278results about How to "Improve modeling efficiency" patented technology

The invention provides a three-dimensional geological modeling parameter optimization method and system based on deep learning, and relates to the field of geological prospecting and modeling.The method comprises the steps that drilling data and remote sensing data of a geological prospecting area are obtained, and multi-source geological data of three-dimensional geological modeling are formed; generating geological profile map data of the geological features according to the drilling data, generating landform profile map data corresponding to the topographic features according to the remote sensing data, and extracting boundary information of the geological exploration area; carrying out gridding processing on a three-dimensional space, dividing a geologic body of the geological exploration area into a plurality of small grid units, and defining geological modeling parameters; the preliminary three-dimensional geological grid model is constructed according to the geological profile map data, the landform contour map data and the boundary information, the size and the resolution of the grid are dynamically adjusted according to the geological change area, the three-dimensional geological model is obtained through optimization and adjustment, the modeling precision is improved, manual intervention is reduced, and computing resources are saved.

The invention discloses a data communication method and system based on information security, and belongs to the technical field of data communication, and the data communication method comprises the stages of preparation, transmission, intrusion detection and defense, receiving verification and cleaning ending. The two parties authenticate and exchange keys during preparation; encrypting data by using a symmetric key and an AES algorithm; automatic defense is performed after intrusion detection; the receiver verifies the data; and cleaning the resources at the end, and performing log optimization on the system. According to the invention, through innovatively improving the intrusion detection and defense method, based on real-time network flow monitoring, intrusion analysis based on machine learning and an automatic defense mechanism, the detection accuracy and efficiency are greatly improved, and false alarms and missing alarms are reduced; defense capability and flexibility are enhanced, attacks are intelligently blocked and isolated, and cooperative emergency response is rapid; data communication security technology progress and expansion are promoted, and network security is powerfully guaranteed.

The invention provides a satellite-borne multi-band synthetic aperture radar signal processing optimization method and system, and relates to the technical field of signal processing, and the method comprises the steps: obtaining original echo data of a satellite-borne multi-band synthetic aperture radar, carrying out Doppler center frequency estimation, carrying out two-dimensional matrix product operation, and obtaining compensation echo data; distance direction position information and scattering intensity information are obtained based on a distance direction matching filtering algorithm of sub-band decomposition; determining spatial distribution density, performing adaptive block processing, and performing phase error modeling in each block to generate a continuous phase correction function; performing wavelet domain convolution operation to obtain corrected echo data, obtaining a multi-band two-dimensional image, extracting a multi-dimensional feature vector through a deep neural network, performing weight learning, performing nonlinear weighted fusion, and performing adaptive histogram equalization enhancement to determine a synthetic aperture radar imaging result.

The invention discloses a geographic scene parameterization three-dimensional modeling method and system driven by a large language model, a storage medium and a program product, belongs to the field of geographic information science, and solves the problems that a geographic 3D scene reconstruction method is time-consuming in the data acquisition and processing process, generated models and scenes lack semantic information and the like. The method comprises the following steps: constructing a progressive three-dimensional scene modeling knowledge graph of a geographic scene; a reasoning context screening mechanism based on spatial autocorrelation and information entropy is constructed based on the geographic entity space and the progressive three-dimensional scene modeling knowledge graph, and a prompt text used for LLMs reasoning is obtained; constructing an implicit association reasoning rule between entities guided by a thinking chain based on a prompt text of LLMs reasoning, and updating a progressive three-dimensional scene modeling knowledge graph; and performing parameterized geographic scene three-dimensional modeling based on a three-dimensional model generation method of a primitive model and modeling object semantics and the updated progressive three-dimensional scene modeling knowledge graph. The method is used for parameterized geographic scene three-dimensional modeling.

The invention relates to a point cloud semantic segmentation method and model based on density perception and feature enhancement, and the method comprises the steps: firstly, carrying out the dynamic density perception sampling in an input point cloud, and carrying out the grouping according to the semantic feature distance; then, after multi-level extraction of deep semantic information, enhancement of relative position information is carried out, and local features of different areas are enhanced; and finally, guiding to recover sampling points according to semantic homogeneity in the up-sampling of the decoder, and fusing the point-level semantic features and the channel-level semantic features by using a bidirectional self-attention mechanism. The model comprises a point cloud input module, a down-sampling module, a cross attention module, a position feature enhancement module, an up-sampling module, a point cloud output module and a trigger threshold judgment module. The method is tested on public data sets S3DIS and Scannet, mIoU reaches 73.0% and 74.8% respectively and is increased by 2.6% and 4.2% respectively relative to a baseline model, and the effectiveness of the method is proved.

The invention provides a method, a device and a product for predicting the state of health of a battery based on a language model, and the method comprises the steps: obtaining the time-varying data of the electrical parameters of a target battery at an application side, carrying out the processing, and obtaining the input data according with the input characteristics of the language model, thereby achieving the prediction of the state of health of the battery. The battery health state corresponding to the target battery is obtained through the output characteristics of the target language model, and the pre-trained model backbone in the basic language model is frozen and the adjustable component is trained at the training side by taking the physical principle of the battery as a physical constraint condition, so that the target language model is obtained. By utilizing the generalization ability of the pre-trained model backbone and the generalization ability brought by the interpretability of the physical constraint, the demand for training data in the model training process is reduced, the modeling process is optimized, and the modeling efficiency is improved, so that the effectiveness of the battery health state prediction is improved.

The invention discloses a user-defined multi-dimensional analysis configuration method, system and equipment based on a constellation model and a medium, belongs to the technical field of data analysis, and aims to solve the technical problem that basic data such as dimensions, indexes and data models in multi-dimensional analysis are complicated to construct. According to the technical scheme, according to the method, the dimensionality, the index and the incidence relation between the fact table and the dimensionality table configured by the model table are imported, the mapping between the dimensionality tables is automatically imported into the correlation table, the attribute and the model relation, the model maintenance cost is reduced, and the model maintenance time is shortened; ordered model construction is realized through dimensions, indexes, fact tables, dimension tables, data models and self-defined multi-dimensional query, multi-fact-table dimensions screen application configuration scenes of reverse mapping of property of the fact tables, required indexes are flexibly selected from the fact tables through dragging operation, and according to a cascade mode of the indexes and the dimensions, the application configuration scenes of reverse mapping of property of the property of the fact tables are selected to be matched with the property of the property of the property of the property of the property of the property of the property of the property of the property of the property of the property of the property. And automatically screening out the generality dimension for display.

The invention provides a three-dimensional geologic model construction method based on potential field interpolation and deep learning coupling. The method comprises the following steps: S1, constructing a sample data set and carrying out normalization processing; s2, according to the characteristics of the sample data, determining a stratum contact relation in a region by using a variation coefficient between upper and lower stratums; s3, designing a loss function based on a scalar field construction rule and an adaptive stratigraphic sequence; s4, designing a three-dimensional geological prediction model based on the convolutional residual implicit hierarchical network architecture, wherein the three-dimensional geological prediction model comprises a concise full-connection module, a complex convolutional residual module and a hierarchical integration module; s5, fitting a pre-training plane according to sample data features, and capturing stratum features in the region to obtain a similar ideal stratum plane; and S6, predicting a three-dimensional geologic model, loading the pre-trained network parameters to each layer of convolutional residual implicit network for training, enabling the model to converge and output a predicted scalar field value, and then performing contour surface extraction to obtain the three-dimensional geologic model.

The embodiment of the invention provides a business modeling guiding method and system, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining object label information of a target object and model demand information input by the object in response to a modeling guide instruction of the object on a visual interface, and then performing model recommendation processing according to the object label information and the model demand information to obtain a recommended model list; the model recommendation processing comprises model recommendation based on similar users and model recommendation based on object demands, displaying a recommendation model list which comprises a plurality of recommendation models meeting user preferences and demands, determining a target model in response to a model selection instruction for the recommendation model list, and recommending the target model to the user. And determining a business model according to the target model and the target parameters thereof. According to the invention, personalized business modeling guidance can be provided for the user, and the business modeling efficiency of the user is improved.

According to the BIM-based parameterized spatial steel truss structure modeling method, electronic drawing spatial steel truss data are extracted through simple operation, an Excel table is processed and generated, spatial steel truss node three-dimensional coordinate data are extracted, precision errors caused by human factors are eliminated, meanwhile, a Revit template file is created, and a BIM-based parameterized spatial steel truss structure modeling method is provided. According to the method, a self-adaptive rod piece and bolt-sphere joint parameterization family is established, the modeling efficiency of the space steel truss in Revit is effectively improved, at least 90% of modeling time is saved, a running program written by Dynamo is applied, table data and parameterization family data are automatically called, accurate space steel truss and bolt-sphere joints are automatically generated, and the modeling efficiency and the model quality are greatly improved.

The embodiment of the invention relates to a processing method and device for carrying out structure optimization on electrolyte formula components. The method comprises the following steps: constructing a structure optimization model; constructing a first data set and a second data set; performing pre-training based on the first data set, and performing tuning based on the second data set; after the optimization is finished, taking an electrolyte formula input by a user as a current electrolyte formula, performing corresponding three-dimensional molecular structure modeling according to each component molecular sequence of the current electrolyte formula, and performing three-dimensional structure optimization on each component modeling structure based on a structure optimization model; forming a corresponding formula component structure optimization record by each component molecular sequence, the corresponding component type and the component optimization structure; and forming a corresponding formula structure optimization report by all the obtained formula component structure optimization records, and feeding back the report to a user. According to the method, the influence of human factors on the molecular structure modeling quality can be reduced, and the modeling quality and the modeling efficiency are improved.

The invention provides a rapid three-dimensional modeling method based on seabed point cloud data, a medium and a system, and belongs to the technical field of seabed depth measurement, and the method comprises the steps: firstly, obtaining low-resolution point cloud data through spatial downsampling, and carrying out the multivariate mixed decomposition of the low-resolution point cloud data, and obtaining a stable component and a variable component; constructing an initial three-dimensional grid model based on the stable component, and then dividing the initial three-dimensional grid model into a plurality of sub-regions by adopting a self-adaptive partitioning strategy; and performing partition processing on the original point cloud data according to sub-regions to obtain a plurality of high-resolution point cloud data blocks. And next, performing anomaly identification and noise reduction processing on each high-resolution point cloud data block, reconstructing a corrected high-resolution point cloud data block, performing grid reconstruction and boundary registration, and constructing a complete high-resolution seabed scene three-dimensional model. And the final high-quality seabed scene three-dimensional model is obtained through processing, so that the technical problem that the existing three-dimensional seabed model cannot fully reflect the detail characteristics of the submarine topography is solved.

The invention provides a modeling method and device for a pouring assembly, a storage medium and electronic equipment. The method comprises the steps that parameter information of the pouring assembly to be modeled is obtained; the parameter information comprises general parameters, module parameters of each module of the pouring assembly and dependency parameters among the modules; according to the module parameters of each module and the general parameters, constructing a model of each module; and the models of the modules are combined according to the dependency parameters between the modules, and the component model of the pouring component is obtained. By applying the method provided by the embodiment of the invention, the modeling efficiency of the pouring assembly can be improved.

The invention provides a digital twin modeling method, device and equipment and a storage medium, and relates to the technical field of digital twin modeling, and the method comprises the steps: obtaining initial point cloud data; obtaining preprocessed point cloud data; obtaining first point cloud feature information according to the preprocessed point cloud data; carrying out object classification and segmentation processing to obtain second point cloud feature information; generating an interactive twin model; and acquiring real-time state information, and updating the interactive twinborn model according to the real-time state information. Convolutional feature extraction processing based on point cloud data is realized by generating the point cloud image, global and local features of the point cloud can be efficiently extracted, the modeling efficiency and precision are improved, the high modeling precision is beneficial to guaranteeing the precision of an interactive twinborn model to accurately reflect an actual scene, and the method is suitable for large-scale popularization and application. And meanwhile, the high modeling efficiency is beneficial to realizing synchronous change of the interactive twinborn model and an actual scene, the monitoring and interaction real-time performance of digital twinborn is improved, and the monitoring and management requirements of a machine room can be met.

The invention belongs to the technical field of civil airport digitization, and discloses a 3D airport model construction method and system based on a GIS system. The method comprises the steps that in the two-dimensional vector GIS data processing process, the three-dimensional modeling process, the abnormal data processing process and the process link execution process, the captured current execution context abnormal information is subjected to generation of an abnormal unique ID, packaging into a message notification object and sending to a monitor, the monitor temporarily stores abnormal data, and after the whole process link is executed, the abnormal data is uniformly displayed to a user for viewing. The method does not depend on heavy BIM commercial software, and the whole scheme is free and light. Based on the above characteristics, a GIS data 3D modeling method depending on BIM software as transition is abandoned, a lightweight GIS data 3D modeling method is adopted, the use cost is reduced, and the modeling efficiency is improved.

The present invention discloses a simulation modeling method based on graphic matching recognition, comprising: obtaining configuration information of drawings in a source file of a first format, the configuration information including line segment information and text information; generating a redrawn picture and a mapping table according to the obtained configuration information, wherein the redrawn picture includes a library composed of line segments and connecting line segments between the libraries, and the mapping table includes a mapping relationship between text content and line segments and their position coordinates; identifying the library category, the attributes of the connecting line segments, and the parameter attributes in the mapping table in the redrawn picture according to a preset feature information library; converting the identified library category, the attributes of the connecting line segments, and the parameter attributes into a simulation model file; importing the simulation model file into a simulation modeling software to generate an executable simulation model. Correspondingly, a simulation modeling device based on graphic matching recognition is also provided. The simulation modeling method can improve modeling efficiency and modeling accuracy.

The invention relates to a mechanical property prediction method for a woven composite material structure, and the method comprises the steps: obtaining a microscopic CT image of the woven composite material structure; carrying out image preprocessing on the CT image; segmenting a fiber bundle in the preprocessed image to obtain a segmented fiber bundle image; extracting a fiber bundle trend center line from the segmented fiber bundle image; establishing a macroscopic geometric model of the woven composite material structure, and performing unit grid division on the geometric model; establishing a relation between a fiber bundle trend center line and a geometric model unit; calculating mechanical property parameters of each unit one by one; and calculating the macromechanical response of the composite material structure. According to the method for predicting the mechanical property of the woven composite material structure, the grid division independent of the microstructure characteristics is adopted, so that the modeling efficiency can be improved, the modeling difficulty can be reduced, and the method is easy to implement.

The invention provides an SVG controller modeling analysis method based on field experiment data, and relates to the technical field of electric power grids. According to the method, the high-low penetration fault test is carried out on the SVG, the field experiment data is obtained, the calculation data of the transient model of the SVG under different model parameters are combined, the least square method is adopted to carry out parameter identification, and the optimal model parameters of the transient model of the SVG controller are obtained. The process avoids modeling of complex topology in the SVG and laboratory communication protocol debugging, is suitable for testing of SVGs of various models, and is high in field test result accuracy, simple in wiring and extremely low in risk. A field test result can truly reflect transient response characteristics of station-level current and reactive power, and a modeling path based on the field test is opened. The SVG control characteristic extraction efficiency is improved, the model precision and modeling efficiency of the complex topology SVG are improved, and therefore the analysis efficiency of the SVG analysis process is improved.

The invention discloses a scattering center modeling method under continuous distance variation, which comprises the following steps of: performing far-field frequency sweeping, azimuth sweeping and pitching sweeping three-dimensional radar scattering cross section simulation on a target by adopting simulation software to obtain far-field three-dimensional scattering data, and performing near-field to far-field scanning distance radar scattering cross section simulation on the target to obtain continuous distance scattering data; according to the far-field three-dimensional scattering data, scattering images of a target in three dimensional directions are obtained; performing amplitude parameter estimation to obtain a target three-dimensional scattering center model; the distance and the attitude angle from the antenna to each scattering center are obtained, a plurality of scattering fields of each scattering center are reconstructed, and a total scattering field is obtained after vector superposition. According to the method, the amplitude of the scattering center is corrected through the position and angle geometrical relationship between the scattering center and the near-field antenna, scattering data at any distance can be reconstructed through far-field data, and the modeling efficiency is greatly improved while the modeling precision is ensured.

The invention relates to the field of electric digital data processing, in particular to an automatic modeling method for airport pavement partitioning based on a BIM technology. The invention discloses an automatic modeling method for airport pavement blocks based on a BIM (Building Information Modeling) technology. The automatic modeling method is characterized by comprising the following steps of: 1, processing a block elevation map; 2, decomposing the drawing; 3, creating a self-adaptive family; step 4, picking up; step 5, converting into lines; 6, obtaining a longitudinal starting point; 7, obtaining an ordered transverse line; 8, obtaining a desired point group; step 9, screening and recombination; step 10, obtaining coordinates; eleventhly, coordinates are obtained; step 12, orderly combining; and 13, through nodes, the modeling speed is high.

The embodiment of the invention provides a modeling method and device for an airborne system function architecture model, computer equipment and a medium, and relates to the technical field of aviation architecture design, the method comprises the following steps: inputting a design requirement document into an airborne large language model, and in the large language model, under the structural constraint of an airborne system knowledge graph, establishing a design requirement document; the method comprises the following steps: extracting a logical relationship between entities required by airborne system modeling from a design demand document, screening a corresponding airborne meta-model according to the extracted logical relationship between the entities, and constructing a demand graph; constructing and outputting a text model of a concept scene, a text model of a task scene, a text model of a system function, a text model of a logic architecture and a text model of a physical architecture of the airborne system based on the demand graph; and inputting each text model into a system modeling language modeling terminal for visualization to obtain a multi-level functional architecture model of the airborne system. According to the scheme, the modeling efficiency, consistency and normalization are improved.

The invention relates to the technical field of modeling, in particular to an interactive nuclear system automatic modeling system and method. The system comprises a text input module used for acquiring text information describing a to-be-modeled nuclear system; the natural language processing module is used for carrying out semantic analysis on the text information to generate model data, and the model data are data describing components forming the to-be-modeled nuclear system, relationships among the components and design parameters of the components; the model generation module is used for generating a three-dimensional model of the nuclear system to be modeled according to the model data; and the model optimization editing module is used for acquiring modification information sent by a user and adjusting the three-dimensional model of the to-be-modeled nuclear system based on the modification information. According to the method, the modeling process is simplified, automatic modeling of the nuclear system is realized, and the modeling efficiency and accuracy are greatly improved.

The invention belongs to the field of live-action three-dimensional modeling, and discloses a live-action three-dimensional modeling method and device based on cloud native task batch processing scheduling, and the method comprises the steps: calculating aerial triangulation encryption data of a three-dimensional modeling task, and carrying out the block processing of the aerial triangulation encryption data through a task segmentation module; the task scheduling module adjusts operation and task issuing of sub-tasks in real time according to available computing resources of the cloud architecture system, and optimizes the utilization rate of distributed computing resources in real time; the task state monitoring module monitors the execution state of the sub-task in real time; the subtask processing module performs corresponding generation on the image data in each block, and uploads a generation result to a storage resource pool after operation is completed; and after all the subtasks are operated, calling a model merging module to perform overall merging. According to the method, the live-action three-dimensional modeling task and the cloud native task batch processing architecture are combined, operator-level scheduling of the live-action three-dimensional modeling function is achieved through the cloud native system architecture and the resource container pool, and cloud native system resources are efficiently utilized.

The invention discloses a hotel room three-dimensional visualization method, system and device, a medium and a program product. The method comprises the following steps: receiving a basic model and scanning parameter data uploaded by a mobile terminal; the basic model is generated by scanning a hotel room based on RoomPlan through a mobile terminal with LiDAR; the scanning parameter data comprises key parameters, and the key parameters comprise the size of a room and the size, position, direction and classification of furniture in the room; key parameters are extracted; searching a matched standardized model in a model library; placing the matched standardized model at the original position in the basic model according to the original size and direction for replacement; and sending the replaced basic model to the mobile terminal. According to the method, the manufacturing cost of the room model can be remarkably reduced, professional equipment is not needed, the modeling efficiency of the room model can be remarkably improved, rapid collection is achieved, timely updating of room space layout information is achieved, large-scale application and popularization are supported, the user experience can be improved, and a user can visually understand the actual layout of the room.

The invention discloses an initial steady-state compiling method and an initial steady-state compiling system for a Modelica model. The initial steady-state compiling method for the Modelica model comprises the following steps: putting an initial value equation / initial constraint condition and a fixed initial value constraint condition in the Modelica model into an initial value equation system set; when a user starts an initial steady-state mode, removing a corresponding redundant initial constraint condition from the initial value equation system set according to an initial steady-state option, and supplementing the initial steady-state constraint condition; putting the initial steady-state constraint condition and the compiled model state equation into an initial value equation system set; and packaging the initial value equation system set into an initialization function, and calling the initialization function to realize initial steady-state solution of the Modelica model. According to the method, by removing the redundant initial constraint conditions and automatically adding the initial steady-state constraint conditions, the initial state of the model is constructed into the steady-state value, and the modeling efficiency of the complex system model is improved.

The invention relates to the technical field of tire simulation design, in particular to a tire force transmissibility finite element simulation method and system and a program product. According to the method, an axial symmetry finite element model comprising a tire, a rim, internal air and an additional deformable object is established, material attributes and contact pairs are defined, and a three-dimensional tire model is generated in combination with inflation simulation. An air unit with a displacement freedom degree and a self-adaptive grid division technology are adopted. The method comprises the following steps: simulating the embedding, inflating and loading processes of a tire under different working conditions by dynamically switching a contact pair relationship, performing steady-state dynamics analysis on the force transmissibility of the tire, and calculating an acceleration frequency response function and a force transmissibility curve of a tread and a rim center. According to the method, the analysis efficiency is greatly improved, the simulation time is shortened by 80%, meanwhile, a high-precision simulation result is kept, and the method is suitable for force transmissibility evaluation of tires with multiple air pressures and multiple specifications and has wide application value.

The embodiment of the invention provides a three-dimensional scene modeling method, a cloud system, a storage medium and an electronic device. The method comprises the following steps: based on a plurality of crowdsourcing data collected and uploaded by a user terminal, performing three-dimensional scene modeling on a to-be-modeled scene through an incremental generation neural radiation field model to obtain a full-field-angle three-dimensional rendering model of the to-be-modeled scene. Through the embodiment of the invention, the problems of difficulty in data acquisition, lack of view angle of a reconstruction main body and low rendering efficiency of the existing three-dimensional reconstruction and rendering method in the related technology can be solved, and the effect of improving the three-dimensional scene modeling efficiency is achieved.

The invention discloses a signal integrity analysis and optimization method considering electrothermal coupling and parasitic effect in an artificial intelligence chip. According to the method, aiming at a random resistive memory cross array in an artificial intelligence chip, an RRAM compact model is combined to research the influence of device electrothermal coupling and parasitic effect on signal integrity in the cross array, evaluation analysis is carried out, and an optimization scheme is provided. Comprising the following steps: (1) based on a compact model of an RRAM device, establishing an equivalent thermal circuit network to represent an electrothermal coupling effect of a device in a cross array; (2) establishing an interconnection line equivalent circuit model containing parasitic resistance, capacitance and inductance, and extracting parasitic parameters in the model by adopting a partial element equivalent circuit (PEEC) method; (3) analyzing a simulation result, and realizing signal integrity evaluation considering electrothermal coupling, parasitic effect and the like; and (4) proposing an optimization scheme for the problems of parasitic voltage drop and leakage path. The method has important application value in random resistive memories and neuromorphic brain-like chips.

The invention discloses an Internet of Things data fusion method, apparatus and device, and a medium. The Internet of Things data fusion method comprises the following steps: determining a target identification equipment image and target identification equipment position data according to video inspection data and a target equipment identification model; according to the target identification equipment image and the target identification equipment position data, creating a static Internet of Things twinborn model; and according to the real-time sensing data of the Internet of Things, adjusting the static twinborn model of the Internet of Things to obtain a dynamic twinborn model of the Internet of Things. According to the technical scheme provided by the embodiment of the invention, the efficiency of accurate twin modeling can be improved, the labor cost of position calibration of the twin model is reduced, and the display effect of the twin model is improved.

The invention belongs to the related technical field of ship vibration and noise reduction, and discloses a method and system for determining vibration of a beam structure containing an acoustic black hole damping layer. The method comprises the following steps that S1, for a beam structure attached with an acoustic black hole damping layer in a ship, a coupling system comprising a uniform beam and the acoustic black hole damping layer is selected as a research object, the research object is simplified into two layers of beams which are connected in a coupling mode, and material attributes and section forms of the two layers of beams are different; s2, constructing a motion control equation of the coupling system; and S3, solving the motion control equation of the coupling system, and respectively obtaining the inherent frequency of the coupling system under free vibration and the vibration response of the coupling system under external excitation. According to the invention, the problems of low efficiency and poor economical efficiency of rapid prediction of the inherent frequency and the vibration response of the beam structure containing the acoustic black hole damping layer are solved.