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This work aims to concentrate on the mixed convection of the stagnation point flow of ternary hybrid nanofluids towards vertical Riga plate. Aluminum trioxide (Al₂O₃), silicon dioxide (SiO₂) and titanium dioxide (TiO₂) are regarded as nanoparticles, with water serving as the base fluid. The mathematical model incorporates momentum boundary layer and energy equations. The Grinberg term for the viscous dissipation and the wall parallel Lorentz force coming from the Riga plate are taken into consideration in the context of the energy equation.

Through the use of appropriate nonsimilar transformations, the governing system is transformed into nonlinear nondimensional partial differential equations (PDEs). The numerical method bvp4c (built-in package for MATLAB) is used in this study to simulate governing equations using the local non-similarity (LNS) approach up to the second truncation level.

Numerous graphs and numerical tables expound on the physical properties of the nanofluid temperature and velocity profiles. The local Nusselt correlations and the drag coefficient for pertinent parameters have been computed in tabular form. Additionally, the temperature profile drops while the velocity profile increases when the mixed convection parameter is included to oppose the flow.

The fundamental goal of this work is to comprehend how ternary nanofluids move towards a vertical Riga plate in a mixed convective domain with stagnation point flow.

Preparing CrAlN coatings on the surface of silicon nitride bearings can improve their service life in oil-free lubrication. This paper aims to match the optimal process parameters for preparing CrAlN coatings on silicon nitride surfaces, and reveal the microscopic mechanism of process parameter influence on coating wear resistance.

This study used molecular dynamics to analyze how process parameters affected the nucleation density, micromorphology, densification and internal stress of CrAlN coatings. An orthogonal test method was used to examine how deposition time, substrate temperature, nitrogen-argon flow rate and sputtering power impacted the wear resistance of CrAlN coatings under dry friction conditions.

Nucleation density, micromorphology, densification and internal stress have a significant influence on the surface morphology and wear resistance of CrAlN coatings. The process parameters for better wear resistance of the CrAlN coatings were at a deposition time of 120 min, a substrate temperature of 573 K, a nitrogen-argon flow rate of 1:1 and a sputtering power of 160 W.

Simulation analysis and experimental results of this paper can provide data to assist in setting process parameters for applying CrAlN coatings to silicon nitride bearings.

This study aims to numerically scrutinize the entropy generation minimization and mixed convective heat transfer of multi-walled carbon nanotubes–Fe₃O₄/water hybrid nanofluid flow in a lid-driven square enclosure with heat generation in the presence of a porous layer on inner surfaces, considering local thermal non-equilibrium (LTNE) approach and the non-Darcy flow model.

The dimensionless governing equations for hybrid nanofluid and solid phases are solved by applying the finite volume method and semi-implicit method for pressure-linked equations algorithm.

The roles of the internal heat generation in the porous layer, LTNE model and nanoparticles volume fraction on mixed convection phenomenon and entropy generation are introduced for lid-driven cavity hybrid nanofluid flow. Based on the investigation of entropy generation and heat transfer, the minimum total entropy generation and average Nusselt numbers are found at 1 ≤ Ri ≤ 10 where the effect of the forced and free convection flow directions being opposite each other is very significant. When considering various nanoparticle volume fractions, it becomes evident that the minimum entropy generation occurs in the case of φ = 0.1%. The outcomes of LTNE number reveal the operating parameters in which thermal equilibrium occurs between hybrid nanofluid and solid phases.

The analysis of entropy generation under various shear and buoyancy forces plays a significant role in the suitable thermal design and optimization of mixed convective heat transfer applications. This research significantly contributes to the optimization of design and the advancement of innovative solutions across diverse engineering disciplines, such as packed-bed thermal energy storage and thermal insulation.

This study aims to reveal how chief executive officer (CEO) transformational leadership affects business model innovation (BMI) by exploring the serial mediating role of top management team (TMT) collective energy and behavioral integration and the moderating role of TMT-CEO value congruence.

The sample of 520 TMT members from 127 enterprises in North China was collected through a two-wave questionnaire survey. Hierarchical regression and bootstrapping were used to test the hypothetical relationships proposed in this study.

The results indicate that TMT collective energy and behavioral integration play a serial mediation role between CEO transformational leadership and BMI. TMT-CEO value congruence positively moderates the relationship between CEO transformational leadership and TMT collective energy as well as the serial mediation effect.

The results suggest that CEOs can stimulate TMT collective energy by demonstrating transformational leadership behaviors, thereby promoting TMT behavioral integration and ultimately achieving BMI. In addition, to enhance the effectiveness of CEO transformational leadership, enterprises should take measures to ensure that TMT members hold values that are consistent with those of CEOs.

Based on social cognitive theory, the mediating mechanism and boundary conditions of CEO transformational leadership that affect BMI are revealed by this study, thus opening the “black box” of the relationship between the two. It also supplements research on the role of TMT among the antecedents of BMI.

The purpose of this study is to investigate the impact of the construction and operation of underground gas storage (UGS) facilities, under the prism of the recent rise in energy prices. The focus is on developing energy markets interconnected with gas producers through pipelines and has access to liquefied natural gas (LNG) facilities in parallel.

Through a focal market in Europe, the authors estimate the economic value for both stakeholders and consumers by introducing a methodology, appropriately adjusted to the specificities of the domestic energy market. The Transmission System Operator, the Energy Market Regulator, the Energy Exchange and Eurostat are the main data sources for our calculations and conclusions.

The authors investigate the perspectives of UGS facilities, identifying financial challenges considering specific energy market conditions which are barriers to new storage facilities. Nevertheless, the energy price rocketing coupled with the security of gas supply issues, which arose in autumn 2021 and were continuing in 2022 due to the Russia–Ukraine crisis, highlight that gas storage remains, at least for the midterm, at the core of European priorities.

The paper emphasizes on developing markets toward green transition, proposing tangible policy recommendations regarding gas storage. A new methodological approach is proposed, appropriate to quantify the economic value of UGSs in such markets. Last, a mix of energy policy options is suggested which include regulatory reforms, support schemes and new energy infrastructures that could make the gas storage investments economically viable.

This study is a targeted review of some of the major changes in European regulation that guided energy policy decisions in the Iberian Peninsula and how they may have aggravated the problem of lack of flexibility. This study aims to assess some of the proposed short-term solutions to address this issue considering the underlying root causes and suggests a different course of action, that in turn, could help alleviate future market strains.

The evolution of the most important (macro) energy and price-related variables in both Portugal and Spain is assessed using market and grid operator data. In addition, the authors present critical viewpoints on some of the most recent EU and national regulation changes (official document analysis).

The Iberian energy policy and regulatory agenda has successfully promoted a rapid adoption of renewables (main goal), although with insufficient diversification of generation technologies. The compulsory closings of thermal plants and an increased tax (mainly carbon) added pressure toward more environmentally friendly thermal power plants. However, inevitably, this curbed the bidding price competitiveness of these producers in an already challenging market framework. Moving forward, decisions must be based on “a bigger picture” that does not neglect system flexibility and security of supply and understands the specificities of the Iberian market and its generation portfolio.

This work provides an original account of unprecedented spikes in energy prices in 2021, specifically in the Iberian electricity market. This acute situation worries consumers, industry and governments. Underlining the instability of the market prices, for the first time, this study discusses how some of the most important regulatory changes, and their perception and absorption by involved parties, contributed to the current environment. In addition, this study stresses that if flexibility is overlooked, the overall purpose of having an affordable and reliable system is at risk.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

The UAE is among the fastest-growing facilities management (FM) markets globally. Nevertheless, conclusive evidence on this market is scarce in the literature. Therefore, this paper aims to provide an in-depth insight into the FM market in the UAE.

Fourteen interviewees were purposively selected to provide insight into FM status through their field experiences. A SWOT analysis of their answers held place.

Interviewees revealed that the main trends of FM in the UAE include interests in sustainability, integration of technology, health and safety, outsourcing FM, switching to total facilities management (TFM), and performance management systems use. Besides, the quality of the service in the FM market is driven by the real-estate boom, services sophistication, the increasing awareness of FM and focus on the quality of services. Furthermore, the interviews found that the recruitment of poorly skilled labors can threaten the FM market to meet the allocated budget, misperception of FM, the value of money, the lack of continuous follow-up with recent advancements in technologies and the lack of performance measurement models.

This paper highlights the major trends, drivers and threats of the FM market in the UAE, and the implications of its findings can direct FM organizations and researchers in their practices.

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.