8 results about "Dam failure" patented technology

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

The invention discloses a reservoir dam break early warning method, which comprises the following steps: acquiring a current data set after the farthest time from a source database according to a first temporary table, updating a second temporary intermediate table according to the current data set, and generating an updating instruction of a target database; the target database updates the target table according to the updating instruction to obtain a to-be-input data set; training the input data by using the LSTM basic model to obtain an LSTM-based target model; preprocessing the to-be-input data set to obtain input features; inputting the input features into the target model, and outputting a dam break risk value; determining a target weight according to the dam break risk value, and calculating a current dynamic threshold value; and determining a dam break risk level according to the current dynamic threshold value or the dam break risk value. According to the method, the source database can be efficiently synchronized to the target database in a low-delay manner, and the accuracy and reliability of risk prediction are remarkably improved. The invention further discloses a system for implementing the method, electronic equipment and a computer readable storage medium.

This invention discloses a method and storage medium for predicting peak discharge of earth-rock dam failures, belonging to the technical field of hydraulic engineering technology. Based on the continuous organization and expansion of historical databases, a comprehensive database containing information on 295 earth-rock dam failure cases has been formed. Correlation analysis was conducted on different dam failure parameters and peak discharge, extracting five influencing parameters: reservoir capacity above the breach bottom, dam height, reservoir capacity, final breach depth, and water depth above the breach bottom at the time of failure. A new earth-rock dam failure parameter prediction model considering different dam types and failure modes was constructed. The model was compared with 20 existing typical parameter models from domestic and international sources. The calculation results show that the root mean square error (Erms) and correlation coefficient (R²) of the proposed prediction model are 0.38 and 0.82, respectively, demonstrating certain advantages compared to other models and verifying the accuracy of the model.

This invention relates to the field of dam failure simulation technology, and discloses a device and method for simulating and monitoring the failure process of a landslide dam. By setting surface markers on the surface of the landslide dam model and combining a camera monitoring system with digital image correlation, this invention achieves non-contact, full-field continuous monitoring of dam surface deformation. It can accurately acquire displacement and strain field data of the dam surface, overcoming the shortcomings of existing technologies that cannot accurately acquire dam deformation characteristics. Simultaneously, by setting up an acoustic emission monitoring system, it collects and locates stress wave signals emitted by the landslide dam model due to internal damage during the stress process, achieving real-time monitoring and spatial positioning of internal damage information of the dam body. This solves the problems of existing technologies being unable to monitor the internal structural response of the dam body and unable to analyze the dynamic process of internal damage evolution.

This invention discloses a multi-source data-driven method for verifying the path analysis of hydropower dam failures, belonging to the field of hydropower dam failure path analysis. The method includes entity extraction and relation extraction based on geological, meteorological, biological, and engineering datasets to construct a hydropower dam failure knowledge graph; supplementing and correcting erroneous and missing relations in the knowledge graph using path ranking and tensor decomposition algorithms; verifying the entity relations in the corrected knowledge graph to obtain a verified hydropower dam failure knowledge graph; and determining all paths from each hazard-causing factor to the dam failure node using a breadth-first search algorithm based on the verified knowledge graph, and visualizing each path to complete the path analysis of the hydropower dam failure event node. This invention solves the problem of low reliability of assessment results due to excessive reliance on human experience in existing methods.

This invention presents a method for generating dynamic reservoir scheduling benchmarks that integrates dual-drive prediction and flood control constraints. It relates to the fields of smart water conservancy, water resource optimization scheduling, and artificial intelligence. The method includes: collecting hydrological and meteorological data; employing a dual-drive hybrid prediction algorithm that combines a physical dynamics numerical model with a spatiotemporal AI large-scale model to dynamically extrapolate the inflow process curve of the reservoir for future periods; prioritizing flood control safety as the highest decision-making constraint, and combining the hybrid predicted inflow input with the reservoir capacity adjustment model for pre-adjustment calculations to generate a safe water release strategy and new reservoir capacity status; and forcibly removing rigid demand water volumes that cannot participate in allocation based on the expected safe and available reservoir capacity, generating a dynamic scheduling benchmark water volume for multi-user water resource hybrid game calculations. This invention improves system robustness and prediction accuracy; by closely integrating flood control safety with economic water resource allocation, it solves the problem of the disconnect between economic water resource allocation and flood control safety, thus avoiding the risk of dam failure.

This application relates to a risk grading standard construction and risk assessment method based on statistical distribution characteristics. It is applicable to the field of reservoir dam risk assessment technology. The scheme includes: based on the design specifications for the failure probability of hydraulic structures, equating the dam failure probability with the failure probability of the structural system, and determining the anchor point for the boundary between dam safety and unsafety probabilities; obtaining a series of risk consequence data for sample dams, and based on their statistical distribution characteristics, using a data-driven method to determine the grading boundaries of consequence severity; combining the dam failure probability level standard with the consequence severity level standard to construct a two-dimensional risk matrix, which defines the final risk level corresponding to different combinations of dam failure probability and consequences, forming a first risk assessment standard; and based on national historical dam failure statistics, determining the key parameter C values ​​of the target line and tolerance line in the F-N curves for life risk and economic risk respectively, and defining the risk graphically, forming a second risk assessment standard.

This application discloses a simulation method for tailings dam instability and failure under continuous rainstorm conditions. The method includes simulating the tailings dam area and downstream topography, simulating the later-stage dam body, designing continuous rainstorm simulation parameters, applying rainfall and inducing instability, dynamic monitoring throughout the process, and analyzing the dam failure mechanism. This application solves the technical problems of low fitting accuracy, inflexible parameter control, and incomplete data acquisition in existing tailings dam failure simulation methods. It can provide reliable experimental simulation support for the safety assessment, risk prevention, and related research of tailings dam instability and failure under continuous rainstorm conditions.