MATLAB Program Research Articles

Study on the Population Balance Dynamics Simulation of Grinding under Impact Crushing

During the grinding process, the crushing of minerals mainly depends on the impact action of the grinding medium. Based on the JK drop weight test data of quartz and pyrrhotite and the research results of their impact crushing characteristic parameters, this paper calculates the specific crushing energy (Ecs) of mineral samples subjected to impact in a ball mill using the grinding medium motion theory and then calculates the cumulative particle size distribution under screening under any mesh size using the JK drop weight test method. On this basis, the breakage distribution function of mineral samples is calculated, and a selection function is obtained based on grinding experiments. Finally, using Matlab programming and function-fitting mathematical methods, as well as a particle size population balance dynamics simulation of grinding, the particle size distribution characteristics of the grinding products of the two mineral samples in the mill that are only subjected to impact action are calculated. The results show that the selection function of quartz and pyrrhotite decreases overall with the prolongation of the grinding time, and the selection function of the coarse particle size changes more significantly than that of the fine particle size. At the same time, the selection function decreases with the decrease in feed particle size, and the smaller the feed particle size, the lower the probability of impact crushing. The Ecs values of quartz and pyrrhotite at each particle level in the mill are different, and the degree of mineral crushing is closely related to the impact energy, feed particle size, and mineral properties.

The prediction of emotional decision making from working memory and inhibitory control in preschool children: using decision tree model

ABSTRACT While there is a theoretical distinction between cool (cognitive) and hot (emotional) executive functions, potential relationships can be identified between tasks associated with these two aspects. A decision tree serves as a model for training and analyzing data, predicting the target variable based on independent variables in a hierarchical fashion. In contrast to other predictive methods, this model doesn’t necessitate statistical expertise and makes decisions akin to human decision-making through hierarchical “if” and “then” rules, providing an easily interpretable framework. To date, no studies have explored the relationship between cool and hot executive functions using decision tree models. In this study, preschool children specifically Persian-speaking Iranian children aged 4 to 5 years (N = 71, M age = 59.07; SD = 6.03), participated in cool (Forward Digit Span, Backward Digit Span, Day-Night inhibitory control, and Happy-Sad Inhibitory control) and hot (Children Gambling Task) executive function tasks. Analyses were performed using MATLAB programming software. The C4.5 version of the decision tree was employed to predict the final CGT blocks’ scores using scores from cool executive function tasks as inputs. By employing this method, a minimal prediction error (approaching zero) was achieved, significantly showing the robust predictive capability of cool executive function in anticipating hot executive function. This outcome suggests potential relationships between the cognitive and emotional aspects of executive function.

Numerical Approach of NiZnFe2O4 (Nickel–Zinc Ferrite) – Ethylene Glycol Magneto Nanofluid Flow Over a Porous Shrinking Sheet with Chemical Reaction and Radiation

The objective of this study is to conduct a numerical examination of the influence of nonlinear chemical reaction and heat source or sink on magnetohydrodynamic (MHD) heat and mass transmission nanofluid flow through a shrinking permeable surface. In addition, the investigation considers thermal radiation and the occurrence of viscous dissipation. Ethylene glycol (EG) is used as the primary fluid medium, whilst the nanoparticles consist of nickel–zinc ferrite. The use of nanofluid flow has garnered significant interest as a result of its potential applications across several sectors. Nanofluids possess a notable benefit in comparison to traditional fluids as a consequence of their enhanced heat transfer capabilities. This advantage may be ascribed to the inclusion of nanoparticles, which augment thermal conductivity and therefore lead to enhanced heat dissipation and efficiency. The mathematical flow model, which is formulated using nonlinear partial differential equations (PDEs), may be transformed into a set of ordinary differential equations (ODEs) by the application of suitable similarity conversions. In order to address the complexities of the nonlinear system, the bvp4c and shooting techniques are used inside the MATLAB program, a widely utilized commercial platform, to effectively solve the associated ODEs by numerical means. This study presents a graphical analysis of the effects of flow parameters on several variables of interest.

Dual effects of additional food supply and threshold control on the dynamics of a Leslie–Gower model with pest herd behavior

Bemisia tabaci is a major agricultural pest and recognized by the United Nations Food and Agriculture Organization (FAO) as the second largest pest in the world. This paper aims to study the management of Bemisia tabaci from theoretical aspects. Firstly, considering the omnivorous nature of natural enemy species and pest herd behavior, a Leslie–Gower type pest-natural enemy model with additional food supply and non-differentiable rational uptake function is put forward, and the effects of additional food supply and aggregation efficiency on the dynamical behavior of the system are analyzed. Secondly, for the slowness of pest control by natural enemy species, a threshold control strategy is adopted to prevent the spread of Bemisia tabaci by spraying a certain intensity of insecticides and releasing a certain number of natural enemies. The complex dynamics of the system induced by the threshold control are discussed such as the existence of predator-extinction periodic solution, the existence and stability of coexisting order-1 periodic solution. Thirdly, from the perspective of cost control, an optimization problem is constructed based on the existence of the order-1 periodic solution, and the optimal control threshold, control strength and control frequency are determined. At last, to illustrate the theoretical results more intuitively, the numerical simulations in MATLAB program are presented to illustrate the effectiveness and practical significance of the control measures. The results of this study provide a reference for the scientific and reasonable management of Bemisia tabaci and is helpful to realize the sustainable development of agricultural production.

A Linear Optimization for Slope Leveling of Ground-Mounted Centralized Photovoltaic Sites

Slope leveling is essential for the successful implementation of ground-mounted centralized photovoltaic (PV) plants, but currently, there is a lack of optimization methods available. To address this issue, a linear programming approach has been proposed to optimize PV slope leveling. This method involves dividing the field into blocks and grids and using hyperbolic paraboloids to simulate the design surface. By programming in MATLAB, the globally optimal solution for PV slope leveling can be calculated. Engineering case studies have demonstrated that this optimization method can achieve significant cut-and-fill volume savings ranging from 58% to 78%, when compared to the traditional segmented plane method. Additionally, the effectiveness of the optimization method improves with larger site areas and more complex terrains. A parameter analysis considering slope ratio, grid size, and block size reveals that grid size has a minimal impact on cut-and-fill volume, while slope ratio and block size have a significant influence. For typical PV projects, the recommended ranges of slope ratio, grid size, and block size are 3–7%, 5–20 m, and 30–50 m, respectively, for slope leveling design. In summary, the proposed linear optimization method provides an optimal slope leveling scheme for ground-mounted centralized PV plants, with convenient operation and fast computation.

A comparison among a fuzzy algorithm for image rescaling with other methods of digital image processing

The aim of this paper is to compare the fuzzy-type algorithm for image rescaling introduced by Jurio et al., 2011, quoted in the list of references, with some other existing algorithms such as the classical bicubic algorithm and the sampling Kantorovich (SK) one. Note that the SK algorithm is a recent tool for image rescaling and enhancement that has been revealed to be useful in several applications to real world problems, while the bicubic algorithm is widely known in the literature. A comparison among the abovementioned algorithms (all implemented in the MatLab programming language) was performed in terms of suitable similarity indices such as the Peak-Signal-to-Noise-Ratio (PSNR) and the likelihood index $S$.

Propagation of plane waves at the initially stressed surface of an orthotropic nonlocal rotating half space under dual-phase-lag model

PurposeThe purpose of the current manuscript is to investigate the reflection of plane waves in a rotating, two-dimensional homogeneous, initially stressed, nonlocal orthotropic thermoelastic solid half-space based on dual-phase-lag model.Design/methodology/approachThe reflection phenomenon has been utilized to study the effects of initial stress, rotation and nonlocal parameter on the amplitude ratios. During the reflection phenomenon three coupled waves, namely quasi displacement primary wave (qP), quasi thermal wave (qT) and quasi displacement secondary wave (qSV) have been observed in the medium, propagating with distinct velocities. After imposing the suitable boundary conditions, amplitude and energy ratios of the reflected waves are obtained in explicit form.FindingsWith the support of MATLAB programming, the amplitude ratios and energy ratios are plotted graphically to display the effects of rotation, initial stress and nonlocal parameters. Moreover, the impact of anisotropy and phase lags is also observed on the reflection coefficients of the propagating waves.Originality/valueIn the current work, we have considered rotation and nonlocality parameters in an initially stressed orthotropic thermoelastic half-space, which is lacking in the published literature in this field. The introduction of these parameters in a nonlocal orthotropic thermoelastic medium provides a more realistic model for these studies. The present work is valuable for the analysis of orthotropic thermoelastic problems involving rotation, initial stress and nonlocality parameters.

Two-phase numerical simulation of thermal and solutal transport exploration of a non-Newtonian nanomaterial flow past a stretching surface with chemical reaction

Abstract Non-uniform heat sources and sinks are used to control the temperature of the reaction and ensure that it proceeds at the desired rate. It is worldwide in nature and may be found in all engineering applications such as nuclear reactors, electronic devices, chemical reactors, etc. In food processing, heat is used to cook such as microwave ovens, pasteurize infrared heaters, and sterilize food products. Non-uniform heat sources are mainly used in biomedical applications, such as hyperthermia cancer treatment, to target and kill cancer cells. Because of its ubiquitous nature, the idea is taken as our subject of study. Heat and species transfer analysis of a non-Newtonian fluid flow model under magnetic effects past an extensible moving sheet is modelled and examined. Homogeneous chemical reaction inside the fluid medium is also investigated. This natural phenomenon is framed as a set of Prandtl boundary layer equations under the assumed convective surface boundary constraint. Self-similarity transformation is employed to convert framed boundary layer equations to ordinary differential equations. The resultant system is solved using the efficient finite difference utilized Keller box method with the help of MATLAB programming. The influence of various fluid-affecting parameters on fluid momentum, energy, species diffusion and wall drag, heat, and mass transfer coefficients is studied. Accelerating the Weissenberg number decelerates the fluid velocity. The temperature of the fluid rises due to variations in the non-uniform heat source and sink parameters. Ohmic dissipation affects the temperature profile significantly. Species diffusion reduces when thermophoresis parameter and non-uniform heat source and sink parameters vary. The Eckert number enhances the heat and diffusion transfer rate. Increasing the chemical reaction parameter decreases the shear wall stress and energy transmission rate while improving the diffusion rate. The wall drag coefficient and Sherwood number decrease as the thermophoretic parameter increases whereas the Nusselt number increases. We hope that this work will act as a reference for future scholars who will have to deal with urgent problems related to industrial and technical enclosures.

Vector form of intrinsic finite element method for incompressible fluids

Vector form of intrinsic finite element (VFIFE) is a numerical method widely used in solid mechanics. However, it's hard to extend the VFIFE method to fluid mechanics since the traditional VFIFE method fails to reflect the analytical equilibrium of multiple variables in the continuum. Therefore, under the framework of analytical mechanics, this paper proposes Lagrange's equation of the second kind in fluid mechanics with the extremum condition of Lagrange power functional. And a vectorized motion equation of incompressible viscous fluids is deduced from Lagrange's equation. By using several efficient algorithms in the finite difference method (FDM) and the finite element method (FEM), the NS equation is decomposed into four governing equations of vector form for fluid mechanics. In addition, with the application of the classic Smagorinsky sub-grid scale model in large eddy simulation (LES), this paper puts forward turbulence modelling with VFIFE procedure, and a corresponding MATLAB program is developed. Two typical examples are given to demonstrate the applicability and efficiency of the proposed large eddy simulation with VFIFE method. The proposed algorithm can effectively eliminate the non-physical oscillation of the pressure, and obtain much accurate results with a small number of grids.

A concentration reflector device of a bifacial photovoltaic module

Abstract At present, the development of bifacial photovoltaic modules is rapid, but there is a lack of concentrating light devices in bifacial photovoltaic modules for power generation. This paper analyzes the changing patterns of solar altitude and azimuth angles and the influence of plane mirror reflection concentrating light on the performance of bifacial photovoltaic power generation. Using MATLAB programming, it calculates the pattern of change of the intensity of reflected light with the installation height h of the plane mirror. Then, a double plane mirror concentrating device is designed, which can do real-time dynamic tracking of the sun’s azimuth and altitude angle and realize the power generation capacity of the PV module is multiplied.

Towards an optimization of automatic defect detection by artificial neural network using Lamb waves

This paper presents a damage detection method based on the inverse pattern recognition technique by artificial neural network (ANN) using ultrasonic waves. Lamb waves are guided elastic waves, are widely employed in nondestructive testing thanks to their attractive properties such as their sensitivity to the small defects. In this work, finite element method was conducted by Abaqus to study Lamb modes propagation. A data collection is performed by the signals recorded from the sensor of 300 models: healthy and damaged plates excited by a tone burst signal with the frequencies: 100 kHz, 125 kHz, 150 kHz, 175 kHz, 200 kHz, and 225 kHz. The captured signals in undamaged plat are the baseline, whereas the signals measured in damaged plates are recorded for various positions of external rectangular defects. To reduce the amount of training data, only two peaks of measured signals are required to be the input of the model. Continuous wavelet transform (CWT) was adopted to calculate the key features of the signal in the time domain. The feed forward neural network is implemented using MATLAB program. The data are divided as follows: 70% for training the model, 25% for the validation, and 5% for the test. The proposed model is accurate estimating the position of the defect with an accuracy of 99.98%.

Mathematical model written by ordinary differential equations for hysteresis games

In game theory, the hysteresis effect manifests itself in the fact that small differences in one or more parameters lead two systems to opposite stable equilibrium. The mathematical model (called smooth model) of hysteresis game writing by ordinary differential equations with the great parameter K is studied. Estimations of closeness of output functions for smooth and classical models through the continuity module of continuous input function are received. This error can be controlled by increasing the parameter K to a sufficiently large value. The result was conducted by studying of mathematical model and using programs Mathematica, Matlab or Maple. Experiments were carried out, and the obtained results were summarized and presented through evaluations and graphical interpretation.

Optimal economic environmental power dispatch by using artificial bee colony algorithm

<span>Today, most power plants worldwide use fossil fuels such as natural gas, coal, and oil as the primary resource for energy reproduction primarily. The new term for economic environmental power dispatch (EEPD) problems is on the minimum total cost of the generator and fossil fuel emissions to address atmosphere pollution. Thus, the significant objective functions are identified to minimize the cost of generation, most minor emission pollutants, and lowest system losses individually. As an alternative, an Artificial Bee Colony (ABC) swarming algorithm is applied to solve the EEPD problem separately in the power systems on both standard IEEE 26 bus system and IEEE 57 bus system using a MATLAB programming environment. The performance of the introduced algorithm is measured based on simple mathematical analysis such as a simple deviation and its percentage from the obtained results. From the mathematical measurement, the ABC algorithm showed an improvement on each identified single objective function as compared with the gradient approach of using the Newton Raphson method in a short computational time.</span>

Entropy generation on the dynamics of volume fraction of nano-particles and coriolis force impacts on mixed convective nanofluid flow with significant magnetic effect

Recent advances in simulating entropy generation for dissipative cross-materials with a quartic auto catalyst are reported. Entropy generation can be used to generate entropy in any irreversible heat transfer process, which is important in thermal machines. This study examines the impact of entropy generation on the thermal transport and momentum of a continuous two-dimensional dusty fluid magnetohydrodynamic (MHD) migration across an inclined stretched sheet. We also conducted an entropy generation study to discuss the effects of viscous dissipation, the volume proportion of dust particles, and mixed convection. The two-phase models that address the fluid phase and the solid phase have been discussed. As part of the flow model’s innovation, the effect of raising particulate matter concentration on the dynamic behavior of the fluid is investigated. The described model transforms the prevailing partial differential equations (PDEs) for two phases into a nonlinearly associated, nondimensional set of equations by implementing appropriate similarity alterations. For graphical results, MATLAB programming incorporates the bvp4c mechanism. This study indicates how to examine the impact of appropriate factors on the dusty phase of fluid and the non-Newtonian fluid phase. Both the entropy generation ( E gen ) and the Bejan quantity (Be) are presented in relation to their associated dimensionless factors. Parametric research is used to evaluate the impact of different flow parameters on temperatures, entropy generation, and Bejan numbers. The heat transfer rate using several quadratic regression models, which provide more clarity in determining physical parameters crucial to engineering, is assessed. It is observed that the entropy ( E gen ) and Bejan number (Be) declines with the rising mass concentration ( β ν ) of dusty particles. Also demonstrated that for both cases, increasing the magnetic influence and dust volume fraction ( Φ D ) resulted in a decrease in velocity profiles at the same time as temperature increased.

Thermo-convection driven Sodium Alginate-based Darcy–Forchheimer EMHD Williamson hybrid nanofluid flow with varying thermal distribution

A computational investigation is furnished to explore the responses of a Darcy–Forchheimer EMHD Williamson flow of a Sodium Alginate [Formula: see text]-based Ag-Al2O3 hybrid nanofluid passing over a vertically exponentially stretching cylinder emerged through a porous region. The prime focus of this research is to encompass the inclusion of nonlinear variations in heat distribution, Newtonian boundary heating (NBH) effects, and the influence of thermo-convection alongside suction effects. Key parameters, including thermal buoyancy, Darcy porous medium effects, heat source/sink effects, Biot number, variable thermal index, and thermal convection factor, are comprehensively analyzed as these combining factors can play a crucial role in optimizing the efficacy of several systems such as heat exchanger, material processing and geothermal system that involve the concept of thermo-transportation mechanism. The physical flow dynamics are modeled, employing suitable similarity transformations, and subsequently translated into a dimensionless form. The ensuing collection of modified nonlinear ordinary differential equations is solved by employing the Bvp4c solver bundled into the MATLAB program. Several parameters are scrutinized through graphical presentations to elucidate their impacts on the velocity curve, temperature curve, skin friction coefficient, and Nusselt index. It is worth mentioning that the heat distribution profile significantly escalated for the rising values of several factors such as electric field parameter, varying thermal index, Biot number and shape factor, but the reverse is the pattern with suction and thermo-convection effect. Also, the thermal transportation rate at the proximity of the vertical cylindrical wall appears to exhibit an increment of about an average of 47% in SA-based Williamson hybrid nanofluid compared to Williamson fluid for thermo-convective effect, NBH, and thermal buoyancy. Furthermore, the proximate shear stress rate appears to be amplified by approximately 39% in Williamson hybrid nanofluid when contrasted with Williamson fluid for electric field parameter and thermo-convection effect alongside the raised Darcy–Forchheimer factor.

Design of a Mobile Industrial Robot Platform based on Fixed Cameras

This study presents a design for an autonomous mobile robot system that utilizes environmental cameras for navigation and obstacle avoidance. Operating within a known environment, the robot employs these cameras to facilitate path planning and to circumvent obstacles. The hardware setup includes fixed cameras strategically placed in the environment to pinpoint the robot’s location and to identify obstacles amidst varying conditions. A computer system is essential for processing the data captured by the cameras, and a wireless transmission system communicates operational instructions to the robot.For navigation, the study explores various algorithms for path planning, selecting the most efficient one through comparative analysis. Once the path is established, the robot’s instructions are computed under the designed control rate, employing the vehicle’s PD control method. This method is informed by the external camera’s simulation of the vehicle, ensuring accurate and responsive navigation.The project’s goal is to create a mobile robot platform that leverages an external camera as its primary sensor. This design promises efficient autonomous navigation and the capability to avoid static obstacles. The robot’s design is conceptualized using SolidWorks and brought to life through implementation in the Python and MATLAB programming languages, demonstrating the system’s practicality and adaptability in real-world scenarios. Additionally, the system’s design considers ease of integration and scalability to accommodate future technological advancements and new application requirements.

Decomposing Method for Space-Time Fractional Order PDEs

Numerical solutions to integer-order differential equations frequently employ decomposition as one of many methods. This paper provides a generalization of integer-order differential equations into fractional order, which is more general, as well as generalizing the decomposing method into the fractional case and then applying it to solve differential equations of fractional order in both space and time. A fractional calculus's theorems and properties to generalize both differential equations and the decomposition method have been utilized. This method to solve different fractional time and space partial differential equations, demonstrating its ability and applicability to various problems have been applied. The method to various cases to highlight its strengths has been used. The graphs and tables of results obtained using Matlab programs have been presented and discussed.

Repeatability, interocular correlation and agreement of optic nerve head vessel density in healthy eyes: a swept-source optical coherence tomographic angiography study.

To assess the repeatability, interocular correlation, and agreement of quantitative swept-source optical coherence tomography angiography (OCTA) optic nerve head (ONH) parameters in healthy subjects. Thirty-three healthy subjects were enrolled. The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm ×3 mm scanning protocol. Images of the radial peripapillary capillary were analyzed by a customized Matlab program, and the vessel density, fractal dimension, and vessel diameter index were measured. The repeatability of the four scans was determined by the intraclass correlation coefficient (ICC). The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient, ICC and Bland-Altman plots. All swept-source-OCTA ONH parameters exhibited certain repeatability, with ICC>0.760 and coefficient of variation (CoV)≤7.301%. The obvious interocular correlation was observed for papillary vessel density (ICC=0.857), vessel diameter index (ICC=0.857) and fractal dimension (ICC=0.906), while circumpapillary vessel density exhibited moderate interocular correlation (ICC=0.687). Bland-Altman plots revealed an agreement range of -5.26% to 6.21% for circumpapillary vessel density. OCTA ONH parameters demonstrate good repeatability in healthy subjects. The interocular correlations of papillary vessel density, fractal dimension and vessel diameter index are high, but the correlation for circumpapillary vessel density is moderate.

Flow of Hybrid Dust Micropolar Nanofluids Along the Symmetric Riga Surface with Heat Generation and Application of Cattaneo-Christov Theory

This study investigates the mechanical characteristics of a hybrid nanofluid containing dust and micropolar particles, flowing under mixed convection past a symmetric Riga surface using the Cattaneo-Christov (C-C) heat flux theory with consideration for heat generation effects. The analysis focuses on dust micropolar flow within a porous medium with a combination of hybrid nanoparticles CNTs - F with blood. The mathematical model describing this system involves a set of partial differential equations (PDEs), which are transformed into dimensionless ordinary differential equations (ODEs) and eventually into a form that can be solved using the MATLAB program. Graphical representations are employed to examine and discuss the impact of various flow parameters on the velocity and temperature profiles of the dust micropolar hybrid nanofluid. Several key findings emerge from this investigation. It is anticipated that an increase in the interaction between fluid particle parameters will result in a decrease in the temperature of the fluid phase and an increase in the temperature of the dust phase. Moreover, the study reveals that the Nusselt number is influenced by the mixed convection effects. Additionally, larger values of the heat generation parameter lead to higher temperatures in both the fluid phase and the dust phase. Conclusion: In summary, this study comprehensively investigates the dynamics of nanofluid flows over a Riga surface, considering parameters like , Pr, and βv. The findings highlight their significant impact on temperature distribution, fluid flow patterns, and friction forces. The results offer insights crucial for optimizing engineering systems like cooling technologies and heat exchangers. This research advances our understanding of nanofluid dynamics and provides valuable guidance for future studies and practical applications.

Embedding numerical methods and MATLAB programming in a fluid mechanics course for undergraduates in engineering technology

Undergraduate students in engineering technology are typically not required to take any courses on numerical methods or computational techniques and thus have little or no knowledge of many basic numerical approaches commonly used in engineering disciplines, such as root finding, curve fitting, numerical integration, and numerical differentiation. In addition, they are only required to take one introductory level programming course and thus usually experience difficulty when working on course projects involving extensive programming. However, the industry is demanding different skillsets than the ones that were expected just a decade ago. Numerical and programming skills are becoming increasingly important. In this case study, the effectiveness of embedding numerical methods and MATLAB programming in MMET 303 Fluid Mechanics and Power, a four-credit junior-level required course offered every semester for undergraduates at the Department of Engineering Technology and Industrial Distribution at Texas A&M University, was assessed. A series of learning modules were purposefully designed and implemented as a trial test in the classes offered in the semester of Fall 2023. Instructor's observation, submitted assignments, and survey results were analyzed. The results suggested that embedding numerical methods and associated MATLAB programming into a required course enhanced students’ analytical skills of tackling practical problems, helping them become better prepared as they move on into the industrial companies or the graduate schools.