Speed Characteristics Research Articles

RESEARCH OF THE COMBUSTION PARAMETERS OF GASOLINE WITH ADDITIONAL HYDROGEN IN A SPARK-IGNITION ENGINE IN EXTERNAL SPEED CHARACTERISTIC MODES

The directions of development and improvement of road transport around the world are inextricably linked to the desire to reduce the use of cars “on traditional fuels” due to limited oil and environmental safety of mankind. Since the modes of external speed characteristic are the most typical for the operation of cars in cities, the study of environmental performance of engines in these modes is an urgent task. Therefore, finding ways to reduce carbon dioxide emissions from automobile engines at high-speed modes is an urgent task. The rapid growth in the number of cars with internal combustion engines and the inevitable decline in world oil reserves necessitate the development and implementation of energy-saving technologies and the use of alternative fuels. Research aimed at finding ways to improve the fuel efficiency and environmental performance of automotive engines is relevant. One of the promising areas is the influence on the combustion process in gasoline engines by using additives of alternative fuels, which include hydrogen. The presented study of the parameters of combustion of gasoline with hydrogen additive in a spark ignition engine at external speed characteristics is a comprehensive analysis of the combustion process of a gasoline-hydrogen mixture and determination of its effect on the concentration of carbon dioxide in exhaust gases by developing a mathematical model that takes into account the composition of the mixture components and features of the combustion process, allows for sufficiently accurate calculation of the operating process of an engine with hydrogen additive at ψ ≤ 10%, its identification by the results of experiments. In the course of the study, dependencies were developed to determine the combustion parameters of the Wiebe model, taking into account the addition of hydrogen to gasoline in the modes of external speed characteristics, and the effect of hydrogen addition on the concentration of CO2 in exhaust gases was analyzed. It is shown that with an increase in the hydrogen additive to 10% by mass fraction to gasoline, there is a decrease in CO2 emissions to almost 30% in the external speed characteristic modes, which corresponds to modern environmental standards for gasoline internal combustion engines.

Hygienic assessment of the protective properties of personal hand protection equipment during vibration testing

Introduction. In industrial environments, at the workplaces of hand tool operators, it is not always possible to completely eliminate increased levels of vibration exposure. The power and speed characteristics of modern hand-held machines are constantly increasing. The impact of local vibration on a person has a negative effect on his body. When working with hand tools, personal protective equipment is used. The purpose of personal hand protection against vibration is to reduce the vibration impact on a person. Materials and methods. Bench tests were carried out on hand protection products consisting of damping materials of various shapes and locations in the product. The vibration sensor was installed and fastened in places where the operator’s hands came into contact with vibration and on the forearm. The effectiveness of protection was determined by the difference in measurement levels. Results. During the tests, vibration levels were recorded on the handle of the vibration stand, the palmar surface, the fingers, and the operator’s forearm. In the low-frequency region of the spectrum, vibration attenuation is minimal, and as the frequency range increases, the attenuation increases. Across all areas of the spectrum, performance levels for mittens are higher than for gloves. In places where the fingers come into contact with vibration, the efficiency is less than when in contact with the hand, and in the low-frequency region of the spectrum a negative efficiency of up to 0.8 dB is noted. Vibration measurements on the operator’s forearm showed vibration levels in the forearm to be lower than in the hand. Limitations. The study was conducted over a period of one year, in laboratory conditions, and was limited to two thousand measurements. Conclusion. Hygienic assessment of the effectiveness of the protective properties of personal protective equipment for hands was carried out in accordance with developed laboratory test methods when installing and securing a vibration sensor on the handle, hand, and forearm of the operator. Determining the effectiveness of the entire product model should be considered when designing and manufacturing new hand protection against vibration.

Study and evaluation of wind power density for the use of small wind turbine under Baghdad conditions

The main aim of this research is to analyze the characteristics of the wind speed and wind power density in Baghdad City within micro-scale meteorological conditions at Mustansiriyah University Meteorological Station (MUMS). Temperature, atmospheric pressure and wind speed data were taken for one year (2016) measured at a height of 18 m above the earth's surface. Hourly, monthly, and seasonal changes in wind speed at an altitude of 30 m were estimated using a power law. The mean diurnal and monthly air density was calculated. Different statistical distributions were used, including the Rayleigh, Gamma and Weibull distributions, and the best distribution function was selected to evaluate the wind power density in the study area. The results showed the highest monthly mean of wind speed recorded in June and July. Therefore, these months have the highest wind power density. The lowest monthly mean of wind speed and wind power density was observed in December. The maximum and minimum values of air density were recorded in December, January and July, August, respectively. The monthly variation of the shape parameter (k) ranges between 0.99 - 1.81, while the monthly variation of the scale parameter(c) ranges between 1.07 - 2.3 m s-1. It was also found that the Weibull distribution was more accurate than the Rayleigh and Gamma distributions. The prevailing wind direction is northeast (NE) and east-northeast (ENE) most of the time. The research results showed that the study area is not suitable for using wind energy to generate energy.

Preparation of flexible SERS substrate with excellent performance based on the electrospraying technique

Paper-based flexible surface-enhanced Raman scattering (SERS) substrate has significant advantages in the detection of pesticide residues on the surface of fruits and vegetables due to its full contact with the sample surface. However, it is found that the development of new paper-based flexible SERS substrate preparation technology is still necessary through the evaluation of the current preparation technology. In addition, the development of new application scenarios can also promote the further development of SERS technology. Herein, a highly sensitive paper-based flexible SERS substrate is prepared by depositing Cu2O/Ag(4) composite particles on commercial filter paper by electrospraying technique. Compared with other preparation technologies, in addition to the characteristics of simplicity and speed, more importantly, it will not cause waste of nanoparticles. By adjusting the parameters, the optimized substrate shows excellent SERS performance with the minimum detection concentrations are 10−9 M and 10−9 M for R6G and thiram, respectively. It also has good linear correlation of concentration (R2 = 0.952), good reproducibility, and excellent time stability. Furthermore, based on the good filtration characteristics of commercial filter paper, the rapid detection of pesticide residues in soil was successfully realized. This proposed a new scheme for the practical application of SERS technology in the field of food and environmental safety.

Study on the Effect of Starved Lubrication on the Dynamic Characteristics of Locally Failed Roller Bearings

When the lubricant is not enough to maintain the ideal lubrication state of the bearing, the deep groove ball bearing will enter the starved lubrication state, which leads to the change of the vibration response of the deep groove ball bearing with localized defects. Previous bearing dynamics models mainly consider the lubrication state as an ideal lubrication condition, which may not reveal the effect of starved lubrication on the vibration characteristics of defective bearings. In this paper, the internal interaction of the system under starved condition is taken into account, and a dynamic model of defective deep groove ball bearings with insufficient lubricant is established to investigate the effects of different starved lubrication degrees on the contact force, friction force, cage speed, and system vibration characteristics. The results show that the lubricant insufficiency significantly changes the contact force inside the bearing, and the increase in friction caused by the increase in the degree of starved lubrication leads to the suppression of the degree of bearing slipping. The root mean square (RMS) value of the time-domain signal and the outer ring fault frequency both increase with the increase of the starved degree. The results of the study are helpful for fault diagnosis and condition monitoring of related equipment.

Environmental Monitoring Data Management and Analysis Based on 5G IoT

As environmental issues become increasingly severe, environmental monitoring has become a crucial measure for protecting and managing ecosystems. The high speed, low latency, and massive connectivity characteristics of 5G technology, combined with the widespread application of IoT technology, provide new solutions for environmental monitoring data management and analysis. This study explores the methods of environmental monitoring data management and analysis based on 5G IoT technology, designs a systematic environmental monitoring framework, and verifies its effectiveness through empirical research. The results show that the environmental monitoring system based on 5G IoT can efficiently, real-time, and reliably collect and analyze environmental data, providing strong support for environmental protection and management.

Semi-Conv-DETR: A railway ballast bed defect detection model integrating convolutional augmentation and semi-supervised DETR

Railway ballast bed defects, including subsidence, mud pumping, and abnormal water, pose significant safety risks by destabilizing the railway ballast beds. Timely detection and repair of railway ballast bed defects are vital for safeguarding the security of both the trains and their passengers. Ground-Penetrating Radar (GPR) is widely used for railway ballast beds inspection and evaluation owing to its high speed and non-destructive characteristics. However, GPR image data contain considerable noise, and the distinct shapes and sizes of each ballast bed defect renders it challenging to apply a unified data annotation standard, which hampers the development of railway ballast bed defect detection models. Considering the distinct wave-like characteristics of GPR data and the vaguely contours of the defects to be identified, we propose a convolutional augmentation operation tailored for GPR images. Furthermore, we also investigate Semi-Supervised Learning by employing limited annotated railway ballast bed inspection data along with a vast amount of unlabeled data to joint train the DETR detection model. To sum up, we proposed a semi-supervised DETR model supplemented with convolutional augmentation for railway ballast bed defect detection, termed as Semi-Conv-DETR model. Experimental outcomes indicate that Semi-Conv-DETR shows an improvement of 58.6 % in accuracy when compared to the classical Faster-RCNN model.

Research on engine dynamic torque modeling for torsional vibration analysis of vehicle powertrain

In order to improve the accuracy of dynamic torque model of engine, a simulation model of quasi-transient engine dynamic torque under all operating conditions was established considering the influence of throttle opening. Firstly, the calculation model of engine output torque and cylinder pressure is established according to the kinematic relation of crank linkage mechanism. Secondly, BP neural network is used to establish the mapping relationship model of throttle opening, rotational speed, and cylinder pressure ratio data. In order to solve the contradiction between calculation accuracy and efficiency of engine cylinder pressure interpolation, a quadratic interpolation method is proposed, which refines data to improve interpolation accuracy, and improves calculation efficiency by online adjacent interpolation, and completes the construction of dynamic torque simulation model of engine in all working conditions. Finally, the experimental data of dynamic torque characteristics of the engine at different speeds are used to verify the accuracy of the model calculation. By using the verified engine model, the dynamic operating characteristics of variable valve opening and variable speed are simulated and analyzed. The results show that the model established in this paper can effectively reflect the dynamic characteristics of the engine, and the model is suitable for the simulation of the torsional vibration of the vehicle powertrain under steady and unsteady conditions.

Analysing the possibility of using a hydraulic transmission with motor wheels for the nomad at off-roader

Problem. The creation of transport vehicles for operation in difficult road conditions requires solving a complex of problems related to the fulfilment of the necessary requirements for speed and traction characteristics, in particular, shifting modes, overcoming climbs, manoeuvrability and increased speed with its stepless change, anti-skid properties. Such requirements are achieved thanks to constructive solutions in transmissions of various types. Goal. The aim is an attempt to create a full-flow continuously variable transmission with hydrostatic transmission and motor-wheels instead of a step-mechanical one to improve the technical characteristics of the all-terrain vehicle and the technological possibilities of manufacturing the transmission by the block method when using standard components. Methodology. Based on the analysis of the technical characteristics of the analogue all-terrain vehicle with a mechanical multi-gear transmission and a review of achievements in modern hydrostatic transmission with hydraulic motor-wheels, static calculations were carried out to assess the possibility of creating a stepless full-flow hydro volume transmission and building its hydraulic schematic diagram. Calculations are based on mathematical models created on the basis of the laws of mechanics and hydraulics. The results. According to the results of the calculations, it has been shown that it is fundamentally possible to create a stepless hydrostatic transmission for an all-terrain vehicle with the specified traction and speed characteristics. Further research is proposed on the analysis of the dynamics of the hydrostatic transmission of the all-terrain vehicle and the creation of a corresponding experimental model of the vehicle. Originality. For the analogue all-terrain vehicle, the hydraulic motor-wheels required for the working volume were selected, which provide the parameters of traction and speed characteristics and allow creating an original transmission without the use of reducers and gearboxes. Practical meaning. The obtained results are planned to be considered as recommended for carrying out a functional and cost analysis in the design and determination of technological possibilities in the manufacture of a hydrostatic transmission of an all-terrain vehicle. It is also proposed to consider the method of calculating the hydrostatic transmission of an all-terrain vehicle in the educational process for master's students of industrial mechanical engineering when studying the disciplines related to the design of hydraulic drives and their tests.

Investigations of BLDC motor speed characteristics via THD under conventional and advanced hybrid controllers

This project investigates brushless direct current (BLDC) motor speed control through total harmonic distortion (THD) analysis, employing proportional integral (PI), fuzzy logic (FLC), adaptive neuro-fuzzy inference system (ANFIS), and an innovative hybrid ANFIS-PD/PI controller. Considering the vital role of BLDC motors in precision-dependent industries like robotics, electric vehicles, and industrial automation, our primary focus is on understanding BLDC motor operation and recognizing THD's significance as a performance metric. Controllers are meticulously implemented in real-time, fine-tuned, and optimized to achieve desired speed characteristics, incorporating considerations like response time, accuracy, and energy efficiency. The project's core involves THD analysis, quantifying harmonic content in the BLDC motor's speed waveform. This facilitates a comprehensive comparative evaluation of controller performance, assessing their capability to maintain speed stability and influence power quality. The discussion covers the merits and limitations of each controller, with a special emphasis on the hybrid ANFIS-PD/PI controller, seamlessly blending ANFIS adaptability with PD/PI control stability. Results illustrate the hybrid controller's excellence in optimizing BLDC motor speed control, demonstrating superior performance in speed accuracy, disturbance rejection, and THD reduction. These findings drive advancements in motor control technology, providing practical guidance for selecting controllers tailored to specific application requirements. Simulation results can be analyzed using MATLAB/Simulink 2018a Software.

Photovoltaic MPPT based on improved Cuckoo algorithm

Abstract Photovoltaic power generation is susceptible to external factors such as light, resulting in a reduction in the actual efficiency of photovoltaic power generation. However, the traditional maximum power point tracking technology has the characteristics of slow convergence speed and poor accuracy. In order to improve the above problems, a new photovoltaic maximum power control algorithm with an improved cuckoo algorithm is proposed. By adjusting the iterative step size in the cuckoo algorithm and changing the probability of finding the bird nest, the iterative convergence speed is accelerated, and the global optimization ability is increased. Finally, the algorithm is applied to the maximum power tracking, and the simulation model is built on the Matlab/Simulink platform. After comparing the standard Cuckoo algorithm with the improved Cuckoo algorithm under static and dynamic conditions, the simulation results show that the improved Cuckoo algorithm has more advantages in maximum power tracking speed and accuracy.

Transient surface pressure of a rectangular cylinder subjected to downburst-like winds

Thunderstorm downbursts are transient in nature and have been responsible for a variety of structural damages in recent years. Currently, the researchers have done several works on the characteristics of downburst wind speed. Nonetheless, rare attention has been placed on the structural aerodynamics characteristics subjected to downburst winds. Based on this, an experimental investigation is performed to reproduce downburst-like winds physically and to study the transient surface pressures (SPs) on a 5:1 rectangular cylinder (RC). The experiment is conducted within a multiple-fan active control wind tunnel (MFACWT) and mainly focuses on simulating the transient characteristics of downburst-like flow, including time-varying mean (TVM) wind speed and nonstationary wind fluctuation. The resulting SPs are measured to understand the influence of transient wind on the aerodynamic behavior of bluff bodies. The spatiotemporal characteristics of the SPs are analyzed using wavelet transform and Priestley's classic spectral theory. The results indicate that the transient nature of the downburst-like flow can be physically reproduced by a MFACWT. The instantaneous pressures of a RC are illustrated by both the turbulence parameters of the transient flow and the flow-separation characteristics. The pressure coefficients normalized by the TVM of the downburst-like winds remain constant, which provides a more appropriate way to estimate the transient gust loading in a quasi-steady manner. Interestingly, the phenomenon of the time-varying phase shift and time-varying correlation of chordwise SPs is observed when the turbulent velocity changes dramatically. In addition, the normalized surface pressure can be regarded as a stationary stochastic process, which provides a significant basis for further establishing the theoretical model of nonstationary gust-loading.

A Prototype Design of a Vertical Axis Wind Turbine as One of the Renewable Energy Sources in Brunei

Background: According to the Asia Wind Energy Association, Brunei can harness the power of wind energy to meet its future demands for a reliable energy source that is both renewable and non-polluting. Objective: A preliminary study to design and manufacture wind turbines needs to be initiated earlier especially in the Brunei with has potential wind energy. Methods: This preliminary study compares several Vertical Axis Wind Turbine (VAWT) types and examines the optimal design in terms of mechanical parts for wind speed characteristics in Brunei. The project focuses on the engineering design stages to obtain a selected design that differs from other available designs. Results: The preliminary study successfully generated a small amount of electricity from the mechanical rotation of the VAWT. Conclusion: Although the preliminary study can generate a small amount of electricity, several design parameters need to be improved in further study. Proper manufacturing technologies are also needed to fabricate a better VAWT.

An energy management strategy based on dynamic programming for fuel cell hybrid trucks in ports

The deterioration of environment and the proposal of carbon neutrality are causing the transformation of port freight transportation. Fuel cell hybrid trucks (FCHTs) may be a promising solution for port logistic with the characteristics of low speed, heavy duty and frequent start-stops. How to achieve efficient energy management for FCHTs in ports is a key issue, which is still in the initial stage. The objective of this study is to investigate the effects of dynamic programming (DP) strategy on energy management of FCHTs. With the intention of calculating power demands, the FCHT structure and the models of each component are established. In the DP method, the state of charge (SOC) of the battery, the power supplied by the battery, and hydrogen fuel consumption are regarded as the state variable, the decision variable, and the objective function, respectively. The simulation results under two different typical working conditions in ports show that the proposed DP outperforms existing genetic algorithm (GA) and rule-based strategy for reducing hydrogen fuel consumption by over 10%. Moreover, a set of instances among several FCHTs with different parameters and conditions suggest different influences of key feature parameters on hydrogen fuel consumption and SOC. Nearly 50% cost reduction of the FCHT in the "quay crane-yard " (QCY) cycle compared with diesel trucks at the current price indicates wide application prospect of FCHTs. At last, the results under different conditions reconfirm that DP is an excellent strategy to tackle energy management of FCHTs in ports with frequent start-stops and heavy-load scenarios.

URS-YOLOv5s: object detection algorithm for UAV remote sensing images

The application of UAV (Unmanned Aerial Vehicle) remote sensing and aerial photography technology is more and more widely. Aiming at the problem of object detection in remote sensing or aerial images, the paper proposes an object detection algorithm for UAV remote sensing images based on YOLOv5s, called URS-YOLOv5s (UAV Remote Sensing - YOLOv5s). Firstly, the paper designs Cross-Connected Dense Network (CCDNet), where each convolution layer is concatenated to the second convolution layer. Secondly, the paper designs Across-Path Fusion Network (APFNet), which the last feature fusion path is directly fused with the backbone network. It increases the location information and semantic information of deep features. Finally, the loss function of the original algorithm is replaced by EIoU (Focal and Efficient IoU), which makes the calculation method of the overall loss more appropriate. On AI-TOD and Visdrone2019 datasets, experiments show that the accuracy of URS-YOLOv5s on mAP@0.5 is 6.3% and 9% higher than YOLOv5s. In addition, compared with YOLOv3 and YOLOv5l which have good detection effect, URS-YOLOv5s has the characteristics of faster detection speed and lower computational cost. Meanwhile, URS-YOLOv5s is more suitable for deployment to mobile devices, such as drones with limited performance.

Effect of UV Top Coating Microcapsules on the Coating Properties of Fiberboard Surfaces.

The commonly used ultraviolet ray (UV) curing coatings have the characteristics of fast curing speed, high hardness, strong abrasion resistance, etc. However, the self-healing properties of UV coatings after being damaged still need to be improved. Self-healing microcapsules can alleviate this problem. The UV top coating itself has good properties, so it can be directly chosen as the core material of microcapsules. UV top coating microcapsules can be added to the UV top coating to increase the self-healing properties of the UV coating to achieve the purpose of better protection of the UV coating and fiberboards. UV top coating microcapsules were prepared and added in different contents to characterize the effect on the physical, chemical, and self-healing properties of the UV coating on a fiberboard surface. The 1#, 2#, and 3# UV top coating microcapsules that were prepared with emulsifier HLB values of 10.04, 10.88, and 11.72, respectively, were added to the UV top coating at contents of 2.0%, 4.0%, 6.0%, 8.0%, and 10.0%. The UV coatings were applied to the fiberboard using a method of two primers and two top coatings, in which no microcapsule was added in the primer, and were tested and analyzed. The results showed that when the content of microcapsules was greater than 6.0%, close to 8.0%, the excessive density of microcapsules produced stacking and extrusion between the microcapsules. As a result, the core material could not flow out smoothly when part of the microcapsule was ruptured. The outflow of the core material was not efficiently utilized, thus leading to a decrease in the self-healing rate. The 2# UV top coating microcapsules of 4.0% made the UV coatings reach the self-healing rate of 26.41%. The self-healing rate of the UV coatings prepared with the 3# UV top coating microcapsules with 6.0% was up to 26.58%. The UV coatings prepared with the 1# UV top coating microcapsules of 6.0% had the highest self-healing rate among the three groups, up to 27.32%. The UV coatings of this group had the best comprehensive properties with a chromatic aberration ΔE of 4.08, a gloss of 1.10 GU, a reflectance of 17.13%, an adhesion grade of 3, a hardness of 3H, a grade 3 of impact resistance, and a roughness of 1.677 μm. An investigation of the UV coatings on fiberboard surfaces with the content of UV top coating microcapsules can provide support for the optimization of the self-healing properties of UV coatings and can also provide innovative ideas for the preparation of the self-healing coatings on fiberboard surfaces.

Vibration damping by enhancing of magneto-rheological damper performance using novel smart fluid

The objective of the present work is to improve the speed and vibration characteristics of tracked vehicles via a semi-active suspension system that uses a Magneto-Rheological (MR) damper. MR damper is designed, manufactured, and tested with different harmonic excitations. The MR damper reliability under high-frequency stresses is considered in the mechanical design phase as well as the configurations and dimensions of the damper. Two fluid samples DELTA and GAMA are prepared, which differ in carrier fluid dynamic viscosities to have different rheological properties and tested to determine the dynamic characteristics of the damper. The damper’s ability to isolate vibration is measured by MTS. The investigation performed not only clarifies MR fluid characteristics but also proves the fact that the fluid is non-Newtonian with good rheological properties. One of the two fluid samples called DELTA is found to have the required properties. The MR damper filled with this DELTA shows a significant increase in damping force according to the excitation current and is much higher than the conventional passive suspension damping force. The proposed damper can cope with the increase in both magnitude and frequency of the input, which represents the speed of the truck and roughness of the road. Upgrading the suspension system of the vehicle from a passive damper to a manufactured semi-active MR damper with MR fluid DELTA can increase the damping force that the passive damper produces by 207% in compression stroke and 136.2% in rebound stroke at the same testing conditions.

A novel multi-modal incremental tensor decomposition for anomaly detection in large-scale networks

Network traffic anomaly detection is a crucial task for today's network monitoring and maintenance. However, with the rapid growth of network data volume, the data structure has become more and more complex, showing multi-modal characteristics, which makes traffic anomaly detection face a great challenge. The earlier proposed anomaly detection methods have the following deficiencies, i) Most of them are static or dynamic detection methods that only grow along the temporal modality. ii) Lower detection rate or higher computational cost. To address these deficiencies, this article proposes a traffic anomaly detection framework based on multi-modal incremental tensor decomposition, which has the following three highlights, i) Constructing traffic data as a tensor model to fully mine the correlation between data, and the proposed framework is applicable to the situation where traffic data grows dynamically along multiple modes. ii) Using the multi-modal incremental tensor decomposition method to process dynamically growing data without decomposing all the data, greatly reducing computational cost and improving data quality. iii) Using the XGBoost classification algorithm for anomaly detection to improve detection accuracy. Finally, the results of experiments on two real network traffic datasets NSL-KDD and CICDDOS 2019 show that the proposed framework can achieve a high detection rate of 99.21%, and has the characteristics of good scalability and fast detection speed.

Multi-fidelity simulation of aeroengine for far-off-design conditions using iterative coupled method based on auxiliary maps

Iterative coupled methods are widely used in multi-fidelity simulation of rotating components due to the simple implementation, which iteratively eliminates the errors between the computational fluid dynamics models and approximate characteristic maps. However, the convergence and accuracy of the iterative coupled method are trapped in characteristic maps. In particular, iterative steps increase sharply as the operation point moves away from the design point. To address these problems, this paper developed an auxiliary iterative coupled method that introduces the static-pressure-auxiliary characteristic maps and modification factor of mass flow into the component-level model. The developed auxiliary method realized the direct transfer of static pressure between the high-fidelity models and the component-level model. Multi-fidelity simulations of the throttle characteristics were carried out using both the auxiliary and traditional iterative coupled methods, and the simulation results were verified using the experimental data. Additionally, the consistency between the auxiliary and traditional iterative coupled methods was confirmed. Subsequently, multi-fidelity simulations of the speed and altitude characteristics were also conducted. The auxiliary and traditional iterative coupled methods were evaluated in terms of convergence speed and accuracy. The evaluation indicated that the auxiliary iterative coupled method significantly reduces iterative steps by approximately 50% at the near-choked state. In general, the auxiliary iterative coupled method is preferred as a development of the traditional iterative coupled method in the near-choked state, and the combined auxiliary-traditional iterative coupled method provides support for successful multi-fidelity simulation in far-off-design conditions.

A Short-Term Vessel Traffic Flow Prediction Based on a DBO-LSTM Model

To facilitate the efficient prediction and intelligent analysis of ship traffic information, a short-term ship traffic flow prediction method based on the dung beetle optimizer (DBO)-optimized long short-term memory networks (LSTM) is proposed. Firstly, according to the characteristics of vessel traffic flow, speed, and density, the traffic flow parameters are extracted from the AIS data; secondly, the DBO-LSTM model is established, and the optimal hyperparameter combinations of the LSTM are found using the DBO algorithm to improve the model prediction accuracy; then, taking the AIS data of a part of the coastal port area in Xiangshan as an example, we compare and analyze the results of the recurrent neural network, temporal convolutional network, LSTM, and DBO-LSTM prediction models; finally, the results are displayed and analyzed by visualization. The experimental results show that each error is reduced in predicting the flow parameter, speed parameter, and density parameter, and the accuracy reaches 95%, 92%, and 95%, respectively. After predicting the three parameters in the next 24 h, the accuracy rate reaches 93%, 91%, and 94%, respectively, compared with the real data, which surpasses the comparison model and achieves better prediction accuracy, verifying the feasibility and reasonableness of the proposed prediction model.