Search Results (25)

Based on admirable porous media performance and the popularity of additive manufacturing technology, gradient porous media are progressively being applied in increasing fields. In this study, convection heat transfer within a square vented cavity, partially occupied by two copper metal foam layers of $10$ and $20$ PPI saturated with nanofluid, was assessed numerically. The left wall was heated uniformly and non-uniformly by applying multi-frequency spatial heating following a sinusoidal function. Governing equations, including continuity, the Darcy–Brinkmann–Forchheimer model, and local thermal non-equilibrium energy equations, were adopted and solved by employing the finite volume method. The influences of relevant parameters, including nanoparticle concentrations $\left(0\%\le \phi \le 10\%\right)$, Reynolds number ($1\le Re\le 100$), inlet and outlet port aspect ratios $\left(0.1\le D/H\le 0.4\right)$, three outlet vent opening locations ($\left(S_o=0\right)$ left, ($S_o=\left(H/2-D/2\right)$) middle, and ($S_o=\left(H-D\right)$) right), sinusoidal offset temperature (${\theta }_o=0.5$, $1$), frequency ($f=1, 3, 5$), and amplitude ($A=0-1$), were examined. The results demonstrate that flow and heat transfer fields are impacted mainly by these parameters. Streamlines are more intensified at the upper-left corner when the outlet opening vent is shifted towards the right-corner upper wall. Fluid- and solid-phase Nusselt number increases $Re$, $D/H$, ${\theta }_o$, $A$, and $f$ are raised, specifically when $A\ge 0.3$. The Nusselt number remains constant when the frequency is raised from $3$ to $5$, definitely when $D/H\ge 0.25$. In uniform and non-uniform heating cases, the Nusselt number of both phases remains constant as the outlet port is shifted right for $Re\le 10$ and slightly for higher $Re$ as the outlet vent location is translated from left to right. Full article

This study focuses on the effect of window openings on the seismic performance of the stone walls of Tibetan and Qiang dwellings. A typical stone wall of a Tibetan and Qiang dwelling constructed using irregular stone and yellow mud masonry in Li County, Sichuan Province, was chosen as a prototype, and two stone walls with different structural window openings were designed for proposed static tests and microscopic electron microscope scanning (SEM), which obtained the damage patterns and microscopic damage mechanisms of the walls and analyzed them in comparison with the test results of the stone walls without window openings. At the same time, a finite element model was established based on the test parameters to study the effects of opening size, shape, and aspect ratio on the seismic performance of the stone walls of Tibetan and Qiang dwellings. The findings indicate that “X”-shaped cracks at the corners of the window openings and extending to the surrounding areas are the primary damage characteristics. The unique microstructure of yellow clay and schist leads to the faster appearance of wall cracks. The peak load, stiffness, and energy dissipation of the windowed walls were less than those of the windowless walls. It was found through simulation that the seismic performance of the wall decreases with the increase in the opening size; as the wall’s openings take on different shapes, the ultimate bearing capacity steadily declines with the order of circular, square, triangular, trapezoidal, and rectangular; and under a range of aspect ratios, the wall’s seismic performance is best when the opening’s aspect ratio is 1:1. The research results of this paper are of reference value for the research, design, and construction of stone walls and other non-engineered masonry works of Tibetan and Qiang dwellings. Full article

The stochastic Green’s function method has been widely used in the field of ground motion simulation in recent years. It is generally assumed that the rise time of each subfault is the same in this method. Since the rise time significantly influences the amplitude of simulation results in the intermediate frequency band, to improve the accuracy of stochastic Green’s function method for near-fault broadband ground motion simulation, referring to the numerical simulation results of Day, the rise time is assumed to be non-uniformly distributed on the fault, and an improved approximate expression of rise time on a rectangular fault considering that the rupture starting point may be at any position and the aspect ratio may be arbitrary is proposed. Additionally, the contributions of P, SV and SH wave are considered, respectively, and an improved stochastic Green’s function method is proposed for 3D broadband ground motion simulation. Taking the 1994 Northridge earthquake in America and 2013 Lushan earthquake in China as examples, under different subfault division numbers, the synthesized source spectra are compared with the omega-squared theoretical source spectra of the large earthquake, and the simulated ground motions at observation points are compared with observed records to verify the effectiveness of the improved method. The results show that when the Northridge earthquake fault and Lushan earthquake fault are divided into 9 × 10 subfaults and 11 × 7 subfaults, respectively, the simulation results obtained using the improved method are close to the observed records in the broadband frequency range. Therefore, the improved method can effectively simulate the 3D ground motion in near-fault regions. Full article

The rise of straintronics—the possibility of fine-tuning the electronic properties of nanosystems by applying strain to them—has enhanced the interest in characterizing the mechanical properties of these systems when they are subjected to tensile (or compressive), shear and torsion strains. Four parameters are customarily used to describe the mechanical behavior of a macroscopic solid within the elastic regime: Young’s and shear moduli, the torsion constant and Poisson’s ratio. There are some relations among these quantities valid for elastic continuous isotropic systems that are being used for 2D nanocrystals without taking into account the non-continuous anisotropic nature of these systems. We present in this work computational results on the mechanical properties of six small quasi-square (aspect ratio between 0.9 and 1.1) graphene nanocrystals using the PM7 semiempirical method. We use the results obtained to test the validity of two relations derived for macroscopic homogeneous isotropic systems and sometimes applied to 2D systems. We show they are not suitable for these nanostructures and pinpoint the origin of some discrepancies in the elastic properties and effective thicknesses reported in the literature. In an attempt to recover one of these formulas, we introduce an effective torsional thickness for graphene analogous to the effective bending thickness found in the literature. Our results could be useful for fitting interatomic potentials in molecular mechanics or molecular dynamics models for finite carbon nanostructures, especially near their edges and for twisted systems. Full article

Urban canopy parameters (UCPs) are parameters which are utilized to define the thermal, radiative, and roughness properties of urban areas, which have a significant impact on the urban microclimate. The rapidly growing urbanization, especially in developing regions, leads to the modification of urban geometry, which calls for the characterization of UCPs in the countries of such regions to account for high population pressure, heterogeneous urban environments, and the subsequent impacts on global climate change. A research study conducted in Delhi, India, found that very-high-resolution (VHR) optical satellite stereo datasets provide reasonable accuracy with respect to the extraction of building heights and footprints, which are further employed for the computation of UCPs. However, the study evaluates only the key input parameters due to the non-availability of the 3D geodatabase. Hence, in this study, an attempt has been made to evaluate all UCPs derived from VHR optical stereo data, along with the key input parameters, against reference data collected from the field in the city of Bhubaneshwar, India. Performance evaluation with reference-data-derived UCPs shows that all the UCPs retrieved from VHR optical stereo data have a high prediction accuracy. Overall bias, overall mean absolute error (MAE), and root mean square error (RMSE) from satellite-derived UCPs were found to be better than 1 m for most of the UCPs, except for building-surface-area-to-plan-area ratio, height-to-width ratio, and complete aspect ratio, which were found to be less than 2.7 m. The correlation coefficient values were also observed to be more than 0.7 for most of the UCPs, except plan area density, roughness length, and frontal area density. This study concludes that UCPs derived from VHR optical stereo data have high accuracy, even in the low-to-medium-rise urban environments of the study area. The study has a high potential to be replicated in countries in developing regions which have similar development characteristics and face resource and policy constraints with respect to the availability of airborne LiDAR and SAR data. Full article

In the current study we have obtained Co₂FeSi glass-coated microwires with different geometrical aspect ratios, ρ = d/D_tot (diameter of metallic nucleus, d and total diameter, D_tot). The structure and magnetic properties are investigated at a wide range of temperatures. XRD analysis illustrates a notable change in the microstructure by increasing the aspect ratio of Co₂FeSi-glass-coated microwires. The amorphous structure is detected for the sample with the lowest aspect ratio (ρ = 0.23), whereas a growth of crystalline structure is observed in the other samples (aspect ratio ρ = 0.30 and 0.43). This change in the microstructure properties correlates with dramatic changing in magnetic properties. For the sample with the lowest ρ-ratio, non-perfect square loops are obtained with low normalized remanent magnetization. A notable enhancement in the squareness and coercivity are obtained by increasing ρ-ratio. Changing the internal stresses strongly affects the microstructure, resulting in a complex magnetic reversal process. The thermomagnetic curves show large irreversibility for the Co₂FeSi with low ρ-ratio. Meanwhile, if we increase the ρ-ratio, the sample shows perfect ferromagnetic behavior without irreversibility. The current result illustrates the ability to control the microstructure and magnetic properties of Co₂FeSi glass-coated microwires by changing only their geometric properties without performing any additional heat treatment. The modification of geometric parameters of Co₂FeSi glass-coated microwires allows to obtain microwires that exhibit an unusual magnetization behavior that offers opportunities to understand the phenomena of various types of magnetic domain structures, which is essentially helpful for designing sensing devices based on thermal magnetization switching. Full article

Standard unit operations/equipment have not evolved for the traditional rice varieties of the Cauvery Deltaic region of Tamil Nadu. The fame of traditional rice is increasing nowadays owing to its health benefits. Non-standard unit operations may cause rice grains to crack during milling, accumulating more broken rice and yields in products of inferior quality. As a result, research into the physical properties of rice is crucial for the development of rice processing equipment that minimizes post-harvest losses during milling. Hence, an assessment was made to evaluate 30 traditional rice cultivars on their Physical (grain length, width, thickness, shape, and size), gravimetric (bulk, true, tapped density, porosity, Carr’s index, and Hausner ratio), and engineering characteristics (equivalent, arithmetic, square mean, and geometric mean diameter) using standard protocols, with the goal of reviving and preserving older varieties. The results from the analysis showed significant variations (p < 0.05) between all properties that were evaluated. According to length, a substantial amount of traditional rice varieties were long grain (76.7%), whereas (16.7%) belonged to the medium type and (3.3%) were short-grain types, respectively. There were variations among the three different categories of local rice grains when it comes to size, ranging from 3.26 to 4.69 mm for arithmetic mean diameter, 2.84 to 4.00 mm for geometric mean diameter, and 3.02 to 4.28 mm for square mean diameter, respectively. Sphericity, aspect ratio, and surface area measurements of the samples varied from 37.7% to 81.2%, 0.26 to 1.00, and 25.4 to 50.1 mm², respectively. Of the 30 varieties, 28 were under the high amylose category, and 2 belonged to the intermediate type. The Pearson correlation was established to study the interrelationships between the dimensions and engineering properties. Principal component analysis (PCA) reduced the dimensionality of 540 data into five principal components (PC), which explained 95.7% of the total variance. These findings suggest that it is possible to revive old landraces through careful selection and analysis of these properties. The superior characteristics of these traditional varieties can be further evaluated for breeding programs in order to improve the cultivation of these cherished rice landraces to enhance nutritional security. Full article

With the rapid development of communication technology as well as a rapid rise in the usage of electronic devices, a growth of concerns over unintentional electromagnetic interference emitted by these devices has been witnessed. Pioneer researchers have deeply studied the relationship between the shielding effectiveness and a few mixed design parameters for cementitious composites incoporating carbon fibres by conducting physical experiments. This paper, therefore, aims to develop and propose a series of prediction models for the shielding effectiveness of cementitious composites involving carbon fibres using frequency and mixed design parameters, such as the water-to-cement ratio, fibre content, sand-to-cement ratio and aspect ratio of the fibres. A multi-variable non-linear regression model and a backpropagation neural network (BPNN) model were developed to meet the different accuracy requirements as well as the complexity requirements. The results showed that the regression model reached an R² of 0.88 with a root mean squared error (RMSE) of 2.3 dB for the testing set while the BPNN model had an R² of 0.96 with an RMSE of 2.64 dB. Both models exhibited a sufficient prediction accuracy, and the results also supported that both the regression and the BPNN model are reasonable for such estimation. Full article

This paper emphasizes the effect of applying a rotating magnetic field on the natural convective flow of CNT/Water nanofluid inside a corrugated square cavity differentially heated through its sidewalls, while the upper and lower boundaries are supposed to be perfectly insulated. The aim of this study is to highlight the impact of a large variety of parameters, namely Hartman number, frequency of rotation, Rayleigh number, nanoparticles volume fraction, and corrugation aspect ratio on the flow behaviour and thermal transport characteristics. The governing non-linear coupled differential equations are solved by using the finite element technique. Outcomes indicated that the thermal energy exchange is improved with the Rayleigh number increment and nanoparticles loading, while it is weakened with the rising of Ha, ascribed to the Lorentz force opposition to buoyancy. Moreover, enlarging the corrugation aspect ratio causes the apparition of stagnant fluid zones and the rate of heat transfer is reduced as a result. Full article

The emergence of advanced machine learning or deep learning techniques such as autoencoders and generative adversarial networks, can generate images known as deepfakes, which astonishingly resemble the realistic images. These deepfake images are hard to distinguish from the real images and are being used unethically against famous personalities such as politicians, celebrities, and social workers. Hence, we propose a method to detect these deepfake images using a light weighted convolutional neural network (CNN). Our research is conducted with Deep Fake Detection Challenge (DFDC) full and sample datasets, where we compare the performance of our proposed model with various state-of-the-art pretrained models such as VGG-19, Xception and Inception-ResNet-v2. Furthermore, we perform the experiments with various resolutions maintaining 1:1 and 9:16 aspect ratios, which have not been explored for DFDC datasets by any other groups to date. Thus, the proposed model can flexibly accommodate various resolutions and aspect ratios, without being constrained to a specific resolution or aspect ratio for any type of image classification problem. While most of the reported research is limited to sample or preview DFDC datasets only, we have also attempted the testing on full DFDC datasets and presented the results. Contemplating the fact that the detailed results and resource analysis for various scenarios are provided in this research, the proposed deepfake detection method is anticipated to pave new avenues for deepfake detection research, that engages with DFDC datasets. Full article

In dairy farming, milking-related operations are time-consuming and expensive, but are also directly linked to the farm’s economic profit. Therefore, reducing the duration of milking operations without harming the cows is paramount. This study aimed to test the variation in different parameters of milking operations on non-automatic milking machines to evaluate their effect on a herd and finally reduce the milking time. Two trials were set up on a dairy farm in Northern Italy to explore the influence of the pulsation ratio (60:40 vs. 65:35 pulsation ratio) and that of the detachment flow rate (600 g/min vs. 800 g/min) on milking performance, somatic cell counts, clinical mastitis, and teats score. Moreover, the innovative aspect of this study relates to the development of an optimized least-squares support vector machine (LSSVM) classification model based on the sparrow search algorithm (SSA) to predict the proper pulsation ratio and detachment flow rate for individual cows within the first two minutes of milking. The accuracy and precision of this model were 92% and 97% for shortening milking time at different pulsation ratios, and 78% and 79% for different detachment rates. The implementation of this algorithm in non-automatic milking machines could make milking operations cow-specific. Full article

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that uses an artificial neural network (ANN) for positioning estimation by considering a multipath channel. Previous results usually rely on the simplistic line of sight model with limited validity. The study considers the influence of noise as a performance indicator for the comparison between different design approaches. Three different ANN algorithms are considered, including Levenberg–Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, to minimize the positioning error (${\epsilon }_p$) in the VLP system. The ANN design is optimized based on the number of neurons in the hidden layers, the number of training epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional received signal strength (RSS) technique using the non-linear least square estimation for all values of signal to noise ratio (SNR). Furthermore, in the inner region, which includes the area of the receiving plane within the transmitters, the positioning accuracy is improved by 43, 55, and 50% for the SNR of 10, 20, and 30 dB, respectively. In the outer region, which is the remaining area within the room, the positioning accuracy is improved by 57, 32, and 6% for the SNR of 10, 20, and 30 dB, respectively. Moreover, we also analyze the impact of different training dataset sizes in ANN, and we show that it is possible to achieve a minimum ${\epsilon }_p$ of 2 cm for 30 dB of SNR using a random selection scheme. Finally, it is observed that ${\epsilon }_p$ is low even for lower values of SNR, i.e., ${\epsilon }_p$ values are 2, 11, and 44 cm for the SNR of 30, 20, and 10 dB, respectively. Full article

A point cloud obtained by stereo matching algorithm or three-dimensional (3D) scanner generally contains much complex noise, which will affect the accuracy of subsequent surface reconstruction or visualization processing. To eliminate the complex noise, a new regularization algorithm for denoising was proposed. In view of the fact that 3D point clouds have low-dimensional structures, a statistical low-dimensional manifold (SLDM) model was established. By regularizing its dimensions, the denoising problem of the point cloud was expressed as an optimization problem based on the geometric constraints of the regularization term of the manifold. A low-dimensional smooth manifold model was constructed by discrete sampling, and solved by means of a statistical method and an alternating iterative method. The performance of the denoising algorithm was quantitatively evaluated from three aspects, i.e., the signal-to-noise ratio (SNR), mean square error (MSE) and structural similarity (SSIM). Analysis and comparison of performance showed that compared with the algebraic point-set surface (APSS), non-local denoising (NLD) and feature graph learning (FGL) algorithms, the mean SNR of the point cloud denoised using the proposed method increased by 1.22 DB, 1.81 DB and 1.20 DB, respectively, its mean MSE decreased by 0.096, 0.086 and 0.076, respectively, and its mean SSIM decreased by 0.023, 0.022 and 0.020, respectively, which shows that the proposed method is more effective in eliminating Gaussian noise and Laplace noise in common point clouds. The application cases showed that the proposed algorithm can retain the geometric feature information of point clouds while eliminating complex noise. Full article

In this paper, the joint impact of the interior heating and chemical reaction on the double diffusive convective flow in porous membrane enclosures soaked by a non-Newtonian Maxwell fluid is investigated applying linear and nonlinear stability techniques. The porous enclosures are square, slender and rectangular. Using the linear stability analysis, the expression for the critical thermal Rayleigh–Darcy number, above which the convective movement occurs, is derived analytically in terms of associated physical parameters. A nonlinear stability examination reliant on the Fourier double series is executed to calculate the convective heat and mass transports of the arrangement. It is observed that the pattern of convective activity is oscillatory only in the occurrence of a relaxation parameter and the threshold value of the relaxation parameter for the occurrence of the oscillatory pattern depends on the other physical parameters. The onset of convective instability accelerates with the increasing chemical reacting parameter, the interior heating parameter, the solute Rayleigh–Darcy number, the Lewis number, the Vadasz number, and the relaxation parameter, while it delays with the heat capacity ratio. The convective heat and mass transfers increase with the solute Rayleigh–Darcy number, the Vadasz number, the relaxation parameter, and the aspect ratio (for rectangular enclosure), while it decreases with the heat capacity ratio and the aspect ratio (for slender enclosure). Additionally, the convective heat transfer enhances with the interior heating parameter, while the convective mass transfer enhances with the chemical reacting parameter and the Lewis number. The effects of Vadasz number, heat capacity ratio, and relaxation parameter are witnessed only on the oscillatory pattern of convection and unsteady convective heat and mass transfers. Further, some existing literature results are compared with the current findings. Full article

In this paper, a Multi Relaxation Time Lattice Boltzmann scheme is used to describe the evolution of a non-Newtonian fluid. Such method is coupled with an Immersed-Boundary technique for the transport of arbitrarily shaped objects navigating the flow. The no-slip boundary conditions on immersed bodies are imposed through a convenient forcing term accounting for the hydrodynamic force generated by the presence of immersed geometries added to momentum equation. Moreover, such forcing term accounts also for the force induced by the shear-dependent viscosity model characterizing the non-Newtonian behavior of the considered fluid. Firstly, the present model is validated against well-known benchmarks, namely the parabolic velocity profile obtained for the flow within two infinite laminae for five values of the viscosity model exponent, n = 0.25, 0.50, 0.75, 1.0, and 1.5. Then, the flow within a squared lid-driven cavity for Re = 1000 and 5000 (being Re the Reynolds number) is computed as a function of n for a shear-thinning (n < 1) fluid. Indeed, the local decrements in the viscosity field achieved in high-shear zones implies the increment in the local Reynolds number, thus moving the position of near-walls minima towards lateral walls. Moreover, the revolution under shear of neutrally buoyant plain elliptical capsules with different Aspect Ratio (AR = 2 and 3) is analyzed for shear-thinning (n < 1), Newtonian (n = 1), and shear-thickening (n > 1) surrounding fluids. Interestingly, the power law by Huang et al. describing the revolution period of such capsules as a function of the Reynolds number and the existence of a critical value, Re${}_c$, after which the tumbling is inhibited in confirmed also for non-Newtonian fluids. Analogously, the equilibrium lateral position $y_{eq}$ of such neutrally buoyant capsules when transported in a plane-Couette flow is studied detailing the variation of $y_{eq}$ as a function of the Reynolds number as well as of the exponent n. Full article