MATLAB Research Articles

Performance analysis of air conditioner system integrated with thermal energy storage using enhanced machine learning modelling coupled with fire hawk optimizer

Integrating air conditioning (AC) systems with thermal energy storage (TES) offers a promising solution for managing large buildings' peak load demands and energy efficiency. Predicting the performance of the AC-TES is a significant index in ensuring optimal cooling load and energy consumption. However, conventional approaches encounter challenges in achieving high levels of accuracy, reliability, and scalability. Therefore, this study introduces leveraging machine learning techniques and in-situ measurements for precise predicting the energy performance of AC-TES system in a semi-arid climate building. The study proposes a hybrid prediction strategy leveraging the benefits of machine learning and meta-heuristic optimization algorithms. The proposed approach integrates a Radial Basis Function Neural Network (RBFNN) with the Fire Hawk Optimizer (FHO) for predicting the performance parameters of the AC-TES system; including, energy consumption, cooling load, air room temperature and performance coefficient (COP). The RBFNN framework in the developed strategy is trained to identify intricate patterns and correlations within the data, while the FHO is utilized to explore the optimal hyperparameters of the RBFNN for maximizing the prediction accuracy. The proposed strategy was modelled in MATLAB software and validated using a publicly available measurements for the AC-TES system. The system maintained improved cooling performance in which the average daily values of energy consumption, cooling load, air room temperature and COP are 1100 kWh/hr, 1.30 kW, 23.97 oC, and 3.12, respectively. The statistical outcomes depict that the developed RBFNN-FHO strategy achieved an impressive prediction accuracy of 95.81% accuracy, a 0.94 correlation coefficient, a 0.4193 mean absolute error (MAE), and a 0.5200 root mean square error (RMSE), respectively. Furthermore, the performance of the proposed RBFNN-FHO is model, is compared with the existing machine-learning approaches utilized for predicting the dynamic performances of HVAC systems. The comparative analysis with existing techniques highlights the robustness and effectiveness of the proposed RBFNN-FHO strategy in predicting AC-TES performances.

Performance analysis of hybrid off-grid renewable energy systems for sustainable rural electrification

Delivering sustainable power to rural communities in sub-Saharan Africa, particularly in Somalia, where many areas are far from the electrical grid and suffer from energy shortages, necessitates the deployment of appropriate technologies. This study evaluates the techno-economic and environmental viability of a hybrid renewable energy system (HRES) comprising a 15 kWp photovoltaic (PV) generator, 10 kW wind turbine (WT), 25 kW diesel generator (DG), and a 72-kWh battery energy storage system (BESS). The HRES is proposed to supply sustainable power to a rural community in Somalia. The techno-economic assessment of the proposed HRES and a comparative analysis of other configurations—namely the PV/WT/BESS and PV/DG/BESS systems is conducted using HOMER and MATLAB software. The results indicate that the proposed PV/WT/DG/BESS HRES demonstrates superior techno-economic performance compared to the other configurations. The lowest net present cost of $96,899.16 and the levelized cost of energy (LCOE) of $0.090/kWh were achieved. This system attains 25 % excess electricity, maintains a 0 % unmet electric load, and demonstrates robust environmental performance with a renewable penetration rate of 91.8 %. Approximately 53.34 % of greenhouse gas emissions are reduced compared to the PV/DG/BESS configuration. The study confirmed the significant impacts of all sensitivity parameters on operational costs, LCOE, fuel prices, fuel intake, and renewable fraction. The overall results indicate superior performance in the optimal system case, offering a feasible and suitable choice for the sustainable electrification of rural communities.

Investigation of magnetite water nanofluid flow through a stretching sheet using the Hamilton and Crosser model for nanoparticle shape factor and effective thermal conductivity

The main objective of this current investigation is to study the heat and mass transfer of the convective MHD Fe3O4−H2O nanofluid through an expanding sheet in the presence of thermal radiation. The Hamilton and Crosser model describes the shape and effective thermal conductivity. The fluid flow governing PDEs has been transformed into a system of ODEs by utilizing appropriate similarity transformation. We used SQLM or Spectral Quasilinearization method to solve them numerically and draw the graphical conclusion using MATLAB software. The skin friction, the Nusselt number and the Sherwood number have been determined numerically and portrayed graphically for the pertinent parameter. It has been observed that for the increment of the volume fraction of Fe3O4 nanoparticles, the fluid velocity tends to reduce while the thermal profile is enhanced. We also observed that for the increment of the buoyancy parameter, the mass transfer is enhanced. Additionally, for the enhancement of the Schmidt number from 0.1 to 1.2, the rate of mass transfer coefficient increases very rapidly. The outcome of the current study has been compared with previously published data, and there is a satisfactory agreement.

Efficient Thermal Integration Model based on a Biogas-fired Gas Turbine Cycle (GTC) for Electricity and Desalination Applications; Thermo-Economic and GA-based Optimization

As the global energy demand continues to rise, there is an urgent need to improve the efficiency and sustainability of power generation systems. This study integrated a modified supercritical carbon dioxide (S-CO2) and multi-effect desalination (MED) units to recover residual heat from a gas turbine cycle (GTC) in two stages, significantly enhancing electricity production while reducing the environmental footprint of the GTC. The significance of this study lies in its comprehensive approach, combining thermodynamic, environmental, and thermoeconomic analyses alongside thorough sensitivity evaluations. A triple optimization framework was implemented to optimize the system's performance, focusing on key metrics such as exergy efficiency, CO2 reduction rates, and levelized energy cost, utilizing the NSGA-II and the TOPSIS decision-making method in MATLAB software. Economic viability was assessed through a net present value (NPV) analysis, demonstrating substantial profitability. Finally, a comparison study of the devised system CO2 emissions rate was performed for different renewable energy sources. A specific application of the devised system is its capacity to generate 1.415 m³/h of distilled water while generating 1441 kW of electricity. Sensitivity analysis identified the combustion chamber temperature as the most critical design parameter, with a sensitivity index of 0.328. The optimum economic indicators showed marked improvement, with the NPV increasing from 2.371 M$ to 10.75 M$ and the payback period decreasing from 13.28 years to 7.18 years.

Employing binary/ternary organic blends in integrated HP-assisted HDH desalination systems

The global demand for potable water is rising, prompting the development of various energy systems for distilled water production. However, the significance of utilizing multicomponent working fluids in these systems has been largely overlooked. This study presents three HDH-based distillation units powered by two conventional heat pump cycles, namely, the simple and vapor injection heat pumps (first and second models) and an innovative heat pump cycle with an ejector expander (third model). The significance of the research lies in its pioneering investigation of utilizing two- and three-component mixtures in heat pump-based desalination units, which has not been previously explored. The study's primary aim is to determine whether using multicomponent working fluids instead of pure fluids or introducing structural modifications can more effectively enhance the performance of heat pump-based distillation units. The proposed models are simulated using EES and MATLAB software, with the study focusing on energetic, exergetic, exergoeconomic, and heat exchanger modeling to evaluate the feasibility of the configurations. The findings revealed that the structural modifications in the third scenario using R134a resulted in the highest GOR, with improvements of 44 % and 26.03 %, respectively, compared to the other scenarios. However, utilizing binary blend R22/R142b with different compositions improved the GOR of the first to three scenarios by 41.26 %, 29.06 %, and 11.87 %, respectively. Furthermore, in this case, the unit cost of distilled water for the first, second, and third scenarios increased by 12.87 %, 14.32 %, and 12.70 %, respectively. Finally, the first scenario has the highest NPV of 4.40 M$ and the shortest PP of 8.13 years. Therefore, utilizing the blend in a simple heat pump proves to be more efficient and cost-effective than implementing structural modifications.

The Clearing Strategy of Primary Frequency Control Ancillary Services Market from the Point of View ISO in the Presence of Synchronous Generations and Virtual Power Plants Based on Responsive Loads

Since the increase in penetration of renewable energy sources connected to the system reduces the inertia of power systems, the penetration of these sources leads to increase in the requirements of primary frequency control (PFC) services. Fortunately, with the expansion of network intelligence platforms, responsive loads (RL) can be effectively useful in ancillary services in the near future and can be used like traditional power plants. Since these equipment have a high rate of change of status, if they are visible in the market by aggregating (with virtual power plant (VPP)), they can compete with synchronous generations (SG). Because the response speed of the participants in the market can affect the decision independent system operator (ISO) in determining the winning units, therefore in this article, we have proposed a market framework to create competition between SGs and VPPs in providing ancillary services. In the proposed framework, ISO minimizes the weighted sum of power purchase costs from VPPs and SGs. The proposed weighting coefficients express the response speed of each unit. In fact, the desired objective function is affected by two terms, cost and speed. The presented model has been simulated on a test system including four SGs units and one VPP unit in matrix laboratory (MATLAB) software and checked under five different scenarios. The comparison of the obtained results indicates an increase in the possibility of accepting units with a smaller weighting factor and a higher response speed (the meaning of accepting units are market players, i.e. SGs and VPPs).

The modeling and mathematical analysis of the fractional-order of Cholera disease: Dynamical and Simulation

In this study, a cholera model with asymptomatic carriers was examined. A Holling type-II functional response function was used to describe disease transmission. For analyzing the dynamical behavior of cholera disease, a fractional-order model was developed. First, the positivity and boundedness of the system’s solutions were established. The local stability of the equilibrium points was also analyzed. Second, a Lyapunov function was used to construct the global asymptotic stability of the system for both endemic and disease-free equilibrium points. Finally, numerical simulations and sensitivity analysis were carried out using matlab software to demonstrate the accuracy and validate the obtained results.

One-pot solvothermal synthesis of Ca-Fe-La composite for advanced removal of phosphate from aqueous solutions in a fixed-bed column: Modeling and resource utilization

The Ca-Fe-La composite was synthesized by the one-pot solvothermal method and applied to the advanced removal of phosphate from aqueous solutions in a fixed-bed column. The effects of some important process parameters on the phosphate adsorption were examined. It was found that the maximum equilibrium loading was 121.1mgg−1 at an influent phosphorus concentration of 30mgL−1, flow rate of 2.5mLmin−1, adsorbent mass of 0.5g and pH of 5.14. The Thomas and fractal-like Thomas models were used to analyze the measured breakthrough curves. Their fitting quality was diagnosed by the adjusted coefficient of determination (Adj. R2), the root of mean squared error (RMSE) and the residual plot. According to the Thomas and fractal-like Thomas models, the breakthrough time and the saturation time were solved by the fzero command of MATLAB software. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were adopted to further determine the optimal model. In all cases, the phosphate adsorption on the Ca-Fe-La composite followed the fractal-like Thomas model. The phosphate loaded Ca-Fe-La composite could be used as a slow-release fertilizer and promote tomato plant growth. This work aimed to provide reliable assessment methods for the modeling of the breakthrough curves and allow for waste management and resource utilization of the phosphate loaded Ca-Fe-La composite.

WACARDIA: graphical MATLAB software for Wireless Assessment of CARDiac Interoceptive Accuracy.

Many theories of psychological function emphasize the importance of bodily sensations and the ability to accurately detect them, known as interoceptive accuracy. The most common measure of interoceptive accuracy uses heartbeat detection tasks such as the Whitehead Task, yet to our knowledge there are no freely accessible programs to conduct this task. In this paper, we present novel software called WACARDIA (Wireless Assessment of CARDiac Interoceptive Accuracy), which is free, open-source software that conducts the heartbeat detection task using Matlab and Psychtoolbox. WACARDIA contains several key features supporting participant engagement, operator convenience, and measurement accuracy. First, the program includes an optional practice trial of unlimited duration, a participant-facing graphical interface, and the ability to perform heartbeat detection training. Second, the operator is provided with a graphical user interface, live trial feedback, an accurate wireless electrocardiogram device, and a separate program to conduct the related Heartbeat Tracking task. Finally, the program ensures the accuracy of collected data by scheduling the delivery of tones with high precision and implementing fail-safes to automatically reset erroneous measurements. This paper includes flowcharts that help create transparency by describing our algorithm. We also outline customizable aspects of the program with the intent to have WACARDIA's algorithm expanded to accommodate more situations and applications. With this paper, we hope to encourage the practice of publicizing research software to contribute to the transparency, rigor, and reproducibility of scientific studies. WACARDIA and video tutorials are available at www.github.com/iankleckner/wacardia and http://wacardia.iankleckner.com.

A frequency control strategy with DC microgrid systems for EV stations

ABSTRACT Fluctuations in power supply and demand lead to frequency deviations, which have detrimental effects on the operation of electrical devices and equipment. Therefore, the implementation of effective frequency control mechanisms is essential for enhancing the strength and dependability of microgrid systems. Research aims to develop a frequency control mechanism for an electrical grid system that integrates both wind and photovoltaic (PV) energy sources. The proposed system utilises a Doubly Fed Induction Generator (DFIG) system with frequency controller for regulating frequency and balancing source and demand of power in the grid. To optimise the solar power output, a Luo converter is implemented, which offers high efficiency with improved conversion of power. Additionally, an adaptive neuro fuzzy inference system (ANFIS) maximum power point tracking (MPPT) controller is engaged to ensure optimal regulation of photovoltaic system. DC link obtained from the PV system is then utilised for powering DC loads and charging electric vehicles (EVs) effectively. In order to accomplish this, a bidirectional converter is used, which permits power flow in both ways and facilitates effective EV charging from the microgrid system. The validation of research is conducted on MATLAB software, and the results proves greater converter efficiency of 94.93%, with reduced total harmonic distortion (THD) of 1.24%.

Analyzing the performance of metaheuristic algorithms in speed control of brushless DC motor: Implementation and statistical comparison.

A brushless DC (BLDC) motor is likewise called an electrically commutated motor; because of its long help life, high productivity, smaller size, and higher power output, it has numerous modern applications. These motors require precise rotor orientation for longevity, as they utilize a magnet at the shaft end, detected by sensors to maintain speed control for stability. In modern apparatuses, the corresponding, primary, and subsidiary (proportional-integral) regulator is broadly utilized in controlling the speed of modern machines; however, an ideal and effective controlling strategy is constantly invited. BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. Model of the brushless DC motor using a sensorless control strategy incorporated metaheuristic algorithms is simulated on MATLAB (Matrix Laboratory)/Simulink. The Integral Square Error (ISE) criteria is used to determine the efficiency of the algorithms-based controller. In the latter part of this article after implementing these mentioned techniques a comparative analysis of their results is presented through statistical tests using SPSS (Statistical Package for Social Sciences) software. The results of statistical and analytical tests show the significant supremacy of WOA on others.

Optimization and synthesis on the dynamics performance of the tensioning and relaxing wearable system in a novel knee exoskeleton using co-simulation

Abstract In this paper, a novel tensioning and relaxing wearable system is introduced to improve the wearing comfort and load-bearing capabilities of knee exoskeletons. The research prototype of the novel system, which features a distinctive overrunning clutch drive, is presented. Through co-simulation with ANSYS, MATLAB, and SOLIDWORKS software, a comprehensive multi-objective optimization is performed to enhance the dynamics performance of the prototype. Firstly, the wearing contact stiffness of the prototype and the mechanical parameters of the relevant materials are simulated and fitted based on the principle of functional equivalence. And then, its equivalent nonlinear circumferential stiffness model is obtained. Secondly, to enhance the wearing comfort of the exoskeleton, a novel comprehensive performance evaluation index, termed wearing comfort, is introduced. The index considers multiple factors such as the duration of vibration transition, the acceleration encountered during wear, and the average pressure applied. Finally, through the utilization of this indicator, the system’s dynamics performance is optimized via multi-platform co-simulation, and the simulation results validate the effectiveness of the research method and the proposed wearable comfort index. The theoretical basis for the subsequent research on the effectiveness of prototype weight-bearing is provided.

The results of a magnetic field on flow past an inclined isothermal vertical plate with heat and varying mass diffusion

This work describes the influence of a magnetic environment on the circulation of matter and thermal energy over an accelerating advanced inclined isothermal sectional surface. The temperature is elevated to . The proximity intensity is increased to . The Laplace-transform approach is applied to solve the dimensionless analytical equation. In this research work different physical variables including thermal grashof number (Tg), mass grashof number (Tm), Schmidt number (Sc), Prandtl number(Pr), time(t), velocity profile ( ), temperature ( ), and intensity ( ) are investigated. The output of the graph produced by the Matlab software commands an energy equation, momentum equation, and concentration equation. The values are shown in an aligned pattern for a variety of flow variables. Diagrammatic representations of the fluid velocity profiles are provided. The velocity rises corresponding to different Tg and the velocity rises corresponding to different Tm. As the angle is decreased, the velocity increases differently. , As the different magnetic environment values lower, the velocity rises. Elevated values of angle ( ), Sc, Pr, and contribute to an enhancement in local skin friction, and an upsurge in Gr, Gc, and t leads to a reduction. A tabulated presentation of Nusselt quantities reveals a positive correlation with increasing Pr. Similarly, Sherwood quantities, as tabulated for various parameters, demonstrate a proportional increase with rising Sc.

Исследование влияния отклонений параметров моделей синхронных генераторов на результаты расчета динамической устойчивости электроэнергетической системы

One of the important tasks solved in planning the electric power system (EPS) operation is the assessment of its transient stability. Use of incorrect parameters for EPS element models, in particular synchronous generators (SG), contributes to the occurrence of errors when determining the operating conditions of power systems, and, therefore, can lead to a decrease in the reliability of EPS operation. This article is devoted to the study of the impact of errors in SG model parameters on the transient stability assessment results. The analysis presented in this article allows us to substantiate the relevance of the SG parameter estimation task using a “passive experiment”, such as synchronized phasor measurements. This research is based on the theory of electrical circuits, mathematical description of electrical machines and transients in EPS, as well as statistical analysis. Computational experiments have been carried out in the software package MATLAB using the simulation modeling environment “Simulink”. During the research, two different multi-machine EPS models have been used, including the well-known “IEEE 9-bus” system. To quantitatively assess the influence of SG parameter uncertainties on transient stability analysis, the values of the maximum permissible fault clearance time are determined, as well as the values of the maximum power output of generating equipment in prefault conditions. The authors have carried out a comprehensive analysis of the influence of deviations in SG model parameters on the maximum fault clearance time, as well as on the maximum power output of generating equipment in the prefault conditions for a given fault duration. During the study, two approaches have been considered; in each case, the EPS transient stability assessment has been performed almost automatically, and quantitative indicators have been computed for the influence of SG model parameter deviations on the outcome of EPS transient stability analysis. Analysis of the computational experiment results has demonstrated a significant influence of the SG model errors on the errors in calculating certain transient stability-related parameters. For the considered scenarios, the spread of errors in calculating the maximum fault clearance time reached 100 % relative to a base-case (errorless) result, and the error in calculating the maximum power output of generating equipment in prefault conditions for a given fault duration may reach 20 % relative to the errorless result.

An Optimization of RSRP on Wi-Fi and LTE-LAA Coexistence Networks

Over the last decade, mobile traffic has grown at an exponential rate, resulting in a scarcity and incompetent use of licensed spectrum by mobile network operators. Therefore, it is important to maintain effective communication to avoid disconnecting signals. The technique of regulating the power of a transmitter in order to improve the communication signal or entire quality of service is known as power control. It is mostly used to improve the performance of a communication device by controlling the transmission power. Power control, in most scenarios, allows the transmission or signal power to be scaled, leading to improved signal quality. On the other hand, power control methods are aimed at avoiding unnecessarily high-power transmission. Hence, particle swarm optimization (PSO) is a computational method for optimizing the reference signal received power (RSRP) by iteratively attempting to improve an unnecessarily high-power transmission solution in terms of a given quality measure. The objective of this research is to evaluate the optimum RSRP value and proposed ideal energy detection threshold for Wi-Fi and LTE-LAA in order to obtain fair coexistence between two networks. Thus, simulations for PSO are carried out using MATLAB software. Based on the results obtained, there are improvement in throughput for both networks after PSO implementation therefore, an ideal energy detection threshold is suitable to use in order to get fair coexistence between Wi-Fi and LTE-LAA networks. Consequently, all the results obtained will be used in following research work in order to evaluate user’s handover in various scenarios.

Brain Tumor Detection and Size Estimation using Microwave Imaging

This project focuses on developing an antenna that utilising microwave imaging technology for visualising, detecting, and estimating the size of human tumors using simulation approach. A rectangular microstrip patch antenna is chosen for its advantages of low cost, convenience, efficiency, and compactness, offering a non-ionised alternative. To meet the antenna specifications, rectangular slots are incorporated into the design. The antenna performs effectively at 7.5 GHz, exhibiting a return loss of -24.20383 dB, well below the -10 dB threshold. Placing the antenna 15 mm away from the human brain model results in a specific absorption rate (SAR) value of 0.2 W/kg for 10g, indicating its safety for brain imaging. By scanning a human head phantom with and without a tumor, the antenna captures reflected signals from different locations, enabling the generation of tumour images. A 10-mm-radius tumor is introduced to the phantom, and the unique reflected signal serves as an indicator for tumor detection, using the signal without a tumor as a reference. MATLAB software is employed for image processing, allowing the generation of tumour images and the estimation of tumor size. The simulation results demonstrate 63% accuracy in tumor size estimation. In conclusion, the antenna proves to be a safe and effective brain imaging system for tumor detection.

Development of a PID-Controlled Refrigeration System for Reduced Power Consumption

Refrigerator systems are used for food preservation as well as other applications. However, the cost of running the system is high due to rising fuel and electricity prices. Traditionally, these systems are controlled by On/Off controllers. This study proposes the use of a proportional-integral-derivative (PID) controller algorithm to reduce costs for domestic and industrial refrigeration without negatively affecting the system performance. To accomplish this, a physical model was developed, comprising a domestic refrigerator, microcontroller, and MATLAB computer software for analysis. A mathematical model of second-order lead and second-order lag transfer function was also developed for a typical refrigerator system. The physical model was connected, and open-loop temperature-time response data was collected for system modeling. In addition, Data were collected from industries namely Fan Milk Industry and Benue State University Teaching Hospital Mortuary for a robust system analysis. All data sets were imported into MATLAB's system identification toolbox to estimate model parameters. The ultimate gains, frequency, and period were determined for each feedback closed-loop model, allowing the application of Ziegler-Nichols and Tyreus-Luyben PID tuning settings. The closed-loop models were then simulated in MATLAB to evaluate system performance. Simulation results showed that the Tyreus-Luyben model performed better, and offered better temperature response, less undershoot, and faster settling time than the Zeigler-Nichols method. Both PID models outperformed the traditional On/Off controller, with energy consumption reduced to less than one-third of the conventional method. The study concludes that PID controllers are a better alternative to On/Off systems when properly tuned.

Kinetic modelling of carbothermal reduction of nickel oxide (NiO): Design of Experiments (DOE) approach

ABSTRACT This study presents a mathematical model to evaluate the kinetics of the carbothermal reduction of NiO using graphite. Based on the shrinking core theory, the model was validated against experimental data obtained under both isothermal and non-isothermal conditions. The shrinking core model for isothermal and non-isothermal conditions was created using MATLAB software for the kinetic modelling of the reduction process to determine the extent of reduction and the reaction rate. The kinetics were mathematically modelled from independently measured physical and thermodynamic properties of the reaction system and experimentally measured properties. The carbothermal reduction method was effective in producing Ni metal from NiO and was considered an established basis for evaluating the modelling aspect of the solid–gas system. The experimental investigation of carbothermal reduction was conducted using a statistical design of experiments (DOE), employing a two-level factorial design (23). The experiments were performed for a range of different factors, namely reduction temperature (800-1000°C), reduction time (1-2 h), and the molar ratio of graphite to NiO (0.5-1.5) on the extent of reduction. The extent of reduction increases with increasing reduction temperature, reduction time, and molar ratio of C to NiO. The highest extent of reduction (77.9%) was achieved at a reduction temperature of 1000°C, 2 h of reduction time, and the molar ratio of C to NiO as 1.5. The X-ray diffraction (XRD) studies confirmed the formation of Ni at a lower reduction time, but the intensity of the Ni phase was higher for a longer duration of reduction. SEM-EDS analysis of the reduced products confirmed the formation of Ni in the form of elongated and larger grains, along with traces of residual or unreacted carbon. The predicted extent of reduction is then compared with the experimentally measured results. The kinetic modelling results proved that both isothermal and non-isothermal shrinking core models showed similarity and significant closeness to the experimental data. The deviation between the experimental and model results could be due to the varying geometry and porosity of the reactants and intermediate products.

Investigation on the Optimization Strategy of DWA Algorithm for Path Planning of the USVs with the Consideration of Environmental Factors

Unmanned surface vessels (USVs) are generally subjected to wind force, wave and undercurrent action. Some unidentified objects such as underwater obstacles and submerged reefs should be monitored and evaded with converged communication, autonomous control and network system so as to achieve autonomous and automatic avoidance of danger and real-time control of flight path. Next, based on performing interference mechanics analysis on the USVs under the disturbance of wind force and wave on water surface, the relationship parameters between the bow angle, the deviation angle, safety evaluation function and the external force were obtained, and the comprehensive information of water surface environment was evaluated in combination with the dynamic window approach (DWA) algorithm. Further, the related model was established for simulation by using the simulation software MATLAB, and both reliability and stability of the modified DWA algorithm were designed and examined. Accordingly, the modified DWA algorithm can enhance the safety of the USVs in autonomous path planning and achieve rapid obstacle avoidance and autonomous path planning of the USVs. Our simulation revealed that the modified DWA algorithm can safely and rapidly correct the bow angle and the deviation angle, optimize the path trajectory and reduce the risk of roll-over of the USVs under sudden external force.

Heat Transfer Characteristics of a Quiescent Fluid over a Moving Flat Surface

Optimizing thermal control methods and enhancing the efficiency of various engineering processes, such as the cooling of hot moving surfaces, is imperative. Therefore, it is crucial to investigate heat transfer and temperature distributions across moving surfaces in stationary fluids. In this study, the combined effects of viscous dissipation, temperature-dependent viscosity, and a moving surface in a quiescent fluid on the temperature and velocity profiles are investigated. A two-dimensional steady laminar boundary layer flow of an incompressible Newtonian fluid, driven by the movement of the surface where viscosity is an inverse function of temperature, is analyzed. The effects of flow parameters, including Reynolds number, Eckert number, Prandtl number, variable viscosity, and surface velocity on temperature and velocity profiles, are determined. The governing boundary layer partial differential equations are transformed into non-dimensional form and solved using the central finite difference numerical method, implemented in MATLAB software. The numerical results demonstrate that an increase in the Reynolds number and the variable viscosity parameter leads to an increase in the velocity profiles. Additionally, an increase in Reynolds number, Prandtl number, variable viscosity, and surface velocity leads to a decrease in temperature profiles. Finally, an increase in the Eckert number results in higher temperature profiles. Therefore, with suitable flow parameters, the temperature of the fluid can be regulated. These findings are useful in cooling hot sheets or metallic plates drawn over a quiescent fluid to obtain high-quality final products.