Actual Conditions Research Articles

Impact of turbine availability and wake effect on the application of dynamic thermal rating of wind farm export transformers

Dynamic thermal rating allows transformers to operate beyond the nameplate rating according to the actual weather and loading conditions. This paper proposes a methodology to improve the application of this technology in the design of new transformers or in the operation of existing transformers connected to wind farms by accurately predicting their load profiles, accounting for the influence of wake effect and turbine availability. Specifically, the variation of turbine availability due to the intermittent wind is considered in the load profile estimation. Additionally, a correction method, which can be incorporated into any wake model, is proposed to improve the accuracy of wake loss computation. A case study shows that the wake effect and the changing turbine availability shorten the time that the transformers maintain at full load, thereby reducing the aging rate of the wind farm export transformers. The findings suggest that considering these two factors in the application DTR application can benefit the longevity and efficiency of wind farm exported transformers.

Regional Evaluation Study of VFTO Interference to Secondary Side Cables Based on Cloud Model and MARCOS.

With the advent of the data era, most power secondary side equipment tends to be digitized. The power system needs more accurate numerical results to further improve its operating efficiency. Therefore, it is important to study the electromagnetic interferences of very fast transient overvoltage (VFTO) generated by gas-insulated switchgear (GIS). To protect the secondary side cable from interferences, the secondary side cable is wrapped with an outer shield and the shield is grounded. When the interference of VFTO comes, it will couple the interference current and interference voltage on the shield of the cable. By grounding, the interference is greatly discharged. However, due to the grounding resistance, there will be a potential difference between the grounding points at the two ends of the shield of the cable. This causes a corresponding interference current to flow through the shield, which will affect the transmission of signals inside the cable. In the actual substation, the resistivity of the soil, the ambient temperature and humidity of the area, and so on will have impacts on the grounding resistance. In addition, the irregularity of the cable arrangement and the time of the use of the cable will have impacts on the signal transmission of the cable. Based on the abovementioned issues, this article proposed a comprehensive assessment method based on the combination of the cloud model and measurement of alternatives and ranking according to compromise solution (MARCOS). The method brings the cloud model into MARCOS by the algorithm of the contribution of the cloud droplets. It overcomes the difficulty of cloud model quantification. By comparing the results of the proposed method with the actual conditions at the substation and the results of the common MARCOS assessment method, the validity of the method is verified, and a reference scheme is provided for substation optimization.

Analysis of swallowtail mutation instability of slope with weak interlayer under blasting disturbance

Abstract The stability analysis of slope under blasting disturbance is one of the important research topics in blasting engineering and geotechnical engineering. Based on the dynamic instabil-ity mechanical model of slope with weak interlayer, the mechanical effect of blasting dis-turbance on slope system is analyzed. The swallowtail mutation model of slope system under blasting disturbance is established. Two methods to determine slope stability under blasting disturbance are proposed: safety factor method and double judgment method. Through the analysis of the dynamic instability mechanism of the slope system under the effect of blast-ing disturbance, it is concluded that: (1) the greater the amplitude of blasting disturbance vibration, the worse the stability of the slope system, and the greater the possibility of land-slide disaster. The slope landslide disaster caused by blasting disturbance mainly occurs in the middle and late stage of blasting disturbance (0.17 ∼ 0.5s). (2) When the period of blast-ing vibration wave (T > 1s), the frequency of blasting disturbance wave can be appropriately increased, which is conducive to reducing the impact of blasting disturbance on slope stabil-ity. When the period of blasting disturbance wave (T < 1s), proper adjustment of blasting disturbance frequency will not have a direct impact on the stability of slope. (3) With the increase of the incident angle of blasting vibration wave, the change of the dynamic self-stability critical height of the slope system shows a trend of increasing, and the in-creasing rate is decreasing. The greater the incident angle of blasting vibration wave, the worse the stability of slope system. Proper reduction of the incident angle of blasting vibra-tion wave is beneficial to improve the stability of slope system. Finally, the rationality and applicability of thse proposed double judgment method are verified based on the actual con-ditions of the current slope in Laoyingzui.

Dynamic evaluation of road and bridge engineering construction safety risk based on Fuzzy Dynamic Bayesian Network research

To comprehensively and objectively evaluate the actual safety condition in road and bridge engineering construction, the road and bridge engineering construction safety risk evaluation index system is constructed combined with the factors induced by emergencies in the road and bridge engineering construction process. Aiming at the dynamic uncertainty of road and bridge construction safety risk, using Fuzzy Set Theory and an improved similar aggregation method to determine the prior probabilities and conditional probabilities of network nodes, and then selecting the transition probabilities of nodes through expert opinions and incident reports, leading to the development of a dynamic evaluation model for safety risks in road and bridge engineering construction based on Fuzzy Dynamic Bayesian Network, this model can make the construction safety risk prediction result accurately. Taking the Hebi City Provincial Highway 304 reconstruction project as an example for analysis, the results indicate that the model can accurately predict the probability of changes in safety risks in road and bridge engineering construction. Additionally, it can identify critical risk factors and provide crucial supporting information for decision-makers to optimize risk management strategies.

Damage Detection in Structural Health Monitoring Using an Integrated ANNIRSA Approach

In the past decade, artificial neural networks (ANNs) have been widely employed to address many problems. Despite their powerful problem-solving capabilities, ANNs are susceptible to a significant risk of stagnation in local minima due to using backpropagation algorithms based on gradient descent (GD) for optimal solution searching. In this paper, we introduce an enhanced version of the reptile search algorithm (IRSA), which operates in conjunction with an ANN to mitigate these limitations. By substituting GD with IRSA within an ANN, the network gains the ability to escape local minima, leading to improved prediction outcomes. To demonstrate the efficacy of IRSA in enhancing ANN’s performance, a numerical model of the Nam O Bridge is utilized. This model is updated to closely reflect actual structural conditions. Consequently, damage scenarios for single-element and multielement damage within the bridge structure are developed. The results confirm that ANNIRSA offers greater accuracy than traditional ANNs and ANNRSAs in predicting structural damage.

Optimizing Retention Bunkers in Copper Mines with Numerical Methods and Gradient Descent

This study examines the optimization of ore receiving bins in underground copper mines, targeting the reduction of rapid wear and tear on bin components. The investigation identifies the primary wear contributors as the force exerted by the accumulated ore and the velocity at which ore particles move. By altering design and operational parameters, the objective is to decrease wear at key points such as transfer areas, thereby improving the efficiency and service life of retention bunkers. A Discrete Element Method (DEM) model of the bin was created and validated against actual mining conditions to study the impact of material flow on wear. The optimization approach used a constrained gradient descent algorithm to minimize factors like particle velocity and pressure force, while maintaining the efficiency of the bin. The findings provide valuable insights for the future design enhancements, potentially improving the operational performance of retention bunkers in the mining industry.

The actual conditions and issues in responding to food allergies during disasters

The actual conditions and issues in responding to food allergies during disasters

An Integrated Monitoring, Diagnostics, and Prognostics System for Aero-Engines under Long-Term Performance Deterioration

In the field of aircraft engine diagnostics, many advanced algorithms have been proposed over the last few years. However, there is still wide room for improvement, especially in the development of more integrated and complete engine health management systems to detect, identify, and forecast complex faults in a short time. Furthermore, it is necessary to ensure that these systems preserve their capabilities over time despite engine deterioration. This paper addresses these necessities by proposing an integrated system that considers the joint operation of feature extraction, anomaly detection, fault identification, and prognostic algorithms for engines with long operation times. To effectively reveal the actual engine condition, light adaptive degraded engine models are computed along with different health indicators that are used as inputs to train and test recognition and prediction models. The system is developed and evaluated using a specialized NASA platform which provides data from a turbofan engine fleet simultaneously experiencing long-term performance deterioration and faults. Contrary to other compared solutions, our results show that the proposed system is robust against the effects of engine deterioration, maintaining its level of detection, recognition, and prediction accuracy over a total engine service life. The low computational cost algorithms has generally fast performance in all stages, making the system suitable for online applications.

Analysis of Potential Water Inflow Rates at an Underground Coal Mine Using a WOA-CNN-SVM Approach

The water yield of aquifers increases the risk of water inflow, threatens the safe production of coal mines, and even causes geological disasters and construction hazards. To predict water yield quickly and accurately, multiple composite factors are used to invert unit water inflow rates to judge water yield grade. Taking the typical representative of north China-type coal fields as an example, six factors are selected: aquifer thickness, the radius of influence, normalized drawdown, permeability coefficient, the core rate of drilling holes, and the proportion of clay thickness to the thickness of the lower group. The whale optimization algorithm (WOA)–convolutional neural network (CNN)–support vector machine (SVM) model is established with the unit water inflow rate as the forecast target, and different models are selected for comparison. The water yield zoning map is obtained by bringing the borehole data into the model for prediction. The findings indicate that the root mean square error and average absolute error of the composite predictive model models are 0.0318 and 0.0268, respectively, and the model outperforms alternative models. The predicted water yield zoning aligns well with the actual conditions, offering a novel paradigm for water yield assessment.

The study of human resource management in Chinese SMEs

With the rapid development of China's economy, small and medium-sized enterprises (SMEs) play an important role in promoting national economic growth, creating job opportunities and promoting technological innovation. However, at present, there are many problems in human resource management in China's SMEs, which limit their development potential and competitiveness, such as the lagging management concept, imperfect training mechanism and high employee turnover rate in human resource management. This paper puts forward the corresponding solutions, such as establishing the people-oriented management concept, increasing the training input, optimizing the salary and welfare system and establishing a good promotion mechanism. At the same time, SMEs should adjust and optimize according to their actual conditions to ensure that these strategies can effectively improve the level of human resource management and provide support for the sustainable development of enterprises.

Bus Lane Design Based on Actual Traffic Loads and Climate Conditions

Bus lanes play a crucial role in urban areas as their primary objective is to increase public transport efficiency and help traffic and public transit systems flow more smoothly. This study starts with traffic and climate monitoring to verify asphalt bus lanes in Rome, Italy, according to the Italian Pavement Design Catalogue published in 1995. KENLAYER software calculated the stress-strain conditions under real traffic loads (i.e., hourly passages of urban buses, considering their axle load and seat occupancy rate), typical subgrade bearing capacity (i.e., resilient modulus equal to 90 MPa), current climate conditions, and road material properties. Then, the Mechanistic-Empirical Pavement Design Guide (MEPDG) was used to verify the response of the pavement structure. The fatigue verification of bound materials resulted in damage values much lower than 1 at the end of the 20-year service life (i.e., 0.12 with the Asphalt Institute and 0.31 with the Marchionna law, respectively) and highlights that the Italian catalogue’s sheets are overdesigned. On the other hand, the rutting verification according to MEPDG is not satisfied after an 11-year service life (i.e., the total rutting is equal to 1.50 cm), forcing frequent and expensive maintenance of wearing and binder courses. Therefore, the results confirm the validity of the Italian catalogue for fatigue service life and suggest the need for high-performance asphalt to prevent early rutting due to bus traffic increasing by load and frequency in previous decades.

Research on the deformation and settlement characteristics of tunnel lining structures based on distributed fibre optic sensing technology

To study the deformation and settlement characteristics of tunnel lining structures, a tunnel lining structure model was designed based on distributed fibre optic sensing technology. Compared to the cylindrical model used in traditional tunnel lining structural model experiments, in this study, a reinforced concrete structural model was adopted, which can embed fibre optics in the structure, which is closer to actual tunnel engineering conditions. Central and symmetrical concentrated loading experiments were carried out with a simply supported reaction frame. The results of the distributed fibre optic monitoring were compared and analysed with those of traditional monitoring methods to verify the reliability of the distributed fibre optic monitoring results. The numerical simulations of the experiments were conducted by using finite element analysis. By comparing and analysing the simulation and experimental results, the correctness of the simulation calculation results were verified. On this basis, the impact of concrete strength, circumferential reinforcement spacing, and longitudinal reinforcement strength on the deformation and settlement of the tunnel lining structure were analysed. The results show that the hierarchical effect of the strain monitoring results obtained by the embedded fibre optic is more obvious, indicating that the radial monitoring effect of the embedded fibre optic on the tunnel structure is less affected by other external factors than the strain gauge, and the monitoring data are more accurate and effective, with good engineering characteristics. Improving the concrete strength, appropriate circumferential reinforcement spacing, and increasing the longitudinal reinforcement strength can effectively enhance the ability of the structure to resist deformation at the stress location. These factors play a significant role in improving the overall resistance to deformation and safety of the structure. The research results provide a theoretical basis and experimental data for the application of distributed fibre optics in monitoring the deformation and settlement of tunnel lining structures.

Study on the indoor thermal comfort of cave dwellings in cold areas of China

Cave dwelling, as a common traditional housing form in rural areas, has long been regarded as a low-cost, green, and environmentally friendly living choice. The purpose of this study was to explore and improve the thermal comfort of cave dwellings, and to systematically evaluate and analyse the thermal comfort of cave dwellings through a combination of visit surveys and indoor environmental parameter monitoring. After statistical analysis and comparison of the collected data, the following conclusions were drawn: (1) The thermal neutrality temperature of 25.15 °C determined by Predicted Mean Vote (PMV) in this study was greater than the thermal neutrality temperature of 19.49 °C determined by Thermal Sensation Vote (TSV) model, indicating that cave dwellers prefer a cooler thermal environments under actual conditions. (2) In cold weather, the maximum value of 80% acceptability is 18.12 °C and the minimum value is 12.00 °C. In hot weather, the maximum value of 80% acceptability is 27.17 °C and the minimum value is 23.66 °C. (3) In winter, the average indoor temperature of 9.71 °C is higher than the average outdoor temperature of 7.85 °C; In summer, the average temperature in the naturally ventilated room of 27.44 °C is much lower than the average outdoor temperature of 35.25 °C. The results showed that the building materials and structure of cave houses can provide a certain degree of thermal insulation, which can provide a basis for the design and improvement of low-cost, energy-saving and environmentally friendly houses in rural areas.

Multi objective optimization scheduling of unmanned warehouse handling robots based on A star algorithm

SummaryThe sorting efficiency of the warehouse management and handling robots (automated guided vehicles [AGVs]) in an unmanned warehouse affects the delivery and lead time of orders. Studying the collaborative sorting of multiple AGVs can significantly improve work efficiency. The goal of this paper is to minimize the overall shortest transportation path and time while ensuring the completion of all orders and corresponding recycling or return tasks. This paper conducts experiments on global path planning for multiple AGVs based on the A* algorithm, both without considering collision and deadlock situations, and considering collision and deadlock situations. The results show that without considering collision and deadlock situations, the method of matching fixed storage locations and picking stations can improve overall efficiency, while considering collision and deadlock problems will result in reduced efficiency. In the future, the model will be further optimized taking into account actual conditions to improve overall efficiency.

Developing Representative Test Specimen Conditions for Rutting Mechanical Test Methods of Airfield Pavements

Developing Representative Test Specimen Conditions for Rutting Mechanical Test Methods of Airfield Pavements

Novel material to enhance the integrity of CCUS cement sheath: Exploration and application of calcium aluminate cement

Carbon dioxide (CO2) emissions are being reduced using the technique known as CCUS (Carbon Capture, Utilization, and Storage). At present, cementing cement paste based on ordinary silicate cement (OPC) and compounded with CO2 corrosion-resistant materials are often used in CCUS wells. CAC cement is characterised by low alkaline hydration content and its study in CCUS wells has rarely been reported. Therefore, CAC cement will be a new cement material for CCUS wells. In this study, we have developed an experimental device to simulate the working conditions of CCUS based on the actual well conditions of CCUS and investigated the effects of stress-coupled CO2 corrosion environment on the performance of CAC cement. According to the experimental findings, CAC cement's compressive strength degraded at a rate of 30.6% after 60 days of CO2 corrosion, which was lower than that of OPC cement (38.3%). When compared to OPC cement, the peak strain and stress of CAC cement increased by 57.2% and 7.85%, respectively. Furthermore, compared to OPC cement sheath, the CAC cement sheath's bearing capacity increased by 8 MPa after stress corrosion, and the crack area of the CAC cement sheath after failure was considerably smaller at 275 mm3 than at 735 mm3. Additionally, after being subjected to stress-coupled CO2 corrosion, the integrity of the CAC cement sheath was much superior to that of the OPC cement sheath, offering a fresh viewpoint for building CCUS cement slurry systems.

Application of machine learning in sanitation management prediction: Approaches for achieving sustainable development goals

Due to lack of understanding about the different conditions of sanitation systems and complexity, mostly in Asia and Africa, the occurrence of unsafely managed sanitation still exists, leading to severe environmental and health impacts. Because of the complexity of this problem, machine learning tools were applied to develop an effective model for health protection and safe sanitation management as a promising way to approach sustainable development goals. This study aimed to examine the incidences of ineffective sanitation management on the prevalence of diarrhea infections using machine learning tools. The prevailing conditions for safely sanitation management were identified, and the effective model to protect the impacts of ineffective sanitation management on the prevalence of diarrhea infections was proposed. Based on information collected from about 1000 households with relatively high diarrhea infections during the period of 2017–2021, factors relating to sanitation facilities for health protection and safe sanitation management were examined. Diarrhea infections and no diarrhea infection were recognized based on actual conditions of the surveyed households and incidences from ground-based observation. Classification tree model as J48 in WEKA was applied for analytic predictive tool using 70:30 ratio of training and validating dataset. The findings showed that the tree model obtained from the training data was with 73% accuracy prediction, while that from the validation data was with 70% accuracy. The correlation of personal hygiene (such as washing hand before meal and drinking water from natural water sources) and sanitation facilities (such as open defecation and distance from on-site sanitation facilities to open drains or storm sewer) was significant with inverse relationship for safely sanitation management and public health protection.

Hydro‐pedo‐transfer‐functions expressing drought and memory effects on pine tree growth

AbstractOver the last 30 years, the impact of climate change in Berlin, Germany, has manifested in the form of reduced summer rainfall, elevated temperatures, and a notable rise in the frequency of days with temperatures surpassing 30°C. All of them are leading to a decreasing water supply and increasing risk of drought. Various field, laboratory, and numerical simulation studies have been done for deriving information on long‐term potential and actual evapotranspiration, water stress during the vegetation period (April–September), and tree ring growth of various pine tree stands in Berlin. Data analysis highlights periodical climate patterns and complex interactions between drought, water supply, and plant growth. Annual tree ring growth is not only related to the actual weather conditions but also to the past climate years. With decreasing water supply, this kind of drought memory effect increases up to 5 years into the past. For Berlin's climate, it is noteworthy that late summer, particularly the water stress in August, represents the most sensitive indicator for tree ring growth.For regionalization purposes, long‐term numerical simulations were done to derive hydro‐pedo‐transfer‐functions (HPTFs) predicting the water stress coefficient of the growing season (Eact‐s/Epot‐s). They only need easily available information such as soil texture, climate water balance, and groundwater depth. Two HPTFs were successfully tested and can be easily applied by geo‐information systems. However, for other climate regions and tree species, HPTFs need to be adapted.

Classification and rating of disintegrated dolomite strata for slope stability analysis

Although disintegrated dolomite, widely distributed across the globe, has conventionally been a focus of research in underground engineering, the issue of slope stability issues in disintegrated dolomite strata is gaining increasing prominence. This is primarily due to their unique properties, including low strength and loose structure. Current methods for evaluating slope stability, such as basic quality (BQ) and slope stability probability classification (SSPC), do not adequately account for the poor integrity and structural fragmentation characteristic of disintegrated dolomite. To address this challenge, an analysis of the applicability of the limit equilibrium method (LEM), BQ, and SSPC methods was conducted on eight disintegrated dolomite slopes located in Baoshan, Southwest China. However, conflicting results were obtained. Therefore, this paper introduces a novel method, SMRDDS, to provide rapid and accurate assessment of disintegrated dolomite slope stability. This method incorporates parameters such as disintegrated grade, joint state, groundwater conditions, and excavation methods. The findings reveal that six slopes exhibit stability, while two are considered partially unstable. Notably, the proposed method demonstrates a closer match with the actual conditions and is more time-efficient compared with the BQ and SSPC methods. However, due to the limited research on disintegrated dolomite slopes, the results of the SMRDDS method tend to be conservative as a safety precaution. In conclusion, the SMRDDS method can quickly evaluate the current situation of disintegrated dolomite slopes in the field. This contributes significantly to disaster risk reduction for disintegrated dolomite slopes.

Monitoring of Ventilation, Portable Air Cleaner Operation, and Particulate Matter in California Classrooms: A Pilot Study

Interest in improving ventilation and indoor air quality (IAQ) in California schools has grown since the COVID-19 pandemic. This paper presents a field protocol for simultaneous monitoring of usage patterns of in-room portable air cleaners (PACs), indoor and outdoor concentrations and composition of particulate matter (PM), and CO2 as an indicator of outdoor air ventilation rates (VRs). This protocol was implemented for a 7-week pilot study in four occupied California classrooms in 2022. Monitoring results showed that VRs and indoor PM were generally well maintained in the classrooms studied. One classroom had much higher overall VRs, as well as higher average indoor PM2.5 concentrations compared to similar classrooms, suggesting a possible strong impact of window/door opening behavior on both VRs and indoor PM. The actual use patterns of PACs in these classrooms varied significantly. No clear correlations were observed between PAC use patterns and indoor PM2.5 concentrations in this pilot study, possibly due to low outdoor PM2.5 concentrations and already efficient central filtration (i.e., MERV 13 filters in central ventilation systems). Information gathered through such field monitoring can help schools to understand the actual classroom ventilation and IAQ conditions and best allocate resources to classrooms that need further IAQ improvements.