Hydropower Station Research Articles

Development of Remote Condition Monitoring System for Panauti Hydropower Station

Abstract Condition monitoring is the process of predicting faults in machine through the measurement and analysis of pre-identified parameters. This paper aims to present the features and process of development of a real time condition monitoring system installed at Panauti Hydropower station. In total, seven different sensors including Pressure, Temperature, Guide Vane Position and Tri-axial Vibration sensor were installed at the power plant. The locations of the pressure sensors are at the inlet of the turbine and the outlet of the draft tube. Tri-axial vibration sensor was installed at the turbine shaft to capture the turbine vibrations at different operating conditions. The temperature sensors provide the temperature data from the bearings and housing of a generator. The sensors were connected to the NI-DAQ (data acquisition system) hardware including current measuring module and sound and vibration module integrated with the LabVIEW program. The data acquisition system is capable of recording the pressure pulsations at the outlet of draft tube. The monitoring system processes the data from sensors and uploads the relevant information to the Kathmandu University’s central server. A remote monitoring program in LabVIEW has been developed which uses an Application Programming Interface (API) to retrieve the information from the central server in the real time, enabling the monitoring of the power plant from any location.

Enhanced river suspended sediment concentration identification via multimodal video image, optical flow, and water temperature data fusion

Monitoring suspended sediment concentration (SSC) in rivers is pivotal for water quality management and sustainable river ecosystem development. However, achieving continuous and precise SSC monitoring is fraught with challenges, including low automation, lengthy measurement processes, and high cost. This study proposes an innovative approach for SSC identification in rivers using multimodal data fusion. We developed a robust model by harnessing colour features from video images, motion characteristics from the Lucas–Kanade (LK) optical flow method, and temperature data. By integrating ResNet with a mixed density network (MDN), our method fused the image and optical flow fields, and temperature data to enhance accuracy and reliability. Validated at a hydropower station in the Xinjiang Uygur Autonomous Region, China, the results demonstrated that while the image field alone offers a baseline level of SSC identification, it experiences local errors under specific conditions. The incorporation of optical flow and water temperature information enhanced model robustness, particularly when coupling the image and optical flow fields, yielding a Nash–Sutcliffe efficiency (NSE) of 0.91. Further enhancement was observed with the combined use of all three data types, attaining an NSE of 0.93. This integrated approach offers a more accurate SSC identification solution, enabling non-contact, low-cost measurements, facilitating remote online monitoring, and supporting water resource management and river water–sediment element monitoring.

Soil quality enhancement by multi-treatment in the abandoned land of dry-hot river valley hydropower station construction area under karst desertification environment.

The medium-intensity karst desertification environment is typically characterized by more rocks and less soil. The abandoned land in the construction areas of the dry-hot river valley hydropower station has more infertile soil, severe land degradation, and very low land productivity. Therefore, it is urgent to improve the soil quality to curb the increasingly degrading land and reuse the construction site. Few studies have focused on the effect of soil restoration and comprehensive evaluation of soil quality with multi-treatment in abandoned land in the dry-hot valley hydropower station construction area. Here, 9 soil restoration measures and 1 control group were installed at the Guangzhao Hydropower Station construction in Guizhou Province, China, for physical and chemical property analysis. In total, 180 physical and 90 chemical soil samples were collected on three occasions in May, August, and December 2022. Soil fertility and quality were evaluated under various measures using membership functions and principal component analysis (PCA). This study showed that almost all measures could enhance soil water storage capacity (The average total soil porosity of 9 soil treatments was 57.56%, while that of the control group was 56.37%). With the increase in soil porosity, soil evaporation became stronger, and soil water content decreased. Nevertheless, no decrease in soil water content was observed in the presence of vegetation cover (soil water content: 16.46% of hairy vetch, 13.99% of clover, 13.77% of the control). They also proved that manure, synthetic fertilizer, and straw could promote total and available nutrients (Soil total nutrient content, or the total content of TN、TP、TK,was presented as: synthetic fertilizer (11.039g kg-2)>fowl manure (10.953g kg-2)>maize straw (10.560g kg-2)>control (9.580g kg-2);Total available nutrient content in soil, or the total content of AN,AP,A,was shown as:fowl manure (1287.670 mg kg-1)>synthetic fertilizer (925.889 mg kg-1)>sheep manure (825.979 mg kg-1)>control (445.486 mg kg-1). They could also promote soil fertility, among which the first two reached the higher comprehensive soil quality. Fertilizer was conducive to improve soil quality and fertility, yet long-term application could cause land degradation like soil non-point source pollution, compaction, and land productivity decline. Ultimately, combining fertilizer with biochar or manure is recommended to improve soil fertility. Biochar and green manure could play an apparent role in soil improvement only when there is abundant soil water. The above views provide theoretical support for curbing soil degradation, improving soil fertility and quality, enhancing land productivity, and promoting the virtuous cycle of the soil ecosystem.

ANALYSIS OF THE DESTRUCTION OF UKRAINIAN NUCLEAR FUEL CYCLE ENERGY FACILITIES AS A RESULT OF RUSSIAN MILITARY OPERATIONS

Problem statement. Due to Russia's ongoing terrorist attacks on Ukraine's energy facilities, the energy system was damaged, resulting in blackouts and rolling blackouts across the country. The destruction of power capacities resulted in the unstable operation of certain critical infrastructure units for electricity generation at thermal, nuclear and hydroelectric power plants and the introduction of forced hourly blackout schedules. Seizure of the Chornobyl Nuclear Power Plant, occupation and full control of the Zaporizhzhia Nuclear Power Plant and the Zaporizhzhia Thermal Power Plant (TPP). Complete destruction of the Kakhovka hydroelectric power station (HPP), partial destruction of the Dnipro HPP, Dniester HPP and Kaniv HPP. During the hostilities, Kryvyi Rih and Prydniprovia TPPs were damaged, Luhansk TPP (90–100 %), Vuhlehirsk TPP (90–100 %), Zmiiv TPP (up to 90 %) were completely destroyed, Burshtyn TPP (80–90 %) and Ladyzhyn TPP (70–95 %) were almost completely destroyed. The purpose of the article is to identify and analyse the damage to Ukrainian TPPs, HPPs and NPPs caused by the Russian military actions against Ukraine and to determine possible consequences for the nuclear fuel cycle of our country and possible prospects for the transition to new nuclear reactors of European and global fuel cell manufacturers, to improve equipment and stabilise the energy market in the context of military operations. Conclusion. In the course of the analysis of potential hazards at radiation hazardous facilities (RHF) in Ukraine, it was determined that the main threat is accidents at RHF with release of radiation into the atmosphere, lithosphere and hydrosphere. In the light of recent events regarding the military seizure of the Chornobyl NPP and Zaporizhzhya NPP, measurements using standard methods of research, screening and monitoring are not possible, and access of IAEA representatives is limited, which is why the latest measurement methods should be used with the use of autonomous remote-controlled ground, surface and air drones in automatic object or sample measurement of radiation parameters at RNS. It is the use of autonomous vehicles (drones) that is currently the most pressing issue of radiation safety not only in the nuclear power industry but also in the entire nuclear fuel cycle as part of the environmental safety of Ukraine. In case of seizure of a nuclear facility or limited access to it, research methods should be changed. If the facility is partially seized or access is available, then express methods of radiation contamination registration or sampling can be used and the method of laboratory research can be used in the future. However, if a nuclear power plant or a facility that is part of the nuclear fuel cycle of Ukraine is captured and access to it is impossible, then only methods of remote measurement of the radiation situation at and around nuclear facilities using ground and airborne autonomous vehicles remain. For further research, it is necessary to identify technical possibilities for using Ukraine's own mineral resources and switching from Soviet RBMK-1000, VVER-440 and VVER-1000 reactors with fuel elements supplied to us from the Russian Federation to newer types of European and American reactors with appropriate fuel elements.

Modelling Steady State and Transient Stability Parameters for Kainji Hydropower Station, Nigeria

The study explores the creation of a simulator for addressing the problem of predicting response of Nigeria’s Kainji’s Hydro Power Plant (KHPP) to system load variations and to determine parameters for stable operation. A virtual KHPP Simulation Model was designed and created using MatLab/Simulink software. The components of the HSS designed and incorporated in the virtual simulator include models of all eight (8) generating units (GUs). Each GU model consists of the Hydraulic Turbine Governor (PID), synchronous generator and an excitation system. The simulator was tested with steady state stability (SSS) and transient stability (TS) disturbances to obtain response values of system operating state parameters. The tests include a variable load increase, and three-phase short circuit fault for a duration of 0.2 s. The SSS limits established are the following: active load – 810 MW, load angle – 850, terminal voltage 0.68 pu, rotor speed 1.08 pu, excitation voltage 1.55 pu, and stator current 7.5 pu. TS limits established are load angle (1700), terminal voltage (0.60 pu), rotor speed (1.05) pu, excitation voltage (1.25 pu), stator current (7.1 pu), and critical clearing time (0.2s). Clearing time should be set at 0.2s to prevent KHPP and connected system’s instability.

Short-term load distribution model for cascade giant hydropower stations with complex hydraulic and electrical connections

The cascade giant hydropower station system (CGHSS) has been widely applied in countries with abundant water resources. However, the dense hydropower stations and power grids bring complex hydraulic and power connections, including the backwater effect, multiple hydroplants sharing one reservoir and one-reservoir multiple dispatch power grid, which leads to modelling difficulties and inefficient model solving. To address these challenges, a short-term load distribution (SLD) model considering complicated hydraulic and electricity constraints is developed. First, the discharge of each hydroplant and the downstream forebay water level are used as inputs to construct a multivariate nonlinear function, and the average tailwater levels are obtained. Second, a head constraint considering the shared water level is added to the model to calculate the head of each hydroplant, making the output more accurate. Finally, the nonlinear constraints are linearly reconstructed using the Big-M method, triangulation technique and special ordered sets to reduce the model solution time. The SLD model is applied to the Xiluodu-Xiangjiaba cascade hydropower system in the Jinsha River. The results show that the developed model reduces water consumption by 4.02 %, 4.70 %, 5.79 % and 5.28 % compared to the constant proportional distribution model and the real operation, generating a more executable SLD scheme.

Analysis and evaluation of development characteristics of debris flow in Longshougou

Long Shougou is located at the exit of Hei he River in Zhang ye City, which is directly facing the reservoir of Long Shougou Hydropower Station. Through site survey, UAV flight and indoor simulation calculation, the development characteristics and risk of Long Shougou debris flow were analyzed and evaluated. The results show that: Long Shougou debris flow is in the "development period", belonging to "small", "easy" and "high frequency" debris flow; The length of Long Shougou Channel is 1.70 km, the circumference is 3.76 km, the area is 0.72 km2 , the relative height difference is nearly 584 m, the longitudinal gradient is 342.27 ‰, and the overall bending coefficient is 1.14; Gully sediments are mainly gully bed deposits and slope collapse deposits, with total reserves of 20.94 ×104 m3 and dynamic reserves of 7.76 ×104 m3 ; Calculated according to the designed rainstorm frequency of 1%, the flow velocity of debris flow at the gully mouth is 2.64m /s, the total amount of primary overflow is 17,296.41m3 , the primary outflow of solid matter is 7956.35m3 , and the overall impact pressure of debris flow is 16.32kPa. The maximum impact force of a single stone is 2.56kN according to 0.5m; It is suggested to consider the impact of the annual inflow of debris flow on the water quality of the Longshou hydropower station reservoir and the impact on the power station switching station near the Gulou port, and do a good job in the relevant sediment discharge measures.

Analysis on cause of erosion of guide vane of high‐head Francis turbine in sandy river

AbstractThe Kizilsu River Basin in China is located in the desert Gobi area with high sediment content and high hardness. After 4798h operation, the maintenance of a high‐head Francis turbine in this basin found that the guide vane was seriously worn, and even most of the top and lower skirts of the front of the guide vane were worn off. In this study, the k‐ε turbulence model, ZGB cavitation model and sediment erosion prediction model were used to simulate the solid‐liquid two‐phase flow and cavitation of guide vane. The research results show that the guide vane of a high‐head Francis turbine in a sandy river has a high sediment velocity and serious surface erosion, with the maximum erosion rate of 1.0 × 10−6 kg/(m2·s), while the area near the skirt of the guide vane is a low‐pressure area lower than the saturated steam pressure, and cavitation is very easy to occur, with the maximum vapor volume fraction of 0.9. Serious cavitation erosion occurs near the skirt of the guide vane, and the combined effect of sand erosion and cavitation erosion on the surface of the skirt of the guide vane aggravates the damage of the skirt structure. The research results provide a technical basis for the antiabrasion design of the guide mechanism of the high‐head Francis turbine and the operation and maintenance of the hydropower station in the sandy river.

Integrated approach of predicting rock stability in high mountain valley underground caverns

High mountain valleys are characterized by the development of intricate ground stress fields due to geological processes such as tectonic stress, river erosion, and rock weathering. These processes introduce considerable stability concerns in the surrounding rock formations for underground engineering projects in these regions, highlighting the imperative need for rigorous stability assessments during the design phase to ensure construction safety. This paper introduces an innovative approach for the pre-evaluation of the stability of surrounding rocks in underground caverns situated within high mountain valleys. The methodology comprises several pivotal steps. Initially, we conduct inverse calculations of the ground stress field in complex geological terrains, combining field monitoring and numerical simulations. Subsequently, we ascertain stress-strength ratios of the surrounding rocks using various rock strength criteria. To assess the stability characteristics of the surrounding rocks in the 1# spillway cave within our project area, we employ numerical simulations to compute stress-strength ratios based on different rock strength criteria. Furthermore, we undertake a comparative analysis, utilizing data from the 5# Underground Laboratory (Lab 5) of Jinping II Hydropower Station, aligning the chosen rock strength criterion with the damage characteristics of Lab 5′s surrounding rocks. This analysis serves as the cornerstone for evaluating other mechanical responses of the surrounding rocks, thereby validating the pre-evaluation methodology. Our pre-evaluation method takes into account the intricate geological evolution processes specific to high mountain valleys. It also considers the influence of the initial geostress field within the geological range of underground caverns. This comprehensive approach provides a robust foundation for the analysis and assessment of the stability of surrounding rocks, especially in high mountain valley areas, during the design phase of underground engineering projects. The insights derived from this analysis hold substantial practical significance for the effective guidance of such projects.

Research on the mechanism of severe unsteadiness of PAT braking condition during the power failure

The Pump-As-Turbine (PAT) technology has become popular in micro hydropower stations due to its simple installation and cost-effectiveness. Nevertheless, power failures present a substantial risk to the secure and steady functioning of PAT’s braking system. The commercial CFD code (ANSYSCFX) is improved by incorporating a secondary development to model the power-off transition using Fortran accurately. This enhancement allows for real-time iterative calculations of angular momentum equations for mixed-flow PAT at different speeds. Meanwhile, the time–frequency domain analysis is utilized to analyze pressure pulsation signals and the evolution of the internal flow field in mixed-flow PAT. An investigation was conducted to have a deeper understanding of braking circumstances. The results revealed that the main frequency of the pressure pulsation aligns with the blade frequency at various flow rates, and there is a sudden change in pressure amplitude during the braking phase. The impeller experienced the majority of energy losses, with the draft tube being the subsequent area of concern. In addition, a thorough examination and comparison of the changes in the internal flow field during braking were carried out. This analysis revealed a distinct double helix structure within the draft tube, with a slower inner helix and a faster outer helix. Furthermore, it was observed that there is a strong correlation between wall shear stresses and hydraulic losses on the blade surface. This research enhanced understanding of the flow characteristics of mixed-flow PAT can help improve system safety and provide valuable guidance for future optimization efforts.

A novel method for measuring center-axis velocity of unmanned aerial vehicles through synthetic motion blur images

Accurate velocity measurement of unmanned aerial vehicles (UAVs) is essential in various applications. Traditional vision-based methods rely heavily on visual features, which are often inadequate in low-light or feature-sparse environments. This study presents a novel approach to measure the axial velocity of UAVs using motion blur images captured by a UAV-mounted monocular camera. We introduce a motion blur model that synthesizes imaging from neighboring frames to enhance motion blur visibility. The synthesized blur frames are transformed into spectrograms using the Fast Fourier Transform (FFT) technique. We then apply a binarization process and the Radon transform to extract light-dark stripe spacing, which represents the motion blur length. This length is used to establish a model correlating motion blur with axial velocity, allowing precise velocity calculation. Field tests in a hydropower station penstock demonstrated an average velocity error of 0.048 m/s compared to ultra-wideband (UWB) measurements. The root-mean-square error was 0.025, with an average computational time of 42.3 ms and CPU load of 17%. These results confirm the stability and accuracy of our velocity estimation algorithm in challenging environments.

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions*

Abstract Induction motors play a vital role in the cooling water supply system of hydropower facilities. However, it is not feasible to collect sufficient fault samples in a hydropower station. The scarcity of labeled samples poses a challenge in developing powerful diagnostic models with high classification accuracy. To address this challenge, this paper proposes a multi-channel data fusion strategy based on a transformer for feature enhancement. Initially, the original signals are transferred into non-overlapping single-channel data patches to preserve correlation features across different channels. Next, temporal and spatial attention modules are applied to process the data patches, which can learn and fuse temporal and spatial information, respectively. Subsequently, the data patches are embedded to retain position information and represent fault-related features through class embedding, which are further processed by a transformer encoder with self-attention mechanisms. Finally, the classification task is achieved by using a multilayer perceptron layer connected to the class embedding. While dealing with limited training samples, the proposed method can learn robust features that are beneficial to improve the fault diagnosis ability of induction motors. The comparison of the proposed method with three basic models and two improved methods demonstrates the superiority of the proposed method in accuracy and feature clustering performance under limited sample conditions. In addition, ablation experiments demonstrate the necessity of each module in the proposed method.

The Motion Estimation of Unmanned Aerial Vehicle Axial Velocity Using Blurred Images

This study proposes a novel method for estimating the axial velocity of unmanned aerial vehicles (UAVs) using motion blur images captured in environments where GPS signals are unavailable and lighting conditions are poor, such as underground tunnels and corridors. By correlating the length of motion blur observed in images with the UAV’s axial speed, the method addresses the limitations of traditional techniques in these challenging scenarios. We enhanced the accuracy by synthesizing motion blur images from neighboring frames, which is particularly effective at low speeds where single-frame blur is minimal. Six flight experiments conducted in the corridor of a hydropower station demonstrated the effectiveness of our approach, achieving a mean velocity error of 0.065 m/s compared to ultra-wideband (UWB) measurements and a root-mean-squared error within 0.3 m/s. The results highlight the stability and precision of the proposed velocity estimation algorithm in confined and low-light environments.

Benchmarking Physical Model Experiments with Numerical Simulations for the Wangjiashan Landslide-Induced Surge Waves in the Baihetan Reservoir Area

The Baihetan Hydropower Station reservoir area began impoundment in 2021, triggering the reactivation of ancient landslides and the formation of new ones. This not only caused direct landslide disasters but also significantly increased the likelihood of secondary surge wave disasters. This study takes the Wangjiashan (WJS) landslide in the Baihetan reservoir area as an example and conducts large-scale three-dimensional physical model experiments. Based on the results of the physical model experiments, numerical simulation is used as a comparative verification tool. The results show that the numerical simulation method effectively reproduces the formation and propagation process of the WJS landslide-induced surge waves observed in the physical experiments. At the impoundment water level of 825 m, the surge waves generated by the WJS landslide pose potential threats to the Xiangbiling (XBL) residential area. In this study, the numerical simulation based on computational fluid dynamics confirmed the actual propagation forms of the surge waves, aligning well with the results of the physical experiments at a microscopic scale. However, at a macroscopic scale, there is some discrepancy between the numerical simulation results and the physical experiment outcomes, with a maximum error of 25%, primarily stemming from the three-dimensional numerical source model. This study emphasizes the critical role of physical model experiments in understanding and mitigating surge wave disasters in China. Furthermore, physical experiments remain crucial for accurate disaster prediction and mitigation strategies. The theories and methods used in this study will provide important references for future research related to landslide disasters in reservoir areas.

Parallel Disassembly Sequence Planning Using a Discrete Whale Optimization Algorithm for Equipment Maintenance in Hydropower Station

In a hydropower station, equipment needs maintenance to ensure safe, stable, and efficient operation. And the essence of equipment maintenance is a disassembly sequence planning problem. However, the complexity arises from the vast number of components in a hydropower station, leading to a significant proliferation of potential combinations, which poses considerable challenges when devising optimal solutions for the maintenance process. Consequently, to improve maintenance efficiency and decrease maintenance time, a discrete whale optimization algorithm (DWOA) is proposed in this paper to achieve excellent parallel disassembly sequence planning (PDSP). To begin, composite nodes are added into the constraint relationship graph based on the characteristics of hydropower equipment, and disassembly time is chosen as the optimization objective. Subsequently, the DWOA is proposed to solve the PDSP problem by integrating the precedence preservative crossover mechanism, heuristic mutation mechanism, and repetitive pairwise exchange operator. Meanwhile, the hierarchical combination method is used to swiftly generate the initial population. To verify the viability of the proposed algorithm, a classic genetic algorithm (GA), simplified teaching–learning-based optimization (STLBO), and self-adaptive simplified swarm optimization (SSO) were employed for comparison in three maintenance projects. The experimental results and comparative analysis revealed that the proposed PDSP with DWOA achieved a reduced disassembly time of only 19.96 min in Experiment 3. Additionally, the values for standard deviation, average disassembly time, and the rate of minimum disassembly time were 0.3282, 20.31, and 71%, respectively, demonstrating its superior performance compared to the other algorithms. Furthermore, the method proposed in this paper addresses the inefficiencies in dismantling processes in hydropower stations and enhances visual representation for maintenance training by integrating Unity3D with intelligent algorithms.

Real-time sharing algorithm of earthquake early warning data of hydropower station based on deep learning

Real-time sharing algorithm of earthquake early warning data of hydropower station based on deep learning

Unified Paradigm of Start-Up Strategy for Pumped Storage Hydropower Stations: Variable Universe Fuzzy PID Controller and Integrated Operation Optimization

Unified Paradigm of Start-Up Strategy for Pumped Storage Hydropower Stations: Variable Universe Fuzzy PID Controller and Integrated Operation Optimization

Seismic landslide susceptibility evaluation model based on historical data and its application to areas with similar environmental settings

Seismic landslide susceptibility evaluation models are usually built on the basis of historical sample data; however, the evaluation results are often unsatisfactory when the environmental settings differ between the historical sample data region and application region. Therefore, similarity between the environmental settings is important for the application of such models. In this paper, a seismic landslide susceptibility evaluation model was first built using data from the 2008 Ms 8.0 Wenchuan earthquake-induced landslide, and the model was then used to evaluate the 2022 Ms 6.8 Luding earthquake area. In addition, the grade of susceptibility is typically represented by the landslide density, which is insufficient for capturing the details of landslides, such as their sizes, frequencies, and spatial distribution patterns. The authors therefore use a large and concentrated landslide as the susceptibility grade for the Luding earthquake area. The test results demonstrate that these two areas have similar background environments. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve of the evaluation accuracy for the model applied to the Luding earthquake area is 0.889, which indicates relatively high accuracy. Besides, the results also demonstrate that the evaluations are consistent with the disaster situation of the Moxi Platform, Wandong Village, as well as the Dagangshan Hydropower Station area. Therefore, it is reliable to apply the susceptibility evaluation model based on the Wenchuan earthquake data to the Luding earthquake area. These results show that better evaluations can be obtained based on environmental similarity tests between the areas used for historical data modeling and areas to which the models are applied.

Complex function method considering rock strength for determining critical warning deformation of deep-buried complex cavern

Most existing deformation warning methods for the safety of surrounding rock rely on empirical index or complicated numerical simulation and are unable to accurately and quickly determine the critical warning deformation, so an accurate determination method of critical warning deformation based on rock strength was investigated by the complex function theory in this study. The complex function theory was used to demonstrate that the elastic deformation of surrounding rock at a point is linearly related to its circumferential stress. Based on this demonstration, the critical warning deformations for blue warning, yellow warning, and red alert can be theoretically determined according to the crack initiation stress, dilatancy stress, and uniaxial compressive strength of surrounding rock, respectively. In addition to these critical stresses, the cavern’s shape, the in-situ stress, the deformation properties, and the position of the surrounding rock were also considered in the determination. The accuracy of the proposed theoretical method was verified by a finite element simulation of an example tunnel. Subsequently, the method was applied to the underground powerhouse on the left bank of the Baihetan hydropower station. Compared with the on-site monitoring displacements of the surrounding rock, the resulting warning displacements could accurately indicate the safety status of all monitoring areas around the cavern after each layer of excavation. In addition, the resulting warning positions, warning times, and warning grades matched the on-site failures of the surrounding rock very well. Thus, the proposed method is highly reliable and can be used for real-time warning of underground engineering.

Water Dams: From Ancient to Present Times and into the Future

Since ancient times, dams have been built to store water, control rivers, and irrigate agricultural land to meet human needs. By the end of the 19th century, hydroelectric power stations arose and extended the purposes of dams. Today, dams can be seen as part of the renewable energy supply infrastructure. The word dam comes from French and is defined in dictionaries using words like strange, dike, and obstacle. In other words, a dam is a structure that stores water and directs it to the desired location, with a dam being built in front of river valleys. Dams built on rivers serve various purposes such as the supply of drinking water, agricultural irrigation, flood control, the supply of industrial water, power generation, recreation, the movement control of solids, and fisheries. Dams can also be built in a catchment area to capture and store the rainwater in arid and semi-arid areas. Dams can be built from concrete or natural materials such as earth and rock. There are various types of dams: embankment dams (earth-fill dams, rock-fill dams, and rock-fill dams with concrete faces) and rigid dams (gravity dams, rolled compacted concrete dams, arch dams, and buttress dams). A gravity dam is a straight wall of stone masonry or earthen material that can withstand the full force of the water pressure. In other words, the pressure of the water transfers the vertical compressive forces and horizontal shear forces to the foundations beneath the dam. The strength of a gravity dam ultimately depends on its weight and the strength of its foundations. Most dams built in ancient times were constructed as gravity dams. An arch dam, on the other hand, has a convex curved surface that faces the water. The forces generated by the water pressure are transferred to the sides of the structure by horizontal lines. The horizontal, normal, and shear forces resist the weight at the edges. When viewed in a horizontal section, an arch dam has a curved shape. This type of dam can also resist water pressure due to its particular shape that allows the transfer of the forces generated by the stored water to the rock foundations. This article takes a detailed look at hydraulic engineering in dams over the millennia. Lessons should be learned from the successful and unsuccessful applications and operations of dams. Water resource managers, policymakers, and stakeholders can use these lessons to achieve sustainable development goals in times of climate change and water crisis.