MATLAB R2018b Research Articles

Energy Management of a Fuel Cell Electric Robot Based on Hydrogen Value and Battery Overcharge Control

The energy management system of a fuel cell electric robot should be highly responsive to provide the required power for various tactical operations, navigation of different routes, and acceleration. This paper presents a new multi-level online energy management strategy for a fuel cell electric robot based on the proposed functions of equivalent hydrogen fuel value evaluation, classification of the battery state of charge via the squared combined efficiency function, identification of the robot maneuver condition based on the proposed operation state of robot function, improvement of the overall energy efficiency based on the proposed function of the battery overcharge control, and separation of the functional points of the fuel cell based on the operational mode control strategy. The simulation study of the proposed online multi-level energy management strategy was carried out with MATLAB R2018b software to verify its superiority by comparing with other strategies. The results indicate a reduction in hydrogen consumption, reduction in fuel cell power fluctuations, prevention of battery overcharging, and incrementation in the total energy efficiency of energy storage systems compared to other energy management strategies.

الحلول العددية لمعادلات أبيل التكاملية الخطية بطريقة متعددات حدود بوبكر

في هذه المقالة، تم تقديم طريقة عددية تستند الى عديدات حدود بوبكر لحل معادلات آبيل التكاملية الخطية من النوع الاول والثاني. تم تحويل معادلات آبيل التكاملية الى نظام جبري من المعادلات الخطية باستخدام المصفوفات. للحصول على معالم بوبكر، تم حل هذا النظام باستخدام طريقة كاوس للحذف. ولتوضيح نتائج هذه الطريقة تم تقديم اربعة امثلة ومقارنتها مع نتائج العديد من الطرق المذكرة في البحوث السابقة. تم استخدام برنامج الماتلاب R2018b لأجراء جميع الحسابات والرسوم البيانية.

Fuzzy-Logic Based Model for VANET Performance Metrics Analysis

Vehicular Ad-hoc Networks (VANETs) allows a spontaneous communication between vehicle to vehicles and road-side units(RSU) using wireless interfaces and road-side infrastructure to form Intelligent Transportation System (ITS). VANET, prime objective is to provide information about accidents or unwanted situations and traffic conditions to the drivers. As VANETs are dynamic in nature, the vehicle nodes to discover the best possible route to broadcast an emergency message is a challenge. To study different highway and urban road scenarios, there is a need to simulate and evaluate the network performance analysis of routing protocols beforehand since real-time implementation is rather challenging or expensive. This paper focuses on the VANET routing protocols evaluation, to find an appropriate protocol which provide suitable Quality of Service (QoS) to end users in both safety and non-safety conditions. To simplify the QoS evaluation problem, Hierarchical Fuzzy Inference System (HFIS) model has been designed and simulated in MATLAB R2018b that analysis the network performance metrics of VANET routing protocols. From the simulations, it is observed that that OLSR routing protocol for both safety and non-safety applications, outperforms other routing protocols as its global QoS reaches to approximately 84% efficiency.

A Modified Iterative Approach for Fixed Point Problem in Hadamard Spaces

The role of iterative algorithms is vital in exploring the diverse domains of science and has proven to be a powerful tool for solving complex computational problems in the most trending branches of computer science. Taking motivation from this fact, we develop and apply a modified four-step iterative algorithm to solve the fixed point problem in the Hadamard spaces using a total asymptotic nonexpansive mapping. MATLAB R2018b is used for numerical experiments to ensure a better convergence rate of the proposed iterative algorithm with existing results.

TOUCHARD POLYNOMIALS APPROACH FOR SOLVING NON- LINEAR FREDHOLM INTEGRO- DIFFERENTIAL EQUATION OF SECOND TYPE

A numerical approach to solve Non- linear Fredholm integro- differential (NLFID) equation of the 1st order and 2nd type has been proposed. The approach was based upon Touchard polynomials. The non-linear Fredholm integro- differential equation was changed into a system of non- linear algebraic equations and solved using Newton repeating approach. The proposed approach was evaluated by displaying three numerical problems, and the approximate numerical solutions were compared with exact solution and four methods in the literature. MATLAB R2018b was used to perform all calculations and graphs.

A Computational Tool to Track Sewage Flow Discharge into Rivers Based on Coupled HEC-RAS and DREAM

Worldwide abatement of untreated sewage discharge into surface water is a challenging task. Sewage discharging into surface waters has a detrimental impact on water quality. This paper presents a MATLAB (R2018b) framework designed to identify sewage flow discharges into rivers from an inverse problem-solving perspective. The computational tool integrates a hydrodynamic model using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS 5.0.0) and an open-source toolbox for Differential Evolution Adaptive Metropolis (DREAM) as the inverse problem method. The proposed framework can effectively infer discharge sources in scenarios of highly transient flow based on hydraulic data at pre-set monitoring sites. To validate its capabilities, one hypothetical case and two real cases of sewage flow discharges entering a river were used to test the developed modeling framework. The results based on three performance metrics showed that this mathematical tool can be extended to simulate complex hydrodynamic flow patterns. This accomplishment underscores its potential as a valuable asset for environmental monitoring and water quality restoration efforts.

Numerical study on heat and flow transfer of biomagnetic fluid with copper nanoparticles over a linear extended sheet under the influence of magnetic dipole and thermal radiation

A steady, two-dimensional flow of biomagnetic fluid namely blood flow with copper nanoparticles across a stretchable sheet that is affected by a strong magnetic field and thermal radiation is investigated in this study. Copper nanoparticles (Cu-NPs) were used for this study because of their important applicability in biomedical research. Thus, the properties of copper nanoparticles render it an antibacterial, antimicrobial, and anti-fungal material. Similarity substitutions were applied to reduce the nonlinear partial differential equations to ordinary differential equations. Utilizing the MATLAB R2018b software bvp4c function technique, the physical solution was established. This model's pertinent dimensions, such as the ferromagnetic parameter, the magnetic field parameter, the radiation parameter, the suction parameter, the ratio parameter, the slip parameter, and the Prandtl Number, were computationally and graphically inspected about the dimensionless velocity, temperature, skin friction, and heat transfer rate. One of the pivotal observations was that a rise in the ferromagnetic parameter and Prandtl number drops the temperature and velocity, correspondingly. A cross-case analysis with the outcome of other published research is also executed for divergent parameter values. Based on the investigations, copper nanoparticles may be advantageous for biomedical purposes and lessen the hemodynamics of stenosis. Owing to the research, copper nanoparticle-concentrated blood exhibits a reduced flow impedance and a larger temperature changeability compared to sheer blood.

Research on watershed water ecological management and compensation based on evolutionary game

Abstract Ecological compensation is an effective way to alleviate watershed water ecological management. Considering the behavior of public participation, this paper constructs a tripartite evolutionary game model of the public, enterprises, and local governments, analyzes the evolutionary stability of the strategic choice of each participant, and discusses the influence of various factors on the strategic choice of the three parties. Combined with regional data, Matlab R2018b is used to simulate and analyze the evolution trend of each subject strategy in the Huaihe River Basin under different situations. The study found that: (1) The government's increase in rewards and punishments has significantly promoted public participation and enterprises' active governance of pollution, but increasing rewards and punishments are not conducive to local governments' own performance of regulatory responsibilities. (2) Increasing the amount of compensation and incentives is an effective way to promote public participation. (3) The sum of reputation gains, reputation losses, and rewards and punishments is greater than the difference between the additional benefits of negative governance and the cost of corporate governance, so as to ensure that enterprises actively control pollution.

Optimization Strategy of Rolling Mill Hydraulic Roll Gap Control System Based on Improved Particle Swarm PID Algorithm

Medium and heavy plates are important strategic materials, which are widely used in many fields, such as large ships, weapons and armor, large bridges, and super high-rise buildings. However, the traditional control technology cannot meet the high-precision control requirements of the roll gap of the thick plate mill, resulting in errors in the thickness of the medium and heavy plate, thereby reducing the quality of the product. In response to this problem, this paper takes the 5500 mm thick plate production line as the research background, and establishes the model of the rolling mill plate thickness automatic control system, using the Ziegler-Nichol response curve method (Z-N), particle swarm optimization (PSO) algorithm and linear weight particle swarm optimization (LWPSO) algorithm, respectively, optimizes the parameter setting of the PID controller of the system, and uses OPC UA communication technology to realize the online semi-physical simulation of Siemens S7-1500 series PLC (Siemens, Munich, Germany) and MATLAB R2018b (The MathWorks, Natick, Massachusetts, United States). Comparative studies show that when the same roll gap displacement step signal is given, the overshoot of the system response using the LWPSO algorithm is reduced by 14.26% and 10.18% compared with the Z-N algorithm and the PSO algorithm, and the peak time is advanced by 0.31 s and 0.05 s. The stabilization time is reduced by 3.71 s and 4.31 s, which effectively improves the control accuracy and speed of the system and has stronger anti-interference ability. It has certain engineering reference and application value.

Fifth‐generation fractal antenna design based on the Koch Snowflake geometry. A fractal theory application

AbstractThe projection of fifth‐generation (5G) fractal antennas and their advantageous geometry are examined. The fact that fractal‐shaped antennas based on Koch Snowflake geometry are suitable for higher frequencies was shown above all. By the instrumentality of this technology, which aims to serve a large number of subscribers by implementing revolutionary devices (e.g. Massive MIMO, beam‐forming, high‐performance processors, etc.), it is possible to obtain multiple facilities. Fractal geometrics forms have been made using fractalKoch function from MATLAB R2018b, having as initial characteristic the series of successful repetitions. 2D and 3D characteristics of directivity at the values of 455, 465, 755.5 and 789.5 MHz (designed antennas), for two, three respectively four iterations of Koch's Snowflake fractals have been highlighted. We mention that all the software and programs developed for the fractal antennas design obtained in this paper are new and genuine.

Towards secured image steganography based on content-adaptive adversarial perturbation

In this paper, a content-adaptive adversarial steganography is proposed to improve steganography security by adaptively adding perturbations to cover images while considering image contents with rich texture, where perturbations are generated using adversarial example generation methods like the fast gradient sign method. In this approach, a hybrid texture descriptor is initially created to describe texture regions by using better local binary patterns based on multi-grained gradient information and the noise residual feature to describe texture regions. The input image is then divided into different sections using local semantics using a segmentation approach called simple linear iterative clustering. Finally, using the hybrid texture descriptor and segmentation results, a weighted mask is created, which may be used to determine the best spots for applying adversarial perturbations of various weights to generate more secure adversarial cover images. Extensive experiments are carried out to compare the suggested method to existing state-of-the-art methods in order to prove its superiority. The experiments were conducted on BOSSbase ver. 1.01, which contains 10,000 grayscale 512*512 images. The images were cropped into four non-overlapping 256*256 images using ‘imcrop’ function in MATLAB R2018b. Consequently, a cropped BOSSbase dataset was constructed that contains 40,000 samples. Besides, we also evaluate the performance on another image dataset, namely BOWS2. Experiments show that the proposed model can increase image steganography security while causing less observable traces.

TOUCHARD METHOD FOR SOLVING NONLINEAR VOLTERRA INTEGRAL EQUATION OF SECOND TYPE

In this paper, a novel numerical method has been outlined for finding a novel solution to nonlinear Volterra integral (NLVI) equation of second type, besides, two kernel type of this equation. Touchard polynomials (TPs) and to different degrees were used for this purpose. The function of approximation was obtained to derive the technique for solving this type of integral equations. Three numerical examples were provided to demonstrate the importance of the method used and the accuracy of the extracted results. In some examples, the results were compared with those of another method. The MATLAB R2018b program was used to carry out all calculations and generate all graphics. Keywords: Nonlinear Volterra Integral Equation, Numerical Method, Touchard Polynomials, Exact Function, Numerical Solution

OpenSANS: A Semi-Analytical solver for Nonlocal plasmonicS

Prompted by the renewed interest the past decade in the hydrodynamic model for the description of nanoplasmonic systems, we present OpenSANS, a MATLAB toolbox for the simulation of canonical (that is, standalone spherical and cylindrical) nanoparticles and planar stratified structures whose critical dimensions are of mere nanometres. The method comprises of a generalisation of Mie theory to properly address the hydrodynamic motion of free electrons in metals and a compact S matrix formulation for the efficient treatment of multiple layers. The toolbox is built in a modular manner; each part (routine) has its own important functionality and can be used independently from the others. Our primary goal is the presentation of a highly efficient and accessible solver for the nanoplasmonics community. This is achieved by the very semi-analyticity of the chosen method and by powerful vectorisation techniques optimised in a very popular environment, MATLAB. Program summaryProgram Title: OpenSANSCPC Library link to program files:https://doi.org/10.17632/hmk224xngb.1Code Ocean capsule:https://codeocean.com/capsule/2246190Licensing provisions: GPLv3Programming language: MATLAB R2018b and newer.Supplementary material: See Appendix A.Nature of problem: Solve the scattering problem from multilayered, dielectric, local or nonlocal metallic nanoparticles, excited by a plane wave and placed in a local (dielectric or metallic) background.Solution method: Mie theory, appropriately extended to incorporate nonlocal effects (longitudinal waves) as predicted by the Hard Wall-Hydrodynamic Model, combined with S matrix theory for efficient handling of the multilayered structure.

Surrogate modeling method for multi-objective optimization of the inlet channel and the basin of a gravitational water vortex hydraulic turbine

This work presents a high-fidelity surrogate model for generating a multi-objective genetic algorithm to allow the search for the optimal geometry of the inlet channel and the basin of a gravitational water vortex hydraulic turbine. Six parameters were considered for the optimization: the relations between the basin diameter (D) and the basin height (H), H/D; the wrap-around angle (γ), the outlet diameter (d) and D, d/D; the inlet channel width (w) and D, w/D; the inlet channel height (h) and D, h/D; and the inlet channel length (L) and D, L/D. Two conflicting objectives were studied: maximizing the vortex strength (Γ) and minimizing the volume flow rate (Q). The multi-objective optimization problem was resolved by applying the gamultiobj function in Matlab R2018b software. The optimization combines the genetic algorithm with Kriging interpolation to obtain the Pareto front. To train the gamultiobj function, an initial population of 40 individuals was used. As a stopping criterion, the maximum generation of 500 individuals was established. To improve the Pareto front, 20 optimization cycles (60 new samples) were required, reaching a final population of 100 individuals. It was found from the Pareto front that the values of the six variables providing the compromise solution, between Γ and Q, were H/D=1.572, L/D=1.518, h/D=0.565, w/D=0.361, d/D=0.108, and γ=92.141°. This solution reaches a Q of 0.00305 m3/s and a Γ of 1.699 m2/s. The results of this study were compared with the results reported by other authors, who optimized this type of turbine by applying the response surface methodology. The difference between these results was less than 9.61%.

Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime

Wireless sensor networks (WSN) have evolved a vibrant and lively research field. It comprises numerous wise and low-power consumption devices for gathering the contiguous atmosphere's data. However, the energy dissipation matter that distorts network lifetime remains the challenge since the sensor node battery is non-rechargeable and irreplaceable. Clustering and routing protocol has become the furthermost solutions and invariably minimizes depletion and prolongs the sensor node lifetime. Such protocols have adopted metaheuristic algorithms to secure the efficiency of the clustering and routing protocols. However, the cluster head's extensive task favors consuming and draining more energy. This study proposed a fine-tuning solution for the sensor node's population and generation sizes. It benefits from the modified problem-oriented genetic algorithm parameters in securing the sensor node lifetime. Besides, the solution works effectively to balance the load of the cluster head nodes. A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.

Novel model predictive control by hypothetical stages to improve energy efficiency of industrial cooling tower

• Mathematical model of cooling tower based on analogy to distillation column. • Aspen Plus model was developed for cooling tower. • Both models were validated with real plant operating data. • Controller was designed to control performance of cooling tower with climate. • Resulted in 30% reduction in overall power consumption of cooling tower. Cooling towers are unit operations that are used in almost every industry to cool down process water either by natural draft or forced draft. The energy intensive components of cooling towers are draft fans and circulating pumps which in traditional practise run at full rated capacities throughout the year ignoring the underlying opportunities for energy savings. The efficiency of a cooling tower is a function of ambient air temperature, relative humidity and wet bulb temperature. This work brings out a novel model of cooling tower along with an energy harnessing control system based on prevailing climatic conditions thus improving the overall efficiency of the system. Based on analogy to a distillation column with hypothetical stages a model for cooling tower is developed. Then a model predictive control is designed to control the draft fan speed and pump flow rate of cooling tower based on climatic conditions. Both the model and control strategy was developed using Aspen Plus (V12.1), MATLAB (R2018b) and Simulink softwares and has been validated and trained based on plant operating data. The developed model was then tested at a pilot cooling tower facility of capacity 1 Ton of Refrigeration and was observed to attain approximately 30% reduction in energy consumption compared to the traditional operation.

How to Promote Logistics Enterprises to Participate in Reverse Emergency Logistics: A Tripartite Evolutionary Game Analysis

Considering the emergency risks and uncertainties of emergency recycling processes, this research builds a tripartite evolutionary game model of government, logistics enterprises, and environmental non-governmental organizations (NGOs) to study the interaction mechanism. Based on the analysis of evolutionary stable strategy (ESS), this research uses MATLAB R2018b to mainly show the strategy choice trends of logistics enterprises in various scenarios including “Government Failure”, as well as the mutual impacts of government and environmental NGOs’ strategy selection. The research found that (1) the government has an important role in efficiently promoting logistics enterprises’ participation; (2) the net benefits of logistics enterprises and environmental NGOs, as key factors that directly affect the game results, are influenced by emergency risks and uncertainty, respectively; (3) environmental NGOs not only play an effective complementary role to government functions, including in the “Government Failure” context, but can also urge the government to perform regulatory functions. This research enriches the study in the field of the combination of evolutionary game theory and reverse emergency logistics as well as providing a reference for the government in developing economic and administrative policies to optimize the recycling and disposal of emergency relief.

Quaternion keyed Least Square Approximation for image encryption

Securing image data from prying hackers is crucial in safeguarding the secrecy of data. Over the years, this was done by encrypting the image using an algorithm and a key, where the visible image was converted into a meaningless object. It is a difficult problem to design an image encryption technique based on chaotic systems with predictable cryptographic features. In this paper, the Quaternion, along with the Rossler attractor, was used to generate the key combination. The ciphering was done using the Least Square Approximation Algorithm (LSA). The algorithm was tested on a grayscale image database. The algorithm was initially tested in software using MATLAB R2018b, and was implemented in the Cyclone II EP2C35F672C6 device FPGA. On average, for a cipher image, the Peak Signal to Noise ratio (PSNR) was 9.09303 dB and the entropy was 7.9990 bits. For the cipher image, the Number of Pixels Change Rate (NPCR) and Unified Average Change Intensity (UACI) were 99.6039 and 33.4980, respectively. This proved that the algorithm could effectively mitigate the statistical and differential attacks. The key space was 2 (M ×N ×7 ×8), which was sufficiently high and mitigated the brute force attacks. The obtained results confirm that the cipher images resulting from the proposed ciphering scheme possess good cryptographic properties in terms of entropy, PSNR, UACI, NPCR, and keyspace analysis. Furthermore, the strength of the key is evaluated by the NIST test suite.

Optimasi Proses Gasifikasi Menggunakan Logika Fuzzy Mamdani

This study aims to test the performance of fuzzy logic in the gasification process. Gasification is the process of converting solids into flammable gases. The gas produced becomes an alternative energy source, namely the Waste Power Plant (PLTSa). The research applies Mamdani's Fuzzy logic. Fuzzy logic was created using Matlab R2018b software. The results obtained indicate that the Mean Absolute Error (MAE) output of H2 on fuzzy logic training data is 6.57. The test results for CO fuzzy output MAE value of 1.12. The test results on CO2 MAE fuzzy are 1.18. In the CH4 test, the MAE fuzzy output is 0,84.

Modeling of the Peristaltic Lithogeic Bile Flow in the Calculus Duct Under the Influence of Heat Transfer with Slip Boundary Conditions

This paper deals with a mathematical model that represents non-Newtonian bile flow through a calculus duct under the influence of heat transfer with wall slip conditions. The peristaltic flow of bile is characterized by a generalized Carreau's model. An ordinate transformation is initiated to map the cosine geometry of the stone into a rectangular grid. It allows evaluation velocity, pressure distribution, flow rate, and reflux occurrence conditions, adopting the perturbation technique, the analytical solution obtained under various parameters, such as Knudsen number, amplitude ratio, Grashof number, Weissenberg number, and power index. These mathematical expressions are analyzed by plotting the graph in MATLAB R2018b software and observed that the axial velocity and the pressure gradient are strongly affected by heat and wall slip parameters.