MATLAB Code Research Articles

Reliability analysis of a three-phase interleaved step-up DC-DC converter for electric vehicle

Increasing the amount of direct current (DC) loads in applications such as airplanes, spacecraft, electric vehicles (EV), and other similar applications DC-DC converters are commonly used. Hence, a three-phase interleaved step-up DC-DC converter (ISC) has been designed, and implemented, which is more appropriate for high-power applications. The modes of operation are explained in detail, and voltage gain calculations are performed. The state space matrix is derived from the voltage equation and the bode diagram is plotted using MATLAB code to investigate the stability study, which makes for a thorough frequency response analysis for the proposed converter. The military handbook (MIL-HDBK-217F) data have been used to perform the calculations to determine each and every component's reliability. The proposed ISC design is implemented into a hardware prototype that produces peak-to-peak output voltage of 139 V, rated voltage of 120 V and the testing outcomes are presented in great depth.

Topology Optimization of Anisotropic Materials with Smooth Fiber Orientation

In the concurrent optimization of topology and fiber orientation, the design of smooth fiber helps to maintain the stability of numerical calculation and the compatibility of the manufacturing process. However, the improvement of fiber continuity is often accompanied by a significant decrease in the overall structural stiffness. Aiming at this problem, this paper proposes a topology optimization method for anisotropic materials with smooth fiber orientation. This method improves the smoothness of fiber orientation and reduces stiffness loss by introducing a fiber angle constraint strategy and adaptive filtering technology. The fiber angle constraint strategy integrates the created angle constraint function into the Method of Moving Asymptotes (MMA) to complete the strong constraint of the angle. This strategy quantifies the continuity of the fiber and effectively improves the continuity of the fiber. At the same time, the application of adaptive filtering technology can adjust a reasonable fiber angle distribution on the basis of smoothing fibers, thereby enhancing the stiffness of the overall structure. In addition, this paper shows the complete optimization process and MATLAB code implementation and verifies the effectiveness of the method through a series of numerical examples, that is, on the basis of improving fiber continuity, the stiffness of the whole structure is guaranteed, and then the effective balance between the two is realized.

Artificial Neural Network–based Prediction Model to Minimize Dust Emission in the Machining Process

BackgroundDust generated during various wood-related activities, such as cutting, sanding, or processing wood materials, can pose significant health and environmental risks due to its potential to cause respiratory problems and contribute to air pollution. Understanding the factors influencing dust emission is important for devising effective mitigation strategies, ensuring a safer working environment, and minimizing environmental impact. This study focuses on developing an artificial neural network (ANN) model to predict dust emission values in the machining of black poplar (Populus nigra L.), oriental beech (Fagus orientalis L.), and medium-density fiberboards. MethodsThe multilayer feed-forward ANN model is developed using a customized application built with MATLAB code. The inputs to the ANN model include material type, cutting width, number of blades, and cutting depth, whereas the output is the dust emission. Model performance is assessed through graphical and statistical comparisons. ResultsThe results reveal that the developed ANN model can provide adequate predictions for dust emission with an acceptable level of accuracy. Through the implementation of the ANN model, the study predicts intermediate dust emission values for different cutting widths and cutting depths, which are not considered in the experimental work. It is observed that dust emission tends to decrease with reductions in cutting width and cutting depth. ConclusionThis study introduces an alternative approach to optimize machining-process conditions for minimizing dust emissions. The findings of this research will assist industries in obtaining dust emission values without the need for additional experimental activities, thereby reducing experimental time and costs.

Solving Intuitionistic Fuzzy Unconstrained Optimization Problems Using Interval Newton’s Method

This research work studies the optimization of intuitionistic fuzzy valued functions in unconstrained problems. The Interval Newton's Method using an Intuitionistic approach addresses both single and multivariable optimization problems. The study incorporates a mathematical comprehension of interval intuitionistic fuzzy valued problems, as well as real-world examples to demonstrate their effectiveness. Furthermore, MATLAB code is provided to demonstrate the implementation of the Interval Newton's Method.

Towards a More Objective and High-throughput Spheroid Invasion Assay Quantification Method.

Multicellular spheroids embedded in 3D hydrogels are prominent in vitro models for 3D cell invasion. Yet, quantification methods for spheroid cell invasion that are high-throughput, objective and accessible are still lacking. Variations in spheroid sizes and the shapes of the cells within render it difficult to objectively assess invasion extent. The goal of this work is to develop a high-throughput quantification method of cell invasion into 3D matrices that minimizes sensitivity to initial spheroid size and cell spreading and provides precise integrative directionally-dependent metrics of invasion. By analyzing images of fluorescent cell nuclei, invasion metrics are automatically calculated at the pixel level. The initial spheroid boundary is segmented and automated calculations of the nuclear pixel distances from the initial boundary are used to compute common invasion metrics (i.e., the change in invasion area, mean distance) for the same spheroid at a later timepoint. We also introduce the area moment of inertia as an integrative metric of cell invasion that considers the invasion area as well as the pixel distances from the initial spheroid boundary. Further, we show that principal component analysis can be used to quantify the directional influence of a stimuli to invasion (e.g., due to a chemotactic gradient or contact guidance). To demonstrate the power of the analysis for cell types with different invasive potentials and the utility of this method for a variety of biological applications, the method is used to analyze the invasiveness of five different cell types. In all, implementation of this high-throughput quantification method results in consistent and objective analysis of 3D multicellular spheroid invasion. We provide the analysis code in both MATLAB and Python languages as well as a GUI for ease of use for researchers with a range of computer programming skills and for applications in a variety of biological research areas such as wound healing and cancer metastasis.

UIDS: A Matlab-based urban flood model considering rainfall-induced and surcharge-induced inundations

The Urban Inundation-Drainage Simulator (UIDS) is a new coupled model for simulating urban flooding dynamics, developed as an open-source, MATLAB-based platform. It integrates a rainfall-runoff model with a two-dimensional overland flow model (OFM) and a one-dimensional sewer flow model (SFM). Unlike conventional models limited to either rainfall-induced or sewer surcharge-induced flooding, UIDS captures bidirectional surface-underground interactions to simulate both processes simultaneously. The OFM employs an explicit time-stepping scheme and robust wet-dry front treatment, while a weir equation describes roof-to-ground flow exchange for numerical stability. Timing synchronization facilitates continuous OFM-SFM coupling. Benchmarking and case studies of Gangnam flood events demonstrate UIDS's ability to accurately simulate urban flooding, particularly subcritical flows. The open-source nature of UIDS allows user flexibility in accessing and modifying the MATLAB code. Ultimately, UIDS is expected to serve as an accessible and adaptable tool for urban flood modeling and risk assessment.

Robust Tensor Completion via Capped Frobenius Norm.

Tensor completion (TC) refers to restoring the missing entries in a given tensor by making use of the low-rank structure. Most existing algorithms have excellent performance in Gaussian noise or impulsive noise scenarios. Generally speaking, the Frobenius-norm-based methods achieve excellent performance in additive Gaussian noise, while their recovery severely degrades in impulsive noise. Although the algorithms using the lp -norm ( ) or its variants can attain high restoration accuracy in the presence of gross errors, they are inferior to the Frobenius-norm-based methods when the noise is Gaussian-distributed. Therefore, an approach that is able to perform well in both Gaussian noise and impulsive noise is desired. In this work, we use a capped Frobenius norm to restrain outliers, which corresponds to a form of the truncated least-squares loss function. The upper bound of our capped Frobenius norm is automatically updated using normalized median absolute deviation during iterations. Therefore, it achieves better performance than the lp -norm with outlier-contaminated observations and attains comparable accuracy to the Frobenius norm without tuning parameter in Gaussian noise. We then adopt the half-quadratic theory to convert the nonconvex problem into a tractable multivariable problem, that is, convex optimization with respect to (w.r.t.) each individual variable. To address the resultant task, we exploit the proximal block coordinate descent (PBCD) method and then establish the convergence of the suggested algorithm. Specifically, the objective function value is guaranteed to be convergent while the variable sequence has a subsequence converging to a critical point. Experimental results based on real-world images and videos exhibit the superiority of the devised approach over several state-of-the-art algorithms in terms of recovery performance. MATLAB code is available at https://github.com/Li-X-P/Code-of-Robust-Tensor-Completion.

Comparative Performance of Point-to-Point Multiple Input Multiple Output System under Weibull and Rayleigh Fading Channels

Multiple-input multiple-output (MIMO) technologies use multiple antennas at the sender and the receiver to get the high data rate that the next-generation communication system needs. This paper compares MIMO systems using the Quadrature Phase Shift Keying (QPSK) modulation scheme for two-channel distributions of Rayleigh and Weibull types. The performance of the work is far with the Minimum Mean Square Equalizer (MMSE) in terms of Bit Error Rate (BER) for various antenna number situations on the transmitter and receiver sides. The MIMO module is carried out using MATLAB code. The channel noise will be a signal of random noise that is generated. To mitigate the impact of inter-channel interference, the MMSE approach employs inverse filtering at the receiver, and BER will be calculated. According to simulation results, the system's performance is primarily influenced by the number of antennas; it decreased as the number of antennas increased, and the BER of the Weibull channel decreased as the two-parameter value increased

Performance of a direct-expansion solar-assisted heat pump for domestic hot water production in Algeria

The focus of this study is to investigate the energy performance of a direct-expansion solar-assisted heat pump water heating system (DX-SAHPWH). The system consists of an unglazed solar collector-evaporator, which can absorb heat from solar energy and air ambient simultaneously, a condenser in the form of a coil immersed in a hot water storage tank, a thermostatic expansion valve and a hermetic reciprocating compressor. The performance of the heat pump system is evaluated using a developed mathematical model under Matlab code. The modelling method is based on lumped and distributed parameter approach of different system components. Numerical calculations were carried-out to study the influence of different parameters, such as ambient temperature, solar radiation intensity and polytropic index on the system performance. Additionally, in order to evaluate the long-term system performance, the system’s model was applied on a case study of a single-family building located in Djelfa (Algeria), which represents the coldest arid region of the country. The results showed that the solar radiation intensity and ambient temperature have significant effects on the heat pump performance. A COP of 5.9 and a collector-evaporator efficiency of 1.9 were obtained at high solar radiation of 850 W/m2 resulting in lower heating time (29 min). In addition, results revealed that the system can operate even at lower ambient temperature due to its ability to take advantage of heat from the ambient air. The results from the case study gave a COP ranging from 2.3 to 3.8, which enhance the promising adoption of this system in domestic hot water production to respond to people daily life needs with clean, abundant and renewable energy.

Assessment and enhancement of thermal performance for ring roughened finned jet impingement solar air heater for low-temperature applications

The current study investigates the synergetic impact of artificial roughness with fins and jet impingement on the performance of flat plate solar air heater. The impingement jet Solar Air Heater (SAH) achieves roughening through the incorporation of conical ring shapes, strategically placed between the straight fins of the absorber plate. The analytical work focuses on maximizing the thermal and effective thermal performance by considering the design parameters: ring thickness ratio (TR/DH) ranging from 0.07 to 0.13, ring diameter to thickness ratio (Do/TR) from 1.67 to 2.67, streamwise pitch to diameter ratio (X/Do) from 4.71 to 7.71, ring diameter ratio (Do/Db) from 1.30 to 2.30, and a number of fins (n) ranging from 4 to 7 based on spanwise pitch ratio (Y/Do) from 2.92 to 5.14. A MATLAB code is created to solve governing equations and validated by comparing results with existing literature. The results indicate that the new configuration of SAH is most effective up to the Reynolds number of 10850 and produces the maximum energy and thermo hydraulic efficiency is 81.4 % and 77.4 %, respectively. It enhances the thermo hydraulic performance by 15.1 % and 4.1 % compared with conventional single pass and parallel pass jet impingement SAH. The system has the capability to increase the air temperature per unit of supplied solar heat flux, is ranging between 0.006 and 0.038 Km2/W.

ArchaeoPyDating: A new user‐friendly release for archaeomagnetic dating

AbstractIn this work, we present ArchaeoPyDating, a new version of the archaeo_dating Matlab software used for archaeomagnetic dating. This updated version introduces a transition from the original Matlab code to Python, enabling the software to be presented as an online tool. By offering a web‐based interface, ArchaeoPyDating eliminates the need for licenses, program installations, or programming expertise, making it widely accessible to users through various devices and browsers. This enhanced accessibility holds great potential for popularizing the archaeomagnetic dating method. This study presents both the new online version of the tool and a Python module that encompasses all the essential classes and functions required for conducting archaeomagnetic dating in a command‐line environment, which can be useful for advanced users.

Aerodynamic shape optimization of NACA airfoils based on a novel unconstrained conjugate gradient algorithm

Airfoils are key factors in maximizing the efficiency of turbomachinery. The ideal configuration of the airfoil is engineered to produce significant lift while minimizing drag, all while adhering to specific structural limitations. In this investigation, an innovative algorithm based on unconstrained conjugate gradient techniques to optimize the aerodynamic shape of airfoils is proposed. NACA4412 and NACA2415 airfoils are chosen to be investigated in detail. Bézier parameterisation method is employed to define the design variables. Optimization is conducted utilizing a MATLAB code and the XFOIL panel method-based flow solver to attain the desired aerodynamic outcomes. The optimization process enhanced aerodynamic performance by increasing the lift-to-drag ratio and decreasing the angle of attack for maximum lift-to-drag ratio. An increase of 13.7 % in performance for the NACA 4412 airfoil and 32 % for the NACA 2415 airfoil was achieved. Comparisons with traditional methods demonstrated the efficiency and robustness of the proposed algorithm.

Optimal Design and Performance Analysis of a Gas-Gas Heat Exchanger for Harvesting Waste Heat

This study reports the design of an optimized heat exchanger capable of efficiently extracting and transferring waste heat from flue gas to air. An experimental setup was constructed to recover waste heat from the exhaust steam of a boiler, using this heat to warm compressed air. Thermocouples recorded the temperatures at the inlet and outlet of both the hot and cold fluids. A MATLAB code is developed to compare the experimental results. According to our code, the cold fluid outlet temperature ranged from 71.5°C to 76°C, while the experimental setup showed temperatures ranging from 66°C to 71.5°C at air mass flow rates of 0.1564, 0.1346, and 0.1794 kg/s. The deviation may arise from the inaccuracies of the flow rate and the temperature measurement devices as well as the constraints in correlations which calculate heat transfer coefficient and friction factor in pressure drop. Future work may focus on minimizing the deviations and propose an improved design of heat exchanger. IUBAT Review—A Multidisciplinary Academic Journal, 7(1): 124-141

Investigating the Effects of Cargo Weight and its Distribution on the Dynamic Performance of a High-Speed Planing Hull

The aim of this article is to evaluate the effects of cargo relative weight and its distribution along the boat’s length in addition to the relative water wavelength on the dynamic performance of a high-speed planing hull. Here, the dynamic performance is measured by the intensity of the boat’s heave and pitch motions. The Zarnick’s strip theory, which divides the vessel’s hull into equal lateral sections, is used to study the applied forces on the vessel, and a MATLAB code is provided based on it. It is demonstrated that increasing the cargo weight and its distribution result in more heave and pitch, and the maximum amount of them are observed in the wave with a length of about 5 times the length of the boat. In addition, the interactive effects of cargo weight and its distribution on the heave and pitch motions are affected by the relative wavelength. Therefore, the more centralized cargo distribution is preferred to increase the dynamic performance of a heavy planing boat with cargo weights more than 50% of the boat’s weight, while moving in short waves (λ⁄L<4); and for light cargo weight, less than 50% of the boat’s weight, the favorite cargo distribution is broad. When the boat sails in long waves, the desired distribution is reversed.

A robust radial point interpolation method empowered with neural network solvers (RPIM-NNS) for nonlinear solid mechanics

In this work, we proposed a robust radial point interpolation method empowered with neural network solvers (RPIM-NNS) for solving highly nonlinear solid mechanics problems. It is enabled by neural network solvers via minimizing an energy-based functional loss. The RPIM-NNS has the following key ingredients: (1) It uses radial basis functions (RBFs) for displacement interpolation at arbitrary points in the problem domain, permitting irregular node distributions. (2) Nodes are placed also beyond the domain boundary, allowing the convenient implementation of boundary conditions of both Dirichlet and Neumann types. (3) It uses strain energy in an integral form as a part of the loss function, ensuring solution stability. (4) A well-developed gradient descendant algorithm in machine learning is employed to find the optimal solution, enabling robustness and ease in handling material and geometrical nonlinearities. (5) The proposed RPIM-NNS is compatible with parallel computing schemes. The performance of this method is tested using nonlinear problems including Cook's membrane and 3D twisting rubber problems, demonstrating its remarkable stability and robustness. This work, which seamlessly integrates the neural network solvers with mechanics governing equations and computational mechanics techniques, offers an excellent alternative for nonlinear solid mechanics problems. MATLAB codes are made available at https://github.com/JinshuaiBai/RPIM_NNS for free downloading.

Assessment of stabilizing feedback control of walking: A tutorial

Walking without falling requires stabilization of the trajectory of the body center of mass relative to the base of support. Model studies suggest that this requires active, feedback control, i.e., the nervous system must process sensory information on the state of the body to generate descending motor commands to the muscles to stabilize walking, especially in the mediolateral direction. Stabilization of bipedal gait is challenging and can be impaired in older and diseased individuals. In this tutorial, we illustrate how gait analysis can be used to assess the stabilizing feedback control of gait. We present methods ranging from those that require limited input data (e.g. position data of markers placed on the feet and pelvis only) to those that require full-body kinematics and electromyography. Analyses range from simple kinematics analyses to inverse dynamics. These methods assess stabilizing feedback control of human walking at three levels: 1) the level of center of mass movement and horizontal ground reaction forces, 2) the level of center of mass movement and foot placement and 3) the level of center of mass movement and the joint moments or muscle activity. We show how these can be calculated and provide a GitHub repository (https://github.com/VU-HMS/Tutorial-stabilizing-walking) which contains open access Matlab and Python code to calculate these. Finally, we discuss what information on feedback control can be learned from each of these.

A Modification to the Novel Toy Model of the Riemann Zeta Function Roots Equation

It is true that my previous series of papers about the Riemann Hypothesis has raised lots of discussions or the concerns among the mathematics society. Indeed, some professionals may think that the Riemann Zeta function at s = 1 or ∑_(n=1)^∞▒1/n is actually divergent and may tend to an infinity, how it can be acted as a denominator in a proof or something like 1/∞ ? This author’s idea is there may be no need to evaluate such kind of summation as one may consider the sum just as an (imaginary) constant (but NOT the complex number). Or we may only consider such summation as a kind of improper integrals with a black-boxed answer. In other words, the true final value of the summation ∑_(n=1)^∞▒1/n is NOT an concerning serious issue. The function ∑_(n=1)^∞▒1/n^s is in practice a smooth function and equals to log N or the logarithmic function for s = 1 or have the infinite differentiable properties except n = 0, that is why the commercial software Maple Soft can compute the Zeta function’s associated Taylor series successfully. In fact, from the above series together with the harmonic properties, one may calculate the artifical Zeta function’s root model equation such as the 0.5 +/- β*cot(ln(x))/(αx+1)n (will be discussed in my next paper of the series). Indeed, this is NOT the best model. Actually, the true Riemann Zeta non-trivial Root model equation is: {z = x + yI | z∈0.5±(y_1⩽y⩽y_2 )I} where y1= (±cot(k))/ln(k) , y2 = (±tan(k))/ln(k) with 0<k<2π. Certainly, this author cannot avoid mistakes. Some of the defects in the previous paper such as one in the linguistic proof of the RH will be stated and amended. Lastly, this author wants to remind that the present series of paper is first to establish a model equation for zeta function’s roots and the Plank’s like constant. This author then applies the telescopic and logarithmic methods for a 3 cases proof of the RH. Also, we have a Matlab code for the evaluation of RH complex contour integral. Finally, the RH problem will be transformed into a linguistic one and hence we may have solved the Riemann Hypothesis issue completely through a 4 cases of truth table collaborations with the logical inference [7] & [15] to the causality (structural) organization of the sentences [16] or just named as “Logical & Organized Context”.

Comparative techno-economic and environmental analysis of a relocatable solar power tower for low to medium temperature industrial process heat supply

The primary objective of this study is to promote the adoption of solar power tower (SPT) technology in low to medium-temperature industrial process heat (IPH) applications and compare it with other heat generation alternatives. Through comprehensive techno-economic and environmental analyses, a proposed relocatable SPT-based IPH plant (PR-SPT-IPH), with a capacity of 1 MWth, is thoroughly evaluated against traditional concentrating solar-thermal power (CSP) technologies like parabolic trough collectors (PTC) and linear Fresnel reflectors (LFR), as well as natural gas (NG) and photovoltaic (PV)-based IPH systems. The techno-economic assessment of the PR-SPT-IPH is performed using an in-house developed MATLAB code, while the system advisor model (SAM) is used to simulate equivalent PTC-, LFR-, and PV-based IPH plants. The primary techno-economic assessment metric is the levelized cost of heat (LCOH), while the environmental analysis quantifies the avoided greenhouse gas (GHG) emissions and other pollutants resulting from NG combustion. The results show that the PR-SPT-IPH plant achieves the lowest LCOH of 2.42 cents/kWhth, generating annual thermal energy of 5.62 GWhth with a capacity factor of 48.27 %. With certain assumptions, this cost can be further reduced to 1.5 cents/kWhth, meeting the U.S. Department of Energy targets. The PR-SPT-IPH plant could annually avoid emitting 1112 kg of CO2, 54 kg of particulate matter, 1201.76 kg of NOx, and 5.08 kg of SO2. It could also save annual external costs between $43,100.28 and $153,194.67, while the annually saved fuel cost could reach $151,632. The study indicates that the PR-SPT-IPH plant surpasses PTC-, LFR-, NG-, and PV-based IPH plants both technically and financially. With reduced capital costs and appropriate incentives, the PR-SPT-IPH plant emerges as an economically and environmentally viable choice for low to medium-temperature IPH applications.

An investigation into the impact of thermal radiation and chemical reactions on the flow through porous media of a Casson hybrid nanofluid including unstable mixed convection with stretched sheet in the presence of thermophoresis and Brownian motion

Abstract This article investigates the unsteady mixed convention two-dimensional flow of magnetohydrodynamic Casson hybrid nanofluids (alumina oxide and titanium oxide nanoparticles with base fluid water) flow through porous media over a linearly stretched sheet. We analyzed the heat and mass transfer in mixed convection, thermal radiation, variable thermal conductivity, variable mass diffusivity, and chemical reaction in the presence of thermophoresis and Brownian motion. A system of partial differential equations is reduced to a solvable system of ordinary differential equations by applying a suitable similarity transformation. We used the Runga–Kutta method along with the shooting procedure to solve the flow, heat, and mass transfer equations along with boundary conditions. The results obtained from MATLAB codes are compared with previously published results of the same type in a limiting case. The results of the velocity, temperature, and concentration profile of the hybrid nanofluid for varying different flow parameters are obtained in the form of graphs, while the rate of shear stress, rate of heat, and mass transfer are expressed in tables. We noticed that velocity and temperature diminish as an unsteady parameter increases; however, the reverse trend was observed in the nanoparticle concentration profile. With an increase in the thermal radiation parameter, the resultant velocity and temperature profile improves, while the concentration of nanoparticle profiles decreases. The velocity and temperature increase with higher Brownian motion, while the velocity increases and temperature decreases with higher thermophoresis.

Neurophysiological recordings from parietal areas of macaque brain during an instructed-delay reaching task

Facilitating data sharing in scientific research, especially in the domain of animal studies, holds immense value, particularly in mitigating distress and enhancing the efficiency of data collection. This study unveils a meticulously curated collection of neural activity data extracted from six electrophysiological datasets recorded from three parietal areas (V6A, PEc, PE) of two Macaca fascicularis during an instructed-delay foveated reaching task. This valuable resource is now accessible to the public, featuring spike timestamps, behavioural event timings and supplementary metadata, all presented alongside a comprehensive description of the encompassing structure. To enhance accessibility, data are stored as HDF5 files, a convenient format due to its flexible structure and the capability to attach diverse information to each hierarchical sub-level. To guarantee ready-to-use datasets, we also provide some MATLAB and Python code examples, enabling users to quickly familiarize themselves with the data structure.