Load Conditions Research Articles

Molecular dynamics simulation of friction in DLC films with different Cr doping levels

This study systematically investigates the impact of varying Cr doping levels on the friction properties of DLC films using molecular dynamics simulations. The results demonstrate that under identical friction velocities and load conditions, the friction force of DLC films significantly decreases when the Cr doping content reaches 16.5 %. High Cr doping levels lead to the formation of Cr atomic clusters at the interface, hindering contact and reducing the number of interface bonds. These clusters act as lubricants, filling the interface gaps and thereby reducing the friction force. Internal stress calculations indicate that Cr doping effectively reduces the average internal stress of DLC films. For DLC films with lower Cr doping levels, the friction force exhibits similar trends under different friction velocities, while films with higher Cr doping levels show a more pronounced response, with friction force increasing at higher velocities. Increasing the load significantly raises the friction force, especially for DLC films with higher Cr doping levels. Furthermore, high Cr doping levels under high loads lead to significant structural damage and adhesive wear. This study provides theoretical and technical references for optimizing the friction performance of DLC films.

Augmented Reality Control based Energy Management System for Residence

Introduction: The roots of virtual reality (VR) go back to the work of Ivan Sutherland in the 1960s. At the time, virtual reality showed promise in universities and labs, peaking in the early 1990s at a stable level. The latest form of IoT is merging with the Internet of Everything (IOE). Using this technology, users can access any device, device, and machine in the environment through any middleware application or system. In recent years, smart speakers have become a common commercial method for controlling household appliances, solving some of the problems of remote control. For example, speech recognition is difficult in noisy environments and is minimized using noise cancellation. It also takes a long time to determine the current state of the device as the user need to request or issue a command to the smart speaker and need to wait for a response. The evaluation of prototype system found, using a device with gestures and interacting with a virtual 3D device instead of a real device was acceptable in terms of usability. In this article, the Unity and Vuforia are used to create an AR-based IoT virtual switch that can control any device connected to a LAN controller via HTTP requests. Methods: The system is made experimental with the Augmented Reality (AR), the virtual communication system is designed instead of physical mode. It provide the real time based image for active control of Energy management. It consist of virtual switches, it supports the AR based power control system. Results: The proposed system are made evaluated and tested under various load conditions. The virtual image consist of virtual switches to make real time control of power equipment. The proposed system achieve the latency of about 0.06 sec. Conclusion: The advancement in day today activities required with AR based energy management system with proper control measures. The designed system is supportive for such mechanism. The further system is proposed to make more energy saving concept for enhancement in proposed work.

ChatEV: Predicting electric vehicle charging demand as natural language processing

The increasing popularity of electric vehicles (EVs) in recent times has introduced considerable load conditions for urban power grids and transportation systems, which highlights the importance of accurately predicting charging demand to enhance charging efficiency. However, current forecasting methods still face challenges in effectively aligning diverse data and generating accurate predictions that can be applied to unseen scenarios. To overcome the challenges, this work introduces a novel perspective: employing large language models (LLMs) as EV charging demand predictors. First, we reformulate the prediction task into a text-to-text format, enabling seamless and effective alignment of various features within a unified language semantic space. Subsequently, we fine-tune a LLM using a meta-learning framework to adapt it specifically for EV charging prediction. Through comprehensive evaluations, it has been demonstrated that the proposed model, ChatEV, achieves outstanding performance in EV charging demand forecasting, particularly in scenarios with limited data.

Dynamic responses of monopile offshore wind turbines under different wind-wave misalignment angles

Wind-wave misalignment is a common occurrence for monopile offshore wind turbines during extreme typhoon conditions. This phenomenon has a significant impact on the structural dynamic response of turbine structures and poses a threat to their structural integrity. In this study, finite element analysis is conducted on 75 sets of working conditions of monopile offshore wind turbines to investigate their dynamic response under different wind turbine operating states, wind-wave misalignment angles, and randomness of wind and wave load conditions. The results of the analysis indicate that the impact of wind-wave misalignment angles on the dynamic response of the monopile offshore wind turbine varies depending on the operational conditions. Furthermore, the study reveals that there are variations in the dynamic response of the monopile offshore wind turbine under different combinations of wind and wave loads. During the parked state and yaw system fault of the monopile offshore wind turbine, the most adverse working conditions need to consider wind-wave misalignment angles of 0° and 180°. In contrast, the most adverse working conditions for operational states emerge when the wind-wave misalignment angle is 90°. These findings highlight the importance of considering wind-wave misalignment angles and the randomness of wind and wave load conditions when assessing the dynamic response and structural integrity of monopile offshore wind turbines.

Investigation of Fiber Bragg Grating Sensor Measurability in Concrete Beams under Static Load Conditions

Investigation of Fiber Bragg Grating Sensor Measurability in Concrete Beams under Static Load Conditions

Static and Thermal Analysis of Internal Combustion Engine Valves

Abstract: In this paper the 3D model of the internal combustion engine valves was realized using Autodesk Inventor Professional 2024 and finite element analysis, static and thermal was performed, in order to determine the state of stress, deformation and temperature evolution, by applying restrictions and loads conditions. Two materials were chosen, for internal combustion engine valves, in accordance with the specialized literature. The materials taken for static and thermal analysis was Stainless Steel AISI 446 and NiCr0TiAl. Following the comparative study for the two models, it can be specified the importance of the material for the construction of the internal combustion engine valves who depends on the material properties and their design.

Artificial Neural Network-Based Hybrid Controller for Electric Vehicle Applications

Power management among different energy sources of electric vehicles (EV) is one of the complex issues during the transition from one to another. A specific control is modeled based on the current and speed range of the electric motor named as Measurement of Parameter-Based Controller (MPBC), which will play a key role during transition of energy sources as per the load requirement. Two bidirectional converters are utilized to control the pulse signals generated by the traditional controllers which are connected at the battery and Supercapacitors (SCap) ends, which are treated as passive sources of the system. The Controller's artificial neural network (ANN), fuzzy logic (FLC), and proportional-integral (PI) are utilized to generate the pulse signal to the switches present in the converters by load. Further, specific controller MPBC is combined with three controllers ANN/FLC/PI individually and obtained three separate hybrid controllers as per the proposed control technique. The MPBC+PI/FLC/ANN controller-based MATLAB/Simulink model was designed, and applied to the electric motor individually at different load conditions. This model considered three different power delivery states from the PV array and assessed the motor's performance under different load scenarios. Compare the three hybrid controllers' final results to find out which one is more effective than the others.

Research of the distribution symmetrical components in an electrical system with a diesel generator at an unsymmetrical load

Purpose. Investigation symmetrical components of current and voltage in microgrid elements with an autonomous synchronous generator of limited power, which works in parallel with a network transformer under the condition of non-metric load. Methodology. During the research, visual programming methods were used in the Simulink/Matlab package, methods of electrical engineering theory in terms of determining symmetrical component currents and voltages in observation branches, methods of synthesizing schemes for replacing elements of electric power systems for symmetrical component currents, methods of data processing and construction diagrams using specialized software tools.. Findings. As a result the analysis known studies, it was established that under the condition of researching low-power generating systems in conditions of asymmetry, insufficient attention is paid to the nature of the asymmetric load. Using the well-known structure of a microgrid, which includes a synchronous generator, a machine load, and an external network transformer, its model was built, in which, by introducing asymmetric loads of various types, a series of experiments was implemented with the registration of voltages and currents of forward, reverse, and zero sequences in the branches of the network. The analysis of the results obtained during the research established that the positive sequence voltage in the case of a change in the active load does not change its level, under the same circumstances, in the case of an active-capacitive and active-inductive load, the voltage change has the opposite character. In the case of increasing asymmetry of an active-inductive nature, the positive sequence voltage decreases, and in the case of an active-capacitive one, it increases. The specified changes in some cases exceed 3%. Positive sequence currents in the case of active load imbalance differ slightly. In the case of a positive sequence current of the transformer, its continuous growth is observed, which in the case of active-capacitive and active-inductive loads exceeds the active one by an average of 1.5 times. Negative sequence currents in the studied model, which are formed by an asymmetrical load, are completely closed to the transformer, causing zero-sequence voltages, and the nature asymmetrical load significantly affects the value of these currents, a 61% increase was noted. Originality. It was established that in a microgrid, which includes a synchronous generator, a machine load, a symmetrical active load of comparable power to the generator, an external network transformer, in addition to the fact of asymmetry caused by an asymmetrical load, the character of an asymmetrical load (active, active-inductive or active-capacitive). Practical value. In the case of using in microgrids devices that provide an increase in the quality of electrical energy, for example, symmetrical devices, it is necessary, in addition to the asymmetry factor, to take into account the natural load that causes the latter.

Improving DC power supply performance: insights into cuk and modified cuk converters' stability and power factor

Abstract The conversion of alternating current (AC) to direct current (DC) is pivotal for modern electrical systems, significantly influencing power delivery efficiency and stability. As the reliance on DC-powered electronic devices grows, optimizing AC-DC converters becomes increasingly important. Various converter topologies, including buck, boost, buck-boost, Cuk, and SEPIC configurations, exhibit unique characteristics that affect their efficiency and impact on the power grid.
This study examines the performance of Cuk and modified Cuk converters, utilizing PSIM software to simulate these converters for a 1.4 kW power supply. The simulations reveal that both the Cuk and modified Cuk converters achieve reduced ripple in voltage and current outputs, addressing a significant concern for DC power supplies. Additionally, the modified Cuk converter demonstrates a marked reduction in the total harmonic distortion (THD) of the source current.
This study explored the interaction between converter topologies and varying load conditions, emphasizing their impact on power factor—a measure of electrical power consumption. A higher power factor indicates improved efficiency and reduced reactive power, benefiting both the electrical system and the grid. The research further investigates how load variations affect power factor and converter performance, providing insights into designing converters that enhance system reliability and efficiency.
By validating the simulation results with experimental data, it has been established that the modified Cuk converter topology offers superior performance and stability. This advancement supports the development of converters that optimize power factor and energy consumption, which are crucial for advancing electrical infrastructure. By bridging the gap between simulation and real-world performance, this work aims to provide valuable insights that can inform future enhancements in domestic EV charging infrastructure, ultimately contributing to the broader adoption of electric vehicles.

An innovative multilayered material fabricated through additive manufacturing for structural applications: method and mechanical properties

Abstract Additive manufacturing (AM) is a cost-effective method for fabricating structurally sound components. Fused filament fabrication (FFF) is a popular AM technique known for its design flexibility, minimal material wastage, and recyclability. Poly lactic acid (PLA) is a thermoplastic widely used in aerospace, biomedical, and automobile industries. Wood-PLA, incorporating wood fillers into PLA, finds applications in several industries. This research explores multilayered materials (MLM) for enhanced performance in various sectors such as aircraft, energy, and biomedical. Mechanical properties of MLM were investigated under different load conditions (tensile, bend, compressive). Properties simulated through Finite Element Method (FEM) showed minimal error (less than 1 %). Microscopic analysis, aided by scanning electron microscope (SEM) fractography, reveals a brittle mode of failure in the specimens. This study provides valuable insights into the mechanical behaviour of MLM, offering potential applications in diverse industries.

Experimental assessment of catalytic biofuel effect on performance and exhaust emission of diesel engine

The present experiment is to analyze the effect of blended biodiesel of chicken fat CF10 (10% chicken fat and 90% diesel), waste cooking oil WC10 (10% waste cooking oil and 90% diesel), and combined chicken fat with waste cooking oil CF&WC10 (5% chicken fat + 5% waste cooking oil and 90% diesel) on the performance of diesel engine. The experiment is conducted at a constant compression ratio of 17, mixing 50 ppm alumina alfa (Al2O3-α) catalyst nanoparticles in each blend. The performance of biodiesel is analyzed at 25%, 50%, 75%, and 100% load conditions and is compared with pure diesel. The results show that the brake torque (BT) and brake power of CF&WC10 were found to be 22.48 Nm and 3.58 kW at full load conditions. However, the indicated thermal efficiency and BTE of CF&WC10 are at full loading conditions of 52.45% and 26.78% respectively. Because the supply of A/F ratio is 18.81, at full load condition and also lowering the brake specific fuel consumption up to 0.32 kg/kWh. Therefore, optimization of both performance and exhaust emission of an engine depends on BTE and NOx as well as HC emissions. Hence, from the emissions reduction point of view, CF&WC10 has lower emissions while achieving brake thermal efficiency similar to diesel fuel. The novelty of research shows CF&WC10 leads to enhanced performance of diesel engine compared to pure diesel fuel.

A novel control strategy for PWM rectifier based on underactuated characteristics

In this paper, a double closed loop controller based on equivalent input disturbances (EID) error perturbation is proposed to solve the problem of abnormal operation of three-phase pulse width modulation (PWM) rectifier caused by load and external conditions. By analysing the buffeting problem and response time problem caused by traditional sliding mode in the current control process, a new current control method of terminal fuzzy sliding mode is designed. The system error is estimated by EID error estimation, and fuzzy control is introduced to improve the accuracy of error estimation, which solves the current buffeting and response problem. In order to solve the problem of response rate and harmonics in the voltage controller design, the extended state observer (ESO) in active disturbance rejection control (ADRC) control is improved, EID error estimation is introduced, the response rate and anti-disturbance ability of the system are further improved, and the harmonics of the system are suppressed. The experimental results show the effectiveness and superiority of the proposed method.

Performance assessment of direct injection stoichiometric and lean burn compressed natural gas engine over port fuel gasoline and compressed natural gas engine

ABSTRACT A direct injection (DI) CNG engine was developed and evaluated under stoichiometric and lean burn conditions, emphasising high compression ratios (CRs). A comparative analysis of PFI gasoline and PFI CNG engines was conducted to provide comprehensive insights. Results showed that the DI CNG engine exhibited a shorter combustion duration, indicating higher combustion speed, and enhanced combustion stability, particularly at low load and speed conditions, with a reduced coefficient of variation of indicated mean effective pressure (COVIMEP) below 1%. The DI CNG engine demonstrated a relative increase in net indicated thermal efficiency by 4–5% compared to the PFI CNG engine. Furthermore, CNG engines operating at a high compression ratio of 16 could run at high loads without encountering knocking issues. Lean burn operation, combined with high compression ratios, improved thermal efficiency while minimising emissions; however, challenges such as combustion instability and increased emissions under lean burn conditions were observed.

Mechanical equipment fault diagnosis method based on improved deep residual shrinkage network.

Fault diagnosis of mechanical equipment can effectively reduce property losses and casualties. Bearing vibration signals, as one of the effective sources of diagnostic information, are often overwhelmed by substantial environmental noise. To address this issue, we present a fault diagnosis method, CCSDRSN, which exhibits strong noise resistance. This method enhances the soft threshold function in the traditional deep residual shrinkage network, allowing it to extract useful information from the fault signal to the maximum extent, thus significantly improving diagnostic accuracy. Additionally, we have developed a novel activation function that can nonlinearly transform the time frequency map across multiple dimensions and the entire region. In pursuit of network optimization and parameter reduction, we have strategically incorporated depthwise separable convolutions, effectively replacing conventional convolutional layers. This architectural innovation streamlines the network. By verifying the effectiveness of the proposed method using Case Western Reserve University datasets, the results demonstrate that the proposed method not only possesses strong noise resistance in high noise environments but also achieves high diagnostic accuracy and good generalization performance under different load conditions.

Modeling and Analyzing of CMOS Cross-Coupled Differential-Drive Rectifier for Ultra-Low-Power Ambient RF Energy Harvesting

This paper models and analyzes the Complementary Metal Oxide Semiconductor (CMOS) cross-coupled differential-drive (CCDD) rectifier for Ultra-Low-Power ambient radio-frequency energy harvesters (RFEHs) working in the subthreshold region. In this paper, two closed-form equations of CCDD rectifier output voltage and input resistance in the subthreshold region were derived based on BSIM4 models of NMOS and PMOS. The model give insight to specify circuit parameters according to different inputs, transistor sizes, threshold voltages, numbers of stages, load conditions and compensation voltages, which can be used to optimize the rectifier circuit. There is a good agreement between the simulation results and these models, and these models have a maximum deviation of 10% in comparison with the simulation results in the subthreshold region. The measurement results of a single-stage CCDD rectifier reported in a previous paper were adopted to verify the model. The output voltage and input resistance predicted by these models provide excellent consistency with corresponding measurement results. The model can be employed to optimize the CCDD rectifier without expensive calculation in the design stage.

Design and performance evaluation of a multi-load and multi-source DC-DC converter for efficient electric vehicle power systems

This paper introduces the design and comprehensive performance evaluation of a novel Multi-Load and Multi-Source DC-DC converter tailored for electric vehicle (EV) power systems. The proposed converter integrates a primary battery power source with a secondary renewable energy source—specifically, solar energy—to enhance overall energy efficiency and reliability in EV applications. Unlike conventional multi-port converters that often suffer from cross-regulation issues and limited scalability, this converter ensures stable power distribution to various EV subsystems, including the motor, air conditioning unit, audio systems, and lighting. A key feature of the design is its ability to independently manage multiple power loads while maintaining isolated outputs, thus eliminating the inductor current imbalance that is common in traditional systems. Experimental validation using a 100 W prototype demonstrated the converter’s ability to deliver stable 24 V and 48 V outputs from a 12 V input, with output voltage deviations kept within ± 1%, significantly improving upon the ± 5% deviations typically seen in existing converters. Furthermore, the system achieved an impressive 93% efficiency under variable load conditions. The modular nature of the converter makes it not only suitable for EV applications but also for a broader range of industries, including renewable energy systems and industrial power supplies. This paper concludes by discussing optimization strategies for future improvements and potential scaling of the technology for commercial use in sustainable energy applications.

Effect of Constant Cyclic Stress Coupling on the Fatigue Behavior of 304LN Stainless Steel

The stress state of the primary circuit main pipeline is very complex mixed constant stress and periodic cyclic stress during the operation of nuclear power plants, which often affects the failure behavior of the stainless steel (SS) pipe. The fatigue behavior of 304LN SS under mixed constant stress and cyclic stress was investigated, and it was found that the coupling effect of constant stress and cyclic stress has a significant collaborative acceleration on the fatigue behavior. The research results showed that the cracks in the 304LN SS did not propagate even after 78 days under both constant load conditions of 5 KN and 7.5 KN, while the crack growth rate (CGR) of the specimen increased by about an order of magnitude when coupled with a cyclic fatigue load. The fatigue life of 304LN SS was the longest under 200 °C high-temperature water, and its life was roughly the same under 250 °C and 300 °C water. In a 300 °C high-temperature water environment, the fatigue life under the coupling of constant stress and cyclic fatigue stress is significantly lower than that under symmetric cyclic stress alone. There is a synergistic acceleration effect on the fatigue life of 304LN SS when constant stress is coupled with periodic cyclic stress, which is attributed to the combined effect of a corrosion environment and mechanical factors.

Design of reliable standalone utility-scale pumped hydroelectric storage powered by PV/Wind hybrid renewable system

With a target of 35 % renewable energy in the country’s energy mix by 2030, the goal of this research is to support the Libyan government’s plan to maximize the use of environmentally friendly and sustainable energy sources. This will be accomplished by making effective use of the region’s plentiful natural resources. The feasibility of wind and solar energy has been established by local research, and the presence of highlands that can store pumped hydropower (PHS) makes hybrid renewable energy systems (HRES) even more feasible. These systems might offer a sizable edge over competitors in the regional energy market. In this study, PHS was utilized to stabilize electricity production in addition to storing energy. A hydropower turbine provides electricity to the load, and the PHS system is powered by a PV/wind supply. By lowering the volatility of wind and photovoltaic power generation, the suggested system could offer a more dependable renewable energy source without requiring complicated control mechanisms. This strategy could encourage a wider adoption of renewable energy, which could be especially advantageous for developing nations. Under particular load and climate conditions, the energy production of different solar PV array and wind turbine farm configurations was estimated using the System Advisor Model (SAM) software. The ideal HRES configuration consists of a 290 MW wind farm, a 154 MW solar PV field, and a 508 MW PHS system. This configuration will provide 100 % of the annual electrical demand of 513 GWh, plus a 20 % safety margin. The levelized cost of energy (LCOE), estimated at $211.65/MWh, is reduced by this configuration. It is anticipated that the $929.02 million initial investment will be recovered in 11 years, and the system will turn a profit in the following 9 years. Also, the planned HRES will stop 532.17 tons of CO2 emissions from being released each year.

Stacking BSRG-PLS: A physical and data-driven real-time stability safety analysis of arch dams during operation

Anti-sliding stability is the foundation for the normal operation of arch dams. In recent years, extreme weather has occurred frequently. It is important to grasp the anti-slide stability of arch dam (ASSAD) under complex load conditions in time. Currently, the ASSAD safety factor is primarily analyzed through the finite element method (FEM), which are time-consuming, labor-intensive, and lack timeliness. To address this, this paper proposes a real-time ASSAD analysis method during operation based on the Stacking BSRG-PLS model, which integrates a Bidirectional long short-term memory network, Residual neural network, Support vector machine, Gaussian process regression model and Partial Least Squares regression method. Firstly, based on the Stacking BSRG-PLS model and measured temperature combing with FEM, the transient temperature field of arch dam is established. Subsequently, a sample dataset containing the load data and the corresponding ASSAD safety factors calculated by FEM is constructed. Whereafter, using the Stacking BSRG-PLS model again, the real-time ASSAD safety factor is obtained based on the sample dataset. Case studies indicate that this method is effective and feasible, and has high analysis precision. It provides an effective way to quickly evaluate the ASSAD safety based on the measured data.

Study on Bearing Mechanism of Steel Screw Pile

In order to study the bearing mechanism of a steel screw pile (SSP), a 3D-FEM of “SSP-stratum” was established based on the large-scale general finite element analysis platform ABAQUS. Secondly, the real friction coefficient between pile and soil was determined by comparing it with the field bearing test data of screw piles. Finally, the bearing mechanism and failure criterion of the SSP was revealed. The research showed that the pile-soil friction coefficient was about 0.6 under the condition of this stratum, and the screw pile was in the elastic working stage under the conditions of compression and tension load, which had a large bearing reserve. The magnitude of Young’s modulus was inversely correlated with the settlement value and the extreme value of principal stress. The increase in the Young’s modulus of the stratum was helpful in improving the bearing capacity of the screw pile. The compressive capacity of circular steel tube + screw pile (CST + SP) was about 2 times higher than CST, and the compressive capacity of circular steel tube + large blade + screw pile (CST + LB + SP) was about 2.4 times higher than CST. The tensile capacity of CST + SP was about 3.4 times higher than CST, and the tensile capacity of CST + LB + SP was about 4.9 times higher than CST. The arrangement of large blades better bore the load of the screw part and optimized the stress distribution of the structure. Based on the mechanical analysis in the vertical direction, the bearing mechanism of the SSP under compression and tension conditions was elaborated. The bearing failure criterion of the SSP was summarized from the aspects of mechanics and displacement. The bearing design of the SSP should meet the control of mechanics and deformation at the same time. The research work could provide a useful reference for the design and construction of SSPs.