Search results

Tip leakage vortex flow (TLV) is a common flow phenomenon in the axial-flow hydraulic machinery. High-efficiency simulation of TLV is still not an easy task because of the complex turbulent vortex-cavitation interactions. As an important basis of CFD, turbulence model directly affects the efficient computation of TLV. The purpose of this paper is to evaluate the newly developed MST turbulence model in predicting the TLV flows.

By using the MST turbulence model and the ZGB cavitation model, numerical simulations of the TLV generated by a NACA0009 hydrofoil were performed under the cavitation-free and cavitation conditions, and the results were compared with the available experimental data.

The important features of TLV are well captured by the MST-based simulation scheme, and the problem of under-predicting the cavitating TLV tube is well solved. Turbulent viscosity is reasonably adjusted in the TLV core regions, and the LES-like mode is activated, which is beneficial to obtain more turbulent information on the same URANS grids. The requirements of grid size and time step of the MST model are much lower than that of the LES method, thereby weighing a good balance between the simulation accuracy and computation cost.

The MST turbulence model is suitable for the high-efficiency simulation of the TLV flows, which can lay a good foundation for efficient engineering computations of the cavitating TLV in the axial-flow hydraulic machinery.

This study aims to investigate the morphing concepts able to manipulate the dynamics of the downstream unsteadiness in the separated shear layers and, in the wake, be able to modify the upstream shock–boundary layer interaction (SBLI) around an A320 morphing prototype to control these instabilities, with emphasis to the attenuation or even suppression of the transonic buffet. The modification of the aerodynamic performances according to a large parametric study carried out at Reynolds number of 4.5 × 10⁶, Mach number of 0.78 and various angles of attack in the range of (0, 2.4)° according to two morphing concepts (travelling waves and trailing edge vibration) are discussed, and the final benefits in aerodynamic performance increase are evaluated.

This article examines through high fidelity (Hi-Fi) numerical simulation the effects of the trailing edge (TE) actuation and of travelling waves along a specific area of the suction side starting from practically the most downstream position of the shock wave motion according to the buffet and extending up to nearly the TE. The present paper studies through spectral analysis the coherent structures development in the near wake and the comparison of the aerodynamic forces to the non-actuated case. Thus, the physical mechanisms of the morphing leading to the increase of the lift-to-drag ratio and the drag and noise sources reduction are identified.

This study investigates the influence of shear-layer and near-wake vortices on the SBLI around an A320 aerofoil and attenuation of the related instabilities thanks to novel morphing: travelling waves generated along the suction side and trailing-edge vibration. A drag reduction of 14% and a lift-to-drag increase in the order of 8% are obtained. The morphing has shown a lift increase in the range of (1.8, 2.5)% for angle of attack of 1.8° and 2.4°, where a significant lift increase of 7.7% is obtained for the angle of incidence of 0° with a drag reduction of 3.66% yielding an aerodynamic efficiency of 11.8%.

This paper presents results of morphing A320 aerofoil, with a chord of 70cm and subjected to two actuation kinds, original in the state of the art at M = 0.78 and Re = 4.5 million. These Hi-Fi simulations are rather rare; a majority of existing ones concern smaller dimensions. This study showed for the first time a modified buffet mode, displaying periodic high-lift “plateaus” interspersed by shorter lift-decrease intervals. Through trailing-edge vibration, this pattern is modified towards a sinusoidal-like buffet, with a considerable amplitude decrease. Lock-in of buffet frequency to the actuation is obtained, leading to this amplitude reduction and a drastic aerodynamic performance increase.

COVID-19 evolved from a local health crisis to a pandemic and affected countries worldwide accordingly. Similarly, the impacts of the pandemic on the performance of global stock markets could be time-varying. This study applies a dynamic network analysis approaches to evaluate the evolution over time of the impact of COVID-19 on the stock markets' network.

Daily closing prices of 55 global stock markets from August 1, 2019 to September 10, 2020 were retrieved. This sample period was further divided into nine subsample periods for dynamic analysis purpose. Distance matrix based on long-range correlations was calculated, using rolling window's length of 100 trading days, rolled forward at an interval of one month's working days. These distance matrices than used to construct nine minimum spanning trees (MSTs). Network characteristics were figured out, community detection and network rewiring techniques were also used for extracting meaningful from these MSTs.

The findings are, with the evolution of COVID-19, a change in co-movements amongst stock markets' indices occurred. On the 100th day from the date of reporting of the first cluster of cases, the co-movement amongst the stock markets become 100% positively correlated. However, the international investor can still get better portfolio performance with such temporal correlation structure either avoiding risk or pursuing profits. A little change is observed in the importance of authoritative node; however, this central node changed multiple times with change of epicenters. During COVID-19 substantial clustering and less stable network structure is observed.

It is confirmed that this work is original and has been neither published elsewhere, nor it is currently under consideration for publication elsewhere.

The stock market is vulnerable to various exogenous factors, and its fluctuations can reflect the effects of political, economic and market factors. The purpose of this paper is therefore to choose the stock market as a representative to analyze the potential impact of the Brexit event on global financial markets and how to prevent the spread of risks across global financial markets.

This study chooses the auto-regressive moving average generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model to fit the financial series and uses it as the marginal distribution model to establish the vine copula model. The maximum spanning tree algorithm is used to select the optimal rattan structure model and pair-copula function. According to the final ARMA-GARCH-R-vine copula model, the tail correlation coefficients of the UK, France, Germany, USA and China stock markets are calculated and used to analyze their dependence structure.

The negative impact of the Brexit event on the British stock market is greater and is more likely to be transmitted to France and Germany. China and the USA are less likely to be impacted by the Brexit incident. The US financial market is more closely linked to France, and it may benefit from the Brexit incident due to the impact of the exchange rate. Although the Chinese stock market is directly connected to the British stock market, due to the existence of national macro-controls and other factors, it will be less affected by the Brexit incident. The main impact comes from the dual devaluation pressure on the RMB.

This paper selects the optimal combination model based on actual data, and the results obtained can accurately reflect the interdependence between relevant stock markets and can guide risk aversion in the financial investment field.

Drawn on self-determination (SDT) and social cognitive theory (SCT), this study examines how participative leadership (PL) influences the creative process engagement of followers (CPE) on fostering followers' radical creativity (FRC) through the supervisor support for creativity (SSC). It also demonstrates the CPE as a cognitive mediator between PL and FRC and SSC as a behavioral moderator between PL and CPE in Asia's manufacturing settings.

The research is quantitative, and data are gathered using a questionnaire and a survey of Bangladesh's 252 textile and apparel industry respondents. SPSS 26 and SMART PLS 3.8 evaluated the measurement and structural models and other descriptive analyses for hypothesis testing and result confirmation.

The findings revealed that PL positively impacted followers' creative process engagement. Again, the CPE of followers was used to mediate PL and FRC to promote and determine radical creativity. Moreover, the research also found a substantial correlation between PL and the creative process involved in supervisor support for creativity, which increases followers' radical creativity.

This study contributes to the current literature by extending the scope of PL, CPE, FRC, SDT and SCT theory incorporating supervisor support.

The findings showed that textile and apparel industry managers, leaders and practitioners could use participatory leadership to engage in collaborative leader-follower creativity goal setting, creativity-relevant thinking and talent flourishing to encourage and motivate creativity through supervisor support to followers to foster radical creativity.

The results demonstrate the colloquial expression in behavioral mechanism (creative process engagement) nurtured with the cognitive tool, shedding insight into the link between PL and radical creativity in followers (SSC for promoting radical creativity).

This paper aims to analyze the dependence structure between the Green Sukuk Spread in Malaysia and uncertainty factors from January 1, 2017, to May 23, 2023, covering two main periods: the pre-COVID-19 and the COVID-19 periods.

This study contributes to the current literature by explicitly modeling nonlinear dependencies using the Regular vine copula approach to capture asymmetric characteristics of the tail dependence distribution. This study used the Archimedean copula models: Student’s-t, Gumbel, Gaussian, Clayton, Frank and Joe, which exhibit different tail dependence structures.

The empirical results suggest that Green Sukuk and various uncertainty variables have the strongest co-dependency before and during the COVID-19 crisis. Due to external uncertainties (COVID-19), the results reveal that global factors, such as the Infect-EMV-index and the higher financial stress index, significantly affect the spread of Green Sukuk. Interestingly, in times of COVID-19, its dependence on Green Sukuk and the news sentiment seems to be a symmetric tail dependence with a Student’s-t copula. This result is relevant for hedging strategies, as investors can enhance the performance of their portfolio during the COVID-19 crash period.

This study contributes to a better understanding of the dependency structure between Green Sukuk and uncertainty factors. It is relevant for market participants seeking to improve their risk management for Green Sukuk.

Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.

In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.

The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.

This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.

The purpose of this paper is to delve into an extensive analysis of different food crops, ranging from bananas, beans, brinjals, cabbages, chillies, creepers, groundnuts, mixed vegetables, pineapples and tomatoes, over three decades. To maintain an ever-increasing population level, much stress is exerted on the production of food crops. However, till date, very little is known about how climate change is influencing the production of food crops in Mauritius, an upper-income developing country found in the Indian Ocean and highly vulnerable to climate risks.

Based on the interactions between production of crops, harvest area for crops and weather metrics, a vector autoregressive model (VAR) system is applied comprising production of each crop with their respective harvest area. Weather metrics are then entered into as exogeneous components of the model. The underlying rationale is that weather metrics are not caused by production or harvest area and should thereby be exogeneously treated. Should there be cointegration between the endogenous components, the vector error correction model (VECM) will be used. Diagnostic tests will also be entertained in terms of ensuring the endogeneity states of the presumed variables under investigation. The impact of harvest area on product is plain, as higher the harvest area, the higher is the production. However, a bi-directional causality can also manifest in the case that higher production leads towards lower harvest area in the next period as land is being made to rest to restore its nutrients to enable stable land productivity over time. Other dynamics could also be present. In case cointegration prevails, VECM will be used as the econometric model. The VAR/VECM approach is applied by virtue of the fact that traditional ordinary least squares (OLS) estimation approach will be biased and susceptible to trigger off unreliable results. Recourse is made towards the Johansen and Juselius (1990) technique. The Johansen and Juselius approach is based on the following VAR specification-bivariate VAR methodology. X1,t = A0 + A1,1X1,t – 1 + A1,2X1,t – 2+ […] .+ A1,p X1,t – p + A2,1X2,t – 1 + A2,2X2,t – 2+ […] .+ A2,pX2,t – p + ßjW + e1,t […] […]..(1) X2,t = B0 + B2,1X2,t – 1 + B2,2X2,t – 2+ […] .+ B2,p X2,t – p + B1,1X1,t – 1 + B1,2X2,t – 2+ […] .+ B1,pX2,t – p + ajW + e2,t […] […] […](2) X1,t is defined as the food crops production, while X2,t pertains to harvest area under cultivation for a given crop under consideration, both constituting the endogeneous components of the VAR. The exogeneous component is captured by W which consists of the nine aforementioned weather metrics, including the cyclone dummy. The subscript j under equation (1) and (2) captures these nine distinct weather metrics. In essence, the aim of this paper is to develop an econometric-based approach to sieve out the impacts of climate metrics on food crops production in Mauritius over three decades.

Results show weather metrics do influence the production of crops in Mauritius, with cyclone being particularly harmful for tomatoes, chillies and creepers. Temperature is found to trail behind bearish impacts on tomatoes and cabbages production, but positive impacts in case of bananas, brinjals and pineapples productions, whereas humidity enhances production of beans, creepers and groundnuts. Evidence is found in favour of production being mainly governed by harvest area. Overall, the study points out the need of weather derivatives in view of hedging against crop damages, let alone initiation of adaptation strategies to undermine the adverse effects of climate change.

To the best of the author’s knowledge, no study has been undertaken in Mauritius, let alone developing of an econometric model that properly integrates production, harvest area and weather metrics. Results show weather metrics do influence the production of crops in Mauritius, with cyclone being particularly harmful for tomatoes, chillies and creepers. Temperature is found to trail behind bearish impacts on tomatoes and cabbages production, but positive impacts in case of bananas, brinjals and pineapples productions, whereas humidity enhances production of beans, creepers and groundnuts. Evidence is found in favour of production being mainly governed by harvest area. Overall, the study points out the need of weather derivatives in view of hedging against crop damages, let alone initiation of adaptation strategies to undermine the adverse effects of climate change.

This study aims to obtain diamond-coated mechanical seals with improved sealing performance and considerable cost. To achieve this purpose, the study focuses on depositing uniform, wear-resistant and easily polished diamond coatings on massive mechanical seals in a large-scale vacuum chamber.

The computational fluid dynamics simulation test and its corresponding deposition experiment are carried out to improve the uniformity of diamond films on massive mechanical seals. The polishing properties and sealing performance of mechanical seals coated with three different diamond films (microcrystalline diamond [MCD], nanocrystalline diamond [NCD] and microcrystalline/nanocrystalline diamond [MNCD]) and uncoated mechanical seals are comparatively studied using the polishing tests and dynamic seal tests to obtain the optimized diamond coating type on the mechanical seals.

The substrate rotation and four gas outlets distribution are helpful for depositing uniform diamond coatings on massive mechanical seals. The MNCD-coated mechanical seal shows the advantages of high polishing efficiency in the initial polishing process and excellent wear resistance and self-lubrication property in the follow-up polishing period because of its unique composite diamond film structures. The MNCD-coated mechanical seal shows the longest working life under dry friction condition, about 14, 1.27 and 1.9 times of that for the uncoated, MCD and NCD coated mechanical seals, respectively.

The effect of substrate rotation and gas outlets distribution on temperature and gas flow field during diamond deposition procedure is simulated. The MNCD-coated mechanical seal exhibits a superior sealing performance compared with the MCD-coated, NCD-coated and uncoated mechanical seals, which is helpful for decreasing the operating system shut-down frequency and saving operating energy consumption.

The paper aims to present an idea of automatic control algorithms dedicated to both small manned and unmanned aircraft, capable to perform spin maneuver automatically. This is a case of maneuver far away from so-called standard flight. The character of this maneuver and the range of aircraft flight parameters changes restrict application of standard control algorithms. Possibility of acquisition full information about aircraft flight parameters is limited as well in such cases. This paper analyses an alternative solution that can be applied in some specific cases.

The paper uses theoretical discussion and breakdowns to create basics for development of structures of control algorithms. Simplified analytical approach was applied to tune regulators. Results of research were verified in series of software-in-the loop, computer simulations.

The structure of the control system enabling aerobatic flight (spin flight as example selected) was found and the method how to tune regulators was presented as well.

It could be a fundament for autopilots working in non-conventional flight states and aircraft automatic recovery systems.

The paper presents author’s original approach to aircraft automatic control when high control precision is not the priority, and not all flight parameters can be precisely measured.