inclined plate is investigated. A magnetic field is applied with a certain angle to the plate, and it can either be fixed in place or move along with the plate as it moves. Our model equations are linear in time, and Laplace transforms form a powerful tool for analyzing and solving linear DEs and systems, while the Stehfest algorithm enables the recovery of original time domain functions from their Laplace transform. Moreover, it offers a powerful framework for handling fractional differential equations and capturing the intricate dynamics of non-Newtonian fluids under the influence of magnetic fields over inclined plates in porous media. So, the Laplace transform method and Stehfest’s numerical inversion algorithm are employed as the analytical approaches in our study for the solution to the model. Several cases for the general motion of the plate and generalized boundary conditions are discussed. A thorough parametric analysis is performed using graphical analysis, and useful conclusions are recorded that help to optimize various processes and the developments of innovative technologies.

Digital Innovations and Market Dynamics of Tourism Businesses in Turkey

This research explores the intricate relationship between digital innovations and market dynamics within the Turkish tourism businesses. Employing a qualitative approach, data were gathered through in-depth interviews with key stakeholders, including representatives from tourism agencies, hoteliers, tour operators, and technology providers. Thematic analysis of the data revealed several key findings. Firstly, digital innovations have enabled tourism businesses to enhance customer engagement and deliver personalized experiences, leveraging social media, online booking platforms, and mobile applications. Secondly, technology adoption has led to improved operational efficiency and cost reduction through automation and optimization of various processes. Thirdly, digital platforms have facilitated market expansion and global reach, enabling businesses to tap into new markets and attract international tourists. However, challenges such as digital literacy, data privacy concerns, and the need for government support remain prevalent. Collaboration between the public and private sectors is crucial in driving digital transformation and fostering sustainable growth in the Turkish tourism industry. While the qualitative nature of this study limits generalizability, future research endeavors could explore longitudinal trends, conduct comparative studies across regions, and investigate the role of emerging technologies. Overall, this study contributes to a deeper understanding of the impact of digital innovations on the Turkish tourism sector and provides valuable insights for academia, industry practitioners, and policymakers alike.

Ensuring Human Rights in the Era of Artificial Intelligence: Ukraine and Practice of ECHR

Artificial intelligence gets into all spheres of life which are familiar to us. Automation and optimization of various processes make our daily tasks much easier. The topicality of the research is due to the rapid development and improvement of artificial intelligence, and therefore it is important to familiarize yourself with all aspects of its application. In the course of the study, laws of Ukraine, the practice of the ECHR, as well as international legal documents was analysed. This research is aimed at determining all aspects of the use of artificial intelligence in various spheres of society, its impact on the ways to protect human rights within the framework of these legal relations. The study pays particular attention to the risks which exist in connection with handling of personal information from artificial intelligence, the extent of the impact on our privacy rights, our freedoms and our opportunities. The research is based on issues of the application of artificial intelligence, for example, on solving problems with discrimination, inequality and various social issues. Furthermore, the proposals for the development of legal aspects of the protection of human rights in the context of artificial intelligence at the Ukrainian and international levels are formulated. This research is very important for understanding and developing effective measures to protect our rights and freedoms in this new technological world.

A new molecular thermodynamic model of liquid-liquid interfacial tension

• A new molecular thermodynamic model of interfacial tension is derived. • This model yields satisfactory prediction results for interfacial tension. • It doesn't require mutual solubility data for interfacial tension predictions. • This model is simple in implementation and reliable in application. Interfacial tension between water and organic liquids plays an important role in the design and optimization of various processes, such as enhanced oil recovery, the entrapment and migration of non-aqueous phase liquid (NAPL), chemical separation technology (liquid-liquid extraction) relevant to ex-situ hazardous waste remediation and chemical processing. A new molecular thermodynamic approach of monolayer interface model was developed in this work, in which the total interfacial energy includes contributions from the excess interface cohesive energy and excess interface entropy (entropy from partially mixing and entropy from free volume change). The accuracy of this model in the prediction of interfacial tension for water-organic liquid and mercury-nonmetallic liquid systems has been examined with satisfactory results. The investigation results indicates that for water-organic liquid systems, the excess interface entropy term makes considerable contribution (9.5%∼46.6%) to the total interfacial energy, which may result in the interaction parameter of Girifalco and Good model being greater than unity (1.04≤ Φ ≤1.15) for water-alcohols; while for mercury-nonmetallic liquid systems, the contribution to the total interfacial energy from interfacial entropy is negligible (1.2%∼2.7%), the difference in cohesive energy of molecules between the bulk phase and interfacial phase dominates the wetting process. This method doesn't require measured mutual solubility data for interfacial tension predictions, which is simple in implementation and reliable in application.

Interactive communication in the process of physical education: are social media contributing to the improvement of physical training performance.

The development of modern technologies and the use of social networks create an environment for the exchange of information, interactive communication, learning, and optimization of various processes. The study describes the results of the effectiveness of using various social media tools to increase the level of physical activity in people of different ages (12–35 years old). Effective tools for increasing the level of physical activity that can be used on social media have been considered. A survey created in Google forms was conducted to select research participants and group them; the pedagogical experiment is the introduction of social media tools to encourage users to do sports. The experiment involved 148 people of different age groups: adolescents, students, adults. After the experiment with the experimental group, there were 59.20% of participants with an average level of physical activity and 22.37% of participants with a high level of physical activity; in the control group, 31.58% of participants had a low level of physical activity, 48.70%—average, 10.53%—high. Most participants of all ages (88.16%) refrained from posting videos of their achievements on social media, while nine participants (5 pupils and 4 students) posted their achievements in the form of short video exercises or screenshots, and reports of exercises in mobile applications in their groups. The research results are applicable to various social groups and can be used to create private groups on social media to encourage physical activity. The data obtained can be used for further development of specialized training programs using digital technology and social networks.

A REVIEW ON THE INFLUENCE OF PROCESS PARAMETERS AND HEAT TREATMENT ON THE CORROSION PERFORMANCE OF NI-BASED THERMAL SPRAY COATINGS

Various typical engineering components fail from surface under aggressive conditions like oxidation and hot corrosion. This paper is focused on the responsible failure mechanism of oxidation and hot corrosion. The surface properties like corrosion resistance can be enhanced by introducing a layer of Ni-based materials by using thermal coating techniques. The coatings developed by using processes like high velocity oxy-fuel, plasma spray and cold spray exhibits some surface defects like porosity, surface roughness and un-melted particles. Such defects can be further minimized by using optimization of process parameters and various heat treatment processes. The current study is restricted to the analysis of Ni-based coatings developed using high velocity oxy-fuel, plasma spray and cold spray process. In this paper, the optimization of various process parameters along with heat treatments has been discussed in regard to the tailoring of microstructure and the mechanical properties of the developed coatings.

The added value of smart stadiums: a case study at Johan Cruijff Arena

PurposeThe objective of stadium owners is to attract visitors to their stadiums and by this optimally use their business potential. Stadiums face increasing competition from home-viewing options, with which especially aging stadiums have trouble competing. This paper aims to study the concept of smart stadiums as a solution to this problem, adding the corona age as an additional challenge.Design/methodology/approachFirst, (smart) stadium literature and theories are reviewed. Then, a case study is conducted, consisting of document review, observations and semi-structured interviews with specialists. The case that is studied is the Johan Cruijff Arena in Amsterdam – the stadium has the ambition to be the most innovative stadium in 2020.FindingsNine different smart tools were identified in the case study, which supports the optimization of various processes in the stadium such as ticketing and crowd control. The findings from this case study showed the potential of the smart stadium concept and how it can add value for the stadium’s stakeholders. The use of smart tools can improve the effectiveness and efficiency of stadium operations, and it can be used to improve the visitors’ experience. However, concrete numbers of progress were difficult to obtain because the smart tools were only recently implemented.Originality/valueAs seen in the past few years, more and more stadiums are branding themselves as a smart stadium. However, research on this subject is still scarce: existing research focused on other types of real estate. By exploring the work done in theory and practice, the authors hope to increase research on the subject of smart stadiums.

Cavitation bubble dynamics in a vicinity of a thin membrane wetted by different fluids

Understanding and controlling the interaction of cavitation bubbles and nearby material is becoming essential optimization of various processes. We examined the interaction of a single bubble with a membrane with different fluids on each side of it. Significant differences in bubble behavior depending on the fluid properties were observed, while the influence of membrane properties was less pronounced. The study has important implications, such as optimization of sonoporation (targeted drug delivery) where the mechanism, by which the permeability of the membrane is increased, is still not well understood. These results show that the focus of the optimization process should, in the first place, lie on the properties of liquids, rather than the mechanical properties of the membrane itself.

Evaluation of Thermodynamic Analysis of Solar Energy Systems Integrated into Sustainable Buildings with Artificial Neural Network: A Case Study

With the increasing concern on the environment and climate change, scientists focused on the way in which new structures, especially in the field of energy. In this sense, the concept of sustainable buildings is developing day by day in terms of energy efficiency. The sustainable building concept identifies five objectives which are resource efficiency, energy efficiency, prevention of pollution, harmonization with the environment; and also using integrated and systemic approaches. To increase energy efficiency in buildings, the integration of Solar Energy Systems into buildings attaches importance in terms of sustainable engineering designs. Evacuated Tube Heat Pipe (ETHP) solar energy systems are also noteworthy in this regard. This paper presents the results of an experimental study that is an ETHP solar collector system. ETHP systems are an alternative solar energy system to low-efficiency planary collectors. Only water was used to avoid losses in the heat transfer from the fluid to the fluid. Water is inserted in the vacuum tube in order to improve the rate of heat transfer, such that the mode of heat transfer from the inner surface of the vacuum tube to the heat pipe becomes convection via the water, as well as conduction through the installed. The exergy efficiency of the ETHP system was calculated as 32.94%. For a long time, artificial neural networks (ANN) have been widely applied in energy efficiency for modeling and optimization of various processes. In the field of processing, recent studies confirm the validity and effectiveness of using ANNs as promising and most powerful computer modeling techniques. Within the scope of this study, exergy efficiency was evaluated on the developed Artificial Neural Network algorithm. The effect rates of parameters such as pressure, temperature, and ambient temperature affecting exergy efficiency were calculated. Finally, significant findings obtained were evaluated in terms of thermodynamics rules.

The response of four braconid parasitoid species to methyl eugenol: Optimization of a biocontrol tactic to suppress Bactrocera dorsalis

Methyl eugenol (ME) is the most common tephritid male lure used in studies investigating Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), a highly destructive pest species. The following four species of braconid wasps (Hymenoptera: Braconidae) are parasites of several Tephritidae flies of economic significance: Fopius arisanus (Sonan), F. vandenboschi (Fullaway), Diachasmimorpha longicaudata (Ashmead) and Psyttalia incisi (Silvestri). An integrated pest management (IPM) strategy involving the release of multiple parasitoid species, the release of sterile males, and the placement of ME-lure traps was recently implemented in southern China. This study evaluated the effects of ME on braconid parasitoids. Based on the results from olfactometer bioassays, all parasitoid species were significantly repelled by undiluted ME. Furthermore, attractant-influenced behavioral activities occurred at relatively low concentrations of ME (e.g., 0.01, 0.1, and 1 μl/ml), whereas the effects of the repellent increased to significant levels as the concentration increased. There were no significant differences in electroantennogram (EAG) responses among different doses of ME, but the number of F. arisanus parasitoids attracted to traps containing host eggs decreased significantly at higher concentrations, e.g., 10, 100 and 1000 μl/ml. In addition, the number of F. arisanus females that were attracted to the host egg trap decreased significantly with higher concentrations of ME (10, 100 and 1 μl/ml). The number of F. arisanus females that exhibited ovipositional behavior in an environment without ME was significantly higher than those with different concentrations of ME. This study improves our understanding of control tactic interactions as well as the optimization of various processes involved in the IPM program.

Modeling the effects of temperature and time of homogenization annealing on the hardness of PdNi5 alloy

Experimental design methodology represents a powerful tool for the analysis and optimization of various processes. PdNi5 alloy is used in the in the production process of nitric acid, as Pd-catalyst-trap. The role of Pd-catalyst-trap consists in reduction of volatile platinum oxide from gas flow to the metal form and retention of platinum metal on the surface of Pd catalyst-trap. Fundamental knowledge about this alloy and its practical use in reduction of volatile platinum oxide, can be improved by experimental planning and statistical analysis. In this study, the effects of annealed temperature and annealed time on the hardness of PdNi5 alloy were evaluated and compared. Full factorial experimental design at three levels was applied. Statistically significant factors were determined considering of hardness of PdNi5 alloy as a system response. By regression analysis, the mathematical model for process description was derived. The correlation between predicted and experimental values was high (R2=0,976 ). In the investigated ranges of parameters, the obtained empirical equation can be applied for the prediction of system response.

Analysis of factors influencing Cu(II) sorption by clinoptiolite

Experimental design methodology represents a powerful tool for the analysis and optimization of various processes. Immobilization of toxic substances by sorption onto low-cost materials gained a lot of attention in the last decade. Fundamental knowledge about sorption processes and their practical use can be improved by experimental planning and statistical analysis. In this study, the effects of initial metal concentration and pH, as well as the sorbent mass and particle size, on Cu(II) sorption by natural clinoptilolite were evaluated and compared. Full factorial experimental design at two levels was applied. Statistically significant factors were determined considering residual Cu(II) concentrations as a system response. The Pareto graphs of standardized effects, Main effect plots and Interaction plots were created using statistical software. Initial sorbate concentration, sorbent mass and their interaction were recognized as statistically significant, at 95 % confidence level. Main effect plot approved that sorbent mass increase and initial Cu(II) concentration decrease caused reduction of residual Cu(II) concentration in solution. On the other hand, the change of initial solution pH and sorbent particle size didn?t provoke significant response changes. Bearing in mind that pH is the factor with large effect on heavy metal sorption, insignificant influence of initial pH detected in this study can be explained by buffering properties of the applied clinoptilolite and relatively narrow pH range chosen in order to prevent sorbent dissolution on one side and sorbate precipitation on the other. By regression analysis, the mathematical model for process description was derived. The correlation between predicted and experimental values was high (R2>0.99). In the investigated ranges of parameters, the obtained empirical equation can be applied for the prediction of system response.

Fabrication of hp 32 nm resist patterns using near-field lithography

Near-field lithography (NFL) has no fundamental limit such as the diffraction limit of light. However, in order to fabricate resist patterns with hp 32 nm, thorough optimization of various processes are indispensable. Previously, we reported on the use of fine and ultra-thin top-layer resist, and designs and fabrication of our special masks. In this paper, the effect of the total resist thickness on the near-field distribution is analyzed by the finite-difference time domain analyses and compared with our experiments. For the fabrication of hp 32 nm patterns, the total resist thickness as well as the tri-layer resist process are accordingly optimized. By the near-field exposure using an i-line mercury lamp and the dry-etching process for thin top-layer photo-resist, we have successfully fabricated the hp 32 nm resist pattern of 120 nm height.

Forging of Compressor Blades: Temperature and Ram Velocity Effects

Forging is one of the most widely used manufacturing process for making high-strength, structurally integrated, impact and creep-resistant Ti-6A1-4V compressor blades for jet engines. In addition, in modern metal forming technology, finite element analysis method and computer modeling are being extensively employed for initial evaluation and optimization of various processes, including forging. In this study, DEFORM, a rigid viscoplastic two-dimensional finite element code was used to study the effects of initial die temperature and initial ram velocity on the forging process. For a given billet, die temperature and ram velocity influence the strain rate, temperature distribution, and thus the flow stress of the material. The die temperature and the ram velocity were varied over the range 300 to 700°F and 15-25 in./sec, respectively, to estimate the maximum forging load and the total energy required to forge compressor blades. The ram velocity was assumed to vary linearly as a function of stroke. Based on the analysis, it was found that increasing the die temperature from 300 to 700°F decreases the forging loads by 19.9 percent and increases the average temperature of the workpiece by 43°F. Similarly, increasing the initial ram velocity from 15 to 25 in./sec decreases the forging loads by 25.2 percent and increases the average temperature of the workpiece by 36°F. The nodal temperature distribution is bimodal in each case. The forging energy required to forge the blades is approximately 18 kips *in./in.