Monitoring Points Research Articles

ResGRU: A deep learning approach for settlement prediction in CFRD based on the spatiotemporal feature fusion method

Settlement is one of the most critical safety evaluation indicators for concrete face rock-fill dams. Deformation measurement data exhibit spatiotemporal correlation due to similar environmental factors and material properties. However, the current research has focused mainly on single-point prediction models, which ignore the relationship between settlement values and various parts of dams. To address these issues, the spatiotemporal correlation of settlements across multiple measurement points is considered and a deep learning approach based on spatiotemporal feature fusion is proposed. First, a density peak clustering algorithm categorizes monitoring points characterized by analogous deformation patterns. Then, a deep learning model combining residual neural networks (ResNet) and gated recurrent unit neural networks (GRU), i.e. ResGRU, is established. In ResGRU, ResNet is used to map the input data’s features to more complex high-dimensional patterns through convolution and obtain deep nonlinear spatial features. GRU is used to capture the temporal dependencies of data to obtain temporal features. Finally, the spatiotemporal features are fused through fully connected layers to predict settlements. The model is validated and compared with deep learning models using monitoring data collected from an actual concrete face rock-fill dam. The proposed approach demonstrates superior performance with an average RMSE and MAE of 0.352 and 0.255, respectively, and an average R2 of 0.988. The results show that the ResGRU model generally outperforms the other models. This approach provides an efficient and convenient approach for the settlement analysis of concrete face rock-fill dams.

Investigating the Mechanism of Land Subsidence Due to Water Network Integration at the Guangzhou Longgui Salt Mine and Its Impact on Adjacent Subway

Water-soluble mining was invariably associated with surface subsidence, which in some cases escalated to the movement, deformation, and even collapse of the overlying rock layers, triggering grave subsidence calamities. The caprock of the salt-bearing strata in the Longgui salt rock mining area was closely adjacent to the third aquifer, which mainly consisted of fractured, porous, high-permeability materials such as mudstone conglomerates, rendering the geological conditions highly complex. Years of water-soluble mining had led to significant surface subsidence in the mining area, with a trend toward accelerated subsidence. In this study, the geological conditions of the Longgui salt rock mining area were analyzed, and through simulated experiments of pillar dissolution mining, the mechanisms of surface subsidence in the area were examined. Over time, the dissolution gradually perforated the pillars and caprock, with the pillars ceasing to support the caprock, ultimately transforming small cavities into a large single cavity. Utilizing subsidence data, this research employed numerical simulation to inverse and predict subsidence patterns from 2019 to 2025, revealing that the maximum subsidence reached 1367.6 mm in mining area I and 1879.5 mm in mining area II, with subsidence rates of 12.05 mm/y and 44.78 mm/y, respectively. Moreover, the impact of ground subsidence on the construction of adjacent subways was assessed by establishing monitoring points and evaluating subsidence along subway cross-sections and longitudinal directions. The findings provided valuable insights for guiding the prevention and control of surface subsidence calamities in the Longgui salt rock mine and similar mining areas in Guangzhou, China.

Analysis of the temporal, spatial, and frequency law of the internal flow in a prototype vaned mixed‐flow pump

AbstractMixed‐flow pump is a typical pump using in low‐head cases of water lifting. The flow field pulsation is usually an important issue in the operation of mixed‐flow pumps and their pumping statins. Due to its large size, it is difficult to monitor the internal flow characteristics well, based on computational fluid dynamics, we use 5678 monitoring points which arranged in the impeller and fixed vane with using the high pulsation tracking network, and the pressure pulsation signals are analyzed by fast Fourier transform and variable mode decomposition to decompose the main frequency and intensity of the pressure pulsation signals, then analyze the energy dissipation with the entropy production rate (EPR). It is found that there are strong low‐frequency (0.416, 0.625, and 1.67 Hz) pressure pulsation near hub, and the pressure pulsation on the shroud is stronger than that on the hub (at least three times or more); there are strong and stable pressure pulsation (25 Hz) on the shroud generated by the rotor–stator interference (RSI); and the EPR in the flow field can be well combined with the signal. Reasonably allocating material strength and controlling the number of vanes and impellers to avoid producing a common multiple can avoid pressure pulsation caused by RSI and reduce energy dissipation. Therefore, it is very effective in improving the efficiency of this part. Under low flow conditions, the siphon outflow passage can predict the high‐frequency (45.833 Hz) attenuation area well through the phase signal decomposition of the signal, which has certain significance for improving its stability and efficiency.

Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics

Co-injection of conservative tracers with carbon dioxide (CO2) is a viable tool for monitoring subsurface processes during geological CO2 storage (GCS). This research investigates the simulation and history-matching of a gas tracer (sulfur hexafluoride, SF6) during CO2 flooding, employing a core flooding result in Berea sandstone. Four extensively used saturation functions are assessed for their efficacy in history matching of CO2/SF6 injection at the core scale. The history-matching process incorporates particle swarm optimization (PSO) to fine-tune constitutive relationships parameters. Next, employing transport models at the aquifer scale, we interrogate the impact on tracer transport and mixing of saturation function uncertainties, arising from the non-uniqueness of constitutive relationships parameters and saturation function types. To assess the effects of geological heterogeneity on behavior of tracer breakthrough curves (BTCs), we employ two normalized parameters assessing the degree of mixing and SF6 breakthrough time. The aquifer-scale investigation encompasses both homogeneous and heterogeneous systems with and without capillary heterogeneity effects. Our findings underscore the critical importance of addressing saturation function uncertainties, emphasizing the significance of auxiliary experiments and innovative methodologies to enhance predictive accuracy. The findings highlight significant disparities in arrival times, BTC peaks, tails, and mixing levels, even under optimal conditions. Heterogeneity, with or without capillary heterogeneity, plays a crucial role in shaping BTC variations, resulting in accelerated SF6 breakthrough times and reduced BTC peaks. Evaluation of monitoring points distant from the injector reveals a dampening effect on the SF6 BTC peak, particularly in heterogeneous systems with capillary heterogeneity, where the peak is halved. These insights underscore the challenges associated with tracer monitoring and the necessity for enhanced methodologies to improve predictive accuracy in subsurface processes during GCS.

CFD study of the residence time distribution of shaft-injected hydrogen in a blast furnace

Hydrogen, as a carbon-free reducing agent, can be adopted in the blast furnace (BF) ironmaking process to replace carbon-bearing materials towards green steelmaking partially. Theoretically, hydrogen can be introduced into the BF via shaft injection, and its residence time distribution (RTD) has not been studied or reported in detail in open literature. In this study, a multi-fluid BF model is developed further to investigate the RTD of hydrogen when injected into the BF through shaft inlets. It is observed that the RTD of shaft-injected hydrogen exhibits some features of piston-type flow but varies at different monitoring points. For the case studied, increasing the hydrogen injection rate decreases the average residence time of hydrogen from 12.2 s to 10.1 s. Similarly, increasing the hydrogen injection temperature slightly reduces the average residence time from 10.4 s to 9.5 s. These results indicate that the hydrogen flow rate has a relatively more significant effect on the RTD than the injection temperature. Moreover, it is found the utilisation efficiency of shaft-injected hydrogen is influenced by both the limited residence time and conditions on the trajectories followed by the fluid particles. The model presented in this study provides an alternative and cost-effective method to enhance our understanding of the hydrogen RTD inside an ironmaking BF.

Emergency monitoring layout model for sudden water pollution accidents in water distribution networks

ABSTRACT The layout of emergency monitoring points (EMPs) in water distribution networks is one of the main measures to ensure the water safety of residents and preserve the sustainable development of cities and society. The impact factors on the layout of EMPs are first analyzed. Then, a new emergency monitoring layout model is presented with the goal of maximizing the number of the excluded possible sources and minimizing the formulated time of emergency response. Finally, taking EPANET Network 3 as a simulation case to verify the proposed model. The results show the new layout model can effectively exclude 60% of the number of possible sources, and shorten 18% of the formulated time of emergency response measure. There are many factors that affect the layout of EMPs, which mainly include the time of arranging EMPs, the latest time to formulate the emergency response measure, the number of emergency monitoring equipment available, and the relative error criteria of pollutant concentration, from apparently to slightly. It provides a new idea for emergency decision-makers to deal with sudden water pollution accidents in water distribution networks.

CFD Characterization and Field Test Study on Plugging Air Leakage with Time-Varying Viscosity Solidified Foam to Prevent Coal Spontaneous Combustion

ABSTRACT From the perspective of plugging air leakage paths and preventing coal spontaneous combustion in the goaf of coal mines, filling and plugging the ends of the working face is crucial. Generally speaking, rapidly solidified foam slurry is beneficial to plugging air leakage paths. However, researchers have not yet clarified the accumulation and diffusion rules of rapidly solidified foam, resulting in low efficiency in plugging air leakage paths. To solve the above problems, this study takes the goaf of 1301 working faces of the Shandong Lilou Coal Industry as the research object, uses the computational fluid dynamics modeling method to construct a physical model of pressure injection foam slurry, and optimizes the on-site application process parameters of plugging the end of the working face. The numerical simulation results show that coagulant can improve the accumulation characteristics and plugging efficiency of foam slurry, and the optimal addition amount is 3 wt%. In addition, as the perfusion flow increases from 5 to 15 m3/h, the airflow rates on the working face gradually increases and the oxidation zone gradually shrinks. Therefore, the grouting flow is preferably 15 m3/h. Field test results show that rapid-setting inorganic solidified foam blocks the airflow at the air inlet corner from leaking into the goaf and weakens the composite reaction of coal and oxygen. The temperature at each monitoring point first decreased, then stabilized, and the final temperature was maintained at 27-28°C. The CO concentration gradually decreased and finally remained below 20 ppm. The CO concentration of the mine’s total return airflow is stable below 10 ppm. This study can provide theoretical guidance for the technological design of using solidified foam to rapidly plug the air leakage paths at the end of the fully mechanized caving working face.

Effect of Integrated Landscape Characteristics Around Chaohu Lake on River Water Quality Based on Watershed Units

Considering the impact of differences in watershed characteristics on river water quality, with the Chaohu Lake Basin as the research object, based on the data of water quality, meteorology, topography, soil, and remote sensing images of the river monitoring points from October 2019 to September 2020, the watershed unit at each monitoring point was divided through digital terrain analysis, and the comprehensive landscape characteristics based on the watershed unit were explored through the comprehensive use of correlation analysis, redundancy analysis, and multiple regression analysis to investigate the influence of comprehensive landscape characteristics based on watershed units (including land use, climate, topography, soil, etc.) on the water quality of rivers around Chaohu Lake. The results showed that:① the water quality of rivers around Chaohu Lake had large spatial differences, with the main pollutants being total nitrogen and ammonia nitrogen. Most of the rivers had total nitrogen concentrations exceeding the Class V water quality standards, and the areas with serious nitrogen and phosphorus pollution were concentrated in the urban area of Hefei and the surrounding rivers, as well as in the middle and lower reaches of the Fengle and Hangbu Rivers. ② The comprehensive landscape characteristics of the watershed unit had a significant impact on the river water quality. Among them, the proportion of built-up land, the density of patches, the dispersion and juxtaposition index, and the Shannon diversity index were positively correlated with the water quality indicators, whereas the proportion of forest and grassland and the spreading index were negatively correlated with the water quality indicators. ③ In different seasons, the effect of the integrated landscape characteristics of the watershed unit on river water quality was stronger in the wet season than in the dry season, which was mainly caused by the difference in precipitation in the dry and wet seasons.

Prediction of Buildings’ Settlements Induced by Deep Foundation Pit Construction Based on LSTM-RA-ANN

In view of the shortcomings of existing methods for predicting the settlement of surrounding buildings caused by deep foundation pit construction, this study uses the monitoring data of a foundation pit project in Shanghai and divides the construction process of the pit into three working conditions, that is, enclosure construction, earthwork excavation, and basement support construction. The attention mechanism and residual update are integrated into the artificial neural network (ANN) model, and the root-mean-square error, average absolute error, and determination coefficient are used as the evaluation indices of the model. The artificial neural network prediction model LSTM-RA-ANN for building settlements in deep foundation pit construction was then established. The prediction performance of the model was also analysed under different working conditions, and the influences of the main factors (including the soil parameter, monitoring point location, activation function, hyperparameter, and input number) on the evaluation index was further explored. The results indicate that the performances of the established LSTM-RA-ANN model are closely related to the construction conditions, the predicted settlements agree well with the monitored ones in three working conditions with the greatest errors occurring at a later time of the working conditions, and the prediction accuracy of the great–small order corresponds to basement support, enclosure construction, and earthwork excavation respectively. The farther the monitoring point is from the edge of the pit, the better the model performance is. The activation function, initial learning rate, and maximum iteration batch have a great influence on the evaluation indices of the model, while the number of input points has little effect on the evaluation indices. These results may serve as a reference for the safe construction and normal operation of foundation pit engineering.

Characterization of heavy metal contamination in groundwater of typical mining area in Hunan Province

Heavy metal pollution in mining areas is a major cause of groundwater contamination, characterized by high toxicity, difficult degradability, and easy accumulation, and the source of pollution is not easily identified. Relying on the results of groundwater quality analysis tests in a typical mining area, this paper uses the SPSS 18.0 statistical analysis model to analyze the statistical characteristics of different indicator factors in the antimony mining area. The conclusions play a crucial role in implementing health and safety measures for the mining area and its surrounding residents. The statistical study results show that Mn, Se, As, and Sb are closely related to human mining activities and are polluted to varying degrees; the principal component analysis model indicates that the upstream monitoring points 26#, 22#, and 25# in the mining area groundwater are less polluted. The five monitoring points with a comprehensive principal component F > 1 are all located within the range of the metal mine cluster, indicating that the groundwater in the mining area is particularly sensitive to the impact of anthropogenic mineral extraction. This research summarizes the hydrogeological and geochemical statistical characteristics of the groundwater in the mining area, providing a reference for groundwater pollution risk diagnosis, ecological restoration, and heavy metal pollution prevention and control in this and similar mining areas.

Multifractal Characteristics and Displacement Prediction of Deformation on Tunnel Portal Slope of Shallow Buried Tunnel Adjacent to Important Structures

The tunnel portal section is often in extremely weak and fragmented strata, and the deformation of the portal side and slope will affect the stability of the surrounding rock and the tunnel-supporting structure. However, the deformation characteristics and displacement development patterns of slopes in the tunnel portal section are not clear. In this paper, the multifractal characteristics and displacement prediction of the deformation sequence of the tunnel portal slope at of a weak and water-rich shallow buried tunnel adjacent to an important structure are studied in depth. Combined with the deformation characteristics of the tunnel portal slope, a suitable slope monitoring and measurement scheme is designed to analyze the deformation pattern of the tunnel portal slope. Based on the multifractal detrended fluctuation analysis (MF-DFA) method, the multifractal characteristics of the deformation monitoring sequences at each monitoring point of the tunnel portal slope are analyzed. The multifractal characteristics of displacement sequences at different monitoring points of the tunnel portal slope are consistent with the actual monitoring results. Furthermore, the Long Short-Term Memory (LSTM) model is optimized using the Particle Swarm Optimization (PSO) algorithm to predict the deformation of the tunnel portal slope. The results show that the maximum mean square error (MSE) of the horizontal displacement test set prediction results is 0.142, and the coefficient of determination (R2) is higher than 91%. The maximum value of MSE for vertical displacement test set prediction is 0.069, and the R2 are higher than 91%. The study shows that the performance of the PSO-LSTM prediction model can meet the requirements for predicting the displacement of the tunnel portal slope. Based on the MF-DFA method and PSO-LSTM prediction model, the fluctuation characteristics of the displacement value of the tunnel portal section can be accurately identified and the displacement development pattern can be effectively predicted. The conclusions of the study are of great practical significance for the safe construction of the tunnel portal section.

Investigation of flow-induced sound source generation in a centrifugal pump

Abstract This study investigates the mechanism of sound source generation in a centrifugal pump under different flow conditions. The calculated results are in good agreement with experimental data by employing the delayed detached eddy simulation and flow-acoustic coupling method to compute the flow-induced noise. Based on the vortex sound theory and vorticity binary decomposition, the sound source (STA) is divided into a shear-induced source (STS) and a rigid rotation-induced source (STR). The results show that the sound source induced by shear is the main factor. The fluctuation amplitude of STS can be nine times larger than STR at monitor point near the tongue under the design flow rate condition. There is a mutual cancellation effect between the STS and STR. The fluctuation amplitude of STA at the blade passing frequency is 86% of STS at monitor point near the tongue under high flow rate conditions, indicating that sometimes rigid rotation can suppress noise generation.

Pressure Fluctuation analysis of pump-turbine in turbine mode under the same head condition

Abstract As the key technical part of pumped-storage power station, the efficient and stable development of pump-turbine units is of great significance for renewable energy power generation. However, pump-turbine units have the characteristics of complex and variable operation conditions. In addition, under different guide vane openings, operation conditions of pump-turbine units also show different flow patterns and pressure fluctuation characteristics. For the sack of studying the pressure fluctuation characteristics of pump-turbine units in turbine mode, a dynamic model of a pump-turbine unit is established in this research. Based on SST k-ω turbulence model, combined numerical simulation and experimental test, pressure fluctuation laws in vaneless region and draft tube under three typical guide vane openings are carried out. The results indicate that, by increasing the guide vane opening, the pressure fluctuation intensity of each monitor point is decreased. Furthermore, the pressure fluctuation at the monitor points in vaneless region between guide vane and the runner presents a periodic change rule, which is mainly due to the two-stage rotor and stator interference between guide vane and runner, and between runner and draft tube. The research further clarifies the pressure fluctuation law in turbine mode, and provides theoretical reference for long-term sustainable development of pump-turbine units.

Analysis of flow characteristics of a pump turbine under the transient condition of 75% load rejection

Abstract In this study, the flow calculations for a pump turbine under the transient condition of 75% load rejection was conducted. The model incorporated a boundary layer on the surface of the guide vane, with the node coordinates of each element in the boundary layer region being updated. This approach ensured the stability of the boundary layer mesh. Experimental measurements provided parameter curves for inlet pressure, outlet pressure, runner speed, and guide vane opening over time. The pressure fluctuation at each monitoring point was compared with the experimental data, and a good agreement was found. Additionally, the variation curve of the axial hydraulic thrust of the head cover and the pressure distribution nephogram of the head cover at typical moments were analysed. The results of this study could be used as a reference for the safe and stable operation of pumped-storage power stations.

Analysis of pressure pulsation in a multi-stage double suction centrifugal pump

Abstract Pressure pulsation is a common phenomenon, which results from different causes. The intenser pressure pulsation occurs in the pump, the severer the damage to the pump. In the paper, with the assistance of detached eddy simulation method, the characteristic of pressure pulsation in the multi-stage double suction centrifugal pump is studied to understanding the internal flow circumstance. The results reveal that the pressure pulsation intensity reaches the maximum at blade trailing edge, which propagates to the tongue region of forward flow channel and double-volute under the low rates. Furthermore, it can be concluded that the pressure pulsation of region with obvious rotor–stator interaction between rotating impeller and stationary volute is generally larger at low flow rates. The pressure pulsation near the suction side of blade trailing edge shows the feature of broadband frequency and with increasing flow rate the bandwidth of broadband decreases drops rapidly except BP1. Due to the influence of the number of impeller blades, the dominant frequency of monitoring points in the inter-stage flow channel and the volute is basically located at a frequency that is twice the blade frequency. Meanwhile, because of the symmetry of the geometric structure of the reverse flow channel, the pressure pulsation curve changes of its internal monitoring points are similar under the same flow rate.

Effectiveness of Air Admission through Short Pipes in Reducing Pressure Fluctuation of Propeller Hydro-turbine Flow Channel

Abstract When the hydro-turbine operates under part-load conditions, a large-scale vortex flow will form in the draft tube. This vortex can cause low-frequency pressure pulsations that endanger the safe operation of the hydro-turbine. By injecting air into the draft tube, the structure of the vortex can be effectively disrupted, reducing the amplitude of the pressure pulsations. In this paper, a propeller hydro-turbine was studied, and the SST k-ω turbulence model based on the Reynolds averaged Navier-Stokes equations (RANS) was utilized to perform a full-channel unsteady numerical simulation on a part-load condition with the guide vane opening (GVO) of 35°. Then, the fast Fourier transform (FFT) was applied to analyze the pressure fluctuations at monitoring points on the draft tube wall, the head cover, and the nose of the spiral casing. The results indicated that injecting air with an appropriate flow rate into the draft tube through short pipes can reduce the pressure fluctuations on the draft tube wall by 51.4% to 72.5% and decrease the pressure fluctuations on the head cover and the nose of the spiral casing by approximately 40% to 42%. This study proposes a new air admission structure that can enhance the operating stability of the propeller hydro-turbine under part-load conditions.

Study on the flow characteristic of pump turbine at partial load

Abstract Pump turbine adopts the same runner to realize forward pumping for pumping condition and reverse power generation for turbine condition, which is a widely used power equipment in pumped storage power station. Compared with conventional pump units or turbine units, the pump turbine has a complex internal flow, especially under part load conditions, and the vibration and noise problems of the structure are prominent. In this paper, the internal flow characteristics of the pump turbine at 60% load are studied by numerical simulation. The low-frequency pressure pulsation 3.5fn and 5.5fn that occur under this operating condition are analyzed. The results show that under partial load conditions, the opening of the guide vane decreases, the angle of attack of the water entering the runner increases, and the rotating stall phenomenon occurs in the pump turbine. The stall vortices show periodic variations on the blade inlet pressure surface and undergo the processes of vortex reduction, fusion, splitting and increase, respectively. The frequency of change is 0.5 times the runner rotation frequency (0.5fn ). The frequency of the corresponding monitoring points in the 7 blade rotor is 7 times (1fn -0.5fn ), which is 3.5fn .

Dynamic stress analysis of a large capacity Pelton turbine runner

Abstract The dynamic stress characteristics of a Pelton turbine runner is an important index to evaluate the stability of unit. Aiming to analyse the dynamic stress of a large capacity prototype Pelton turbine runner influenced by the unsteady impact load of a high-speed jet, the unsteady flow simulation was firstly taken for the Pelton turbine runner to conclude the hydraulic model of internal flow and the performance parameters. Then, the dynamic stress of the Pelton runner was solved by fluid-structure coupling numerical method. The dynamic stress variation trend of several monitor points distributed on the splitter, brim, bucket root was analysed. It is concluded that the impact load of the jet could lead to the significant change in the dynamic stress on specific location of the bucket surface, and the stress concentration was found at the bucket root.

Numerical simulation on unsteady cavitating flows in a rotational hydrodynamic cavitation reactor

Abstract The RNG k-ε turbulence model and mass transport cavitation model Zwart-Gerber-Belamri are used to simulate unsteady cavitating flows in a rotational hydrodynamic cavitation reactor (RHCR). The RHCR is mainly composed of rotor and stator. Unsteady cavitation flow field analyses in RHCR are focused mainly near the rotor surface. The numerical simulation results are in good agreement with the experimental data. The frequency of pressure fluctuations and streamline distribution are discussed by setting 10 monitoring points near the rotor surface. The numerical simulation results shows that the main frequency of pressure fluctuation inside RHCR is 24f r and 72f r; the maximum amplitude of pressure fluctuations appears near the inlet, and its value about 3 times than the minimum. Moreover, the streamline distribution analyses demonstrate that the vortex appears near the rotor surface, and is generating, growth and disappearing with time. The shape, vortex center and intensity of the vortex near the inlet change drastically with time. This research provided a reference for the optimization design of RHCR.

Subway track foundation settlement deformation prediction based on the BiLSTM-AdaBoost model

The rapid economic expansion has spurred extensive construction near subway networks, impacting the stability of their track foundations. Consequently, it’s crucial to monitor and predict settlement in subway track foundations. However, the dynamic deformation patterns often exhibit nonlinearity and non-stationarity, posing challenges for traditional linear regression models. To tackle this, our study integrates the BiLSTM (bi-directional long short-term memory) network with the AdaBoost ensemble learning algorithm. Using settlement data from Shanghai metro monitoring points, the model is trained and evaluated employing R2 (coefficient of determination), MAE (mean absolute error), and RMSE (root mean square error). Results show that our proposed model displays superior predictive accuracy compared to the LSTM and the BiLSTM, with an average training set R2 of 0.99, test set R2 of 0.78, average MAE of 0.32 mm, and average RMSE of 0.4 mm. Consequently, for forecasting subway track foundation deformations, employing our network model ensures highly accurate predictive capabilities.