Safe Operation Research Articles

MFE-SSNet: Multi-Modal Fusion-Based End-to-End Steering Angle and Vehicle Speed Prediction Network

AbstractIn the field of autonomous vehicles, accurately predicting steering angle and speed is a pivotal task. This task affects the accuracy of the final decision of the autonomous vehicle and is the basis for ensuring the safe and efficient operation of the autonomous vehicle. Previous studies have often relied on data from only one or two modalities to make predictions for steering angle and vehicle speed, which were often inadequate. In this paper, the authors propose a Multi-Modal Fusion-Based End-to-End Steering Angle and Vehicle Speed Prediction Network (MFE-SSNet). The network innovatively extends the one-stream and two-stream structure to a three-stream structure and cleverly extracts features of images, steering angles, and vehicle speeds using HRNet and LSTM layers. In addition, in order to fully fuse the feature information of different modal data, this paper also proposes a local attention-based feature fusion module. This module improves the fusion of different modal feature vectors by capturing the interdependencies in the local channels. Experimental results demonstrate that MFE-SSNet outperforms the current state-of-the-art model on the publicly available Udacity dataset.

Characteristics of flow structure of lateral inlet/outlet in pumped storage power stations

Investigating the complex separated flows in lateral inlet/outlets of pumped-storage power stations(PSPS) is crucial for optimizing their design to ensure safe and efficient operation. In this study, Large Eddy Simulations (LES) are employed to reveal the relationship between turbulence intensity and the distribution of coherent structures in separated flows, as well as the evolution characteristics of hairpin vortices. The flow separation is notably influenced by the vertical diffusion angles α, which causes recirculation zones at the top of the inlet/outlet, leading to significant local flow velocities at the trash racks and increasing the risk of flow-induced vibration damage. Areas of high turbulence intensity exist at the top and bottom of the core flow, caused by the propagation of corresponding streams of vortical flow, which is identified as the primary cause of head loss in the inlet/outlet. Based on the average turbulence intensity, the inlet/outlet can be divided into zones of sharp turbulence increase, high turbulence intensity, and decreasing turbulence intensity. The vortical flow mainly includes three types of coherent structures: attached vortices, hairpin vortices, and quasi-streamwise vortices. Among these, the frequency of top hairpin vortices and the growth angle of hairpin vortex packets are highly susceptible to α. The growth direction of hairpin vortex packets closely aligns with the direction of turbulence intensity propagation. These findings contribute to optimizing the design of inlet/outlet of PSPS.

An efficient state-of-health estimation method for lithium-ion batteries based on feature-importance ranking strategy and hybrid kernel extreme learning machine algorithm

The safe and reliable operation of battery systems depends critically on accurately and dependably estimating the state of health (SOH) of lithium-ion batteries (LIBs). However, accurate prediction of SOH still needs improvement due to the complex battery aging mechanism. This paper introduces a hybrid kernel extremum learning machine (HKELM) for estimating battery SOH. To improve estimation accuracy, we enhance the standard dung beetle optimization algorithm (DBO) with a new initialized population, adaptive weights method, and improved population diversification. We then use the enhanced IDBO algorithm to optimize the parameters of HKELM. This study examines two distinct anode types of LIBs from NASA and Oxford datasets. Fifty significant features are extracted from charging voltage, current, temperature, and incremental capacity (IC) curves. The importance indices of these features are then computed using statistical analyses, including Pearson's correlation coefficient and Spearman's rank correlation coefficient, followed by optimal ranking. The optimal number of final features is determined by comparing various combinations of high-level features, thus reducing model complexity and improving estimation accuracy. This paper proposes the IDBO-HKELM algorithm for SOH estimation. Compared to other methods, the algorithm shows superior estimation performance and anti-interference capability. Both B0007 and Cell8 estimate SOH with MAE < 0.15, RMSE <0.2, and R2 > 99.9 %. Experimental results demonstrate the robustness of the proposed method, achieving accurate and noise-immune SOH estimation.

Fuel Cell-Based Distributed Robust Optimal Scheduling for Combined Heat and Power Supply

At present, the safe operation of integrated energy systems is significantly affected by the considerable uncertainty inherent to wind and photovoltaic power generation. Based on this, this paper proposes an optimal scheduling model for integrated electricity, heat, and hydrogen-based energy systems on distributed robust optimization (DRO). Firstly, a combined heat and power microgrid system considering hydrogen energy systems was constructed based on the thermoelectric cogeneration characteristics of fuel cells and electrolyzers. Then, a data-driven two-stage distribution robust optimization scheduling model is built by combining typical historical data of wind power output, photovoltaic power output, and load. The results show that the distributed robust method reduces the running cost by 6% compared to the deterministic method. The proposed method and model are capable of meeting the demand for thermoelectric loads within the microgrid in a more cost-effective manner, thereby achieving stable and independent operation of the system.

Simulation-based adaptive optimization for passenger flow control measures at metro stations

Effective passenger flow control measures are essential for the safe operation of metro stations. Existing in-station control measures include adjusting the operation mode of escalators and setting up temporary fences. However, in practice, metro operators often adopt fixed operation modes during fixed periods, indicating that the current passenger flow control measures at metro stations are overly rigidified. Therefore, developing an adaptive control strategy to constantly balance the wildly fluctuating passenger flow and optimize the operation performance is a key issue in current research. In this study, transportation efficiency and congestion risk are selected as evaluation objectives for passenger transportation risk, and passenger flow feature, station structure, and passenger flow control measures are considered key influential factors. Subsequently, an adaptive optimization method integrating simulation and data interpolation is proposed. The software Legion is used to conduct 150 orthogonal simulations, and prediction models for passenger transportation risk are obtained by performing data interpolation on the simulation results. Finally, taking a certain metro station as a case study, the optimal passenger flow control strategy under any passenger flow composition is obtained by scenario acquisition, risk identification, and adaptive decision-making. The results show that setting up temporary fences can reduce the passenger density near the fare gates, while adjusting the running direction of escalators can reduce overcrowding on the platform. Under varying passenger flow composition, the optimal strategy for the current scenario can be obtained, controlling passenger transportation risk within an acceptable range and providing assistance for metro operators in decision-making.

Transient behavior of pumped storage-wind hybrid power system under grid-connected operation condition

The large-scale grid connection of renewable energy represented by wind power threatens the safe and stable operation of electric system. The vigorous development pumped storage power station (PSPS) is a global consensus to support the grid-connected of renewable energy. This paper investigates the transient behavior of pumped storage-wind (PSW) hybrid power system under grid-connected operation condition (GCOC). Firstly, a model of PSW hybrid power system under GCOC is constructed. The stable domain is determined according to Hopf bifurcation theory. The influence of system parameters on the stability of PSW hybrid power system under GCOC is analyzed. A synergetic control strategy is designed to improve the dynamic performance of the system. Then, the mechanism of multi-time-scale dynamic response is revealed. Finally, the transient behavior of PSPS under different application scenarios and the interaction between PSPS and wind power station (WPS) are studied. The results show that the stability of PSW hybrid power system under GCOC can be judged by stable domain. The designed synergetic control strategy can improve the dynamic performance of the system. The dynamic response is composed of three oscillations with different frequencies, namely, mass oscillation at low frequency, water hammer oscillation at medium frequency, and electrical oscillation at high frequency. The principal oscillation is caused by water hammer. The interaction between PSPS and WPS has a significant effect on the transient behavior. By adjusting the interaction between PSPS and WPS, the system can absorb more wind power while ensuring safe and stable operation, which can increase profits and avoid unnecessary operation oscillations. The analytical methods and results presented in this paper are of great significance for improving the ability of power grid to accept renewable energy.

Advancement of Finite Element Method Solver Used in Dam Safety Monitoring System by Interpolation of Pore Pressure and Temperature Values

In this paper, we focused on the advancement of Dam Monitoring Software that incorporates the Finite Element Method (FEM), as these large infrastructure constructions are crucial for ensuring a dependable water supply, irrigation, flood control, renewable electric energy generation, and safe operation, which is of utmost importance to any country. However, the material properties and geotechnical environments of dams can change (deteriorate) over time, while the standards and legal norms that govern them become more and more rigorous, so in order to accurately assess the state of a dam and detect any concerning behavior, the software must be updated as well. The custom-developed FEM solver, unlike many commercial alternatives, is adaptable and can be reconfigured to function within a Dam Monitoring System. In this paper, we present the procedure for interpolating numerical values at measurement points, when the position of the measurement point does not align with the node of the element, allowing for additional instrument locations to be added to the monitored system without the need for remeshing the numerical model. This procedure is used to compare the actual pore pressures and temperature values of the concrete dam structure with the prediction of the numerical model, and the agreement is much greater with the new interpolation algorithm in comparison to the nearest nodal values, with the average relative difference for pore pressure reduced from 8.89% to 8.10%, justifying this implementation.

A Review on Mechanism and Influencing Factors of Shear Performance of UHPC Beams

Ultra-High-Performance Concrete (UHPC) is increasingly used in various engineering projects due to its exceptional mechanical properties. This work conducts a literature review of research on the shear performance of UHPC beams in recent decades, with a focus on summarizing the formulas for calculating shear capacity and the main factors influencing shear performance. Firstly, this work reviews the calculation methods for the shear capacity of UHPC beams in different countries, along with their respective advantages and limitations. Subsequently, it provides a detailed analysis of various factors influencing the shear performance of UHPC beams, including longitudinal and stirrup reinforcement, steel fiber content, aggregates, admixtures, the shear-span ratio, shear keys, bolts, shear-reinforcement techniques, and environmental impacts. Through horizontal comparisons, the performance of UHPC beams and ordinary concrete beams under similar experimental conditions is examined to reveal the optimal shear working conditions for UHPC beams. Additionally, it is found that UHPC performs exceptionally well in composite beams, being compatible with numerous materials and significantly enhancing the shear strength of these beams. Lastly, the paper proposes suggestions for maximizing the shear performance of UHPC beams within a safe and reliable operating range and outlines future research directions.

A review of load forecasting technology based on artificial intelligence

Abstract. Driven by the "dual carbon" goals and the construction of new-type power systems, the importance of power load forecasting technology has become increasingly prominent. Accurate power load forecasting can not only ensure the safe and stable operation of the power system, but also promote the efficient use of clean energy and reduce carbon emissions. Traditional power load forecasting methods have become insufficient in dealing with the complexity and nonlinear growth of power systems, and the development of artificial intelligence technology has brought new possibilities for power load forecasting. Power load forecasting methods based on machine learning and deep learning have gradually become a hot topic of research due to their powerful nonlinear mapping capabilities and advantages in processing big data. These methods not only perform well in short-term forecasting, but also show potential in medium- and long-term forecasting. This paper discusses the application of different artificial intelligence technologies in power load forecasting by sorting out the development status of related technologies, and provides a reference direction for future research.

Development of calculation methods for the uncertainty of special mechanical characteristics of structural steel

Understanding of an accuracy related to the evaluation of special mechanical performances of materials is an essential part of the quality control system providing for safe operation of modern structures in severe climatic conditions in far locations where any emergency and repair activities are hindered. In absence of a priori known values of such performances the methodic basis of uncertainty calculation procedures should be developed. Relevance of the problem is supported by the requirement of Russian Accreditation Agency regarding the availability and due application of the corresponding methods in test laboratories as for directly measured parameters as for ones calculated from the test results. Uncertainty calculation procedures are suggested as a background for the developed specialized software.

Dynamic response characteristics of proton exchange membrane fuel cell during transient loading: An experiment study

The dynamic performance of Proton Exchange Membrane Fuel Cell (PEMFC) is crucial for safe and efficient operation and remains a major barrier to commercialization. In this paper the dynamic response characteristics of PEMFC under serpentine flow field (SFF) and parallel flow field (PFF) are discussed. The effects of current loading, operating pressures, anode and cathode stoichiometric ratios, as well as operating temperatures on the dynamic response characteristics of PEMFC are systematically studied through experimental methods. Furthermore, the principle and mitigation strategies for voltage undershoot are investigated. It shows that lower current density, higher back pressure and higher temperature are benefit to alleviate voltage undershoot. Compared with the SFF, the Second-stage time delay of PFF is shortened by 9.2 s, the VU is decreased by 17.27 mV, and the energy loss is reduced by 0.71%. Moreover, Pearson correlation coefficient is proposed to evaluate the correlation between index and PEMFC performance.

Dynamic state awareness for distribution network based on robust adaptive cubature kalman filter

With the rapid development of the economy and society, the demand for power quality is constantly increasing. As a crucial part of grid situational awareness, distribution network state estimation plays a vital role in providing critical data support for other advanced applications, which is significant for ensuring the safe and reliable operation of the distribution network. Therefore, this paper proposes a dynamic state awareness method for distribution networks based on the robust adaptive cubature Kalman filter (RACKF). The proposed solution, grounded on the core computational concept of the cubature Kalman filter (CKF), constructs a robust noise statistical estimator (NSE) composed of a biased NSE and an unbiased NSE to adapt to the unknown and time-varying process noise parameters in the dynamic state estimation process. The proposed solution can ensure that the calculated process noise parameters always meet the constraints and guarantee the robustness of the algorithm. In addition, an estimation strategy for the fusion of multi-time scale measurement data is developed according to the RACKF-based dynamic state estimation features in order to realize system state corrections and updates. The results of simulation experiments and comparisons with traditional CKF methods demonstrate the accuracy and superiority of the proposed solution.

Laboratory Experimental Investigation on the Structural Optimization of a Novel Coupled Energy Tunnel

Freezing damage to tunnels in cold regions has long posed a threat to the safe operation of high-speed trains and other means of transportation. Finding a reasonable and effective solution to this problem, while also considering green, low-carbon, energy-saving, and environmental protection measures, has garnered widespread attention. Herein, the concept of a novel coupled energy tunnel is proposed, which combines the technologies of an air curtain and ground source heat pump (GSHP). The aim is to effectively address the issue of freezing damage in tunnels located in cold regions, while ensuring traffic safety. First, the multifunctional experimental apparatus for testing the anti-freezing and insulation performance of a coupled energy tunnel was independently designed and developed for laboratory experiments. Second, single-factor experiments and orthogonal experiments are conducted, and the influences of five key factors (i.e., the air outlet hole diameter, air outlet hole spacing, circulating water temperature of the GSHP, wind speed at the tunnel model entrance, and airflow jet angle) on the internal temperature field of the tunnel model are discussed. Third, combined with range analysis and variance analysis, the ranking of importance for each key factor and the optimal scheme of the coupled energy tunnel are obtained as follows: wind speed at the tunnel model entrance D &gt; circulating water temperature of GSHP C &gt; airflow jet angle E &gt; air outlet hole spacing B &gt; air outlet hole diameter A, and the optimal scheme is A2B1C4D1E2, i.e., the air outlet hole diameter is 3 mm, the air outlet hole spacing is 10 mm, the circulating water temperature of GSHP is 50 °C, the wind speed at the tunnel model entrance is 1.5 m/s and the airflow jet angle is 45°. In conclusion, the research achievements presented in this paper can offer a new perspective for the structural design of tunnels in cold regions. Additionally, they contribute to the early achievement of a carbon dioxide emissions peak and carbon neutrality, and provide some valuable and scientific references for both innovators and practitioners.

A comprehensive framework for examining the influence of tower crane safe operations on sustainable practices in modular integrated construction

PurposeThis study aims to explore the tower crane safety factors (TCSFs) that influence tower crane safe operations (TCSOs) in modular integrated construction (MiC). It evaluates how the adoption of these factors contributes to achieving TCSOs and promoting sustainable practices (SPs) within MiC.Design/methodology/approachTo achieve this aim, the study employed a systematic search to ensure a comprehensive collection of variables. Additionally, it conducted a questionnaire survey involving professionals and utilized a brainstorming technique to categorize the different variables. Finally, partial least squares structural equation modeling (PLS-SEM) was employed to test the relationship between TCSOs and SPs.FindingsThe results of measurement models indicated strong convergent and discriminant validity, with each observed variable correlating well with its latent variable. Moreover, a significant positive correlation between TCSOs and SPs was evidenced by a path coefficient (β = 0.755) and a p-value of &lt;0.05. Lastly, the structural model revealed that the independent variables strongly influence the dependent variable (i.e. SPs) by 57%, underscoring safety's pivotal role in advancing sustainability within MiC projects. These findings provide empirical evidence that improving tower crane safety can directly enhance sustainable practices, offering a dual benefit of increased safety and sustainability for the construction sector.Originality/valueThis study makes a unique and previously undiscovered contribution to the field by identifying the TCSFs in MiC and employing a novel approach by utilizing PLS-SEM to create a unique mathematical model. It offers valuable insights into the relationship between TCSFs, TCSOs and SPs, thus contributing to methodological advancements within Safety Science and providing a foundation for future research and practical implementation in the construction industry.

Numerical and experimental study on corrosion mechanism of the water-oil two-phase flow in the atmospheric tower top system

The atmospheric tower is the main component of the crude oil refining units and is a critical area of concern due to the risk of corrosion failure. Research on the corrosion mechanism and risk protection of atmospheric tower top systems plays a vital role in the safe operation of refineries. In this paper, the water-oil two phase process flow of the atmospheric tower top system was simulated by Aspen software. A corresponding flow corrosion simulation experiment was designed according to the main characteristic parameters of the simulated stream. The experimental results under varying temperature and impact angle conditions were analyzed by using microanalysis technology and CFD simulation methods. The process and mechanism of corrosion failure of tower top system under ammonia salt and dew point corrosion environment are revealed in physicochemical aspects. The results show that the corrosion rate was highest at the dew point temperature, but as the temperature decreases, the corrosion products adsorbed and accumulated on the surface are more difficult to remove from the surface, which slows down the corrosion rate. When the impact angle increased from 0° to 60°, the increment of the surface fluid impact force and turbulence intensity makes the corrosion products easier to be stripped off, which enhances the mass transfer efficiency between the corrosive medium and the surface to accelerate the corrosion rate. Different phase states and flow modes affected the morphology of corrosion pits on the surface. The depth and size of the pits in only water phase corrosion were larger than those in the two-phase flow corrosion, Additionally, as the impact angle increased from 0°, the morphology of pits changes from a relatively flat pattern to a more undulating shape. The research results reveal the characteristics of the main corrosion types occurring in the atmospheric tower top system of the oil refining industry, and provide a reference for corrosion risk protection methods.

Risk assessment of transmission towers based on variable weight theory and matter-element extension model

Abstract The risk assessment of transmission towers is a critical approach to ensuring the safe and stable operation of power grids. In response to the increasingly frequent and severe impacts of seasonal permafrost on transmission towers in permafrost regions, this paper proposes a novel risk assessment method based on Variable Weight Theory and the Matter-Element Extension Model. By incorporating key influencing factors—such as the number of freeze-thaw cycles, soil moisture content, temperature fluctuations, soil dry density, melting settlement coefficient, and porosity ratio—an indicator system tailored to risk assessment in seasonal permafrost regions is established. Utilizing the Matter-Element Extension Model, this approach applies Variable Weight Theory to integrate both the best-worst method and the entropy weight method for calculating subjective and objective indicator weights. The risk level of the towers is then determined by their proximity to risk thresholds. Finally, a case study involving transmission towers in a specific region of a province in China is presented, where the assessment results are compared with the actual conditions to validate the rationality and effectiveness of the proposed method.

Research on the Optimization Method of Bus Travel Safety Considering Drivers’ Risk Characteristics

Bus drivers have an important role in ensuring road safety, as their driving circumstances fluctuate due to the combined influence of physiological, psychological, and environmental dynamics, which can cause complex and varied driving dangers. Quantifying and assessing drivers’ risk characteristics under various scenarios, as well as finding the best fit with their work schedules, is critical for enhancing bus safety. This research first uses the entropy weight method, which is based on historical warning data, to examine the risk characteristics of bus drivers in various complicated contexts. It then creates an objective function targeted at minimizing the operational risk for a specific bus route. This function uses the quasi-Vogel approach and an improved simulated annealing algorithm to optimize and restructure the scheduling table, taking individual driver risk characteristics into account. Finally, the analysis is confirmed and examined with actual operational data from the Zhenjiang Bus Line 3. The data show that enhanced bus operations resulted in a 7.22% gain in overall safety and a 33.76% improvement in balancing levels. These insights provide valuable theoretical guidance as well as practical references for the safe operation and administration of public buses.

UAV 2D Path Planning Considering Ground Suitability for Flying Safety in Digital Twin

Abstract. The utilization of various UAVs such as facility inspection and delivery is increasing. Ensuring safety in carrying out various UAV missions is an important issue related to human and property damage. Safe operation of UAVs flying autonomously along pre-located routes requires safe route planning to prevent collisions between aircraft in consideration of ground and air obstacles. Pass flight is also essential to minimize damage in the event of a crash. This paper deals with the optimal UAV 2D routing plan considering ground compatibility for flight safety. High ground compatibility here means that the damage caused by the crash is less than when it is not. In this paper, we first defined dynamic and static obstacles. Next, we derived ground compatibility considering dynamic and static obstacles. We used estimation algorithms and land use data to calculate ground compatibility values for flight safety, and through experiments, we calculated an optimal 2DUAV route plan for flight safety.

Operations Regarding Safe Educational Institutions of Educational Institutions under the Jurisdiction of the Saraburi Primary Educational Service Area Office 2

Background and Aims: The purpose of this research is to study and compare the opinions of personnel regarding safe educational operations in educational institutions under the jurisdiction of Saraburi Primary Educational Service Area Office 2. Classified by position educational institution size and work experience in addition, the objective is to study guidelines for promoting and developing the operation of safe educational institutions in educational institutions under the same affiliation. Methodology: The sample group used in the research consisted of 317 personnel from educational institutions under the Saraburi Primary Educational Service Area Office, Area 2, obtained by stratified random sampling (Stratified Random Sampling). The research instrument was the questionnaire has a 5-level rating scale with an IOC between 0.80 - 1.00 and a confidence value (Cronbach's Alpha) equal to 0.79. Structured interviews were also used to collect additional information. Statistics used in data analysis include frequency, percentage, mean, and standard deviation, T-test (t-test) and analysis of variance (ANOVA or F-test). Results: The results of the research found that: (1) The operation of educational institutions is safe. of educational institutions under the jurisdiction of the Saraburi Primary Educational Service Area Office 2, overall and in each aspect It was found to be at a "very high" level in all aspects, which shows that the operation of safe educational institutions has been carried out efficiently in every dimension. (2) Results of comparative analysis operations in the area of ​​safe educational institutions. Classified by position It was found that there was a statistically significant difference at the 0.05 level while categorizing by school size and work experience found that there was no difference. (3) Operational guidelines Regarding safe educational institutions under the Saraburi Primary Educational Service Area Office 2, it was found that: 1) In terms of preventive measures should proceed with the preparation of a safety plan that covers all dimensions. 2) Instilling measures safety workshops should be organized for teachers. educational personnel and students 3) suppression measures guidelines for managing or suppressing incidents should be established. Including assistance when an incident occurs in an educational institution and create mutual awareness in all sectors. Conclusion: Operations regarding safe educational institutions of educational institutions. There should be a safety plan for educational institutions that covers all dimensions. Educational institutions provide an environment and atmosphere that is safe for students, teachers, and educational personnel. There are guidelines for managing or suppressing incidents. Assistance when an incident occurs in an educational institution and there are workshops on safety of educational institutions for teachers, educational personnel and students.

Geotechnical Justification for Designing Landslide Prevention Measures

Abstract When designing anti-landslide measures, slope stability assessment is an important factor and is determined by conducting comprehensive engineering and geological studies on a slope with potential landslide risks. The results of correct engineering and geological justification for the design of anti-landslide measures lead to the preservation of the structure and safe operation of infrastructure facilities. Our experience shows that to eliminate the negative effects of landslide processes, it is necessary to accurately determine the engineering and geological conditions of the slope, including the stability of the slope, taking into account natural dynamic phenomena (seismicity of the territory and tectonic processes) and, if possible, to see the complete elimination of the causes that lead to landslide processes when developing anti-landslide measures. To achieve these goals, the geotechnical justification of the design is the only correct solution. Geotechnical justification of protective measures intended to protect the structural elements of the Baku-Russian Federation State Border highway, which is part of the north-south transport corridor and passes through the foot of a potentially landslide-hazardous slope west of the city of Shabran, is one of the most important conditions that increase the effectiveness of these measures. On a slope located 1500 meters southwest of the current research area, the results of our scientific research were not properly utilized and many of our warnings were not heeded, resulting in a landslide during construction, leading to serious damage to the road's structural elements (Fig. 1) and additional costs. This event once again confirms that landslides are the most common natural and man-made processes that pose a threat to the safe operation of infrastructure facilities, civil and industrial construction in mountainous and foothill areas (Shiraliyev et al., 2024)