368 results about "Coastal zone" patented technology

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention provides a digital twin model correction method and system based on machine vision. The method comprises the steps that a comprehensive data set is constructed by collecting sounding data, tidal flow velocity data and unmanned aerial vehicle images, wave disturbance deviation and water surface reflection distortion are eliminated based on geometric feature matching, and a dynamic compensation coefficient is generated in combination with tidal parameters; after time deviation of sounding data is corrected, a dynamic incidence relation between terrain elevation and sediment migration rate is calculated, a digital twinborn model fusing sedimentary layer thickness distribution and tidal flow velocity driven erosion boundary prediction is established, and a visual terrain curved surface is generated; through reverse verification of real-time sediment accumulation characteristics and terrain curved surfaces, migration rate weight parameters are adjusted in a self-adaptive mode, and dynamic optimization of the model is achieved. High-precision dynamic coupling simulation of sea area terrain evolution and sediment migration is achieved, the real-time performance and reliability of island surface change prediction are improved, and coastal zone safety and economic collaborative decision making is supported.

The invention discloses a coastal zone carbon sink data acquisition management system and method, and particularly relates to the technical field of carbon sink evaluation, and the method comprises the following steps: dividing carbon flux parameter partitions based on vegetation types, sediment characteristics and historical carbon storage levels, and establishing initial reference values; plant biomass, soil organic carbon content and non-carbon dioxide greenhouse gas flux are regularly collected according to fixed sampling points, and a carbon sink observation data sequence is formed; when data exception triggers an evaluation process, generating a carbon sink credibility index and an ecological interference response index; inputting the two indexes into a prediction model to output an adjustment vector, generating an adjustment strategy in combination with a weight, and dynamically updating an initial carbon flux reference value of each partition; according to the method, regionalized management is realized by constructing carbon flux parameter partitions, a carbon sink observation data sequence is established, an evaluation index is dynamically generated, intelligent updating of a carbon flux reference value is completed in combination with a prediction model, and the precision, responsiveness and adaptive adjustment capability of carbon sink monitoring are improved.

The invention discloses a vegetation-submerged embankment coupled tough coast protection method and system and a storage medium, and the method comprises the steps: firstly, determining a research region, and systematically collecting the near-shore terrain, water and sand power conditions, vegetation parameters and other data; secondly, constructing a water-sand-vegetation coupling numerical simulation model based on the collected data, and performing precision verification on the model; then selecting a suitable vegetation type in combination with environmental characteristics of the research area, carrying out artificial seeding and planting work in a vegetation potential habitat of the tidal flat, and determining a design elevation and an offshore distance of the submerged dike; and finally, evaluating the coast protection effect under the synergistic effect of the submerged embankment and the vegetation, and quantitatively analyzing the improvement degree of the coast protection effect on wave attenuation and beach stability. A sustainable tough coast protection system can be formed under the climate change background through a collaborative protection mechanism integrating natural vegetation and an artificial submerged embankment. The method has the advantages of low cost, remarkable wave reduction effect and the like, and the capability of coping with climate change challenges and comprehensive protection of coastal zones can be effectively improved.

The invention provides a tidal flat evolution prediction method and system based on a hybrid model, and relates to the field of dynamic geomorphology and artificial intelligence cross technology, and the method comprises the steps: constructing a tidal flat erosion and deposition evolution database under different scenes of a target coastal zone; constructing a landform prediction model through an artificial intelligence algorithm based on the database, and taking hydrodynamic characteristic data as input and seabed erosion and deposition variation as output; hybrid simulation is executed based on the physical mechanism model and the landform prediction model, and long-duration evolution prediction is realized by updating terrain boundary conditions through loop iteration; and the configuration service application module is used for receiving user input parameters through the interactive interface and outputting a visual result. According to the method, traditional hydrodynamic force-sediment-landform coupling calculation is decoupled into a physical mechanism and AI coordinated chain process, the calculation complexity is remarkably reduced, offline rapid calculation business of tidal flat evolution is achieved, and real-time technical support is provided for coastal zone planning and disaster prevention decision making.

The invention relates to a coastal zone remote sensing observation-oriented Landsat image prediction synthesis method, which comprises the following steps of: acquiring a real image of an adjacent year of a to-be-predicted synthesis image, preprocessing the real image, and constructing time sequence observation; screening time sequence observation according to seasons and cloud cover; removing abnormal observation values for time sequence observation pixel by pixel; dividing an image water body pixel and a land pixel; respectively fitting available observations of the water body pixels and the land pixels through a functional equation, and respectively constructing surface reflectance time sequence observation curves of the water body pixels and the land pixels; solving an undetermined coefficient of the functional equation; and predicting and synthesizing a Landsat image at the corresponding time according to the fitted time sequence observation curve. The method has the beneficial effects that the Landsat images with high confidence in different time periods in the growth period can be synthesized, so that the requirements of large-range, long-time and high-precision coastal zone monitoring caused by rapid change of land utilization can be met.

The invention discloses a foundation pit gas film foundation and a construction method thereof.The foundation pit gas film foundation comprises H-shaped steel which is sequentially connected end to end, the H-shaped steel is composed of an upper flange plate, a lower flange plate and a web, one end of the web is connected with the upper flange plate, the other end of the web is connected with the lower flange plate making contact with the ground, and the lower flange plate is provided with an open hole and a fixing mechanism; the foundation pit air film foundation further comprises spiral ground piles penetrating through the open holes and extending into the ground. The fixing mechanism is used for limiting the spiral ground pile; a connecting mechanism connected with a gas film material is arranged on the upper flange plate; the spiral ground pile is of a hollow structure, and a buffering mechanism and a reinforcing mechanism are arranged in the spiral ground pile. When the H-shaped steel is subjected to drawing force, the fixing mechanism is driven to trigger the buffering mechanism to counteract the drawing force, and meanwhile the reinforcing mechanism is triggered to increase the underground shearing force of the spiral ground pile. The problems that when an existing foundation pit air film foundation is used in coastal areas, the foundation is unstable and an air film is turned over due to low soil bearing capacity and strong wind cannot be handled are solved.

The invention discloses a coastal region storm surge disaster prediction method based on multiple modes, which combines multi-source meteorological environment data, three-dimensional geographic space data and storm surge historical occurrence data, and comprises the following steps: on one hand, performing long-term prediction and trend fitting on future storm surge conditions by using a multi-mode network; fitting to obtain a linear component and a nonlinear component related to storm surge prediction, combining the linear component and the nonlinear component, and converting the combined component into a storm surge prediction probability P1 through an activation function; on the other hand, for the three-dimensional geographic space data, respectively obtaining a predicted value of supervised learning of a labeled scene and a predicted value of hierarchical supervised learning of an unlabeled scene of the three-dimensional geographic space data; averaging the predicted values of the two, and converting the averaged predicted values into a storm surge prediction probability P2 through an activation function; and finally, weighting the storm surge prediction probability P1 and the storm surge prediction probability P2 to obtain a final storm surge prediction value.

The invention discloses a tidal flat automatic extraction method fused with an irregular hexagonal grid. The method comprises the following steps: step 1, constructing a time sequence remote sensing data set; step 2, establishing a precision verification sample library; step 3, screening spectral indexes; 4, synthesizing an extreme tide level image; 5, generating an irregular hexagonal grid; step 6, carrying out adaptive threshold segmentation; step 7, secondary elimination of confused ground features; step 8, tidal flat range extraction and precision verification; according to the method, based on a time sequence remote sensing image set, pixels at all positions are screened through a specific spectral index maximum value, a new extreme tide level image is formed through combination, spatial heterogeneity of a complex coastal zone is adapted through an irregular hexagonal grid and a bottom-to-top hierarchical merging strategy, local self-adaptive threshold segmentation is achieved in cooperation with a local Otsu algorithm, and a new extreme tide level image is obtained. The optimal grid scale is automatically determined by means of an elbow method, and the confused ground features are secondarily eliminated through the time sequence standard deviation, so that the problem of miscarriage of the confused ground features is effectively solved, and high-precision full-automatic extraction of the tidal flat is realized.

The invention relates to the technical field of coastal zone renovation and repair, in particular to a siltation promotion device for coastal zone renovation and repair, which comprises a siltation promotion assembly and a caisson which are sequentially arranged from top to bottom, the siltation promotion assembly comprises a plurality of siltation promotion modules which are connected through side edges, and the top side of the siltation promotion assembly is used for being fixedly connected with a coast; each siltation promotion module comprises a frame and a plurality of anti-flow plates, the multiple anti-flow plates are sequentially arranged in the frame from top to bottom, the two ends of each anti-flow plate are rotationally connected with the two opposite sides of the frame correspondingly, and every two adjacent siltation promotion modules are rotationally connected through one side edge of the frame; a sedimentation cavity is formed in the top of the caisson, a permeable material is arranged in the sedimentation cavity, flow guide holes penetrating through the two sides are formed in the upstream face and the downstream face of the caisson correspondingly, and the bottom side of the siltation promotion module is connected with the caisson and located above the sedimentation cavity; the siltation promotion device is formed in a splicing mode, the siltation promotion device can be well suitable for complex terrains, and the anti-flow plate is arranged to effectively resist water flow impact.

The invention provides a submarine topography and land elevation matching method based on multi-source data fusion, and belongs to the technical field of geographic information technology and ocean engineering cross fusion. Seamless splicing of sea and land topographies is realized through multi-source data preprocessing, topographic feature correlation extraction, dynamic compensation matching and adaptive weight fusion; according to the method, the problems of data heterogeneity, dynamic environment adaptability and insufficient feature association can be solved, the matching precision can reach + / -3cm, the processing efficiency is also improved, and the method is suitable for coastal zone modeling, ocean engineering and other scenes.

The invention relates to a coastal zone mangrove forest biomass prediction method and device, a storage medium and equipment, and the method comprises the steps: obtaining the image data of a target region and the text description information of the image data, extracting a visual feature vector of the image data based on a pre-trained image feature extraction model, and carrying out the prediction of the biomass of a mangrove forest based on a normalized vegetation coefficient and the image data; the method comprises the following steps: acquiring a visual feature vector, acquiring a spectral feature vector, fusing based on text description information and knowledge graph information to obtain a text feature vector, splicing the visual feature vector, the spectral feature vector and the text feature vector to obtain a fusion feature vector fusing multiple modes of vision, spectrum, text and knowledge graph, and then based on the fusion feature vector, obtaining a fusion feature vector based on the fusion feature vector. And the predicted biomass is obtained by using the trained biomass prediction model, so that the accuracy of predicting the biomass of the mangrove forest in the coastal zone is improved.

The invention discloses a mangrove forest seedling survival rate evaluation method and system based on deep learning. The method comprises the following steps: acquiring a digital orthoimage data set of a mangrove forest restoration target area; a C2fSE module, a DSACmix attention module and a C2fGP module are introduced, and an improved YOLOv8 network model is constructed; based on an improved YOLOv8 network model, performing identification detection on the digital orthoimage data set of the mangrove forest restoration target area to obtain a bounding box and confidence detection data of survived mangrove forest seedlings; and performing redundancy elimination and counting on the spliced detection data of the survived mangrove forest seedlings through a non-maximum suppression algorithm to obtain a mangrove forest seedling survival rate evaluation result. According to the method, the characteristics of the survival mangrove forest seedlings under the complex coastal zone environment background can be extracted from the unmanned aerial vehicle data, and the accuracy and efficiency of survival mangrove forest seedling identification are improved. The mangrove forest seedling survival rate evaluation method and system based on deep learning can be widely applied to the technical field of forest surveying and mapping remote sensing.

The invention relates to the technical field of flame-retardant cables, and particularly discloses a drip-proof flame-retardant cable and a preparation method thereof.The drip-proof flame-retardant cable comprises conductors and further comprises an elastic supporting layer, and the outer surfaces of the five conductors are wrapped with the elastic supporting layer. According to the drip-proof flame-retardant cable and the preparation method thereof, when the cable is bent, the elastic supporting layer can perform elastic pressure relief on the shearing force of wind, so that the bending strength of the cable is reduced, and the situation that the cable is greatly shaken due to the fact that the cable is often influenced by strong wind in coastal areas is avoided; when the cable is partially bent, the filling cavity at the bent part is extruded, so that the oxygen barrier layer is prevented from generating microcracks at the bent part, and the risk that rainwater permeates into the cable and is vaporized and exploded at high temperature when encountering an electric arc is avoided. Therefore, the non-Newtonian fluid in the local filling cavity is locally hardened under the action of the extrusion force, the bending strength of the cable is greatly reduced, and the internal conductor is protected.

The invention discloses a multispectral remote sensing accurate extraction method for an offshore wind turbine point location, and the method comprises the steps: 1, collecting a multi-temporal satellite remote sensing image covering a coastal zone region, carrying out the water body information enhancement and threshold segmentation processing, generating a sea-land binary image, and separating an offshore research region; 2, collecting and dividing a multi-stage remote sensing data set of the offshore wind plant; constructing an offshore wind turbine enhancement index capable of effectively distinguishing the offshore wind turbine and the background ground feature, and generating an offshore wind turbine enhancement image; constructing a visible light superposition index capable of retaining shadow information of the offshore wind turbine, and generating an offshore wind turbine shadow enhanced image; 3, multi-directional gray-level co-occurrence matrixes are calculated for the multi-stage offshore wind turbine enhanced images respectively, and a low-noise wind turbine binary image is obtained through synthesis; and 4, performing mathematical morphology expansion processing and vectorization on the low-noise fan binary image, and performing calculation to obtain accurate position data of the offshore fan.

The invention belongs to the technical field of remote sensing image data processing, and relates to a multi-feature fusion coastal zone culture pond extraction method, which comprises the following steps: obtaining spectral features and polarization features based on an obtained Sentinel-1 image and an obtained Sentinel-2 image; calculating and evaluating an NDWI time sequence based on the NDWI to generate a time sequence synthesis NDWI image; a water body main body is obtained through the hierarchical feature fusion decision tree; obtaining morphological characteristics based on the water body object; obtaining the chlorophyll a concentration and the dynamic characteristic factor of the chlorophyll a concentration based on the Sentinel-2 image; and extracting a culture pond through a random forest classifier, and generating a culture pond spatial distribution diagram. According to the method, the spectral features, the polarization features, the morphological features, the chlorophyll a concentration and the chlorophyll a concentration dynamic feature factors are fused, and the decision tree and the random forest classifier are fused through the hierarchical features, so that the problems of low accuracy and poor stability of existing culture pond extraction are solved.

The invention discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. Comprising the following steps: S1, collecting environment variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time sequence expression of the data through data preprocessing; s2, constructing a quarterly time sequence maximum entropy model, and performing time sequence evaluation on each grid habitat state to form a habitat evolution type; s3, identifying time sequence significant hot spots and hot spot persistence and intensity features, constructing ecological development relationship comprehensive representation, and identifying ecological development conflict types; and S4, spatially superposing the habitat evolution type and the ecological development conflict type to form a self-adaptive access rule, and generating differentiated planning suggestions according to regions. The problem that planning lacks dynamic adaptability due to the fact that coastal zone habitat suitability and development intensity depend on static time point data for a long time and a time sequence evolution rule cannot be recognized is solved.

The invention relates to the technical field of land planning analysis, in particular to a coastal zone land utilization space planning method based on big data analysis, which comprises the following steps: acquiring a multi-time-sequence remote sensing image and environment monitoring data of a planning area, and calculating an ecological safety index of each space unit in the planning area; obtaining economic activity big data and infrastructure data of a planning area, and calculating a land development suitability index of each space unit in the planning area; and establishing a multi-target collaborative game model taking the land utilization demand and the occupancy identifier as constraint conditions, and finally generating and outputting an optimal coastal zone land utilization space planning scheme. According to the method, the real interpretability of the model is improved, rapid adaptation can be conveniently realized through parameter configuration in different regions and different policy tendencies, and the method has high transportability and engineering deployment value.

The invention discloses an element quantitative fusion-based urban coastal zone landscape evaluation and prediction method, which comprises the following steps of delimiting a vector boundary of a target urban coastal zone based on land change data, and dividing an area covered by the vector boundary into a plurality of grid units; associating the preprocessed spatial element data to the corresponding grid units, and constructing a structured spatial database; establishing a multi-element quantitative index system, calculating a combined weight, and outputting a comprehensive evaluation score of each grid unit through weighted summation; calculating global and local Moran's I indexes based on the comprehensive evaluation score, and identifying a spatial aggregation region and an abnormal region with statistical significance; obtaining dynamic monitoring data in a coastal zone range of a target urban area, and updating the structured spatial database; and based on the updated structured spatial database, comprehensively evaluating the score and the recognition results of the spatial accumulation area and the abnormal area, and generating an evaluation and prediction result.

The invention belongs to the technical field of image processing, and discloses a coastal zone ground feature coverage information extraction method and system based on a remote sensing cloud platform. Multi-source remote sensing data are integrated, and a standardized image is generated after preprocessing; an improved U-Net model is constructed, an encoder of the improved U-Net model adopts a residual convolution module to enhance feature extraction, a decoder recovers details through bilinear interpolation up-sampling and jump connection, the segmentation precision of an artificial shoreline and a natural shoreline is optimized in combination with a weighted cross entropy loss function, and the recognition robustness of a complex ground feature coverage area is improved; and superposing the coastline segmentation result and the ground feature classification data space, generating a vector result, and verifying the precision through a comprehensive evaluation system fusing multiple indexes. According to the method, high-precision extraction of coastal zone ground feature information is realized, and technical support is provided for ocean space planning and implementation and coastal zone resource management.

The present invention relates to the technical field of coastal geological data analysis, specifically a coastal geological stability evaluation system, the system includes: a geological data partition identification module collects geological monitoring data, summarizes all geological monitoring data into GIS, extracts features from geological monitoring data, obtains a coastal feature set, divides the coastal feature set into different regions according to location in geographic space, calculates partition purity by conditional information entropy, takes the partition with the highest purity as the judgment standard, gradually refines other partitions with purity lower than the judgment standard, and generates a partition geological structure description set. In the present invention, a refined expression of geological features is achieved through a partition refinement method based on information entropy. The accuracy of geological feature analysis is effectively improved, avoiding possible regional feature confusion problems. In the instability risk classification, the linkage analysis of key features improves the coverage and recognition ability of classification results for various types of geological instability.

The invention provides a turbid water area mud flat shoreline fine extraction method based on a hyperspectral satellite, and relates to the technical field of image processing, and the method comprises the following steps: S1, obtaining a plurality of Landsat series satellite original hyperspectral satellite remote sensing images according to a research target area and research time; s2, obtaining a preprocessed image; s3, performing multi-scale segmentation on the preprocessed image and calculating a normalized differential water body index of image data; and S4, performing threshold classification on the image after multi-scale segmentation in combination with a normalized differential water body index, adjusting and setting a proper normalized differential water body index, distinguishing a water body from a non-water body, and extracting a shoreline. According to the method, the long-time change rule of the coastline can be better researched and analyzed, the change trend of the coastline can be predicted, a basis is provided for development of coastal areas, and the method has a good application prospect in the fields of coastline research, coastline engineering construction and the like.

The invention discloses a device for simulating migration of pollutants under mining and tidal conditions. The device comprises an aquifer loading tank, a pollution tank simulation pollution source and a plastic pipe simulation pumping well are arranged in the tank; the left side and the right side of the aquifer loading groove are divided into a salt water chamber and a fresh water chamber by acrylic plates with seepage holes; the same constant water head device is arranged in the salt-fresh water chamber; and a tide device is arranged on the salt water chamber to simulate the tidal effect of seawater. The positions of the pollution tank and the pumping well are not fixed and can be adjusted; a plurality of salinity concentration monitoring devices are arranged on the rear side of the aquifer loading groove; the inhomogeneous medium of the coastal zone aquifer is simulated by filling the aquifer loading groove with sand samples in a layered manner, so that seawater invasion is simulated. The device can simulate the migration of pollutants in the aquifer under different tide conditions and exploitation conditions, monitor the concentration change of the pollutants and the water pressure change of each part in the horizontal direction in real time, and can simulate the migration situation of the pollutants under the combined action of tide coupling underground water exploitation.

The invention discloses an ocean disaster comprehensive decision-making system based on reinforcement learning, and relates to the technical field of ocean disaster analysis, the ocean disaster comprehensive decision-making system comprises an ocean disaster decision-making platform, the ocean disaster decision-making platform is in communication connection with an ocean environment sensing module, a disaster decision-making analysis module, a disaster risk early warning response module and a feedback optimization module, the modules are in electric signal connection; the marine environment sensing module is used for collecting and integrating marine environment data of a target sea area in real time. According to the method, the historical marine environment data and the real-time marine environment data are learned and analyzed through the reinforcement learning model, the early-stage features and evolution trends of marine disasters can be accurately recognized, the occurrence time, intensity and influence range of the disasters can be accurately predicted in advance, and then high-precision early warning information is quickly generated in combination with historical similar scenes, so that the early warning efficiency is improved. And more time is won for precaution preparation for coastal areas, and disaster loss is effectively reduced.

The invention relates to the technical field of coastline segmentation and extraction, and discloses a coastline segmentation and extraction method and system based on remote sensing data. Acquiring multi-source remote sensing image data of the target coastal zone area; constructing a dual-path U-Net model, wherein the dual-path U-Net model comprises a natural shoreline coding path and an artificial shoreline coding path; fusing the output features of the natural shoreline coding path and the artificial shoreline coding path through a dynamic weight fusion module to generate a fused feature map; and performing sea-land segmentation and morphological optimization based on the fused feature map, and performing segmentation extraction on the coastline. Differentiation features of a natural shoreline and an artificial shoreline are respectively processed by constructing a dual-path U-Net model, and adaptive feature fusion of multi-source remote sensing data is realized in combination with a dynamic weight fusion module. Through end-to-end sea-land segmentation and morphological optimization processes, automatic and efficient extraction from multi-source remote sensing data to a coastline vectorization result is realized.

The invention relates to the technical field of seaweed farm restoration management, in particular to an effect evaluation method for ecological restoration of a seaweed farm. Comprising the following steps: analysis diagnosis and early-stage preparation: diagnosing the degradation degree of a seaweed field, carrying out ecological restoration suitability evaluation on the seaweed field, and carrying out monitoring preparation work before restoration; formulating and implementing a scheme, determining a restoration target, formulating a restoration scheme, and selecting a seaweed field restoration mode and a restoration measure; monitoring a repair project; effect evaluation: comprehensively evaluating the restoration effect from the aspects of engineering index completion degree, seaweed field ecological function and social benefit; and feeding back and adjusting. According to the invention, a whole set of work flow for ecological restoration and effect evaluation of the seaweed farm is provided, and effective technical support can be provided for development of ecological restoration and effect evaluation of the seaweed farm nationwide; the requirement for comprehensively and accurately evaluating the restoration effect can be met, benign interaction between ecological protection and economic development is achieved, and sustainable development of coastal areas is promoted.

A UAV for the geographical surveying of coastal terrain, characterized by: Including quadrotor UAV; Geographic surveying equipment is attached to the underside of the quadrotor UAV; The four sides of the quadrotor UAV are secured with buffer mechanisms; The buffer mechanism includes a lateral support frame, and the lateral support frame is fixed to the side of the quadrotor UAV; the body of the lateral support frame is provided with an inner lateral support plate; The upper end of the inner support plate is provided with an upper support arm, and the lower end of the inner support plate is provided with a lower support arm; The end of the lower support arm and the end of the upper support arm rotate together and are provided with an outer support plate; The upper end of the outer lateral support plate is articulated to the upper spring damper by means of a joint connection; the lower end of the outer lateral support plate is articulated to the outer support arm by means of a joint connection; the end of the outer support arm and the end of the upper spring damper are rotated together and fitted to the outer support plate; the outer support plate and the lower support arm are connected by the middle spring damper; the outer support plate is rigidly fitted to the external spring damper.

The invention relates to a coastal zone sediment erosion pore scale flow field observation system and observation method. The observation system comprises a wave-flow water tank, a sediment accumulation body arranged in the wave-flow water tank and PIV equipment used for observing the internal flow field and the pore size of sediment. A wave making plate and a wave dissipating plate opposite to the wave making plate are arranged in the wave flow water tank, experimental fluid used for simulating waves is arranged between the wave making plate and the wave dissipating plate, and a wave height meter floats on the experimental fluid; the sediment accumulation body is formed by accumulation of transparent solid particles with the same refractive index as the experimental fluid; the PIV equipment comprises a laser light source and a camera, the laser light source is focused on the sediment accumulation body, and the camera directly faces the sediment accumulation body and is used for collecting images. Compared with the prior art, a clearer sediment pore internal flow field image is obtained through the combination of the refractive index matching technology and the image particle velocity measurement method, so that effective observation of the pore scale flow field eroded by the sediment in the coastal zone is realized.

The utility model discloses a recycled aggregate concrete dense rib hollow three-dimensional planting wall which comprises a planting wall body, a plurality of hollow building blocks are arranged on the planting wall body, a plurality of placing through holes are formed in the hollow building blocks, and a plurality of planting boxes are detachably inserted into the placing through holes. As an assembly type building, the whole wall body is processed and completed in a factory, when the wall body is used, the wall body only needs to be hoisted to a corresponding position, meanwhile, corresponding planting boxes can be added, different crops can be planted, the attractiveness of the wall body is improved, meanwhile, the planting area can be increased, and due to the fact that the planting boxes are detachable, the wall body is convenient to use. Different shapes can be designed, meanwhile, when typhoons come in coastal areas, the planting boxes can be detached, the containing through holes of the hollow building blocks become ventilation through holes, and the wind resistance of the hollow building blocks is improved.

The invention discloses an anti-floating buffering flexible pool for a high underground water level. According to the invention, the anti-floating problem of the flexible pool body when the underground water level is relatively high is effectively solved through the interlayer structure. The interlayer material can automatically expand when the underground water level rises to form supporting force to resist the jacking effect of water buoyancy on the pond bottom, so that the pond body is prevented from floating upwards. Therefore, the application limitation of a traditional flexible pool body in areas with the high underground water level is broken through, the application range of the flexible pool body is widened, and the flexible pool body can be applied to more areas, especially occasions with poor foundations, the high underground water level and the high requirement for the water storage capacity. The anti-floating buffering flexible pool can effectively solve the problems in coastal areas, areas with rich underground water resources, urban underground spaces and the like, and a safe and reliable water storage solution is provided for the areas.