Search results

This study aims to analyse the non-linear losses of a porous media (stack) composed by parallel plates and inserted in a resonator tube in oscillatory flows by proposing numerical correlations between pressure gradient and velocity.

The numerical correlations origin from computational fluid dynamics simulations, conducted at the microscopic scale, in which three fluid channels representing the porous media are taken into account. More specifically, for a specific frequency and stack porosity, the oscillating pressure input is varied, and the velocity and the pressure-drop are post-processed in the frequency domain (Fast Fourier Transform analysis).

It emerges that the viscous component of pressure drop follows a quadratic trend with respect to velocity inside the stack, while the inertial component is linear also at high-velocity regimes. Furthermore, the non-linear coefficient b of the correlation ax + bx² (related to the Forchheimer coefficient) is discovered to be dependent on frequency. The largest value of the b is found at low frequencies as the fluid particle displacement is comparable to the stack length. Furthermore, the lower the porosity the higher the Forchheimer term because the velocity gradients at the stack geometrical discontinuities are more pronounced.

The main novelty of this work is that, for the first time, non-linear losses of a parallel plate stack are investigated from a macroscopic point of view and summarised into a non-linear correlation, similar to the steady-state and well-known Darcy–Forchheimer law. The main difference is that it considers the frequency dependence of both Darcy and Forchheimer terms. The results can be used to enhance the analysis and design of thermoacoustic devices, which use the kind of stacks studied in the present work.

This paper aims to investigate the relationship between the impact of COVID-19 on the performance of financial managers of medium and large companies.

This research used the data of 173 listed large and over-the-counter as medium-size companies from 2018 to 2021. The results of these tests have been analyzed using panel data and STATA 15 software.

The results showed that COVID-19 has no significant relationship with the return on equity in large and medium-size companies. This variable does not significantly affect Tobin’s Q index in medium-size companies either. Other financial indicators examined in this research have decreased considerably in all companies under the influence of COVID-19. Still, the intensity of this effect is different in large and medium-size companies. Funds from borrowings and Tobin’s Q ratios in medium-size companies compared with large companies have been more severely affected by the COVID-19 disease; the return on assets, book value to market value and large companies compared with medium-size companies have been more severely and significantly affected by COVID-19; and financing funds through the issuance of shares in large companies and medium-size companies have been affected by COVID-19 almost equally.

Despite the studies related to financial crises and their effect on the performance of companies, no research has examined the financial performance indicators during the outbreak of COVID-19 in large and small companies. Therefore, the results of this research can affect different groups: financial managers and the board of directors of companies to better understand the impact of the corona disease on the company’s performance; investors benefit from research results in line with investment decisions; developing theory and educational topics for the benefit of students and studying and conducting more experimental research in this regard; and the stock exchange organization and regulatory and support institutions need to find out the depth of the disaster and the effect of COVID-19 on the performance of companies.

To date, there are no studies in the literature that provide a comprehensive understanding of the interrelationships between the slenderness ratio and the main design criteria in supertall towers (=300 m). In this paper, this important issue was explored using detailed data collected from 75 cases.

This paper was carried out with a comprehensive literature review including the database of the Council on Tall Buildings and Urban Habitat(CTBUH) (CTBUH, 2022), peer-reviewed journals, MSc theses and PhD dissertations, conference proceedings, fact sheets, architectural and structural magazines and other Internet sources. In this study, the case study method was also used to gather and consolidate information about supertall towers to analyze the interrelationships. Cases were 75 supertall buildings in various countries [44 from Asia (37 from China), 16 from the Middle East (6 from Dubai, the United Arab Emirates), 11 from the United States of America and 3 from Russia, 1 from the UK].

The paper's findings highlighted as follows: (1) for buildings in the height range of 300–399 m, the slenderness ratio was usually between 7 and 7.9 and megatall towers were frequently built at a slenderness ratio of 10–15; (2) the median slenderness ratio of buildings in the 400–599 m height ranges was around 8.6; (3) a trend towards supertall slender buildings (=8) was observed in Asia, the Middle East and North America; (4) residential, office and mixed-use towers had a median slenderness ratio of over 7.5; (5) all building forms were utilized in the construction of slender towers (>8); (6) the medium slenderness ratio was around 8 for supertall buildings constructed with outriggered frame and tube systems; (7) especially concrete towers reached values pushing the limits of slenderness (>10) and (8) since the number of some supertall building groups (e.g. steel towers) was not sufficient, establishing a scientific relationship between aspect ratio and related design criteria was not possible.

To date, there are no studies in the literature that provide a comprehensive understanding of the interrelationships between the slenderness ratio and the main design criteria in supertall towers (=300 m). This important issue was explored using detailed data collected from 75 cases.

Spaciousness is defined as “the feeling of openness or room to wander” that has been affected by various physical factors. The purpose of this paper is to assess the spaciousness of space to determine how spacious the space is. Furthermore, the study intends to propose a fuzzy-based model to assess the degree of spaciousness in terms of physical parameters such as area, proportion, the ratio of window area to floor area and color value.

Fuzzy logic is the most appropriate mathematical model to assess uncertainty using nonhomogeneous variables. In contrast to conventional methods, fuzzy logic depends on partial truth theory. MATLAB Fuzzy Logic Toolbox was used as a computational model including a fuzzy inference system (FIS) using linguistic variables called membership functions to define parameters. As a result, fuzzy logic was used in this study to assess the spaciousness degree of design studios in universities in the Iraqi Kurdistan region.

The findings of the presented fuzzy model show the degree to which the input variables affect a space perceived as larger and more spacious. The relationship between parameters has been represented in three-dimensional surface diagrams. The positive relationship of spaciousness with the area, window-to-floor area ratio and color value has been determined. In contrast, the negative relationship between spaciousness and space proportion is described. Moreover, the three-dimensional surface diagram illustrates how the changes in the input values affect the spaciousness degree. Besides, the improvement in the spaciousness degree of the design studio increases the quality learning environment.

This study attempted to assess the degree of spaciousness in design studios. There has been no attempt carried out to combine educational space learning environments and computational methods. This study focused on the assessment of spaciousness using the MATLAB Fuzzy Logic toolbox that has not been integrated so far.

This study aims to investigate the influence of wall curvature in a semicircular thermal annular system on magneto-nanofluidic flow, heat transfer and entropy generation. The analysis is conducted under constant cooling surface and fluid volume constraints.

The mathematical equations describing the thermo-fluid flow in the semicircular system are solved using the finite element technique. Four different heating wall configurations are considered, varying the undulation numbers of the heated wall. Parametric variations of bottom wall undulation (f), buoyancy force characterized by the Rayleigh number (Ra), magnetic field strength represented by the Hartmann number (Ha) and inclination of the magnetic field (γ) on the overall thermal performance are studied extensively.

This study reveals that the fluid circulation strength is maximum in the case of a flat bottom wall. The analysis shows that the bottom wall contour and other control parameters significantly influence fluid flow, entropy production and heat transfer. The modified heated wall with a single undulation exhibits the highest entropy production and thermal convection, leading to a heat transfer enhancement of up to 21.85% compared to a flat bottom. The magnetic field intensity and orientation have a significant effect on heat transfer and irreversibility production.

Further research can explore a wider range of parameter values, alternative heating wall profiles and boundary conditions to expand the understanding of magneto-nanofluidic flow in semicircular thermal systems.

This study introduces a constraint-based analysis of magneto-nanofluidic thermal behavior in a complex semicircular thermal system, providing insights into the impact of wall curvature on heat transfer performance. The findings contribute to the design and optimization of thermal systems in various applications.

This paper analyzes real and welfare effects of a permanent change in inflation rate, focusing on macroprudential policy’ role and its interaction with monetary policy.

While investigating disinflation costs, the authors simulate a medium-scale dynamic general equilibrium model with borrowing constraints, credit frictions and macroprudential authority.

Providing discussions on different policy scenarios in a context where still it is expected high inflation, there are three key contributions. First, when macroprudential authority actively operates to improve financial stability, losses caused by disinflation are limited. Second, a Taylor rule directly responding to financial variables might entail a trade-off between price and financial stability objectives, by increasing disinflation costs. Third, disinflation is welfare improving for savers, while costly for borrowers and banks. Indeed, while savers benefit from policies reducing price stickiness distortion, borrowers are worried about credit frictions, coming from collateral constraint.

The paper suggests threefold policy implications: the macroprudential authority should actively intervene during a disinflation process to minimize costs and financial instability deriving from it; policymakers should implement a disinflationary policy stabilizing also output; the central bank and the macroprudential regulator should pursue financial and price stability goals, separately.

This paper is the first attempt to study effects of a permanent inflation target reduction in focusing on the macroprudential policy’ role.

Tehran’s health-care system is growing, yet it lacks emergency planning procedures. The premise of this study is that the urban environment around a hospital is just as robust as the hospital itself. This study aims to look at hospital resilience in an urban setting to see where it may be improved to keep the hospital operational during a disaster.

The urban resilience (UR) of Amir-Alam Hospital was analyzed in this study using a customized version of the United Nations Office for Disaster Risk Reduction’s City Resilience Profiling Tool. The 34 indications were broken down into five categories.

The result revealed that the hospital’s UR score was 51.75 out of 100, indicating medium resilience. The results of this study enable the decision-makers to determine what measures they may take to improve the hospital’s resilience in terms of its surrounding urban context.

The originality of this research is based on the surrounding urban environment’s resilience as an integral part of hospital resilience.

The present work focuses on evaluating the physical and mechanical characteristics of geopolymer concrete (GPC) by replacing the sodium silicate waste (SSW) in place of traditional river sand. The aim is to create eco-friendly concrete that mitigates the depletion of conventional river sand and conserves natural resources. Additionally, the study seeks to explore how the moisture content of filler materials affects the performance of GPC.

SSW obtained from the sodium silicate industry was used as filler material in the production of GPC, which was cured at ambient temperature. Instead of the typical conventional river sand, SSW was substituted at 25 and 50% of its weight. Three distinct moisture conditions were applied to both river sand and SSW. These conditions were classified as oven dry (OD), air dry (AD) and saturated surface dry (SSD).

As the proportion of SSW increased, there was a decrease in the slump of the GPC. The setting time was significantly affected by the higher percentage of SSW. The presence of angular-shaped SSW particles notably improved the compressive strength of GPC when replacing a portion of the river sand with SSW. When exposed to elevated temperatures, the performance of the GPC with SSW exhibited similar behavior to that of the mix containing conventional river sand, but it demonstrated a lower residual strength following exposure to elevated temperatures.

Exploring the possible utilization of SSW as a substitute for river sand in GPC, and its effects on the performance of the proposed mix. Analyzing, how varying moisture conditions affect the performance of GPC containing SSW. Evaluating the response of the GPC with SSW exposed to elevated temperatures in contrast to conventional river sand.

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

Customer experience management (CXM), which aims to achieve and maintain customers' long-term loyalty, has attracted the attention of many organizations. Improving customer experience management in organizations requires that, first, their relevant capabilities be evaluated. The present study aimed to offer a set of key performance indicators for evaluating customer experience management in commercial banks.

The study, first, attempted to identify the components of evaluating customer experience management by reviewing the related literature and conducting interviews with experts. Then, the extracted components were transformed into assessable metrics using the goal question metric method, and the key performance indicators relevant to customer experience management in commercial banks were selected according to the experts' opinions and the Fuzzy Delphi method.

According to the findings of the study, 21 key performance indicators were identified for customer experience management in commercial banks, and customer satisfaction, the mean number of calls to resolve an issue in customer journey touchpoints, the NPS, and the ratio of the budget allocated to the CXM department to the budget of the marketing department were found as the most significant performance indicator according to banking experts.

The present study was among the first research projects intended to evaluate CXM and offer key performance indicators that could help the managers of commercial banks assess the maturity levels of their CXM.