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In view of the problems such as too many times of rejected tasks and waste of resources in fault - tolerant fair scheduling FT-FS(Fault Tolerate Fair Scheduler) algorithm, a new fair scheduling algorithm PA - FTFS (Primary Alternate and Fault Tolerant Fair Scheduling) is proposed based on FT-FS algorithm by integrating the main/alternative PA (Primary Alternate) fault-tolerant strategy. This algorithm can reduce the number of rejected tasks in multi core processor system and reduce the waste of resources. MATLAB simulation software is used to verify the above algorithms. The experimental results show that PA-FTFS algorithm using proportional replacement task strategy has significantly reduced the number of task rejection times compared with FT - FS algorithm after permanent kernel failure. Data analysis shows that PA-FTFS algorithm has better failure rate and scheduling rate than FT-FS algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xihua University (Natural Science Edition) is the property of Xihua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to examine the 5G enhancement, this work generates a variety of Filtered-Orthogonal Frequency Division Multiplexing (F-OFDM) waveforms. Windowed-Sinc filters are studied to deploy waveforms in real time. The Blackman-Harris window and the Bohman window have been combined to create a new window, which has been studied. Waveforms built utilizing this window have been compared to traditional Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) waveforms using the MATLAB evaluation package. Data from simulations reveals a number of tradeoffs between bit error rate (BER) and power spectral density. The designer, however, has some leeway in how the window is used. However, BER and power spectral density (PSD) measurements demonstrate that the windows chosen for this work nearly outperform the CP-OFDM signal. Compared to the central lobe, the sidelobe PSD of CP-OFDM is found to be close to -50dBW/Hz. However, -214.177 dBW/Hz is the value obtained for the new-window. [ABSTRACT FROM AUTHOR]

Abstract This study introduces three soft computing (SC) optimization algorithms aimed at enhancing the efficiency of photovoltaic water pumping systems (PVWPS). These algorithms include the Gorilla Troop Algorithm (GTO), Honey Badger Algorithm (HBA), and Snake Algorithm (SAO). The goal of the SC optimizers is to maximize the output power of the PV array (P PV ) and enhance the efficiency of the DC motor (η), thereby optimizing the water flow rate (Q) of the pumping system. The analytical modeling approach proposed in this study involves forecasting the optimal duty cycle (D op ) for a buck-boost converter, taking into account variables such as solar radiation (G) and ambient temperature (T). A comparative analysis is conducted between the suggested SC optimizers and analytical modeling. MATLAB simulation is employed to explore an adaptive neuro-fuzzy inference system (ANFIS) trained for the proposed system. The objective is to assess system performance and accuracy. Findings indicate a strong convergence between the analytical model and the simulation model utilizing SC optimizers. Moreover, the neuro-fuzzy system trained offline, coupled with the proposed SC optimizers, demonstrates superior performance compared to traditional control methods like perturb and observe (P&O) and incremental conductance (IC). This superiority is evident across various metrics including motor efficiency (η), photovoltaic (PV) output power (P PV ), water flow rate (Q), and time response.

[Objective] To meet the requirements of constant and adjustable rotation speed of rolling barrel and constant rotation speed of rolling barrel when tea is rolled. [Methods] The 6CR-55 single-column disc twisting machine was used as the research object in this paper. Fuzzy control algorithm and PWM closed-loop control method were investigated to study the stable control of rotating speed of rolling drum, and established the mathematical model of rotating speed control system of rolling drum based on the STM32 single-chip microcontroller. The simulation experiments of uncorrected, PID and fuzzy PID algorithm control system were carried out by MATLAB. [Results] Compared with uncorrected control and PID control, the output speed of the fuzzy PID speed control system was more stable and accurate, and the anti-interference ability was stronger. The speed error was controlled within 3 r/min. [Conclusion] The fuzzy PID control method can meet the requirement for the constant and adjustable rotating speed of the rolling drum during tea rolling, and improve the rate of tea forming and cell breakage.

Featured Application: A novel active range while drilling method, based on the drilling well, with dual-electrode current excitation, is proposed. The range while drilling model utilizing dual-electrode current excitation is established, and the calculation methods for the current amplitude of the casing and the formation-induced magnetic field distribution are derived. The accuracy and effectiveness of this approach are validated through numerical calculations and simulation analyses of the impact of each key factor. It is particularly appropriate for targeted well ranging operations that entail safety risks, especially in the relief well connectivity operations at space-constrained drilling platforms. Based on a comprehensive analysis of the existing methods for measuring adjacent well distances, along with their advantages and disadvantages, this study employs theoretical analysis, simulation experiments, and other comprehensive research methods to investigate a distance measurement method based on current excitation. In response to the need for measuring and controlling the connection of relief wells, a method utilizing dual-electrode current excitation during drilling is proposed. This approach facilitates synchronous excitation measurements while drilling, significantly reducing both time and costs while ensuring safety and efficiency, making it particularly suitable for the connection operation of relief wells that involve safety risks. Firstly, this paper establishes a drilling with measurement model corresponding to the excitation mode, which derives the calculation formulas for the target casing current amplitude attenuation, as well as the induced magnetic field distribution within the formation. Additionally, it provides the calculation methods for determining the target well distance and azimuth direction. Lastly, the impact levels of various key factors are verified through numerical calculations and simulation analyses, which confirm the correctness and effectiveness of this distance measurement method. The findings from this research establish both a core theoretical foundation and a technological basis for the real-time measurement of adjacent well distances during relief well operations. [ABSTRACT FROM AUTHOR]

ABSTRACT This study delves into the advancements, challenges, and opportunities in the solar grid technology, emphasizing its integration into the existing power infrastructure. The proposed ML‐FOGI (multilayer fourth‐order generalized integrator) algorithm presents a promising solution for modern grid synchronization requirements, addressing challenges posed by the integration of renewable energy into the distributed generation. This technology enhances system robustness and dynamic response, particularly in weak distribution grids characterized by voltage distortions and imbalances. This innovative approach enhances system stability and performance, particularly in polluted grid conditions. Through MATLAB/Simulink modelling and experimental validation, the effectiveness of the proposed control strategy is investigated across diverse testing conditions. Emphasizing the significant role of the control strategy in enhancing power quality and grid stability in the solar photovoltaic systems, this research underscores the importance of robust and adaptive control mechanisms for optimizing performance and ensuring grid reliability in modern microgrid. This study delves into this complex issue of working of the grid connected photovoltaic (GCPV) system, emphasizing the importance of balanced unit templates and a stable DC link voltage with unpredictable grid harmonics. This research aims to enhance the resilience of solar PV systems against grid disturbances by drawing inspiration from the adaptable nature of ADALINE filters and adhering to the IEEE519 requirements. This study employs OPAL‐RT's resilient experimental configuration. [ABSTRACT FROM AUTHOR]

This study proposes intelligent control strategies for optimizing the grid integration of photovoltaic (PV) and wind energy in hybrid systems using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS control aims to enhance grid stability, improve power management, and maximize renewable energy (RE) utilization. The hybrid system's performance is evaluated through simulations, considering various environmental conditions and load demands. Results demonstrate the effectiveness of the proposed ANFIS-based control in dynamically adjusting the power output from PV and wind sources, ensuring efficient grid-connected operation. The findings underscore the potential of intelligent control strategies to contribute to the reliable and sustainable integration of RE into the grid. [ABSTRACT FROM AUTHOR]

In order to solve the issue of less automated orchard hedge trimming tools, high labor intensity of trimming operations, and low work efficiency, a practical hydraulic driven four-degree-of-freedom trimming manipulator was designed according to the requirements for orchard hedge trimming operations, and the motion range of each joint was determined. Based on the standard D-H parameter method, the coordinate systems of each link of the manipulator were established, and the forward and inverse kinematics calculations of the manipulator were completed. A kinematic model of the manipulator was established using the MATLAB Robotics Toolbox, and the forward and inverse kinematics of the manipulator, as well as the motion trajectories of each joint, and the angular displacement curves, angular velocity curves, and angular acceleration curves of each joint of the manipulator during the trimming of the top and side of the hedge were simulated and verified. In addition, the workspace of the manipulator was simulated and analyzed by using the Monte Carlo method, thus 3D and planar cloud images of the workspace were calculated. Finally, an experimental prototype was produced for trimming testing. The research results show that the correctness of the forward and inverse kinematics solutions of the manipulator are verified, and the designed end effector of the manipulator can fully reach the desired trimming target position. The experimental results of the trimming machine prototype are consistent with expectations. The joints of the manipulator move smoothly during operation, with high trimming efficiency and good results, which can meet the automatic trimming requirements for medium and high hedge, and greatly reduce the labor intensity of trimming operations. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Phase unwrapping technology can reflect the true phase information of an image, but it is affected by adverse factors such as noise, shadows, and fractures when extracting the true phase information of an object. Therefore, corresponding unwrapping algorithms need to be studied for different interference images. This paper summarizes and analyzes various phase unwrapping algorithms and ultimately selects the required method based on their advantages and disadvantages. Using the four-step phase-shift method to reconstruct the phase of the optical field and then combining it with the least squares method to unwrap the phase through multiple improvement iterations, the simulated collected interference fringe images are simulated using the MATLAB program to complete the phase unwrapping of the interference information field. Based on the analysis of the final experimental results, the reliability of this research method was verified. [ABSTRACT FROM AUTHOR]

In order to solve the problems of long adjustment time and poor stability of the commonly used speed current variable frequency negative feedback speed control system in engineering, the author proposes an improved fish school algorithm application method in variable frequency speed control systems. A fish swarm algorithm optimized based on the arena method is applied to a variable frequency speed control system, and the optimization algorithm is applied to the speed control system to screen the PI parameters that meet the requirements of the speed control system. The simulation results show that compared with manual parameter tuning, the controller parameters optimized by the improved fish school algorithm have better control performance. In the absence of overshoot starting, the starting time was shortened by 0.21s, and the system response speed was improved. When a sudden load of 6 N m is applied, the speed drop is reduced by 3 r · min−1, and the recovery time is shortened by 0.15 s, resulting in stronger anti-interference performance of the system. Conclusion: The new algorithm shortens the control time and improves the robustness of the system.

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

These days, one of the most used layouts in the wind power industry is a variable-speed doubly-fed induction wind generator (DFIWG). For providing active power (P) and reactive power (Q) control during grid failures, this research examines the DFIWG. The system's transient behavior is examined under normal and abnormal circumstances. Through control of rotor side (RSC) and grid side (GSC) converters, Q assistance for the grid, and power converter stress reduction, the suggested control approach achieves system stability while enabling DFIWG to operate smoothly during grid failures. The DFIWG is exposed to three- and two-phase faults to analyze the machine's performance. The crowbar and STATCOM tools are implemented to enhance the system performance under faults and compared with the base case. The implemented tools successfully suppress rotor and stator overcurrent, over voltage at the DC link (DCL), and power oscillations, as well as supporting the grid voltage understudied cases. The obtained results prove that both STATCOM and crowbar not only enhance the system's effectiveness and performance but also enable the system to achieve the fault ride-through capacity (FRTC). MATLAB/SIMULINK 2017b is used for time-domain computer simulations. [ABSTRACT FROM AUTHOR]

One of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits. The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement. [ABSTRACT FROM AUTHOR]

The practices of prefabricated buildings illustrate the incentives in prefabricated markets as well as the decision-making behavior of stakeholders, which can influence the transformation, upgrading, and sustainability of the buildings sector. The game between the stakeholders in the prefabricated buildings market becomes complicated by the fact that they dynamically adjust their strategies in response to changing market conditions. With the aim of quantitatively studying the implications of the dynamic decision behavior of prefabricated construction stakeholders on the prefabricated construction market, this study introduces component suppliers as participating agents and government subsidies and penalties as the main measures. And a three-way model of the evolutionary game involving government subsidies and punitive schemes is constructed by this study. The essay examines the evolutionary equilibrium strategies of each game subject as well as the effect of original strategies and different parameter choices on the decision-making of each subject using MATLAB. The findings reveal that (1) decision-making behaviors among the government, component suppliers, and developers are both interrelated and constrained, but governments are the dominant agents in the evolution of prefabricated buildings. (2) Parameters such as subsidies, penalties, costs, and benefits affect the stability of the tripartite evolutionary model, which remains consistent with the previous research. (3) Component suppliers have an equally important position in the development of prefabricated buildings as recognized entities such as developers and contractors. (4) When subsidies are kept at 40% of the incremental cost and penalties at 80% of the incremental cost, the model combines a fast evolutionary rate with stable model evolution. In conclusion, the article's research findings not only validate the rationality and feasibility of component suppliers as research subjects and confirm the importance of component suppliers but also propose a more reasonable boundary value for penalties and subsidies, which provides a reference for the government to improve the incentive and punishment measures as well as the dynamic adjustment strategy of stakeholders and also provides a new perspective to achieve the goal of sustainable development of construction. [ABSTRACT FROM AUTHOR]

The efficient placement of Phasor Measurement Units (PMUs) is crucial to minimize their number while ensuring full power system observability. A power system is deemed observable when the voltage at every bus is known. This study proposes a topology transformation approach that combines a Zero-Injection Bus (ZIB) with one of its neighboring buses to achieve optimal PMU placement. The choice of the neighboring bus for combination with the ZIB significantly influences the outcome of the merging process. To identify the optimal candidate bus for merging with the ZIB, the proposed approach utilizes three selection principles aimed at determining the minimal number of PMUs necessary for complete system observability. This study also examines the scenario of power flow measurements, formulating the problem using Integer Linear Programming (ILP). The effectiveness of the proposed method is demonstrated through simulations conducted in MATLAB on various IEEE Bus systems, with a detailed explanation provided using the IEEE 14-Bus system. Comparative analysis reveals that the number of PMUs obtained with the suggested method is competitive with existing techniques. Furthermore, this study includes a comparison between the IEEE 30-Bus and IEEE 14-Bus systems by inducing faults at specific buses. This is done to verify whether PMUs placed at optimal locations ensure complete coverage of all buses in both systems. The comparison also extends to evaluating the cost implications of placing PMUs solely at these optimal locations. [ABSTRACT FROM AUTHOR]

As electric vehicles (EVs) gain momentum in the shift towards sustainable transportation, the efficiency and reliability of energy storage systems become paramount. Lithium-ion batteries stand at the forefront of this transition, necessitating sophisticated battery management systems (BMS) to enhance their performance and lifespan. This research presents an innovative simulation of a 4S3P lithium-ion battery pack using MATLAB R2023b, designed to refine BMS capabilities by employing advanced mathematical modelling and computational intelligence. The simulation meticulously analyses critical operational metrics such as state of charge (SOC), state of health (SOH), temperature variations, and electrical behaviour under diverse load scenarios, offering deep insights into the intricate dynamics of lithium-ion batteries in EV applications. The results corroborate the simulation model's accuracy in reflecting actual battery pack performance and underscore significant improvements in BMS strategies, especially concerning predictive maintenance and adaptive charging techniques. By seamlessly integrating computational intelligence into BMS, this study lays the groundwork for more durable, efficient, and intelligent energy storage systems in electric vehicles, marking a significant stride in e-mobility technology. [ABSTRACT FROM AUTHOR]

Wireless power transfer (WPT) technology is a contactless wireless energy transfer method with wide-ranging applications in fields such as smart homes, the Internet of Things (IoT), and electric vehicles. Achieving optimal efficiency in wireless power transfer systems has been a key research focus. In this paper, we propose a tracking method based on full current mode impedance matching for optimizing wireless power transfer efficiency. This method enables efficiency tracking in WPT systems and seamless switching between continuous conduction mode and discontinuous mode, expanding the detection capabilities of the wireless power transfer system. MATLAB was used to simulate the proposed method and validate its feasibility and effectiveness. Based on the simulation results, the proposed method ensures optimal efficiency tracking in wireless power transfer systems while extending detection capabilities, offering practical value and potential for widespread applications. [ABSTRACT FROM AUTHOR]

Considering the fact that ships at sea will be affected by waves, sea breeze and air currents, which usually results in serious interference of equipment that needs to work in a stable environment, such as lifting platforms, radar signal capture, etc. In response to the above problems, the S-RPS-SPS parallel mechanism is established to stabilize the platform. It can realize the roll angle of the rotation around the X axis and the pitch angle of rotation around the Y axis; it can also indirectly eliminate the rotation of the hull on these two axes. Model this parallel mechanism in Solidworks software and verify the degrees of freedom. The relation between the length of two driving rods and the pose angle of the moving platform is calculated by the method of inverse pose solution. Two sets of data are obtained by inputting different angles in the range of the rotating angle of the moving platform and the expansion length of the driving rod. The calculation formula, rotation angle range and coordinates are simulated by algorithms in Matlab software, and the correctness of the moving platform pose is verified. The simulation results show that the accuracy and reliability of this mechanism in terms of kinematics are well guaranteed.

Fan power generation, a form of new energy, has gained significant attention. However, as fan capacities grow, the challenges in the development process also increase. A wind maneuver model experiment system must be constructed to simulate the actual fan operation dynamics. The wind turbine simulator is essential for conducting experiments on wind turbines and advancing the research of wind power production technology. However, due to the insufficient moment of inertia in wind turbine simulators under laboratory conditions, physical compensation methods are challenging to implement. Therefore, most scholars rely on software compensation algorithms to realize the stability simulation of wind turbine simulators with small moments of inertia and actual wind turbines with large moments of inertia. Under this research background, this paper presents the existing moment of inertia compensation strategies based on current research hotspots. The theoretical foundation covers the mechanical dynamic models of both actual wind turbines and simulators along with an analysis of inertia compensation strategies, including high-order filters and feedforward bias suppression. Finally, the Simulink simulation platform is used to compare and validate the effectiveness of these strategies.

In this study, a MATLAB simulation model was developed for the purpose of calculating the energy dissipation of runoff over submersible dams. A laboratory model of a submersible dam with standard dimensions was used, and two angles of inclination of the dam surface 16° and 24.5° were used downstream. In the laboratory work, the discharge and water depth were measured, in addition to the length of the hydraulic jump and the distance from the source, and by using the basic flow equations, the percentage of flow energy dissipation was calculated for both models, and the discharges were counted. The values of the Froude number ranged from 3.612 to 10.784. A simulation model was built in the MATLAB program using the basic equations of flow, finding the values of energy dissipation percentage and comparing them with the laboratory results. Then drawing the relationships between each of the discharge (Q), energy dissipation percentage (E%), Froude number (Fr), hydraulic jump length (Lj), and the distance of the hydraulic jump from the submerged dam (Dj). The numerical and experimental data have been compared, and it has been determined that there is an acceptable agreement between them. The results also showed the efficiency of using the MATLAB simulation method to obtain accurate and fast results. [ABSTRACT FROM AUTHOR]

In order to achieve accurate transmission of protection signals in fiber optic communication networks, it is necessary to perform channel balancing configuration of fiber optic communication networks and adaptive forwarding control processing of relay protection signals, the author proposes an accurate transmission method for relay protection signals in fiber optic communication networks based on time-varying multipath fading suppression and adaptive beamforming. The system analyzes the sources of wireless long-distance pain signal interference signals, introduces anti-interference technologies such as two-dimensional joint processing (STAP), provides anti-interference algorithms and related gain analysis, and conducts signal processing gain simulation using MATLAB. Based on the analysis of comprehensive simulation results, at a given symbol length, the signal bandwidth increases, and the processing gain infinitely approaches the given theoretical limit value, rather than increasing nonlinearly. The reason is that the channel is affected by noise, and the channel estimation value and signal conjugate multiplication produce a noise quadratic term. At this point, the estimated value of the coherent region channel is reduced by the influence of noise, and the signal-to-noise ratio loss caused by the noise quadratic term is reduced, so the processing gain increases. During the process of infinite increase in signal bandwidth, the input signal-to-noise power ratio of the receiver tends to decrease towards an infinite value, limited by the size of the coherent region. The channel estimation value increases under the influence of noise, and the noise quadratic term is the main factor affecting the output noise power. When the symbol length is greater than the coherent time, the smaller the maximum Doppler frequency shift and the larger the coherent detection area, the greater the processing gain. [ABSTRACT FROM AUTHOR]

In view of the traditional agricultural irrigation in hills and mountains, which usually uses artificial control solenoid valve for irrigation, the problems of water waste and high labor cost has come into being. A set of automatic irrigation control system based on fuzzy control and PID control is designed. The stability of PID control and adaptability of fuzzy control are combined to control irrigation time. The irrigation system of hills and mountains built by Simulink is controlled by conventional PID and fuzzy PID respectively. The simulation experiments show that compared with the conventional PID control, the fuzzy PID control system has significantly reduced overshoot and adjustment time, and has higher stability, adaptability and adjustment performance. It can be used in the automatic irrigation system of hilly and mountainous agriculture. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents the development and examination of a streamlined $H_{\infty }$ loop-shaping continuous-time controller tailored for nonlinear Hard Disk Drive (HDD) systems. Using the Hankel-norm approximation technique, the complexity of the controller is systematically reduced, emphasizing preserving the system’s efficacy while enhancing computational efficiency. The dynamics of the HDD system and the performance of the proposed controller are investigated through MATLAB simulations. The effectiveness of the controller is quantitatively measured by employing the ITAE (Integral of Time multiplied by Absolute Error) criterion. The results indicate that a controller of the 10th-order provides a desirable compromise between maintaining robust control and minimizing disturbances and noise without significant loss in performance. This method illustrates the capacity for implementing more straightforward controllers in complex HDD systems, paving the way for their application in precision-critical industrial settings.

Based on a comprehensive analysis of the existing methods for measuring adjacent well distances, along with their advantages and disadvantages, this study employs theoretical analysis, simulation experiments, and other comprehensive research methods to investigate a distance measurement method based on current excitation. In response to the need for measuring and controlling the connection of relief wells, a method utilizing dual-electrode current excitation during drilling is proposed. This approach facilitates synchronous excitation measurements while drilling, significantly reducing both time and costs while ensuring safety and efficiency, making it particularly suitable for the connection operation of relief wells that involve safety risks. Firstly, this paper establishes a drilling with measurement model corresponding to the excitation mode, which derives the calculation formulas for the target casing current amplitude attenuation, as well as the induced magnetic field distribution within the formation. Additionally, it provides the calculation methods for determining the target well distance and azimuth direction. Lastly, the impact levels of various key factors are verified through numerical calculations and simulation analyses, which confirm the correctness and effectiveness of this distance measurement method. The findings from this research establish both a core theoretical foundation and a technological basis for the real-time measurement of adjacent well distances during relief well operations.

Background The escalating global population, surpassing seven billion in 2012, amplifies the strain on existing resources for food, housing, and conventional energy. Addressing these challenges requires the development of economically and environmentally viable renewable energy technologies. Photovoltaic (PV) solar modules stand out for their eco-friendly operation and reliability. In off-grid communities, stand-alone PV systems, coupled with battery storage, play a pivotal role in meeting electrical energy needs. Methods This study enhances the understanding of stand-alone PV systems through modeling and simulation using MATLAB software. A multi-crystalline PV system, specifically the Kyocera KC130GT, is investigated under varying conditions, and a pulse width modulation (PWM) controller is employed for battery charging. Results The study reveals profound effects on energy production based on the I-V and P-V characteristics of the modeled system when a PWM controller is utilized. The system demonstrates successful energy generation under different conditions, accounting for temperature variations and PV battery voltage mismatches. Conclusion The simulated model serves as a versatile system capable of detecting different conditions in varying light and temperature scenarios. Effective temperature monitoring, voltage adjustment using a suitable charger controller, and the selection of optimal materials for solar modules can significantly enhance the system’s efficiency. The results emphasize the importance of careful consideration of PV system sizing corresponding to battery capacity for improved solar system efficiency. While the cost of the modeled stand-alone PV system is currently low, scalability to larger projects may incur increased costs due to the high prices of photovoltaic panels, batteries, and other components.

For the voltage stability enhancement of power system, the reactive power compensation is vital important. With the advancement in technology, the Flexible AC Transmission System Devices (FACTS) are widely used for stability improvement. In the primary substation, the stability is poor due to load conditions and system faults. In this research, the voltage stability enhancement for a Primary Substation using Static VAR (volt-amp reactive) compensator (SVC) is presented. SVC can be used to improve system voltage stability and addition of damping control. With the application of SVC, the voltage stability can be improved under normal condition as well as under contingency conditions. Shunt reactive power sources, including capacitive and inductive, are controlled by high power electronic switching devices in an SVC to enhance voltage stability. The goal of this attempt is to use SVC to improve the voltage stability of the 230/33 kV system. To evaluate the voltage stability improvement by SVC, a simulation model is implemented in Matlab/Simulink and performance analysis are carried out based on the simulation results.

Growing demand for renewable and sustainable energy sources has prompted research into bioethanol production as a viable alternative to hydrocarbon fuel for automobile engines. Based on their high carbohydrate content, Chlorella vulgaris microalgae were chosen for this study as a feasible biomass for bioethanol synthesis. After conducting microwave-based acid hydrolysis with varying acid concentrations of sulfuric acid (H2SO4) for 1–15 min, this study found that 3% H2SO4 for 5 min yielded the highest yield of reducing sugar (6.77 g/L). In this work, the RSM approach of central composite design (CCD) was utilized for modeling and optimization of ethanol fermentation and the MATLAB Simulink approach was employed for the simulation of ethanol fermentation. This study compared the effects of using Saccharomyces cerevisiae yeast for fermentation at different fermentation times (12 to 48 h), temperatures (28 to 32°C), and size of inoculum (0.5–1.5 g/L). Based on the actual and predicted results, the best conditions for fermentation were 36 h of time, 30°C of temperature, and 1.5 g/L of inoculum size. This gave the maximum ethanol concentration of 3.31 g/L. Furthermore, the RSM method provides minimum error and maximum R² value results for ethanol production compared to MATLAB simulation prediction (MSP). In addition, residue biomass from biofuel production is evaluated for its suitability for a further form of biofuel production. This research explores the opportunities for zero-waste biomass utilization in the development of biofuels. [ABSTRACT FROM AUTHOR]

This paper explores the potential of bifacial solar panels in desert environments, focusing on their integration with Artificial Intelligence (AI) for optimal energy generation. Bifacial panels, capturing sunlight from both sides, are well-suited for high-albedo desert regions but face challenges such as dust accumulation, high temperatures, and wind resistance. This paper will examine the role of AI-driven optimization systems in improving solar panel efficiency and their integration with Smart Cyber-Physical Systems (CPS) in agriculture and industry. To address existing research gaps, the proposed solutions include AI-based cleaning mechanisms, advanced cooling systems, and enhanced machine learning algorithms tailored for extreme environmental conditions. [ABSTRACT FROM AUTHOR]

Due to its long-range detection capabilities and resilience in a variety of weather conditions, radar technology is essential for Autonomous Vehicles (AVs) which are managed by Advanced Driver-Assistance Systems (ADAS). This review addresses critical aspects to enhance object detection in autonomous vehicles, focusing on the integration of radar systems with other sensor technologies such as LiDAR and cameras. By examining recent advancements in radar signal processing and machine learning algorithms, this review highlights the improvements in detection accuracy and reliability. Additionally, it discusses the challenges of radar interference and proposes potential solutions to mitigate these issues. [ABSTRACT FROM AUTHOR]

The location of Low-Altitude Flight Service Station (LAFSS) is a comprehensive decision work, and it is also a multi-objective optimization problem (MOOP) with constraints. As a swarm intelligence search algorithm for solving constrained MOOP, the Immune Algorithm (IA) retains the excellent characteristics of genetic algorithm. Using some characteristic information or knowledge of the problem selectively and purposefully, the degradation phenomenon in the optimization process can be suppressed and the global optimum can be achieved. However, due to the large range involved in the low-altitude transition flight, the geographical characteristics, economic level and service requirements among the candidate stations in the corridor are quite different, and the operational safety and service efficiency are interrelated and conflict with each other. And all objectives cannot be optimal. Therefore, this article proposes a Modified Immune Algorithm (MIA) with two-layer response to solve the constrained multi-objective location mathematical model of LAFSS. The first layer uses the demand track as the cell membrane positioning pattern recognition service response distance to trigger the innate immunity to achieve the basic requirements of security service coverage. In the second layer, the expansion and upgrading of adjacent candidate sites are compared to the pathogen's effector, and the adaptive immunity is directly or indirectly triggered again through the cloning, mutation and reproduction between candidate sites to realize the multiobjective equilibrium of the scheme. Taking 486,000 km2 of Sichuan Province as an example, MIA for LAFSS is simulated by the MATLAB platform. Based on the Spring open source application framework of Java platform, the cesiumjs map data is called through easyui, and the visualization of site selection scheme is presented with the terrain data of Map World as the background. The experimental results show that, compared with dynamic programming and ordinary immunization, the immune trigger mode of double response and the improved algorithm of operation parameter combination designed by the Taguchi experiment, the total economic cost of location selection is reduced by 26.4%, the service response time is reduced by 25%, the repeat coverage rate is reduced by 29.5% and the effective service area is increased by 17.5%. The security risk, service efficiency and location cost are balanced. The present work is to provide an effective location method for the layout number and location of local transfer flight service stations. For complex scenes with larger scale of low-altitude flight supply and demand and larger terrain changes in the region, the above research methods can be used to effectively split and reduce the dimension. [ABSTRACT FROM AUTHOR]