Search Results (25)

This study investigates the effects of modifying a beam model for octet-truss lattice structures to calculate the homogenized material properties using the average stress method. While alignment is observed at low relative densities, the unmodified beam model derives underestimated results at higher relative densities, reaching up to 40% and 30% for elastic and shear modulus values, respectively, for a relative density of 0.5. Beam model modification achieved by increasing strut stiffness at the joints is investigated in detail, and we conclude that both modulus values cannot fit the solid model’s results with this type of modification. This study proposes a novel modification method involving seven spring elements with two constants to capture both the elastic and shear moduli. This study concludes by compensating differences between the solid and beam models’ moduli with the inserted springs, providing an analytical solution for the linear elastic system. The performance of the unit cell models is tested by solving two lattice structures at which the elastic modulus and shear modulus were dominant, respectively, on the mechanical behavior. The results converge to a constant value when the number of unit cells is six, and the beam with a spring model achieved a performance that was close to that of the solid model for the shear-modulus-dominant lattice structure. Full article

Accurate segmentation of the sky region is crucial for various applications, including object detection, tracking, and recognition, as well as augmented reality (AR) and virtual reality (VR) applications. However, sky region segmentation poses significant challenges due to complex backgrounds, varying lighting conditions, and the absence of clear edges and textures. In this paper, we present a new hybrid fast segmentation technique for the sky region that learns from object components to achieve rapid and effective segmentation while preserving precise details of the sky region. We employ Convolutional Neural Networks (CNNs) to guide the active contour and extract regions of interest. Our algorithm is implemented by leveraging three types of CNNs, namely DeepLabV3+, Fully Convolutional Network (FCN), and SegNet. Additionally, we utilize a local image fitting level-set function to characterize the region-based active contour model. Finally, the Lattice Boltzmann approach is employed to achieve rapid convergence of the level-set function. This forms a deep Lattice Boltzmann Level-Set (deep LBLS) segmentation approach that exploits deep CNN, the level-set method (LS), and the lattice Boltzmann method (LBM) for sky region separation. The performance of the proposed method is evaluated on the CamVid dataset, which contains images with a wide range of object variations due to factors such as illumination changes, shadow presence, occlusion, scale differences, and cluttered backgrounds. Experiments conducted on this dataset yield promising results in terms of computation time and the robustness of segmentation when compared to state-of-the-art methods. Our deep LBLS approach demonstrates better performance, with an improvement in mean recall value reaching up to 14.45%. Full article

Significant strides have been made in enhancing the thermoelectric properties of p-type PbTe alloys, whereas the thermoelectric performance of n-type alloys lags behind that of p-type alloys, primarily owing to the difficulty of improving their Seebeck coefficient via band convergence. In this work, Mn was introduced into the n-type Pb_0.985Sb_0.015Te alloy, and Mn doping increases the absolute value of the Seebeck coefficient significantly by increasing the effective mass and reducing carrier concentration, resulting in a higher power factor of 20.8 μW/K²cm being achieved for 0.5% Mn-doped sample at 573 K. Additionally, the decrease in electronic thermal conductivity, combined with the reduction in lattice thermal conductivity caused by the strengthened point defect scattering, leads to a significant decrease in the total thermal conductivity of the sample. And the lowest total lattice thermal conductivity of 1.16 Wm⁻¹K⁻¹ for a 2.0% Mn-doped sample has been achieved at 773 K. In the end, a maximum zT of 1.0 (773 K) and zT_ave of 0.62 (323–773 K) are attained in 1.0% Mn-doped Pb_0.985Sb_0.015Te alloy. Full article

This study proposes a single-stage lattice-type acoustic filter using an analytical solution method for either a narrow passband filter or a wider passband filter using two kinds of parameter assignments in the Butterworth–Van Dyke (BVD) model. To achieve the goal of a large bandwidth or high return loss, two first-order all-pass conditions are used. For multi-stage lattice-type filters, the cost function is defined and design parameters are extracted by using pattern search, while the initial values are provided through single-stage design to shorten optimization time and allow convergence to a better solution. This method provides the S-parameter frequency response for the filter on the YX 42° cut angle of lithium tantalate (electromechanical coupling coefficient of about 6%) that can meet the system specifications as much as possible. Finally, the three-stage lattice-type was applied to various 5G bands with a fractional bandwidth of 2–5%, resulting in a passband return loss of 10 dB and an out-of-band rejection of 40 dB or more. Full article

Discrete tomography is a specific case of computerized tomography that deals with the reconstruction of objects made of a few density values on a discrete lattice of points (integer valued coordinates). In the general case of computerized tomography, several hundreds of projections are required to obtain a single high-resolution slice of the object; in the case of discrete tomography, projections of an object made by just one homogeneous material are sums along very few angles of the pixel values, which can be thought to be 0’s or 1’s without loss of generality. Genetic algorithms are global optimization techniques with an underlying random approach and, therefore, their convergence to a solution is provided in a probabilistic sense. We present here a genetic algorithm able to straightforwardly reconstruct binary objects in the three-dimensional space. To the best of our knowledge, our methodology is the first to require no model of the shape (e.g., periodicity, convexity or symmetry) to reconstruct. Experiments were carried out to test our new approach in terms of computational time and correctness of the solutions. Over the years, discrete tomography has been studied for many interesting applications to computer vision, non-destructive reverse engineering and industrial quality control, electron microscopy, X-rays crystallography, biplane angiography, data coding and compression. Full article

Cu-based ternary oxides with delafossite structure have received considerable attention in recent years for their versatility in a wide range of applications, among which is the possibility to use them in heterostructure solar cells as hole transport layers, due to their promising behavior as p-type conducting oxides. Ab initio calculations have been performed with density functional theory to investigate the role of the trivalent metal within the CuMO₂ structure and the dependence of structural and electronic properties with the species (M = Al, Ga, In, Fe, Cr, Co, Sc, Y) occupying the site of the metal. Generalized Gradient Approximation also including a Hubbard term and nonlocal Heyd–Scuseria–Enzerhof screened hybrid functional schemes were tested and their results were compared. Excellent agreement with experimental lattice parameters and measured gaps have been found. The use of hybrid functionals in HSE approximation considerably improves the bandgaps when compared with the experimental results but takes considerable time to converge, hence the need to explore less demanding methodologies. Trends in the geometry as well as in the electronic properties are discussed, and the effect of mixing different metals (CuM_xN_1−xO₂, M, N being the aforementioned elements) in the geometry and electronic properties of these delafossite materials is investigated. Due to the high cost of HSE calculations, especially when supercells are needed to model several x concentrations, statistical models and techniques based on machine learning have also been explored to predict HSE bandgap values from GGA and structural information. Full article

The generalized Zakharov equation is a widely used and crucial model in plasma physics, which helps to understand wave particle interactions and nonlinear wave propagation in plasma. The solitary wave solution of this equation provides insights into phenomena such as electron and ion acoustic waves, as well as magnetic field disturbances in plasma. The numerical simulation of solitary wave solutions to the generalized Zakharov equation is an interesting problem worth studying. This is crucial for plasma-based technology, as well as for understanding nonlinear wave propagation in plasma physics and other fields. In this study, a numerical investigation of the generalized Zakharov equation using the lattice Boltzmann method has been conducted. The lattice Boltzmann method is a new modeling and simulating method at the mesoscale. A lattice Boltzmann model was constructed by performing Taylor expansion, Chapman–Enskog expansion, and time multiscale expansion on the lattice Boltzmann equation. By defining the moments of the equilibrium distribution function appropriately, the macroscopic equation can be restored. Furthermore, the numerical experiments for the equation are carried out with the parameter lattice size $m=100,$ time step $\Delta t=0.001$, and space step size $\Delta x=0.4$. The solitary wave solution of the equation is numerically simulated. Numerical results under different parameter values are compared, and the convergence and effectiveness of the model are numerically verified. It is obtained that the model is convergent in time and space, and the convergence orders are all 2.24881. The effectiveness of our model was also verified by comparing the numerical results of different numerical methods. The lattice Boltzmann method demonstrates advantages in both accuracy and CPU time. The results indicate that the lattice Boltzmann method is a good tool for computing the generalized Zakharov equation. Full article

In financial and statistical computations, calculating expectations often requires evaluating integrals with respect to a Gaussian measure. Monte Carlo methods are widely used for this purpose due to their dimension-independent convergence rate. Quasi-Monte Carlo is the deterministic analogue of Monte Carlo and has the potential to substantially enhance the convergence rate. Importance sampling is a widely used variance reduction technique. However, research into the specific impact of importance sampling on the integrand, as well as the conditions for convergence, is relatively scarce. In this study, we combine the randomly shifted lattice rule with importance sampling. We prove that, for unbounded functions, randomly shifted lattice rules combined with a suitably chosen importance density can achieve convergence as quickly as $O\left(N^{-1+ϵ}\right)$, given N samples for arbitrary $ϵ$ values under certain conditions. We also prove that the conditions of convergence for Laplace importance sampling are stricter than those for optimal drift importance sampling. Furthermore, using a generalized linear mixed model and Randleman–Bartter model, we provide the conditions under which functions utilizing Laplace importance sampling achieve convergence rates of nearly $O\left(N^{-1+ϵ}\right)$ for arbitrary $ϵ$ values. Full article

Natural circulation loops are thermohydraulic circuits used to transport heat from a source to a sink in the absence of a pump, using the forces induced by the thermal expansion of a working fluid to circulate it. Natural circulation loops have a wide range of engineering applications such as in nuclear power plants, solar systems, and geothermic and electronic cooling. The Lattice Boltzmann Method was applied to the simulation of this thermohydraulic system. This numerical method has several interesting features for engineering applications, such as parallelization capabilities or direct temporal convergence. A 2D model of a single-phase natural circulation mini-loop with a small inner diameter was implemented and tested under different operation conditions following a double distribution function approach (coupling a lattice for the fluid and a secondary lattice for the thermal field). An analytical relationship between the Reynolds number and the modified Grashof number was used to validate the numerical model. Two regimes were found for the circulation, a laminar regime for low Reynolds numbers and a non-laminar regime characterized by a traveling vortex near the heater and cooler’s walls. Both regimes did not present flux inversion and are considered stable. The recirculation of the fluid can explain some of the heat transfer characteristics in each regime. Changing the Prandtl number to a higher value affects the transient response, increasing the temperature and velocity oscillations before reaching the steady state. Full article

Based on the first-principles calculations, the electronic structure and transport properties of BiMChO (M=Cu and Ag, Ch=S, Se, and Te) superlattices have been studied. They are all semiconductors with indirect band gaps. The increased band gap and decreased band dispersion near the valence band maximum (VBM) lead to the lowest electrical conductivity and the lowest power factor for p-type BiAgSeO/BiCuSeO. The band gap value of BiCuTeO/BiCuSeO decreases because of the up-shifted Fermi level of BiCuTeO compared with BiCuSeO, which would lead to relatively high electrical conductivity. The converged bands near VBM can produce a large effective mass of density of states (DOS) without explicitly reducing the mobility µ for p-type BiCuTeO/BiCuSeO, which means a relatively large Seebeck coefficient. Therefore, the power factor increases by 15% compared with BiCuSeO. The up-shifted Fermi level leading to the band structure near VBM is dominated by BiCuTeO for the BiCuTeO/BiCuSeO superlattice. The similar crystal structures bring out the converged bands near VBM along the high symmetry points $\Gamma -X$ and $Z-R$. Further studies show that BiCuTeO/BiCuSeO possesses the lowest lattice thermal conductivity among all the superlattices. These result in the ZT value of p-type BiCuTeO/BiCuSeO increasing by over 2 times compared with BiCuSeO at 700 K. Full article

The article describes the results of research aimed at identifying the parameters of the equivalent circuit of a lithium-ion battery cell, based on the results of HPPC (hybrid pulse power characterization) tests. The OCV (open circuit voltage) characteristic was determined, which was approximated using functions of various types, while making their comparison. The internal impedance of the cell was also identified in the form of a Thevenin RC circuit with one or two time constants. For this purpose, the HPPC pulse transients were approximated with a multi-exponential function. All of the mentioned approximations were carried out using an original method developed for this purpose, based on the PSO (particle swarm optimization) algorithm. As a result of the optimization experiments, the optimal configuration of the PSO algorithm was found. Three different cognition methods have been analyzed here: GB (global best), LB (local best), and FIPS (fully informed particle swarm). Three different swarm topologies were used: ring lattice, von Neumann, and FDR (fitness distance ratio). The choice of the cognition factor value was also analyzed, in order to provide a proper PSO convergence. The identified parameters of the cell model were used to build simulation models. Finally, the simulation results were compared with the results of the laboratory CDC (charge depleting cycle) test. Full article

Cu₂SnS₃ (CSS) has gained great attraction due to its constitutive earth-abundant elements and intrinsic low lattice thermal conductivity, ${\kappa }_l$, potentially providing high quality factor, B, and high zT value. However, the lack of band convergence is the bottleneck to enhancing the thermoelectric performance of Cu₂SnS₃ when performing the band engineering. To study the doping effect on the band structure and the thermoelectric performance, the composite Cu₂Sn_0.7Co_0.3S₃-xCuCl (x = 0, 0.1, 0.2, 0.3) (CSCS-xCuCl) has been investigated for the first time. The samples showed excellent data repeatability at high temperatures of up to 700 K. It was found that CuCl could compensate the Cu loss, enhance the phonon scattering and minimize the adverse effect on the power factor, PF. The ultralow lattice thermal conductivity could reach 0.38 W m⁻¹ K⁻¹ for the nominal composition of CSCS-0.3CuCl at 700 K. A peak zT of 0.56 (evaluated with no cold finger effect) was realized at 700 K when x = 0.3, which is almost double the performance of pristine samples. Full article

A Kuratowski topology is a topology specified in terms of closed sets rather than open sets. Recently, the binary metric was introduced as a symmetric, distributive-lattice-ordered magma-valued function of two variables satisfying a “triangle inequality” and subsequently proved that every Kuratowski topology can be induced by such a binary metric. In this paper, we define the strong convergence of a sequence in a binary metric space and prove that strong convergence implies convergence. We state the conditions under which strong convergence is equivalent to convergence. We define a strongly Cauchy sequence and a strong complete binary metric space. Finally, we give the strong completion of all binary metric spaces with a countable indexing set. Full article

Lead-free and eco-friendly GeTe shows promising mid-temperature thermoelectric applications. However, a low Seebeck coefficient due to its intrinsically high hole concentration induced by Ge vacancies, and a relatively high thermal conductivity result in inferior thermoelectric performance in pristine GeTe. Extrinsic dopants such as Sb, Bi, and Y could play a crucial role in regulating the hole concentration of GeTe because of their different valence states as cations and high solubility in GeTe. Here we investigate the thermoelectric performance of GeTe upon Sb doping, and demonstrate a high maximum zT value up to 1.88 in Ge_0.90Sb_0.10Te as a result of the significant suppression in thermal conductivity while maintaining a high power factor. The maintained high power factor is due to the markable enhancement in the Seebeck coefficient, which could be attributed to the significant suppression of hole concentration and the valence band convergence upon Sb doping, while the low thermal conductivity stems from the suppression of electronic thermal conductivity due to the increase in electrical resistivity and the lowering of lattice thermal conductivity through strengthening the phonon scattering by lattice distortion, dislocations, and twin boundaries. The excellent thermoelectric performance of Ge_0.90Sb_0.10Te shows good reproducibility and thermal stability. This work confirms that Ge_0.90Sb_0.10Te is a superior thermoelectric material for practical application. Full article

Within the cuprate constellation, one fixed star has been the superconducting dome in the quantum phase diagram of transition temperature vs. the excess charge on the Cu in the CuO₂-planes, p, resulting from O-doping or cation substitution. However, a more extensive search of the literature shows that the loss of the superconductivity in favor of a normal Fermi liquid on the overdoped side should not be assumed. Many experimental results from cuprates prepared by high-pressure oxygenation show T_c converging to a fixed value or continuing to slowly increase past the upper limit of the dome of p = 0.26–0.27, up to the maximum amounts of excess oxygen corresponding to p values of 0.3 to > 0.6. These reports have been met with disinterest or disregard. Our review shows that dome-breaking trends for T_c are, in fact, the result of careful, accurate experimental work on a large number of compounds. This behavior most likely mandates a revision of the theoretical basis for high-temperature superconductivity. That excess O atoms located in specific, metastable sites in the crystal, attainable only with extreme O chemical activity under HPO conditions, cause such a radical extension of the superconductivity points to a much more substantial role for the lattice in terms of internal chemistry and bonding. Full article