4346 results about "Hydrology" patented technology

The invention discloses an urban rainwater pipe network blockage risk early warning method and system based on edge calculation, and relates to the technical field of urban drainage monitoring. The problems that existing pipe network blockage detection lags behind, and the early warning precision is insufficient are solved. Dynamic hydraulic parameters and sediment migration state data of a pipe section are collected in real time through edge calculation equipment deployed at a pipe network node, the hydraulic state deviation rate is calculated, and the local blockage risk is rapidly recognized; when the deviation rate exceeds a threshold value, a dynamic sensing network is established by the trigger nodes, and a pipe network hydraulic topological relation is established by integrating the liquid level and flow velocity characteristics of the upstream and downstream nodes; executing distributed collaborative analysis based on the topological relation, identifying an abnormal attenuation area, calculating a sediment dynamic equilibrium index, and generating a blockage diagnosis parameter; and further combining real-time rainfall intensity to predict an overflowing capacity attenuation curve, generating a multi-stage early warning instruction according to an attenuation slope, and distributing the multi-stage early warning instruction to an operation and maintenance terminal, thereby realizing accurate early warning and active regulation and control of the blockage risk of the rainwater pipe network.

The invention relates to the technical field of reservoir dam safety monitoring, and discloses a reservoir dam siltation dynamic monitoring and early warning system. Multi-dimensional sensing node arrays of the system are arranged at key positions of a dam body structure and a reservoir area, and sediment thickness distribution data, water flow velocity field data and sediment concentration gradient data are synchronously collected. And the edge computing node receives the original monitoring data, executes data cleaning and space-time alignment processing, and generates a standardized siltation feature data set. And the cloud analysis platform receives the data set, calculates a deposition evolution trend matrix through a space-time coupling prediction model, and outputs a reservoir area deposition risk level distribution map. And the dynamic visualization engine analyzes the risk level distribution map, generates a three-dimensional dynamic deposition situation model, and marks the space coordinates of the abnormal deposition area. And the early warning decision center generates a graded early warning instruction set according to the space coordinates of the abnormal region, and triggers a corresponding emergency response strategy.

The invention provides an in-tunnel inrush water pressure monitoring method and system based on dual-acquisition multi-modal data, and belongs to the technical field of inrush water pressure monitoring. Comprising the steps of collecting video data by adopting a high-definition camera; sequentially performing water flow area intelligent segmentation, optical flow calculation and ConvLSTM time sequence prediction on the video data to predict the water flow velocity; an infrared camera is adopted to collect temperature data; self-adaptive temperature gradient calculation and temperature anomaly detection are sequentially carried out on the temperature data to predict the water flow temperature; aligning and fusing the predicted data of the water flow velocity and the water flow temperature, and constructing a water pressure calculation model to obtain a water pressure predicted value; and determining an early warning level according to the water pressure predicted value so as to adjust the monitoring mode of the inrush water pressure in the tunnel. According to the method, the infrared technology and the vision field technology are combined, accurate prediction of the inrush water pressure in the tunnel can be achieved, and a corresponding early warning monitoring mode is provided according to the prediction result.

The utility model discloses an electrolytic bath bipolar plate with micropore flow channels and an electrolytic bath, a micropore flow channel network is arranged on the side surface of an anode of a plate body, and the micropore flow channel network comprises a plurality of groups of micropore flow channel units which are arranged at intervals along the width direction of the plate body; each micropore flow channel unit comprises a main flow channel arranged in the length direction of the plate body and a plurality of first-stage branch flow channels arranged in the length direction of the main flow channel at intervals, a plurality of short branch flow channels are arranged on the two sides of each first-stage branch flow channel at intervals, and a jet hole is formed in the top of each short branch flow channel. The jet flow holes are formed in the direction perpendicular to the side surface of the anode, the length of the short branch runner is smaller than that of the first-stage branch runner, and the short branch runner is perpendicular to the first-stage branch runner. And the microporous flow channel network adopts a structure of combining tree fractal and T-shaped nodes, so that the mass transfer uniformity of water flow in the microporous flow channels can be improved, and the water-membrane contact efficiency is improved, thereby ensuring the hydrogen production efficiency of the bipolar plate.

The invention provides a prediction method for a sudden change type signal of gas dissolved in oil. The prediction method comprises the following steps: firstly, acquiring a time sequence signal of transformer gas monitoring; processing the time sequence signal according to a variational mode decomposition algorithm to obtain a plurality of mode components; according to the variational mode decomposition algorithm, the sum of confusion entropies of all mode components is used as an objective function of parameter optimization; and finally, according to a pre-established prediction model, performing prediction and superposition reconstruction on each modal component to obtain a prediction result of the abrupt change type signal of the gas dissolved in oil. According to the method, the VMD decomposition architecture optimized by the frost ice algorithm is introduced, the non-stationarity of the signal is quantified and obviously reduced through the chaos entropy index, higher prediction precision and robustness of the gas signal in the mutation type oil are realized, and the method has obvious innovativeness and superiority in the field of transformer fault trend prediction.

A system is for cooling at least one computing device using water. The system has a body of water defining a first waterline and a structure at least partially submerged in the body of water. An internal volume of water defines a second waterline. At least one outlet drains water from the internal volume of water to the body of water. A container is at least partially submerged in the internal volume of water and has at least one computing device that generates heat in use. An inlet pipe has a pump to move water from the body of water to the internal volume of water. A flow path of water is provided across the container towards the at least one outlet. The second waterline is at a height above the first waterline to drive the flow path to provide cooling of the container and computing device therein.

The invention relates to a water depth estimation method of a KAN network based on self-adaption and physical constraint, and belongs to the technical field of remote sensing data processing. Grades are divided according to different water body turbidity, different KAN expert networks are adopted for different grades to learn the complex nonlinear relation between B3 and B4 wave band reflectivity and water depth, and KAN initial model parameters corresponding to different grades of water bodies are obtained through independent self-adaptive training; taking the B3 and B4 wave band reflectivity after normalization processing as input, selecting a corresponding KAN network model according to the water turbidity grade, and outputting predicted water depth; and training the KAN network by using the physical constraint loss function L, and finally extracting an interpretable mathematical inversion formula of the wave band reflectivity and the water depth after the training is completed. Through deep fusion of B3 / B4 waveband spectral characteristics of the KAN, a remote sensing technical solution with high precision, low cost and strong adaptation is provided for dynamic monitoring of the water depth of the shallow water area.

The invention relates to the related technical field of climate monitoring, in particular to a freezing circle climate change monitoring method and system suitable for an Asian alpine region, and the method comprises the steps: configuring a monitoring network, receiving a frozen soil multi-source monitoring data set, constructing a frozen soil and climate coupling response model, embedding a region climate assessment engine, and generating a frozen soil degradation risk grade distribution map. And judging whether risk reminding is triggered or not according to the dynamic frozen soil degradation threshold value, and if the risk reminding is triggered, marking an abnormal region in the frozen soil degradation risk level distribution diagram. The technical problems that Asian alpine region freezing circle climate change monitoring abnormity reminding mostly depends on static data, the dynamic evolution process of frozen soil cannot be accurately captured, and the frozen soil degradation risk identification precision is limited are solved, a frozen soil and climate coupling response model constructed based on multi-source data is achieved, and the frozen soil degradation risk identification accuracy is improved in combination with a dynamic degradation threshold value set according to the frozen soil type. And risk reminding is triggered in time and an abnormal region is marked, so that the frozen soil degradation risk identification precision is improved.

The invention discloses a carbon emission factor calculation method adaptive to a gateway meter and a functional module, and belongs to the technical field of power system carbon emission, and the method comprises the following steps: collecting real-time carbon emission power flow data and upstream and downstream position information of a power system by using a carbon emission measurement function of the gateway meter; filling missing data; aiming at a source side carbon emission factor calculation function module, establishing a thermal power generating unit carbon emission model of a thermal power generating unit carbon emission quantification algorithm based on time sequence feature enhancement; calculating grid-side and load-side carbon emission factors; according to different positions of a gateway meter, a carbon emission factor calculation function module with corresponding carbon metering factor calculation and communication functions is designed, calculated carbon emission factors are uploaded to a cloud electric carbon platform, and regional node hour-level carbon emission factors are displayed on a local carbon emission factor calculation function module. According to the method, the accuracy, the real-time performance and the reliability of the regional carbon emission data are remarkably improved by constructing the MS-CBAM-CNN cascade architecture.

The invention discloses an aquifer energy storage dynamic pressure regulation and control system and method based on multi-parameter feedback, and relates to the field of pressure regulation and control. Data normalization is ensured through a standardized parameter type set, and high-quality input is provided for a subsequent model; a pressure mapping model trained based on historical data can accurately predict pressure response under an injection-production strategy, and deviation caused by experience dependence is avoided; through partition clustering and mean value calculation, the aquifer with high heterogeneity is converted into a regulation and control unit with uniform characteristics, and the pertinence of an injection-production strategy is remarkably improved; through dynamic adjustment of a pressure interval, the energy storage efficiency reduction caused by an overpressure risk or underpressure is effectively prevented; an introduced physical intervention mechanism breaks through the limitation of pure data optimization, and the hydrogeological condition is directly improved when model adjustment is invalid; the three purposes of stabilizing the pressure of the aquifer, improving the energy storage efficiency and preventing and controlling geological risks are achieved, and scientific support is provided for long-term sustainable energy storage operation.

The invention relates to a tide level obtaining method and system based on an OWC wave energy conversion device. The method comprises the following steps: constructing an energy loss prediction model in the air chamber; acquiring field incident wave energy, reflected wave energy, water potential energy increment, kinetic energy increment and pneumatic output energy at the current time period; inputting incident wave energy and reflected wave energy into the model to obtain predicted energy loss; and the tide level variation is solved based on the energy conservation relational expression, and the current tide level is calculated. The system comprises an energy loss prediction module, a wave energy acquisition module, a water body energy acquisition module, a pneumatic output acquisition module, an energy loss calculation module, a tide energy solving module and a tide level calculation module, which cooperatively realize the method. According to the scheme, an external tide gauge station is not needed, the local sea area tide level can be inversed in situ, at high frequency and with high precision, the method is suitable for an OWC-breakwater fusion scene, and cooperative operation of a port and ocean energy is supported.

The utility model discloses a high-low pressure conversion structure of a composite elasticizer, which comprises a low-pressure header pipe, a high-pressure header pipe, a low-pressure drainage pipe, a high-pressure drainage pipe, a first air supply pipe and a second air supply pipe, a first filtering bubble bottle is arranged at the air inlet end of the first air supply pipe, and a second filtering bubble bottle is arranged at the air inlet end of the second air supply pipe. A low-pressure airflow adjusting device is arranged at the air outlet end of the low-pressure drainage pipe, and a high-pressure airflow adjusting device is arranged at the air outlet end of the high-pressure drainage pipe. Pressure gas output by the low-pressure drainage pipe and the high-pressure drainage pipe can be conveyed into any one of the first filtering bubble bottles or the second filtering bubble bottles through the low-pressure gas flow adjusting device and the high-pressure gas flow adjusting device respectively. The first air supply pipe and the second air supply pipe can simultaneously and independently supply air through the low-pressure air flow adjusting device and the high-pressure air flow adjusting device. The problem that two surfaces of one composite elasticizer cannot be simultaneously produced when different pressure varieties are processed can be solved, the cost is low, and the practicability is high.

The invention discloses a system and a method for measuring the release flux of methane in a water body, and belongs to the technical field of measurement of the release flux of methane gas in the water body. When the diffusion flux is measured, the box body is placed on the liquid level of the water body in a floating manner, and the partition plate is arranged below the first opening of the box body at the interval of the first preset distance, so that methane gas released in the form of bubbles in the water body below the partition plate can be prevented from entering the accommodating cavity, and the interference of bubble release on the measurement result can be reduced; the determination accuracy of the diffusion flux is improved. When the bubble flux is measured, the cover body covers the sediment at the bottom of the water body below the box body, and the methane gas released by the sediment is collected by the gas collection container below the liquid level, so that the probability that bubbles are dissolved in the water body in the floating process can be reduced, and the measurement accuracy of the bubble flux is improved.

The invention discloses a frozen soil temperature feature recognition algorithm and a moisture and electric field state prediction model, and the method comprises the steps: synchronously collecting temperature, moisture, resistivity and meteorological data through arranging a multi-depth sensor array, and constructing a multi-source data set with time-space alignment; utilizing continuous wavelet transform and cross-modal coherence analysis, and combining a hidden semi-Markov model to extract a depth-periodic characteristic profile; a time domain fusion Transform model embedded with physical constraints is adopted to realize frozen soil multi-parameter physical consistency prediction and uncertainty quantification; and finally, outputting a prediction result through a visual interface and setting an automatic alarm. The problem of cycle identification caused by weak and non-stable deep frozen soil signals is solved, the prediction accuracy and the physical rationality are remarkably improved, an end-to-end solution from data quality control to early warning is formed, and the reliability and the practicability of frozen soil engineering monitoring are greatly enhanced.

The invention discloses a seepage field adaptive analysis method and device based on a flexible polygon unit, and the method comprises the steps: dividing the polygon unit into a plurality of sub-regions, and constructing an internal water head field of each sub-region; recognizing a free water surface according to water head features extracted from the internal water head field of each sub-region; if the free water surface is recognized for the first time at present, or the error of the positions of the free water surfaces recognized by two adjacent rounds of iteration does not meet a preset condition, quadtree decomposition is carried out on the free water surface to obtain new sub-regions; returning to the step of extracting the water head features according to the internal water head field of each sub-region until the error of the positions of the free water surfaces identified by two adjacent rounds of iteration meets a preset condition, and obtaining a grid division result of the polygon unit; and performing seepage field analysis on the polygon units based on a grid division result to obtain a seepage field analysis result. According to the method, the complex seepage field is accurately simulated, and the optimal balance between high-precision discretization near the free water surface and the overall calculation efficiency is realized.

The invention relates to an unbalanced data-oriented electric power system lightning disaster risk detection method, which comprises the following steps of: S1, gridding a target detection land parcel to obtain a plurality of grid units; S2, based on latitude and longitude coordinates of each grid unit, obtaining line parameters and environment characteristics of each grid unit in combination with a line database and a geographic information base, wherein the line parameters comprise tower height, span, grounding resistance, loop number, lightning arrester number and transformer capacity, and the environment characteristics comprise soil conductivity, building height and land utilization type; and S3, inputting the line parameters and the environment characteristics of each grid unit into a trained first detection model to obtain the thunder and lightning probability and the maximum peak current of each grid unit. Compared with the prior art, the multi-source data such as the tower height, the span, the grounding resistance and the soil conductivity are comprehensively considered, and the risk assessment result has higher regional adaptability and accuracy.

The invention relates to the technical field of data processing, and discloses a drainage pipe network rain and sewage mixed connection tracing and spatial positioning method for a micro monitoring station network, which comprises the following steps: defining an upstream convergence pipe network range of each micro monitoring station according to a flow direction connection relationship of a drainage pipe network and layout nodes of the micro monitoring stations, establishing a unique mapping relation library between each pipe section and the corresponding multi-stage monitoring topological sequence; obtaining water quality and water level data of a monitoring station, intercepting an analysis time period, and identifying a target monitoring topological sequence which generates a response currently in the mapping relation library based on a time-space propagation association attribute of data between stations; locking an isomorphic mapping candidate pipe section set corresponding to the sequence, and constructing a pollutant source emission inversion model of each candidate pipe section according to a pipe network fluid transport diffusion mechanism; and calculating the fitting deviation degree of the source hypothesis of each candidate pipe section to the monitoring data by using the model, and selecting the pipe section with the minimum deviation degree as a positioning result.

The invention provides a landslide probability prediction method and system, computer equipment and a storage medium, and belongs to the field of geological disaster early warning, and the method comprises the steps: obtaining the soil cohesion, internal friction angle and permeability coefficient of rock soil in a landslide region to be predicted; random field generation is carried out on the soil body cohesion, the internal friction angle and the permeability coefficient of the rock soil in the landslide area to be predicted, and soil body cohesion random field data, internal friction angle random field data and permeability coefficient random field data are obtained; carrying out discrete processing on the soil mass cohesion random field data, the internal friction angle random field data and the permeability coefficient random field data to obtain random variables of rock soil in the landslide area to be predicted; inputting the random variables of the rock and soil of the landslide area to be predicted into a pre-trained machine learning model, and calculating and outputting a plurality of slope safety coefficients; and determining the failure probability of the rock soil of the to-be-predicted landslide area according to the plurality of slope safety factor sets. According to the method, soil parameter spatial variability is considered, and the landslide probability prediction accuracy is improved.

The invention provides a mud tank liquid level height accurate measurement early warning system and method, the mud tank liquid level height accurate measurement early warning system comprises a measurement support and a control unit comprising a main processor, and the control unit is further connected with a plurality of liquid level detection assemblies, a temperature compensation module, a stirring assembly, an early warning device, a data storage unit and a calibration assembly. The multiple liquid level detection assemblies comprise laser and ultrasonic range finders, the main processor receives detection signals and then corrects the liquid level height in combination with temperature compensation, early warning is started when the liquid level height is abnormal, the detection precision can be calibrated periodically through the calibration assembly, and meanwhile remote data transmission and historical data storage are supported. The method solves the problems that traditional measurement is low in precision, depends on manpower and is delayed in early warning, and is suitable for monitoring the liquid level of the mud tank in various drilling operations.

The invention discloses a marine pipeline leakage point and oil leakage accurate detection system and method, a focused ultrasonic detection module of the system emits ultrasonic focused sound beams to a pipeline wall, a signal acquisition and analysis module is used for receiving an ultrasonic echo signal and performing feature extraction, a fluid noise elimination and compensation module filters and corrects the signal, and a detection module is used for detecting the leakage point and oil leakage of a marine pipeline. The sensor array attached to the pipe wall can monitor the temperature, pressure and environment change of the marine pipeline in real time, the control and feedback unit automatically adjusts the focus depth and acoustic beam energy according to an analysis result, fine scanning and enhanced detection of a target area are achieved, and finally leakage point space coordinates and leakage rate estimated values are output. The system can stably operate for a long time in a high-noise and high-pressure marine environment, is high in detection sensitivity and strong in anti-interference capability, can achieve millimeter-level leakage point positioning precision, and is suitable for online health monitoring and intelligent safety management of marine oil and gas conveying pipelines, offshore wind power cooling systems and deep sea energy channels.

The invention discloses a system and a method for automatically measuring pipe network parameters based on three-dimensional scanning of a wellhead of an inspection well, and belongs to the technical field of municipal engineering measurement. The system comprises a wellhead fixing assembly, a three-dimensional laser scanning assembly, a posture sensing assembly, a distance measuring assembly, a coordinate input assembly, a control processing assembly and a telescopic rod assembly. According to the method, through system deployment leveling, coordinate reference establishment, working condition judgment, point cloud acquisition, data processing and result output, automatic measurement of inspection well depth, pipe network pipe diameter, pipeline trend and pipe orifice center coordinates is realized. The system is fixed at a wellhead, does not need to descend, and adapts to scenes such as shallow wells / deep wells and good / weak signal areas; based on a high-density point cloud and an automatic algorithm, the measurement precision is high, the efficiency is improved, and output data can be directly used for pipe network modeling. The method solves the problems of low efficiency, strong manual dependence and poor safety of traditional measurement, and is suitable for parameter measurement of various inspection wells and pipe networks.

The invention provides a device and method for measuring the flow velocity and flow of gas in a pipeline, and particularly relates to the technical field of measuring instruments, and the device comprises a flow field optimization assembly, a flow velocity sensing assembly and a signal processing assembly. The flow field optimization assembly comprises a plurality of air duct partition plates and straight pipe sections, and the gas conveying pipeline is divided into a plurality of independent divided air ducts; the flow velocity sensing assembly comprises a rectification assembly and a pressure sensing assembly, the rectification assembly comprises a pore plate and / or a grid, and the pressure sensing assembly comprises a plurality of uniformly distributed pressure sensing elements; the signal processing assembly comprises a differential pressure sensing transmitter, a static pressure sensing transmitter, a temperature sensing transmitter, an atmospheric pressure sensing transmitter and a data processing module. The pressure sensing element detects differential pressure signals, the differential pressure sensing transmitter converts the signals, the data processing module calculates the average flow velocity and flow of gas based on the signals and measurement data, and the measurement precision and accuracy are improved.

The invention discloses a salt lake brine mining method and system for hydraulically gradient-driven water replenishing and ore dissolving of a sedimentation funnel, and relates to the technical field of salt lake mineral resource development, the method comprises the following steps: S1, collecting water level data of a sedimentation funnel area, calculating gradient distribution, dividing functional areas, and generating zoning parameters; s2, based on the partition parameters, a water injection well network is arranged in the gradient direction, water injection parameters are determined according to the water level difference, and a well network scheme is generated; s3, based on a well pattern scheme, injecting the proportioning solvent into an ore bed in a layered manner to form a directional seepage field, and generating solute transport data; s4, on the basis of solute transport data, enriched brine is extracted in the collection area, the concentration is monitored, and brine parameters are generated; and S5, based on the deviation between the brine parameter and the target value, calculating the regulation amount, adjusting the injection-production parameter to maintain dynamic balance, and outputting the salt lake brine with the target concentration. By regulating and controlling the hydraulic gradient, the form of the settlement funnel is stabilized, the phenomena of stratum disturbance and ground settlement are reduced, and the ecological risk is reduced.

The invention discloses a device and a method for acquiring a water tank experiment sedimentary profile based on a frozen profile technology, and belongs to the technical field of sedimentology and experimental simulation, and the device and the method are characterized in that stable freezing extraction of the sedimentary profile in a water tank is realized through a wedge-shaped freezing device. The device is internally provided with a liquid nitrogen channel and is provided with an external control interface, and a section freezing state can be kept by injecting liquid nitrogen in batches, so that a complete sedimentary section sample is obtained. Meanwhile, the invention provides a corresponding profile acquisition method, and emphasizes speed control, friction force control, liquid nitrogen injection rhythm and pull-out stability of the insertion device, so as to ensure that an undisturbed frozen profile sample is acquired. According to the method, disturbance to a sedimentary body structure can be remarkably reduced, and the precision and analysis efficiency of profile data are effectively improved, so that reliable technical support is provided for source-sink system and sedimentary geomorphology research.

The invention provides a drought and flood sudden change prediction method and system based on artificial intelligence, and the method comprises the steps: collecting the in-out reservoir runoff observation data of a reservoir in a target region, obtaining a restored natural reservoir runoff series based on a water balance method, calibrating a long-short-term memory model through a minimum batch gradient descent method, and carrying out the prediction of the drought and flood sudden change. Based on the natural reservoir runoff, the actual reservoir runoff and meteorological data, constructing a long-short-term memory model to simulate the influence of water conservancy project regulation and storage on the runoff; based on an earth system mode set and a multivariable deviation correction method, performing spatial downscaling on output data of earth system modes to obtain corrected meteorological variables; driving a multi-member set of an earth system mode, and separating by adopting a detection attribution technology to obtain a contribution rate of man-made climate compulsion to drought and flood sudden turning event evolution; and predicting a daily runoff process under future climate change, and predicting a future drought and flood sudden turning event by adopting deep learning and superposition of regulation and storage influence of a water conservancy project.

The invention provides a water leakage point positioning method and device based on resistance gradient calculation, and the method comprises the steps: obtaining a total resistance value and a tail end resistance value of a water leakage induction rope, and reading a preset resistivity parameter per unit length; calculating the distance of a water leakage point based on the total resistance value, the tail end resistance value and the resistivity parameter per unit length; according to the mapping relation between the length of the induction rope and the physical position established in the installation and debugging stage, the distance of the water leakage point is converted into the physical position described by corresponding 3D coordinates or characters; the physical position information is combined with real-time monitoring data to generate alarm prompt information containing a specific water leakage point location, and the alarm prompt information is output to a monitoring interface, so that accurate positioning of the water leakage point can be realized, the fault response time is remarkably shortened, and through a multi-thread data acquisition and dynamic alarm judgment mechanism, the real-time performance and the alarm accuracy of the system are improved; and the false alarm and repeated alarm frequency is reduced.

The invention discloses a landslide risk early warning method, device and equipment based on multi-source data fusion, relates to the technical field of natural disaster monitoring, and aims to solve the problem of low precision and timeliness of landslide risk early warning. The method comprises the following steps: collecting multi-source monitoring data of a target area in real time and constructing a multi-source parameter set, wherein the multi-source parameter set comprises rainfall characteristic data, soil hydrogeological parameters and slope morphological parameters; performing space-time discretization moisture migration simulation based on the multi-source parameter set, and generating space-time distribution data reflecting the dynamic change of the slope moisture field; calculating a slope stability index sequence according to the spatial and temporal distribution data to construct a prediction model reflecting a risk evolution trend; and setting a dynamic grading early warning threshold based on a prediction model output result, and triggering multi-grade early warning information when the risk grade reaches a preset condition.

The invention relates to the technical field of environmental science, and discloses a water and soil conservation carbon sink measuring and calculating method and system based on artificial intelligence, and the method comprises the steps: obtaining soil parameters, climate parameters, terrain parameters and environmental parameters, carrying out the adaptive uncertainty quantification processing, and constructing a standardized data set; on the basis of the standardized data set, combined with a biomass-carbon sink dynamic constraint model, forest and grass carbon sink data are generated; engineering carbon sink data are generated through the microtopography-carbon sink dynamic correction model; further generating cultivation carbon sink data through a carbon turnover-cultivation interaction stability feedback model; performing nonlinear collaborative causal reasoning on the forest and grass carbon sink data, the engineering carbon sink data and the cultivation carbon sink data, and fusing to generate total carbon sink data; and finally, performing error correction prediction on the total carbon sink data, and outputting a carbon sink prediction result. According to the method, accurate quantification of water and soil conservation carbon sequestration with multi-measure cooperation and multi-path interweaving is realized, and the measurement and calculation precision and reliability are effectively improved.

A system, device and method to pick and / or place specimen containers may include a pick and / or place head, a first secondary reservoir, and optionally a second secondary reservoir which hold cryogenic fluid in a liquid form, above a main reservoir of cryogenic liquid, to cool the pick and / or place head and / or to cool or recharge the specimen containers during transfer operations. Storage locations may be arrayed in wedge-shaped sets spaced above cryogenic liquid of the main reservoir of a cryogenic storage tank at one or more levels, and pivotal about a central axis via a motor and control system. A gap (e.g., wedge shaped gap) between two successively angularly adjacent sets of storage locations of the sets of storage locations at an upper level provides access to the storage locations of the sets of storage locations at a lower level. Cryogenic liquid temperatures and levels in reservoirs are monitored.

The invention discloses a method and a device for determining a maximum submerging range and a nonvolatile storage medium, and relates to the field of remote sensing data processing. The method comprises the following steps: determining first distribution information of normalized difference water body indexes of a target area in a first time period; second distribution information of the normalized difference water body index of the target area in a second time period is determined, and the second time period is a time period after the flood event occurs in the target area; comparing the second distribution information with the first distribution information to obtain difference distribution information of the normalized difference water body index of the target area in the second time period; and determining the maximum submerging range in the target area according to the difference value distribution information. The technical problem that the maximum flood inundation range cannot be accurately determined when the flood inundation range is determined directly based on remote sensing data in related technologies is solved.