Curtain wall energy-saving monitoring analysis method and system based on finite element analysis

Abstract

The application provides a curtain wall energy-saving monitoring analysis method and system based on finite element analysis, and relates to the technical field of energy-saving analysis. The method comprises the following steps: performing hierarchical topology reconstruction of curtain wall assembly on a design information model of a target building, and completing construction of a building curtain wall twin model; performing climate characteristic rhythm discretization, and constructing multiple cyclic simulation working conditions; performing non-homogeneous grid subdivision based on heat transfer gradient, and obtaining a finite element grid model; performing long-course transient coupling monitoring tracking, and obtaining a decay process cloud atlas sequence; performing alignment deviation tracing, obtaining fatigue vulnerable site distribution, and performing design defect display. The application solves the technical problem in the prior art that multiple typical meteorological year data or meteorological station statistical values are relied on as boundary input, the specific micro environment of the building is ignored, and systematic distortion exists between the environment load on which the curtain wall thermal analysis is based and the real service environment.

Description

Technical Field

[0001] This invention relates to the field of energy-saving analysis technology, specifically to a method and system for monitoring and analyzing energy-saving performance of curtain walls based on finite element analysis. Background Technology

[0002] Throughout its entire life cycle, building curtain walls are continuously affected by the coupled effects of multiple climatic factors, including temperature, solar radiation, wind speed, humidity, and day-night cycles. Their thermal performance is not statically stable but exhibits a gradual decline over time. This decline depends not only on the material's inherent properties but also on the local climatic rhythms of the site's microenvironment. For example, factors such as the urban heat island effect, differences in surface albedo, and local wind disturbances can all alter the actual load-bearing pattern of the curtain wall.

[0003] However, existing methods for curtain wall energy conservation analysis and finite element simulation typically remain at the level of standard meteorological data-driven or single-condition analysis. They lack the ability to finely characterize the microenvironmental climate rhythms and the systematic expression of long-term thermal degradation processes under the coupled effects of multiple climate factors. This makes it difficult to establish a stable and traceable correspondence between climate input and structural response. Specifically, traditional methods often rely on typical meteorological year data or meteorological station statistics as boundary inputs, ignoring the specific microenvironment in which the building is located, such as shading relationships, surface morphology, and local thermal environment differences. This results in a lack of spatial resolution and local characteristic expression ability for climate inputs, leading to systematic distortion between the environmental loads on which curtain wall thermal analysis is based and the actual service environment. Summary of the Invention

[0004] This application provides a method and system for monitoring and analyzing energy conservation of curtain walls based on finite element analysis. It aims to solve the technical problem that existing technologies rely heavily on typical meteorological year data or meteorological station statistics as boundary inputs, ignoring the specific microenvironment in which the building is located, resulting in systematic distortion between the environmental load on which the thermal analysis of the curtain wall is based and the actual service environment.

[0005] The first aspect disclosed in this application provides a method for energy-saving monitoring and analysis of curtain walls based on finite element analysis. The method includes: performing hierarchical topology reconstruction of the curtain wall assembly on the design information model of the target building to complete the construction of a building curtain wall twin model; performing climatic characteristic rhythm discretization on the target building under micro-environment site attribution to construct multiple cyclic simulation conditions; performing heterogeneous mesh subdivision of the building curtain wall twin model based on heat transfer gradient to obtain a finite element mesh model; stitching the multiple cyclic simulation conditions into a climate fidelity cycle sequence, performing long-term transient coupling monitoring and tracking on the finite element mesh model to obtain a degradation process cloud map sequence; using multiple expected performance cloud maps under the multiple cyclic simulation conditions, referring to the climate fidelity cycle sequence to trace the alignment deviation of the degradation process cloud map sequence to obtain the distribution of fatigue vulnerable sites, and displaying design defects in the building curtain wall twin model.

[0006] The second aspect of this application discloses a curtain wall energy-saving monitoring and analysis system based on finite element analysis. The system is used in the aforementioned curtain wall energy-saving monitoring and analysis method based on finite element analysis. The system includes: a hierarchical topology reconstruction module for reconstructing the hierarchical topology of the curtain wall assembly on the design information model of the target building, thus constructing a building curtain wall twin model; a characteristic rhythm discretization module for discretizing the climate characteristic rhythm of the target building under micro-environment site attribution, constructing multiple cyclic simulation conditions; a mesh subdivision module for subdividing the building curtain wall twin model into a heterogeneous mesh based on heat transfer gradients, obtaining a finite element mesh model; a monitoring and tracking module for stitching the multiple cyclic simulation conditions into a climate fidelity cycle sequence, performing long-term transient coupling monitoring and tracking of the finite element mesh model, and obtaining a degradation process cloud map sequence; and a design defect display module for using multiple expected performance cloud maps under the multiple cyclic simulation conditions, referencing the climate fidelity cycle sequence to trace the alignment deviation of the degradation process cloud map sequence, obtaining the distribution of fatigue vulnerable sites, and displaying design defects in the building curtain wall twin model.

[0007] One or more technical solutions provided in this application have at least the following beneficial effects: By reconstructing the hierarchical topology of the curtain wall assembly in the design information model and constructing a curtain wall twin model, the connection relationships, functional levels, and thermal properties of the various curtain wall components are uniformly expressed, thereby improving the model's ability to describe the actual structural behavior and providing a high-fidelity computational foundation for subsequent multiphysics simulations. Through microenvironment site attribution and climatic characteristic rhythm discretization, complex continuous meteorological data are transformed into a set of cyclic simulation conditions with engineering significance, improving the representativeness and computability of climatic boundary conditions and enabling the structural analysis model to stably reproduce extreme environmental effects. Through heterogeneous mesh subdivision based on heat transfer gradients, adaptive discretization optimization of the finite element model at the spatial scale is achieved, thereby ensuring the accuracy of calculations. While improving computational efficiency, it significantly enhances the accuracy of local response and improves the numerical reliability of thermo-mechanical coupling analysis. By constructing a climate-fidelity cycle sequence and performing long-term transient coupling tracking, it realizes the progressive performance degradation simulation of the curtain wall under multi-cycle real climate action, and can output a time-continuous degradation process cloud map sequence, thereby depicting the dynamic law of structural performance degradation over time. Through the source analysis of the alignment deviation between the expected performance cloud map and the degradation cloud map, it realizes the spatial location and working condition attribution of structural response deviation, and then identifies fatigue vulnerability sites sensitive to multi-working-condition resonance. The results are mapped to the curtain wall twin model for visualization, realizing the visualization, traceability and interpretability of curtain wall design defects.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] Figure 1 A schematic diagram of the process for a curtain wall energy-saving monitoring and analysis method based on finite element analysis provided in this application embodiment.

[0010] Figure 2 Line graph of working condition type-degradation index in the curtain wall energy-saving monitoring and analysis method based on finite element analysis provided in the embodiments of this application.

[0011] Figure 3 A schematic diagram of the structure of a curtain wall energy-saving monitoring and analysis system based on finite element analysis provided in this application embodiment.

[0012] Figure labeling: Hierarchical topology reconstruction module 10, feature rhythm discretization module 20, mesh subdivision module 30, monitoring and tracking module 40, design defect display module 50. Detailed Implementation

[0013] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0014] Example 1, as Figure 1 As shown in the embodiments of this application, a method for monitoring and analyzing energy-saving curtain walls based on finite element analysis is provided. The method includes: A100: On the design information model of the target building, perform hierarchical topology reconstruction of the curtain wall assembly to complete the construction of the building curtain wall twin model.

[0015] Based on the Building Information Model (BIM) of the target building, the curtain wall system is first structurally deconstructed and semantically reorganized. Elements from the original design, such as panels, keels, connectors, sealing structures, and insulation layers, are hierarchically divided according to thermal function and assembly relationships, forming a multi-level set of component units. Based on the spatial adjacency relationships, force transmission paths, and assembly constraints between components, a hierarchical topological relationship network is constructed to express the connection logic and structural dependencies of the curtain wall system. The essence of topological reconstruction is to transform the geometric model into a graphical structure of "component-relationship-hierarchy." Furthermore, material thermal properties, such as thermal conductivity, specific heat capacity, and thermal resistance, are injected to give the model heat conduction and environmental response capabilities, thus forming a twin model of the building curtain wall that can be used for simulation analysis, realizing the transformation from design information to a computable physical model.

[0016] A200: Discretize the climatic characteristic rhythm of the target building under the micro-environment site attribution and construct multiple cyclic simulation conditions.

[0017] Based on the microenvironment of the target building, and using spatial location as an index, combined with surrounding topography, urban thermal environment, and land cover characteristics, a causal analysis of the local climate formation mechanism is conducted. Further integration of historical hourly meteorological data, including temperature, humidity, wind speed, and solar radiation, identifies climate event types that dominate the thermal response of the curtain wall, such as prolonged periods of high temperatures, drastic diurnal temperature variations, and strong winds coupled with rainfall. Based on building thermal design thresholds, the aforementioned climate events are segmented into time series and discretized rhythmically, transforming continuous meteorological processes into discrete loading segments with boundary constraints. Through segment recombination and envelope merging, various representative cyclic simulation conditions are formed for subsequent finite element long-period loading analysis, transforming the climate input from a continuous natural process into a set of controllable simulation conditions.

[0018] A300: The building curtain wall twin model is subdivided into a heterogeneous mesh based on the heat transfer gradient to obtain a finite element mesh model.

[0019] Finite element method (FEM) discretization was performed on the twin model of the curtain wall. First, based on the internal material distribution and boundary heat transfer conditions of the components, the heat transfer gradient field in the curtain wall system, i.e., the spatial non-uniformity of the temperature change rate, was calculated. The mesh density was adaptively adjusted according to this gradient field. In high-gradient regions, such as the glass-profile interface and thermal bridges, a high-density, finer mesh was used, while in low-gradient regions, a relatively coarser mesh was used, thus forming a heterogeneous mesh structure. This reduces computational cost while maintaining accuracy. Finally, the component geometry, material properties, and boundary conditions were mapped to mesh nodes and elements to generate a finite element mesh model, providing a numerical basis for subsequent transient thermo-mechanical coupling calculations and giving the curtain wall system a solvable discrete physical representation.

[0020] A400: The various cyclic simulation conditions are spliced ​​into a climate fidelity cycle sequence, and the finite element mesh model is subjected to long-term transient coupling monitoring and tracking to obtain a decay process cloud map sequence.

[0021] Multiple cyclic simulation conditions are spliced ​​together according to the statistical frequency and temporal structure of the actual annual climate cycle at the target site to form a climate-fidelity cycle sequence, ensuring the authenticity and representativeness of the simulation input in terms of temporal distribution. This sequence is used as the boundary load input to the finite element mesh model for transient coupling analysis on a long time scale. The coupling process considers the combined effects of heat conduction, material thermal stress response, and environmental load changes. During the simulation, the spatial distribution evolution of key physical field variables, such as temperature field, stress field, and energy loss indicators, is continuously recorded, forming a time-varying degradation process cloud map sequence. This cloud map sequence characterizes the dynamic process of performance degradation and stress accumulation of the curtain wall under long-term climate action, realizing the monitoring and expression from instantaneous response to the entire life cycle evolution.

[0022] A500: Using multiple expected performance cloud maps under various cyclic simulation conditions, and referring to the climate fidelity cycle sequence, the alignment deviation of the degradation process cloud map sequence is traced to obtain the distribution of fatigue vulnerable sites, and the design defects are displayed in the building curtain wall twin model.

[0023] Based on the expected performance cloud maps under multiple operating conditions, i.e., the target response distribution under design or standard conditions, a temporal and spatial alignment analysis is performed on the degradation process cloud map sequence. First, according to the operating condition mapping relationship, the cloud map results under different climatic conditions are registered and compared with the corresponding expected states, and performance deviation regions are extracted through difference segmentation. At the finite element node level, cumulative statistics are performed on the deviation regions to identify high-deviation nodes that repeatedly appear in multiple operating conditions, forming a preliminary fatigue node set. Through multi-condition intersection screening, structural locations exhibiting sensitivity under different climatic effects are extracted, determining the distribution of fatigue vulnerable sites. Finally, this distribution result is mapped back to the curtain wall twin model to achieve a visual display of design defects, intuitively showing risk areas in the form of heat maps or annotations, providing a basis for structural optimization.

[0024] Furthermore, the target building undergoes micro-environmental site-specific climatic characteristic rhythm discretization to construct various cyclical simulation conditions. The method includes: A210: Based on the micro-environment site location of the target building, conduct environmental parameter tracing to construct multiple standard extreme climate conditions; A220: Combine the thermal design index thresholds of the target building to discretize the characteristic rhythms of the multiple standard extreme climate conditions and construct the multiple cyclic simulation conditions.

[0025] Based on the site location of the target building's microenvironment, boundary conditions for climate analysis are established through spatial positioning. Environmental parameter attribution involves tracing back from the building's microenvironment to identify key factors influencing the region's climate formation, including topographic shielding, surface albedo, urban heat island effect, and local ventilation conditions, and combining these with historical meteorological data for joint analysis. Building upon this, extreme climate scenarios are abstracted from continuous meteorological sequences to construct a representative set of standard extreme climate conditions. Each type of extreme climate condition corresponds to a typical environmental state, characterizing the high loads or extreme operating conditions that the curtain wall may encounter, providing standardized input boundaries for subsequent thermal analysis.

[0026] Based on standard extreme climate conditions, thermal design thresholds for the target building, such as heat transfer coefficient limits, indoor temperature control ranges, and shading performance indicators, are introduced to conduct response constraint analysis on climate conditions. By segmenting continuous or long-term climate changes according to thermal response-sensitive intervals, time segments with structural impact are extracted to discretize climate rhythms. These discrete segments are then combined and reconstructed to form loading sequences with periodic or repetitive characteristics, thereby constructing various cyclic simulation conditions. This set of conditions retains extreme climate characteristics while meeting the requirements of finite element analysis for boundary condition stability and repeatability.

[0027] Furthermore, based on the micro-environmental site location of the target building, environmental parameters are traced back to their causes, and multiple standard extreme climate conditions are constructed. The method includes: A211: Using the location of the microenvironment site as a spatial index benchmark, and based on a preset geographical buffer radius, retrieve local surface feature data and historical hourly meteorological data from geospatial data sources and meteorological time-series data sources, respectively; A212: Using the local surface feature data as the microenvironment correction boundary, perform causal screening of sensitive parameters in the historical hourly meteorological data to obtain the dominant environmental event cluster; A213: Perform multi-index extreme envelope condensation on the dominant environmental event cluster to construct the various standard extreme climate conditions.

[0028] A spatial index baseline is established centered on the microenvironment site location, and a predefined geographical buffer radius is set to limit the data collection range. Within this spatial range, local surface characteristic data, including topographic elevation, building density, vegetation cover, and surface material reflectivity, are obtained from geospatial data sources. Simultaneously, historical hourly meteorological data, such as temperature, humidity, wind speed, solar radiation, and rainfall information, are obtained from meteorological time-series data sources. Through multi-source data fusion, the meteorological data is no longer a single-site observation but rather microenvironment input data corrected for spatial environmental constraints, providing fundamental data support for subsequent causal analysis.

[0029] Using local surface characteristic data as boundary conditions for microenvironment correction, historical hourly meteorological data are screened and reconstructed. Sensitive parameter attribution refers to identifying combinations of meteorological factors that significantly affect the thermal response of the curtain wall, such as coupled conditions like high radiation superimposed with high temperature or strong wind accompanied by low temperature. Through statistical analysis and response sensitivity assessment, weak influencing factors are eliminated, and dominant influencing parameters are retained, thus forming a set of physically meaningful climate events. These events are further clustered according to temporal continuity and characteristic similarity to obtain dominant environmental event clusters, which are used to characterize recurring or representative climate action patterns within the region.

[0030] Multi-indicator extreme value analysis and envelope processing are performed on the dominant environmental event clusters, with the core objective of extracting extreme boundary conditions. These multiple indicators include key environmental parameters such as outdoor air temperature, total solar radiation intensity, wind speed, effective sky temperature, and relative humidity. Through joint distribution analysis of these indicators, extreme combinations of states are identified, and an envelope condensation method is used to compress the complex event clusters into a finite number of representative extreme states. Each of the resulting standard extreme climate conditions is an independent environmental state with a well-defined set of numerical parameters, which can be directly used as boundary inputs for finite element simulations, achieving the conversion from complex climate data to standardized simulation conditions.

[0031] Furthermore, by combining the thermal design index thresholds of the target building, the characteristic rhythms of the various standard extreme climate conditions are discretized to construct the various cyclic simulation conditions. The method includes: A221: Based on a preset sliding response analysis window, thermal transient response simulation is performed on the various standard extreme climate conditions to obtain multiple thermal response time series data; A222: The thermal design index threshold is used to traverse the multiple thermal response time series data to extract segment boundaries, resulting in multiple sets of discrete loading segments; A223: The multiple sets of discrete loading segments are merged by overlapping envelopes to obtain multiple sets of independent operating condition envelopes, and then threshold-driven sequence arrangement is performed to obtain the various cyclic simulation operating conditions.

[0032] To address various standard extreme climate conditions, a pre-defined sliding response analysis window is introduced for time-domain segmentation. The sliding response analysis window refers to a time interval that slides continuously across the climate input sequence with a fixed or adaptive time length, used to capture the transient thermal response behavior of the curtain wall at different time scales. Within each time window, extreme climate conditions are used as boundary inputs, and transient heat conduction and energy exchange simulations are performed in conjunction with the curtain wall thermal model to obtain the corresponding temperature field, heat flux density, and interface thermal response changes. Through full-time-domain sliding calculations, multiple time-continuous thermal response time-series data are generated, providing a dynamic response basis for subsequent operating condition segmentation.

[0033] Using building thermal design thresholds as constraints, a comprehensive analysis of multiple thermal response time-series data was conducted. These thresholds included limits on indoor-outdoor temperature difference, upper limits on component temperatures, and control ranges for heat flux density. When the response curve touched or exceeded a threshold on the time axis, it was identified as an engineering-significant boundary point. Based on these boundary points, the continuous response sequence was segmented, extracting time segments with significant thermal variation characteristics to form multiple sets of discrete loading segments. These segments are essentially key stresses or thermal shock processes extracted from the continuous thermal response, representing typical loading processes of the curtain wall under extreme conditions.

[0034] Multiple discrete loading segments are structurally reorganized. First, overlapping envelope analysis is used to merge segments that are similar in time or response characteristics, eliminating repetitive or redundant loading processes and forming independent sets of operating condition envelopes. Envelope merging refers to using the response peak range or characteristic boundary as the outer envelope to unify and summarize multiple segments into a typical loading mode. Based on this, different envelopes are sorted and combined according to the dominant relationship of thermal thresholds to form physically meaningful cyclic sequence structures, ultimately obtaining various cyclic simulation conditions to simulate the long-term response behavior of the curtain wall under periodic or repetitive extreme environments.

[0035] Furthermore, by stitching together the various cyclic simulation conditions into a climate fidelity cycle sequence, and performing long-term transient coupled monitoring and tracking on the finite element mesh model, a decay process cloud map sequence is obtained. The method includes: A410: Using the site climate annual cycle as the time series reference, frequency splicing of the various cyclic simulation conditions is performed to obtain a climate fidelity cycle sequence; A420: A multi-round traversal loading queue is configured for the climate fidelity cycle sequence, and long-term transient coupling monitoring and tracking are performed on the finite element mesh model to obtain the decay process cloud map sequence.

[0036] Using the annual climate cycle of the target site as a time reference, various cyclical simulation scenarios are spliced ​​and reconstructed according to the frequency, duration, and seasonal distribution characteristics of real climate events, thus forming a climate-fidelity cycle sequence. Climate fidelity refers to maintaining the true climate distribution characteristics in a statistical sense, including the proportion of extreme events, seasonal variation rhythms, and duration structure. In this way, discrete scenarios are no longer loaded independently, but are embedded in a sequence that closely approximates the actual annual climate evolution process, thereby enhancing the engineering realism and long-term predictive ability of the simulation results.

[0037] A climate-fidelity cycle sequence is used as input load to perform multi-round ergonomic loading calculations on the finite element mesh model. The multi-round ergonomic loading queue refers to repeatedly applying climate cycles in chronological order, allowing the model to experience the cumulative effects over multiple virtual years. During the calculation, heat conduction, material performance degradation, and environmental coupling effects are simultaneously considered to perform long-history transient analysis of the curtain wall structure. Key physical field distribution results are continuously output, including temperature field, stress field, and energy loss evolution, ultimately forming a time-varying degradation process cloud map sequence to characterize the degradation trajectory of the curtain wall performance over its service life.

[0038] Taking a coastal building curtain wall with high humidity and high salinity as an example, the climate fidelity period is set to 1 year (8760h), with high temperature and high radiation conditions accounting for 18% and strong wind conditions accounting for 12%. The finite element thermal response can be expressed by a simplified transient heat transfer control formula: Q(t) = h·A·(T) out (t)-T surf (t))+α·I(t), where Q(t) is the transient heat flux, and h is the convective heat transfer coefficient, taken as 18 W / m. 2 K and A represent the area of ​​the curtain wall unit (1.2m²), and T represents the area of ​​the curtain wall unit. out The outdoor temperature, T surf Let t be the surface temperature, α be the solar absorptivity (taken as 0.6), and I(t) be the solar radiation intensity. Example data are shown in Table 1.

[0039] Table 1 Example Data Table

[0040] Based on the above data, a line chart of "Operating Condition Type - Decline Index" is drawn, as follows: Figure 2 As shown, the influence intensity of different climate cycles on the cloud map sequence of curtain wall degradation process is characterized, thereby verifying the rationality and computability of long-term coupling analysis in A420.

[0041] Furthermore, by employing multiple expected performance cloud maps under the aforementioned various cyclic simulation conditions, and referencing the climate fidelity cycle sequence to trace the alignment deviation of the degradation process cloud map sequence, the distribution of fatigue vulnerable sites is obtained. The method includes: S1: Based on the time-series mapping relationship between the first cyclic simulation working condition and the climate fidelity cycle sequence, extract multiple first working condition aligned decay cloud maps from the decay process cloud map sequence; S2: Overlap the first expected performance cloud map to the multiple first working condition aligned decay cloud maps to perform deviation segmentation, obtaining multiple decay region distributions; S3: Align the multiple decay region distributions with the node layer of the finite element mesh model to perform frequency accumulation positioning, locating multiple first working condition fatigue nodes; A510: Repeat steps S1 to S3 to perform multi-working condition deviation tracing of the decay process cloud map sequence, obtaining multiple working condition fatigue node sets corresponding to the multiple cyclic simulation working conditions and corresponding multiple working condition labels; A520: After spatial intersection identification of the multiple working condition fatigue node sets, use the multiple working condition labels to perform multi-working condition coupling attribute identification, generating the fatigue vulnerability site distribution.

[0042] Based on the temporal mapping relationship between the first-cycle simulation condition and the climate fidelity cycle sequence, the decay process contour map sequence is aligned at the condition level. The temporal mapping relationship refers to establishing a one-to-one correspondence between the loading time periods of different cyclic conditions in the simulation and the corresponding time slices in the climate fidelity cycle, thereby establishing a unified time reference. On this basis, local response results corresponding to the first condition are extracted from the continuous decay contour map sequence, forming multiple first-condition aligned decay contour maps. This process enables slicing from the global time series according to condition semantics, making the structural responses under different climate effects comparable.

[0043] Using the first expected performance contour map as a baseline reference, spatial overlay analysis is performed on it with multiple first-condition alignment degradation contour maps obtained from S1. The expected performance contour map refers to the ideal thermal or mechanical response distribution that the curtain wall should achieve under design or standard operating conditions. By comparing the numerical differences between the two types of contour maps node-by-node or unit-by-unit, deviation areas are identified, and deviations are segmented using thresholding or segmentation methods, thereby obtaining the distribution of multiple degradation regions. These regions characterize the spatial location of performance degradation or abnormal response of the curtain wall under specific operating conditions, providing basic data for subsequent fatigue analysis.

[0044] At the node level of the finite element mesh model, spatial alignment analysis is performed on the distribution of multiple decay regions obtained in S2. Specifically, the decay regions are mapped back to mesh nodes, and the frequency of each node appearing in the decay region across multiple time steps or segments is statistically analyzed to form a node-level cumulative index. The higher the frequency, the more prone the node is to performance degradation under that operating condition. By setting statistical thresholds or sorting and filtering, multiple fatigue nodes under the first operating condition are located to characterize the weak points of the local structure under specific environmental conditions.

[0045] The S1-S3 processes are executed iteratively, repeatedly performing degradation contour map alignment, deviation segmentation, and node frequency analysis for various cyclic simulation conditions, thereby achieving deviation source tracing analysis under multiple operating conditions. Through this process, fatigue node sets corresponding to different operating conditions are obtained, and each node set is assigned an operating condition label to identify its source climate type or loading mode. Deviation source tracing refers to tracking the climate driving factors corresponding to different performance degradation results, realizing the analytical process of inferring the impact path of operating conditions from the results.

[0046] Spatial intersection operations are performed on multiple fatigue node sets under various operating conditions to identify high-frequency fatigue nodes that repeatedly occur under different climatic conditions. The intersection results are used to screen structural locations with cross-condition stability sensitivity, thereby excluding points affected by occasional or single operating conditions. By combining multiple operating condition labels corresponding to each node, multi-dimensional attribute annotations are applied to these intersection nodes to achieve multi-condition coupled feature expression. Finally, a fatigue vulnerability site distribution is formed, which characterizes the comprehensive weak areas of the curtain wall system under long-term complex climatic conditions, providing a basis for structural optimization and design improvement.

[0047] Furthermore, the fatigue vulnerability site distribution is subjected to multi-condition superposition statistical rendering to obtain a multi-condition coupled vulnerability heat map, which is then used to display design defects in the building curtain wall twin model.

[0048] To further analyze and visualize the distribution of fatigue-vulnerable sites, multi-condition superposition statistical analysis was conducted. Multi-condition superposition refers to the comprehensive index of the cumulative intensity and repetition frequency of fatigue or performance degradation of the same spatial node under different climatic conditions. By weighting and superimposing the node responses under each condition label, a spatial intensity distribution field is formed, and this field is mapped onto the surface of the curtain wall model using heatmap rendering to generate a multi-condition coupled vulnerability heatmap. This heatmap is then superimposed onto the 3D structure of the building curtain wall twin model to visualize design defects, allowing weak areas to be intuitively presented in the model using color gradients or highlighted markers, thereby supporting design optimization and risk identification.

[0049] Furthermore, on the design information model of the target building, a hierarchical topology reconstruction of the curtain wall assembly is performed to complete the construction of a building curtain wall twin model. The method includes: A110: Based on the thermal function role, the curtain wall design information is split and mapped into hierarchical component sets, and a hierarchical component model set is constructed based on the hierarchical component set; A120: In the design information model, based on the inter-layer assembly contact relationship, the topological association of the hierarchical component model set is performed to obtain a hierarchical assembly topology diagram; A130: Material thermal properties are injected into the hierarchical assembly topology diagram to complete the construction of the building curtain wall twin model.

[0050] Based on the thermal function division of the curtain wall system, the curtain wall structure in the original design information model is semantically decomposed and functionally mapped. Thermal function roles refer to the positioning of different components in heat conduction and thermal barrier; for example, the outer panel provides radiation protection, the intermediate insulation layer provides thermal blocking, and the supporting structure provides thermal bridging constraints. Based on this, the curtain wall design information is divided into multiple hierarchical component sets, and corresponding hierarchical component model sets are established according to functional and spatial relationships. This ensures that each component possesses both geometric and thermal properties, thus providing basic data units for subsequent topology modeling.

[0051] Based on the hierarchical component model set, topological modeling is performed by introducing the assembly contact relationships between components. Inter-layer assembly contact relationships refer to the physical connections formed by different components in an actual curtain wall system through connectors, interlocking, or structural constraints. By representing these contact relationships using a graph structure, with components as nodes and connections as edges, a hierarchical assembly topology graph is constructed. This topology graph not only reflects geometric connections but also expresses mechanical and heat conduction paths, thereby realizing the transformation of the curtain wall system from discrete components to a networked structural model.

[0052] Based on the hierarchical assembly topology diagram, material thermal property parameters are assigned to complete the physical properties. These thermal property parameters include key indicators such as thermal conductivity, specific heat capacity, density, coefficient of thermal expansion, and thermal resistance, which determine the thermal response behavior of components under different climatic conditions. By mapping material properties to the nodes and edge relationships of each component in the topology diagram, the model simultaneously possesses structural topology information and thermal physical properties. This ultimately forms a twin model of the building curtain wall, which can be used for finite element simulation and long-term performance analysis, achieving a complete transformation from a design information model to a computable, multiphysics coupled analysis model.

[0053] Furthermore, the hierarchical component set includes an outer surface layer component set, an intermediate heat insulation layer component set, an internal support layer component set, a connecting and fastening layer component set, and a boundary sealing layer component set, and the hierarchical component model set includes an outer surface layer component model set, an intermediate heat insulation layer component model set, an internal support layer component model set, a connecting and fastening layer component model set, and a boundary sealing layer component model set.

[0054] The hierarchical component set and the hierarchical component model set are a two-layer expression system in the digital twin modeling of curtain walls. The "component set" focuses on functional semantic decomposition, while the "model set" focuses on the integrated expression of geometry, physics and topology.

[0055] The external surface layer component set refers to the collection of components on the outermost side of the curtain wall that are directly exposed to the environment, including glass panels, metal cladding, or photovoltaic panels, etc. Its core functions are radiative heat insulation, protection against wind and rain erosion, and regulation of solar radiation. At the model level, this component is expressed as a continuous shell unit or solid unit with complete geometric boundaries and surface heat transfer boundary conditions, and is endowed with high radiation absorptivity and surface convection heat transfer coefficient.

[0056] The intermediate insulation layer component set refers to the insulation and air gap structure located between the outer and inner layers, including insulation materials, vacuum layers or low thermal conductivity filling layers. Its model is expressed using low thermal conductivity volume elements, which are used to model the dominant thermal resistance path and are the key area for heat flow attenuation.

[0057] The internal support layer component set is used to represent the load-bearing structural system of the curtain wall, such as aluminum profile keel, steel structure frame, etc. Its model is represented by beam element or shell-beam hybrid element, focusing on describing mechanical stiffness, deformation transmission and thermal bridge effect, which is the main transmission channel of thermal-mechanical coupling.

[0058] The fastening layer component set is used to describe connecting components such as bolts, hangers, and clips. Its model uses discrete connection elements or spring-damped elements to characterize the node constraint stiffness, slip and contact nonlinear behavior, which are key control factors for topological stability.

[0059] The boundary sealing layer component set includes sealant, adhesive strips, and airtight and watertight structures. Its model is represented by flexible contact elements or nonlinear constitutive material elements, and is mainly used to describe permeation resistance, thermal convection suppression, and interface coupling effects.

[0060] In terms of overall modeling logic, the hierarchical component set provides functional zoning and semantic classification, while the hierarchical component model set further maps the above functional units into finite element computable objects. Through the unification of geometric discretization, material assignment and topological connection, the complete mapping relationship of the curtain wall system from the structural level to the calculation model level is realized, thereby supporting subsequent thermal analysis and long-term performance simulation.

[0061] Example 2, based on the same inventive concept as the curtain wall energy-saving monitoring and analysis method based on finite element analysis in the previous examples, such as... Figure 3 As shown in the embodiment of this application, an energy-saving monitoring and analysis system for curtain walls based on finite element analysis is provided. The system includes: The hierarchical topology reconstruction module 10 is used to perform hierarchical topology reconstruction of the curtain wall assembly on the design information model of the target building, and complete the construction of the building curtain wall twin model; the characteristic rhythm discretization module 20 is used to perform climate characteristic rhythm discretization on the target building under micro-environment site attribution, and construct multiple cyclic simulation conditions; the mesh subdivision module 30 is used to perform heterogeneous mesh subdivision on the building curtain wall twin model based on heat transfer gradient, and obtain a finite element mesh model; the monitoring and tracking module 40 is used to stitch the multiple cyclic simulation conditions into a climate fidelity cycle sequence, and perform long-term transient coupling monitoring and tracking on the finite element mesh model to obtain a decay process cloud map sequence; the design defect display module 50 is used to use multiple expected performance cloud maps under the multiple cyclic simulation conditions, refer to the climate fidelity cycle sequence to trace the alignment deviation of the decay process cloud map sequence, obtain the fatigue vulnerability site distribution, and display the design defect on the building curtain wall twin model.

[0062] Furthermore, the characteristic rhythm discretization module 20 is used to perform the following operation steps: Based on the micro-environment site location of the target building, environmental parameters are traced back to their causes, and multiple standard extreme climate conditions are constructed. Combined with the thermal design index thresholds of the target building, the characteristic rhythms of the multiple standard extreme climate conditions are discretized, and multiple cyclic simulation conditions are constructed.

[0063] Furthermore, the characteristic rhythm discretization module 20 is used to perform the following operation steps: Using the location of the microenvironment site as a spatial index benchmark, and based on a preset geographical buffer radius, local surface feature data and historical hourly meteorological data are retrieved from geospatial data sources and meteorological time-series data sources, respectively. Using the local surface feature data as the microenvironment correction boundary, sensitive parameter tracing and screening of the historical hourly meteorological data are performed to obtain the dominant environmental event cluster. Multi-index extreme envelope condensation is performed on the dominant environmental event cluster to construct the various standard extreme climate conditions.

[0064] Furthermore, the characteristic rhythm discretization module 20 is used to perform the following operation steps: Based on a preset sliding response analysis window, thermal transient response simulations are performed on the various standard extreme climate conditions to obtain multiple thermal response time series data. The thermal design index threshold is used to traverse the multiple thermal response time series data to extract segment boundaries, resulting in multiple sets of discrete loading segments. The multiple sets of discrete loading segments are then merged with overlapping envelopes to obtain multiple sets of independent operating condition envelopes. Finally, threshold-driven sequence arrangement is performed to obtain the various cyclic simulation operating conditions.

[0065] Furthermore, the monitoring and tracking module 40 is used to perform the following operation steps: Using the annual climate cycle of the site as the time series reference, the frequency splicing of the various cyclic simulation conditions is performed to obtain a climate fidelity cycle sequence; a multi-round traversal loading queue is configured for the climate fidelity cycle sequence, and long-term transient coupling monitoring and tracking are performed on the finite element mesh model to obtain the decay process cloud map sequence.

[0066] Furthermore, the design defect display module 50 is used to perform the following operation steps: S1: Based on the time-series mapping relationship between the first cyclic simulation working condition and the climate fidelity cycle sequence, extract multiple first working condition aligned decay cloud maps from the decay process cloud map sequence; S2: Overlap the first expected performance cloud map to the multiple first working condition aligned decay cloud maps to perform deviation segmentation, obtaining multiple decay region distributions; S3: Align the multiple decay region distributions with the node layer of the finite element mesh model to perform frequency accumulation positioning, locating multiple first working condition fatigue nodes; Repeat steps S1 to S3 to perform multi-working condition deviation tracing of the decay process cloud map sequence, obtaining multiple working condition fatigue node sets corresponding to the multiple cyclic simulation working conditions and corresponding multiple working condition labels; After spatial intersection identification of the multiple working condition fatigue node sets, use the multiple working condition labels to perform multi-working condition coupling attribute identification, generating the fatigue vulnerability site distribution.

[0067] Furthermore, the fatigue vulnerability site distribution is subjected to multi-condition superposition statistical rendering to obtain a multi-condition coupled vulnerability heat map, which is then used to display design defects in the building curtain wall twin model.

[0068] Furthermore, the hierarchical topology reconstruction module 10 is used to perform the following operation steps: Based on the thermal function roles, the curtain wall design information is split and mapped into hierarchical component sets, and a hierarchical component model set is constructed based on the hierarchical component set. In the design information model, based on the inter-layer assembly contact relationship, the topological association of the hierarchical component model set is performed to obtain a hierarchical assembly topology diagram. Material thermal properties are injected into the hierarchical assembly topology diagram to complete the construction of the building curtain wall twin model.

[0069] Furthermore, the hierarchical component set includes an outer surface layer component set, an intermediate heat insulation layer component set, an internal support layer component set, a connecting and fastening layer component set, and a boundary sealing layer component set, and the hierarchical component model set includes an outer surface layer component model set, an intermediate heat insulation layer component model set, an internal support layer component model set, a connecting and fastening layer component model set, and a boundary sealing layer component model set.

[0070] Through the foregoing detailed description of the curtain wall energy-saving monitoring and analysis method based on finite element analysis, those skilled in the art can clearly understand the curtain wall energy-saving monitoring and analysis system based on finite element analysis in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section.

[0071] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for monitoring and analyzing energy-saving performance of curtain walls based on finite element analysis, characterized in that, The method includes: On the design information model of the target building, the hierarchical topology of the curtain wall assembly is reconstructed to complete the construction of the building curtain wall twin model; The target building is subjected to micro-environmental site attribution-based climatic characteristic rhythm discretization to construct various cyclical simulation conditions. The building curtain wall twin model is subdivided into a heterogeneous mesh based on the heat transfer gradient to obtain a finite element mesh model. The various cyclic simulation conditions are spliced ​​together to form a climate fidelity cycle sequence, and the finite element mesh model is subjected to long-term transient coupling monitoring and tracking to obtain a decay process cloud map sequence. Using multiple expected performance cloud maps under various cyclic simulation conditions, and referring to the climate fidelity cycle sequence, the alignment deviation of the degradation process cloud map sequence is traced to obtain the distribution of fatigue vulnerable sites, and the design defects are displayed in the building curtain wall twin model. The target building was subjected to micro-environmental site attribution-based climatic characteristic rhythm discretization, and various cyclic simulation conditions were constructed, including: Based on the micro-environmental site location of the target building, environmental parameters are traced back to their causes, and various standard extreme climate conditions are constructed. By combining the thermal design index thresholds of the target building, the characteristic rhythms of the various standard extreme climate conditions are discretized to construct the various cyclic simulation conditions. Based on the micro-environmental site location of the target building, environmental parameters are traced back to their causes, and various standard extreme climate conditions are constructed, including: Using the location of the microenvironment site as a spatial index benchmark, and based on a preset geographical buffer radius, local surface feature data and historical hourly meteorological data are retrieved from geospatial data sources and meteorological time series data sources, respectively. Using the local surface feature data as the microenvironment correction boundary, the sensitive parameter tracing of the historical hourly meteorological data is performed to obtain the dominant environmental event cluster. Multi-index extreme envelope condensation is performed on the dominant environmental event cluster to construct the various standard extreme climate conditions; Based on the thermal design index thresholds of the target building, the characteristic rhythms of the various standard extreme climate conditions are discretized to construct the various cyclic simulation conditions, including: Based on a preset sliding response analysis window, thermal transient response simulations are performed on the various standard extreme climate conditions to obtain multiple thermal response time series data. The thermal design index threshold is used to traverse the multiple thermal response time series data to extract segment boundaries, resulting in multiple sets of discrete loading segments. After merging the overlapping envelopes of the multiple sets of discrete loading segments to obtain multiple sets of independent working condition envelopes, threshold-driven sequence arrangement is performed to obtain the multiple cyclic simulation working conditions.

2. The curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in claim 1, characterized in that, By splicing the various cyclic simulation conditions into a climate fidelity cycle sequence, and performing long-history transient coupled monitoring and tracking on the finite element mesh model, a decay process cloud map sequence is obtained, including: Using the annual climate cycle of the site as the time series reference, the frequency splicing of the various cyclic simulation conditions is performed to obtain a climate fidelity cycle sequence. A multi-round traversal loading queue is configured for the climate fidelity cycle sequence, and long-term transient coupling monitoring and tracking are performed on the finite element mesh model to obtain the decay process cloud map sequence.

3. The curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in claim 2, characterized in that, Using multiple expected performance cloud maps under the aforementioned various cyclic simulation conditions, and referencing the climate fidelity cycle sequence, the alignment deviation of the degradation process cloud map sequence is traced to obtain the distribution of fatigue vulnerable sites, including: S1: Based on the time-series mapping relationship between the first type of cyclic simulation working condition and the climate fidelity cycle sequence, extract multiple first-condition aligned decay cloud maps from the decay process cloud map sequence; S2: Overlap the first expected performance cloud map with the multiple first operating condition aligned decay cloud maps and perform deviation segmentation to obtain multiple decay region distributions; S3: Align the distribution of the multiple decay regions at the node layer of the finite element mesh model and perform frequency accumulation positioning to locate multiple fatigue nodes under the first working condition; Repeat steps S1 to S3 to trace the multi-condition deviation of the decay process cloud map sequence, and obtain multiple fatigue node sets corresponding to the multiple cyclic simulation conditions and the corresponding multiple condition labels. After spatial intersection identification of the multiple fatigue node sets under various working conditions, the multiple working condition labels are used to identify the multi-working condition coupling attributes, thereby generating the fatigue vulnerability site distribution.

4. The curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in claim 3, characterized in that, The fatigue vulnerability site distribution is subjected to multi-condition superposition statistical rendering to obtain a multi-condition coupled vulnerability heat map, which is then used to display design defects in the building curtain wall twin model.

5. The curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in claim 1, characterized in that, On the design information model of the target building, perform hierarchical topology reconstruction of the curtain wall assembly to complete the construction of the building curtain wall twin model, including: Based on the thermal function roles, the curtain wall design information is split and mapped into hierarchical component sets, and a hierarchical component model set is constructed based on the hierarchical component sets. In the design information model, based on the inter-layer assembly contact relationship, the topological association of the hierarchical component model set is performed to obtain the hierarchical assembly topology diagram; Material thermal properties are injected into the hierarchical assembly topology diagram to complete the construction of the building curtain wall twin model.

6. The curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in claim 5, characterized in that, The hierarchical component set includes an outer surface layer component set, an intermediate heat insulation layer component set, an internal support layer component set, a connecting and fastening layer component set, and a boundary sealing layer component set. The hierarchical component model set includes an outer surface layer component model set, an intermediate heat insulation layer component model set, an internal support layer component model set, a connecting and fastening layer component model set, and a boundary sealing layer component model set.

7. A curtain wall energy-saving monitoring and analysis system based on finite element analysis, characterized in that, The system is used to implement the curtain wall energy-saving monitoring and analysis method based on finite element analysis as described in any one of claims 1 to 6, the system comprising: The hierarchical topology reconstruction module is used to perform hierarchical topology reconstruction of the curtain wall assembly on the design information model of the target building, and to complete the construction of the building curtain wall twin model. The characteristic rhythm discretization module is used to discretize the climate characteristic rhythm of the target building under the micro-environment site attribution and construct various cyclic simulation conditions. The mesh subdivision module is used to subdivide the building curtain wall twin model into a heterogeneous mesh based on the heat transfer gradient to obtain a finite element mesh model. The monitoring and tracking module is used to stitch together the various cyclic simulation conditions into a climate fidelity cycle sequence, perform long-term transient coupling monitoring and tracking on the finite element mesh model, and obtain a decay process cloud map sequence. The design defect display module is used to use multiple expected performance cloud maps under various cyclic simulation conditions, refer to the climate fidelity cycle sequence to trace the alignment deviation of the degradation process cloud map sequence, obtain the distribution of fatigue vulnerable sites, and display the design defects in the building curtain wall twin model.

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