Green building life cycle assessment method and system based on pile foundation data

Abstract

This invention provides a green building life cycle assessment method and system based on pile foundation data. It acquires material and energy consumption data during the construction phase, including pile foundation data, and calculates the building's inherent environmental load by combining this data with an environmental impact factor database. During the service life, it collects pile foundation structural response monitoring data and uses a structure-foundation correlation model to invert and obtain the equivalent load time series of the superstructure reflecting the building's actual usage state. The equivalent load time series is input into a pile foundation performance degradation model to generate a maintenance plan and calculate the maintenance environmental load. Simultaneously, it identifies the building's actual usage mode and calibrates the building energy consumption model to calculate the operational environmental load. Based on the predicted state of the pile foundation performance degradation model at the end of the planned lifespan, it assesses the remaining bearing capacity of the pile foundation, formulates demolition, renovation, or reuse disposal strategies, and calculates the disposal environmental load. Finally, it summarizes the inherent, maintenance, operational, and disposal environmental loads to obtain the building's full life cycle environmental load assessment results.

Description

Technical Field

[0001] This application belongs to the field of assessment, and in particular relates to a method and system for green building life cycle assessment based on pile foundation data. Background Technology

[0002] The Life Cycle Assessment (LCA) method divides the building lifecycle into the gestation, operation, maintenance, and decommissioning phases, and conducts inventory analysis and impact assessment of material consumption, energy consumption, and emissions at each phase. However, during the operation and maintenance phases, environmental load calculations are based on assumptions or standardized building usage patterns, climate data, and maintenance plans from the planning phase. Operational energy consumption fluctuates due to actual occupancy rates and user behavior factors; structural maintenance needs are also related to the actual load history and environmental effects.

[0003] Calibrating LCA models using measured data, for example, by deploying energy monitoring systems within buildings to obtain real operational energy consumption data, or by using drones and sensor technologies for structural health monitoring to assist maintenance decisions, has failed to establish a correlation between the building structure and its environmental load throughout its entire life cycle. Pile foundations, as load-bearing components of a building, provide structural response data on stress and deformation during service, including information reflecting the building's actual usage status. However, existing LCA methods fail to utilize measured pile foundation data to invert superstructure loads, identify actual usage patterns, and, based on this, conduct a linked assessment of environmental loads during operation, maintenance, and decommissioning phases. This limits the practical utility of LCA in guiding sustainable building life cycle management. Summary of the Invention

[0004] This invention proposes a green building life cycle assessment method based on pile foundation data to address the problems of existing LCA methods failing to establish the correlation between the building entity and the environmental load throughout its entire life cycle, and failing to utilize measured pile foundation data to infer superstructure loads and identify actual usage patterns. The method includes:

[0005] Data on material and energy consumption during the construction phase, including pile foundations, are obtained and combined with an environmental impact factor database to calculate the building's inherent environmental load. During the building's service life, structural response monitoring data of the pile foundations are collected, and inversion analysis is performed using a structure-foundation correlation model to solve for the equivalent load time series of the superstructure that reflects the building's actual usage state.

[0006] The equivalent load time series of the superstructure is input into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan and calculate the corresponding maintenance environmental load; and, based on the equivalent load time series of the superstructure, the actual usage mode of the building is identified, and the building energy consumption model is calibrated according to the actual usage mode to calculate the operational environmental load.

[0007] Based on the predicted state of the pile foundation performance degradation model at the end of the planned life, assess the remaining bearing capacity of the pile foundation, determine the scrapping strategy for demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping.

[0008] By summarizing the environmental loads contained therein, the environmental loads of maintenance, the environmental loads of operation, and the environmental loads of decommissioning, the full life-cycle environmental load assessment results of the building are obtained.

[0009] Furthermore, this invention also relates to a green building life cycle assessment system based on pile foundation data, comprising the following modules:

[0010] The analysis module is used to acquire material and energy consumption data during the construction phase of a building, including pile foundations, and calculate the building's inherent environmental load by combining it with an environmental impact factor database. During the building's service life, it collects structural response monitoring data of the pile foundations and performs inversion analysis through a structure-foundation correlation model to solve for the equivalent load time series of the superstructure that reflects the building's actual usage state.

[0011] The first calculation module is used to input the equivalent load time series of the superstructure into the pile foundation performance degradation model, predict the performance evolution trend of the pile foundation, generate a maintenance plan and calculate the corresponding maintenance environmental load; and, based on the equivalent load time series of the superstructure, identify the actual usage mode of the building, calibrate the building energy consumption model according to the actual usage mode, and calculate the operational environmental load.

[0012] The second calculation module is used to assess the remaining bearing capacity of the pile foundation based on the predicted state of the pile foundation performance degradation model at the end of the planned life, determine the scrapping strategy of demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping.

[0013] The summary module is used to summarize the environmental loads contained therein, the environmental loads of maintenance, the environmental loads of operation, and the environmental loads of decommissioning, so as to obtain the environmental load assessment results of the building throughout its entire life cycle.

[0014] This invention obtains the equivalent load of the superstructure reflecting the actual usage state of a building through inversion analysis of pile foundation monitoring data. Based on the actual load data, it identifies the actual usage patterns of the building, calibrates the energy consumption model, and predicts the evolution trend of structural performance, thus making the environmental load calculations during the operation and maintenance phases closer to reality. Simultaneously, by assessing the actual remaining bearing capacity of the pile foundation at the end of the planned lifespan, it provides a scientific basis for decisions regarding the demolition, renovation, or reuse of the building. By establishing the correlation between the actual state of the structural entity and its environmental impact, the environmental load assessment results throughout the entire life cycle are made more reliable. Attached Figure Description

[0015] Figure 1 A flowchart of the first embodiment;

[0016] Figure 2 This is a schematic diagram of pile foundation performance degradation and maintenance planning based on a fatigue damage model.

[0017] Figure 3 A schematic diagram illustrating the load inversion results and building usage pattern identification;

[0018] Figure 4 A schematic diagram for assessing the environmental load composition of a building throughout its entire life cycle. Detailed Implementation

[0019] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0021] In the first embodiment, the present invention proposes a green building life cycle assessment method based on pile foundation data, such as... Figure 1 ,include:

[0022] S1. Obtain material and energy consumption data during the construction phase of the building, including the pile foundation, and calculate the environmental load inherent in the building by combining the environmental impact factor database; during the service life of the building, collect structural response monitoring data of the pile foundation, and perform inversion analysis through the structure-foundation correlation model to solve the equivalent load time series of the superstructure that reflects the actual use state of the building.

[0023] By extracting the bill of quantities for each component using Building Information Modeling (BIM), or by compiling the construction unit's material procurement records and on-site energy consumption ledgers, the specific quantities of steel, cement, and aggregate used during the construction phase, as well as the consumption of diesel and electricity, can be obtained. The China Life Cycle Database (CLCD) or the internationally recognized Ecoinvent database can be used to find the unit environmental impact factor for each material and energy source, such as the carbon emissions per unit weight of steel during production and transportation. The consumption of each material and energy source is multiplied by its corresponding environmental impact factor and summed to obtain the total environmental load.

[0024] During pile foundation construction, fiber Bragg grating (FBG) strain sensors are pre-embedded along the pile shaft, and strain data of the pile shaft is continuously collected at a frequency of, for example, once per hour after the building is put into use. Simultaneously, a three-dimensional finite element model is established, including the superstructure, pile foundation, and surrounding soil. Specifically, the structure-foundation correlation model includes the superstructure representing the building frame, the pile foundation transmitting loads, and the foundation soil bearing and reacting upon the pile foundation. The construction of this structure-foundation correlation model is preferably performed in three-dimensional finite element software. First, the geometric models of the superstructure, pile foundation, and foundation are established and discretized into finite element meshes. For example, the superstructure and pile foundation are often simplified to beam elements, and the foundation uses solid elements. Then, realistic material properties are assigned to each part, such as the elastoplasticity of concrete and the Mohr-Coulomb constitutive relation of the foundation soil. Furthermore, the contact and connection relationships between the parts and the boundary conditions of the model are defined, thereby obtaining a digital twin that reflects the actual stress state for forward analysis or inverse calculation.

[0025] The Kalman filter inversion algorithm is used to continuously adjust the load applied to the superstructure of the finite element model, taking the measured pile foundation strain time series as the target. When the error between the pile foundation strain calculated by the model and the measured strain is minimized, the applied load time series is the equivalent load time series of the superstructure obtained by inversion.

[0026] In an optional embodiment, the collection of structural response monitoring data of the pile foundation during the building's service life includes:

[0027] Fiber Bragg grating strain sensors are uniformly distributed and fixed along the circumferential direction at different depths in the pile foundation reinforcement cage, including the pile top, the middle of the pile body, and the pile bottom;

[0028] During the building's service life, the strain readings of each sensor are continuously acquired at a preset acquisition frequency using a fiber optic demodulator to obtain the time-series data of the pile's strain.

[0029] Specifically, taking a 30m long and 1.5m diameter bored pile as an example, fiber Bragg grating strain sensors are fixed along the main reinforcing bars during the fabrication of the reinforcing cage. To monitor the stress state of the pile, sensors are deployed at three depth sections: the top of the pile (0.5m below ground level), the middle of the pile (15m below ground level), and the bottom of the pile (29.5m below ground level). At each depth section, four sensors are evenly distributed around the circumference at 90° intervals, for a total of 12 sensors, thereby monitoring the axial and bending strain of the pile section.

[0030] After the building enters service, all fiber optic sensors are connected to a fiber optic demodulator. The acquisition frequency is set; for example, 1Hz can be used for office buildings primarily subjected to static loads. The demodulator continuously transmits broadband light into the fiber optic cable and monitors the center wavelength reflected back from each grating sensor in real time. When the pile body is subjected to stress and strain, the center wavelength of the grating will drift. The demodulator calculates the strain value at each measuring point in real time based on the wavelength drift and the pre-calibrated strain sensitivity coefficient of the sensor. These readings, along with timestamps, are continuously recorded to form a multi-channel pile body strain time-series database, for example, in the format of [timestamp, sensor number, strain value / microstrain].

[0031] In an optional embodiment, the step of performing inversion analysis through a structure-foundation correlation model to solve for the equivalent load sequence of the superstructure reflecting the actual usage state of the building includes:

[0032] A three-dimensional finite element model including the superstructure, pile foundation and ground is established. The superstructure and pile foundation are simulated using beam elements, and the ground is simulated using solid elements and the Mohr-Coulomb constitutive model.

[0033] Using the measured pile strain time series data as the inversion target, the Kalman filter algorithm is used to iteratively adjust the equivalent nodal load applied to the superstructure of the model until the root mean square error of the difference between the pile strain calculated by the model and the measured strain is less than a preset error threshold. The equivalent nodal load is then output as the equivalent load time series of the superstructure.

[0034] In the finite element method (FEM) software, a geometric model of the superstructure and pile foundation is established based on the planning drawings and simplified into a skeleton composed of beam elements to improve computational efficiency. A model of the foundation soil within a certain range around the piles is created, for example, a cubic region with dimensions of 100m x ...

[0035] The measured pile strain time series data, such as the strain readings of all 12 sensors at 10:00 AM on a certain day, is used as the inversion target for that moment. The Kalman filter algorithm takes the equivalent load applied to the column base nodes of the superstructure as the state variable to be estimated. At the beginning of the algorithm, an initial load guess is given and applied to the model to calculate the strain at the corresponding location of the pile. The difference between the calculated strain and the measured strain, i.e., the residual, is fed back to the Kalman filter. The filter updates the estimate of the nodal load based on the internal state transition matrix and observation matrix, generating a new set of load values. This prediction-update iterative process is repeated until the root mean square error between the pile strain calculated by the model and the measured strain is less than a preset threshold, such as 5 micro-strains. The nodal load obtained at this time is regarded as the true equivalent load at that moment. This process is repeated for the data at each time point to obtain the complete equivalent load time series of the superstructure.

[0036] S2, The equivalent load time series of the superstructure is input into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan and calculate the corresponding maintenance environmental load; and, based on the equivalent load time series of the superstructure, the actual usage mode of the building is identified, and the building energy consumption model is calibrated according to the actual usage mode to calculate the operational environmental load.

[0037] For maintenance loads, a pile foundation performance degradation model based on load cycles and soil corrosion is established. This model predicts the gradual decline in pile foundation bearing capacity over time. Specifically, it includes a load processing module to transform continuously changing load history into a series of statistically significant damage events; a damage accumulation module to calculate and accumulate the minute damage caused by each damage event based on material fatigue or aging patterns; and a performance mapping module to establish a correlation between the abstract cumulative damage degree and specific physical performance indicators such as bearing area and remaining bearing capacity. The amplitude and number of cyclic loads are extracted from the input load time series data using methods such as rainflow counting. Based on Palmgern-Miner linear cumulative damage theory and combined with the material's SN curve, the cumulative damage index under load cycles is calculated. A functional relationship is established between the damage index and the attenuation of bearing area or reduction in bearing capacity at the critical section of the pile foundation, thereby outputting a predicted performance state curve for the pile foundation at any future time.

[0038] Using the inverted load time series as input, the curve of pile foundation bearing capacity decreasing over time is predicted. A maintenance threshold is set, for example, when the predicted bearing capacity decreases to 1.2 times the planned value, a maintenance event for high-pressure grouting reinforcement is generated. Based on the grout and equipment energy consumption required for grouting reinforcement, the environmental load of this maintenance is calculated by querying the environmental impact factor database. For the operational load, Fourier transform is used to analyze the periodicity of the load time series, identifying the office building usage pattern of high load during weekdays and low load at night and on weekends. This identified actual personnel activity schedule is used to replace the original standardized settings in the building energy consumption simulation software Energy Plus. The calibrated model is run to obtain the annual average heating and cooling energy consumption data, which is then multiplied by the environmental impact factor per unit energy consumption to calculate the operational environmental load.

[0039] In an optional embodiment, the step of inputting the equivalent load time series of the superstructure into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation includes:

[0040] Rainflow counting is performed on the equivalent load sequence of the superstructure to extract the amplitude and number of load cycles;

[0041] Calculate the cumulative damage D(t):

[0042]

[0043] in, The stress amplitude within time t is The number of load cycles, To the stress amplitude The number of cycles required for the material to reach fatigue failure;

[0044] Calculate the bearing area of ​​the critical section of the pile foundation based on the cumulative damage degree. The decay curve over time is used as the performance evolution trend, and the calculation formula is as follows:

[0045]

[0046] in This represents the initial bearing area.

[0047] Specifically, the equivalent load time series of the superstructure obtained from the above inversion is transformed into the stress time series of the critical section of the pile foundation, usually the pile top section, through a finite element model. Rainflow counting is then applied to this stress time series data. This method can decompose irregular stress fluctuations into a series of complete loading-unloading cycles. For example, after processing one week's stress data, the output is a list containing the number of cycles for different stress amplitude ranges, such as 1200 cycles for a stress amplitude of 5 MPa and 350 cycles for a stress amplitude of 8 MPa.

[0048] Establish the SN curve for concrete materials, i.e., the stress amplitude-fatigue life curve, which represents the number of cycles N required for the material to undergo fatigue failure under a constant stress amplitude S. For each stress amplitude obtained from rainflow counting... The loop occurs the number of times. The corresponding fatigue life was found using the SN curve. According to the Palmgren-Miner linear cumulative damage theory, the total cumulative damage D(t) within time t is the sum of damage caused by all stress amplitude levels. The cumulative damage is then correlated with the physical performance indicators of the pile foundation. Assume the initial bearing area of ​​the pile foundation is... For example, 0.785 square meters, then the bearing area at time t is... The calculation is performed using a formula. By calculating the cumulative damage and bearing area at different time points, such as 1 year, 5 years, and 10 years, a curve showing the area decaying over time can be plotted, which represents the performance evolution trend of the pile foundation.

[0049] In an optional embodiment, the step of inputting the equivalent load time series of the superstructure into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan, and calculate the corresponding maintenance environmental load includes:

[0050] Based on the bearing area decay curve, which represents the performance evolution trend, the evolution trend of the remaining bearing capacity of the pile foundation is calculated.

[0051] Set a maintenance threshold for pile foundation performance, that is, when the predicted remaining bearing capacity of the pile foundation decreases to a first preset proportion of the planned bearing capacity, maintenance is triggered.

[0052] When the evolution trend of the remaining bearing capacity reaches the threshold, a pile foundation reinforcement and maintenance event is generated;

[0053] The reinforcement and maintenance adopts the pressure grouting method. The environmental load of maintenance is calculated by multiplying the amount of materials required for reinforcement and the energy consumption of equipment operation by the corresponding environmental impact factor.

[0054] The bearing area attenuation curve This is transformed into the remaining bearing capacity evolution trend P(t). Bearing capacity is proportional to area; therefore, the remaining bearing capacity P(t) equals the initial design bearing capacity. Multiply by the area attenuation ratio. For example, if the initial planned bearing capacity is 8000 kN, then Set a performance maintenance threshold, for example, set the first preset ratio to 85%, that is, when the remaining bearing capacity of the pile foundation drops to 85% of the initial planned bearing capacity, i.e. 6800 kN, maintenance is required.

[0055] Based on the residual bearing capacity evolution trend curve P(t), the timing of the maintenance threshold of 6800 kN is predicted. For example, the model predicts that this condition will be triggered in the 32nd year of the building's service life. Therefore, a maintenance event is generated in the maintenance plan, namely, pile reinforcement in the 32nd year. The reinforcement method is pressure grouting, requiring an estimation of resource consumption. It is assumed that reinforcing one pile requires 800 kg of cement-based grout and 150 kWh of electricity to drive the grouting pump and mixer. Environmental impact factors for each consumption are obtained from an environmental database, such as the environmental load of 0.8 kg CO2 equivalent per kg of cement and 0.5 kg CO2 equivalent per kWh of electricity. The environmental load for this maintenance is calculated as the sum of material load and energy load, i.e., 715 kg CO2 equivalent. Figure 2 .

[0056] In an optional embodiment, identifying the actual usage pattern of the building based on the equivalent load sequence of the superstructure includes:

[0057] The equivalent load sequence of the superstructure is segmented according to a preset time period. The K-means clustering algorithm is applied to the load data of each period to divide the load data into a predetermined number of cluster centers, which are defined as different usage patterns, thereby identifying the actual usage pattern sequence of the building.

[0058] Specifically, the continuous equivalent load time series of the superstructure is segmented by day, forming several data segments with a 24-hour period. For each day's data segment, numerical features that represent the load characteristics are extracted to form a feature vector. For example, four features can be extracted: daily average load value, daily peak load value, peak load occurrence time, and daily total load impulse. The load data for one year is then converted into a set of 365 four-dimensional feature vectors.

[0059] Using the feature vectors of all days as input, the K-means clustering algorithm is applied. The number of clusters, K, is preset; for example, for an office building, K=3, aiming to identify three patterns: weekdays, weekends, and special event days. The 365 data points are iteratively divided into three clusters, and the center point of each cluster, i.e., the cluster center, is found. The feature values ​​of the three cluster centers are analyzed; for example, one center exhibits a high mean, high peak value with the peak occurring in the afternoon; another center exhibits a low mean and low peak value; and the third falls between the two. Based on this, the three cluster centers can be defined as the special event day pattern, the weekend and holiday pattern, and the regular weekday pattern, respectively. Each day is then assigned to its corresponding cluster, generating an annual sequence of actual usage patterns, such as [regular weekday, regular weekday, ..., weekend, weekend, ..., special event day], etc. Figure 3 .

[0060] In an optional embodiment, calibrating the building energy consumption model based on the actual usage pattern and calculating the operational environmental load includes:

[0061] Replace the default personnel, lighting, and equipment schedules of the building energy consumption model with schedule parameters corresponding to the identified different usage patterns, and rerun the energy consumption simulation to obtain the calibrated operating environment load.

[0062] A baseline model is established in building energy consumption simulation software, incorporating information on building geometry, building envelope, and HVAC system. This model typically uses a standard operating schedule, for example, a full-capacity schedule from 9 am to 5 pm Monday to Friday, with no staff on weekends. The identified actual usage patterns are then mapped to specific operating schedule parameters. For example, a regular weekday pattern corresponds to a schedule with 90% staff density, 80% lighting power, and 75% equipment power; a weekend and holiday pattern corresponds to a schedule with 5% staff density, 10% lighting power, and 10% equipment power; and a special event day pattern corresponds to a schedule with 120% staff density, 100% lighting and equipment power, and extended operation until 10 pm.

[0063] The generated sequence of actual usage patterns, such as a one-year sequence, is used as input. Before the energy consumption simulation begins, a control script or program retrieves the corresponding schedule from a preset schedule library based on the day's usage patterns, replacing the default schedule in the model. For example, if the simulation shows a special event day in the pattern sequence, the personnel, lighting, and equipment schedules for that day in the model will all be switched to the parameters corresponding to the special event day. The schedule is replaced day by day in this manner to complete the one-year simulation. The simulation output, such as hourly electricity consumption and gas consumption, will reflect the building's actual operating energy consumption. Multiplying the energy consumption data by the corresponding carbon emission factor yields the calibrated operating environmental load.

[0064] S3. Based on the predicted state of the pile foundation performance degradation model at the end of the planned life, assess the remaining bearing capacity of the pile foundation, determine the scrapping strategy for demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping.

[0065] Extending the time axis of the pile foundation performance degradation model to the end of the building's planned life, such as year 50, yields the predicted remaining bearing capacity of the pile foundation at that time. If the remaining bearing capacity is significantly lower than the safety standard, a complete demolition strategy is developed, calculating the fuel consumption of demolition machinery, and the environmental loads generated by waste transportation and landfill. If the remaining bearing capacity is still acceptable, a modification strategy is developed, such as converting the superstructure to a lower-load application, and calculating the material and energy consumption loads during the modification process. If the remaining bearing capacity is still high, a pile foundation reuse strategy is developed, where the scrapping load is reflected as the environmental benefits of avoiding the construction of a new foundation, i.e., a negative value.

[0066] In an optional embodiment, the step of assessing the remaining bearing capacity of the pile foundation based on the predicted state of the pile foundation performance degradation model at the end of its planned life, and determining a scrapping strategy for the entire building to be demolished, renovated, or reused based on the remaining bearing capacity, includes:

[0067] The remaining bearing capacity of the pile foundation is calculated based on the bearing area predicted by the pile foundation performance degradation model at the end of the planned life.

[0068] If the remaining carrying capacity is greater than the first threshold ratio of the initial planned carrying capacity, then the strategy of "structural preservation and functional reuse" will be adopted.

[0069] If the remaining bearing capacity is between the second threshold ratio and the first threshold ratio of the initial planned bearing capacity, then the strategy of "structural reinforcement and upgrading" will be adopted.

[0070] If the remaining carrying capacity is lower than the second threshold ratio of the initial planned carrying capacity, the "overall demolition" strategy will be adopted.

[0071] Specifically, using an established pile foundation performance degradation model, the time parameter is set to the planned lifespan of the building, for example, 50 years. The model will output the predicted cumulative damage degree D(50) of the pile foundation at year 50, and calculate the bearing area at that time accordingly. The remaining load-bearing capacity is calculated based on the ratio of the load-bearing area to the initial area. For example, if the predicted carrying capacity in 50 years is 82% of the initial area, then the remaining carrying capacity is the initial planned carrying capacity. 82%.

[0072] Two decision threshold ratios are pre-set; for example, the first threshold ratio is set to 80%, and the second threshold ratio is set to 60%. The calculated remaining load-bearing capacity ratio is compared with these two thresholds. In this example, the predicted remaining load-bearing capacity is 82%, which is greater than the first threshold of 80%. According to the decision rule, when the remaining load-bearing capacity is greater than the first threshold ratio, it indicates that the structural foundation is in good health and has great reuse potential; therefore, a scrapping strategy is adopted to preserve the structure and reuse its function. If the predicted result is 70%, between 60% and 80%, the strategy is structural reinforcement and upgrading. If the predicted result is 55%, below the second threshold of 60%, the strategy is complete demolition.

[0073] S4. Summarize the environmental loads, maintenance environmental loads, operational environmental loads, and decommissioning environmental loads to obtain the full life cycle environmental load assessment results of the building.

[0074] The environmental loads calculated above, the sum of the environmental loads from all maintenance events and operational activities throughout the building's service life, and the determined environmental loads at the end of the building's lifespan are categorized and added together according to different environmental impact categories of Global Warming Potential (GWP) and Acidification Potential (AP). This yields a set of quantified indicators, such as the total carbon emissions over the building's entire lifespan in tons of CO2 equivalent. This set of data constitutes the assessment result of the building's life-cycle environmental load. Figure 4 This invention is particularly suitable for high-rise buildings that are sensitive to wind loads, or industrial green buildings that contain power equipment.

[0075] In the second embodiment, the present invention also proposes a green building life cycle assessment system based on pile foundation data, comprising the following modules:

[0076] The analysis module is used to acquire material and energy consumption data during the construction phase of a building, including pile foundations, and calculate the building's inherent environmental load by combining it with an environmental impact factor database. During the building's service life, it collects structural response monitoring data of the pile foundations and performs inversion analysis through a structure-foundation correlation model to solve for the equivalent load time series of the superstructure that reflects the building's actual usage state.

[0077] The first calculation module is used to input the equivalent load time series of the superstructure into the pile foundation performance degradation model, predict the performance evolution trend of the pile foundation, generate a maintenance plan and calculate the corresponding maintenance environmental load; and, based on the equivalent load time series of the superstructure, identify the actual usage mode of the building, calibrate the building energy consumption model according to the actual usage mode, and calculate the operational environmental load.

[0078] The second calculation module is used to assess the remaining bearing capacity of the pile foundation based on the predicted state of the pile foundation performance degradation model at the end of the planned life, determine the scrapping strategy of demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping.

[0079] The summary module is used to summarize the environmental loads contained therein, the environmental loads of maintenance, the environmental loads of operation, and the environmental loads of decommissioning, so as to obtain the environmental load assessment results of the building throughout its entire life cycle.

[0080] In an optional embodiment, the collection of structural response monitoring data of the pile foundation during the building's service life includes:

[0081] Fiber Bragg grating strain sensors are uniformly distributed and fixed along the circumferential direction at different depths in the pile foundation reinforcement cage, including the pile top, the middle of the pile body, and the pile bottom;

[0082] During the building's service life, the strain readings of each sensor are continuously acquired at a preset acquisition frequency using a fiber optic demodulator to obtain the time-series data of the pile's strain.

[0083] In an optional embodiment, the step of performing inversion analysis through a structure-foundation correlation model to solve for the equivalent load sequence of the superstructure reflecting the actual usage state of the building includes:

[0084] A three-dimensional finite element model including the superstructure, pile foundation and ground is established. The superstructure and pile foundation are simulated using beam elements, and the ground is simulated using solid elements and the Mohr-Coulomb constitutive model.

[0085] Using the measured pile strain time series data as the inversion target, the Kalman filter algorithm is used to iteratively adjust the equivalent nodal load applied to the superstructure of the model until the root mean square error of the difference between the pile strain calculated by the model and the measured strain is less than a preset error threshold. The equivalent nodal load is then output as the equivalent load time series of the superstructure.

[0086] In an optional embodiment, the step of inputting the equivalent load time series of the superstructure into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation includes:

[0087] Rainflow counting is performed on the equivalent load sequence of the superstructure to extract the amplitude and number of load cycles;

[0088] Calculate the cumulative damage D(t):

[0089]

[0090] in, The stress amplitude within time t is The number of load cycles, To the stress amplitude The number of cycles required for the material to reach fatigue failure;

[0091] Calculate the bearing area of ​​the critical section of the pile foundation based on the cumulative damage degree. The decay curve over time is used as the performance evolution trend, and the calculation formula is as follows:

[0092]

[0093] in This represents the initial bearing area.

[0094] In an optional embodiment, the step of inputting the equivalent load time series of the superstructure into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan, and calculate the corresponding maintenance environmental load includes:

[0095] Based on the bearing area decay curve, which represents the performance evolution trend, the evolution trend of the remaining bearing capacity of the pile foundation is calculated.

[0096] Set a maintenance threshold for pile foundation performance, that is, when the predicted remaining bearing capacity of the pile foundation decreases to a first preset proportion of the planned bearing capacity, maintenance is triggered.

[0097] When the evolution trend of the remaining bearing capacity reaches the threshold, a pile foundation reinforcement and maintenance event is generated;

[0098] The reinforcement and maintenance adopts the pressure grouting method. The environmental load of maintenance is calculated by multiplying the amount of materials required for reinforcement and the energy consumption of equipment operation by the corresponding environmental impact factor.

[0099] In an optional embodiment, identifying the actual usage pattern of the building based on the equivalent load sequence of the superstructure includes:

[0100] The equivalent load sequence of the superstructure is segmented according to a preset time period. The K-means clustering algorithm is applied to the load data of each period to divide the load data into a predetermined number of cluster centers, which are defined as different usage patterns, thereby identifying the actual usage pattern sequence of the building.

[0101] In an optional embodiment, calibrating the building energy consumption model based on the actual usage pattern and calculating the operational environmental load includes:

[0102] Replace the default personnel, lighting, and equipment schedules of the building energy consumption model with schedule parameters corresponding to the identified different usage patterns, and rerun the energy consumption simulation to obtain the calibrated operating environment load.

[0103] In an optional embodiment, the step of assessing the remaining bearing capacity of the pile foundation based on the predicted state of the pile foundation performance degradation model at the end of its planned life, and determining a scrapping strategy for the entire building to be demolished, renovated, or reused based on the remaining bearing capacity, includes:

[0104] The remaining bearing capacity of the pile foundation is calculated based on the bearing area predicted by the pile foundation performance degradation model at the end of the planned life.

[0105] If the remaining carrying capacity is greater than the first threshold ratio of the initial planned carrying capacity, then the strategy of "structural preservation and functional reuse" will be adopted.

[0106] If the remaining bearing capacity is between the second threshold ratio and the first threshold ratio of the initial planned bearing capacity, then the strategy of "structural reinforcement and upgrading" will be adopted.

[0107] If the remaining carrying capacity is lower than the second threshold ratio of the initial planned carrying capacity, the "overall demolition" strategy will be adopted.

[0108] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0109] The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0110] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0111] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0112] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A green building life cycle assessment method based on pile foundation data, characterized in that, include: Obtain material and energy consumption data during the building construction phase, including pile foundations, and combine this data with an environmental impact factor database to calculate the building's inherent environmental load. During the building's service life, structural response monitoring data of the pile foundation is collected, and inversion analysis is performed through the structure-foundation correlation model to solve the equivalent load time series of the superstructure that reflects the actual use state of the building. The equivalent load time series of the superstructure is input into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan and calculate the corresponding maintenance environmental load; The actual usage patterns of a building are identified based on the time sequence of equivalent loads on the superstructure, and the building energy consumption model is calibrated according to the actual usage patterns to calculate the operational environmental load. Based on the predicted state of the pile foundation at the end of its planned life according to the pile foundation performance degradation model, assess the remaining bearing capacity of the pile foundation, determine the scrapping strategy of demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping. By summarizing the environmental loads contained in the building, the environmental loads during maintenance, the environmental loads during operation, and the environmental loads at the end of life, the environmental load assessment results of the building's entire life cycle are obtained; The equivalent load time series of the superstructure is input into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, including: counting rainflows on the equivalent load time series of the superstructure and extracting the amplitude and number of load cycles; calculating the cumulative damage degree D(t). ;in, Let the stress amplitude be S within time t. i The number of load cycles, N i For stress amplitude S i The number of cycles required for the material to reach fatigue failure; the bearing area A of the critical section of the pile foundation is calculated based on the cumulative damage degree. eff (t) Evolutionary trend, calculated using the following formula: Where A0 is the initial bearing area; The equivalent load sequence of the superstructure is input into the pile foundation performance degradation model to predict the performance evolution trend of the pile foundation, generate a maintenance plan, and calculate the corresponding maintenance environmental load. This includes: calculating the residual bearing capacity evolution trend of the pile foundation based on the bearing area decay curve, which serves as the performance evolution trend; setting a pile foundation performance maintenance threshold, i.e., triggering maintenance when the predicted residual bearing capacity of the pile foundation decreases to a first preset proportion of the planned bearing capacity; generating a pile foundation reinforcement and maintenance event when the residual bearing capacity evolution trend reaches the threshold; the reinforcement and maintenance adopts the pressure grouting method, and the maintenance environmental load is calculated by multiplying the amount of materials required for reinforcement and the energy consumption of equipment operation by the corresponding environmental impact factor. Identifying the actual usage patterns of a building based on the equivalent load time sequence of the superstructure includes: segmenting the equivalent load time sequence of the superstructure into preset time periods; applying the K-means clustering algorithm to the load data of each period to divide the load data into a predetermined number of cluster centers, and defining each cluster as a different usage pattern, thereby identifying the actual usage pattern sequence of the building; calibrating the building energy consumption model according to the actual usage patterns and calculating the operational environmental load, including: replacing the default personnel, lighting, and equipment schedules of the building energy consumption model with schedule parameters corresponding to the identified different usage patterns, rerunning the energy consumption simulation, and obtaining the calibrated operational environmental load.

2. The method according to claim 1, characterized in that, During the building's service life, structural response monitoring data of the pile foundation is collected, including: fiber Bragg grating strain sensors are uniformly distributed and fixed along the circumference at different depths in the pile foundation's reinforcement cage, including the pile top, the middle of the pile body, and the pile bottom; during the building's service life, the strain readings of each sensor are continuously acquired at a preset acquisition frequency using a fiber optic demodulator to obtain the time-series data of the pile body strain.

3. The method according to claim 1, characterized in that, Inversion analysis using a structure-foundation correlation model is performed to solve for the equivalent load time series of the superstructure reflecting the actual usage state of the building. This includes: establishing a three-dimensional finite element model containing the superstructure, pile foundation, and foundation, where the superstructure and pile foundation are simulated using beam elements, and the foundation is simulated using solid elements and a Mohr-Coulomb constitutive model; using the measured pile strain time series data as the inversion target, the Kalman filter algorithm is used to iteratively adjust the equivalent nodal loads applied to the superstructure of the model until the root mean square error of the difference between the calculated pile strain and the measured strain is less than a preset error threshold, and the equivalent nodal loads are output as the equivalent load time series of the superstructure.

4. The method according to claim 1, characterized in that, Based on the predicted state of the pile foundation performance degradation model at the end of the planned life, the remaining bearing capacity of the pile foundation is assessed. Based on the remaining bearing capacity, a scrapping strategy for the entire building—demolition, renovation, or reuse—is determined, including: calculating the remaining bearing capacity of the pile foundation based on the bearing area predicted by the pile foundation performance degradation model at the end of the planned life; if the remaining bearing capacity is greater than a first threshold ratio of the initial planned bearing capacity, a "structural preservation, functional reuse" strategy is adopted; if the remaining bearing capacity is between a second threshold ratio and a first threshold ratio of the initial planned bearing capacity, a "structural reinforcement, upgrading and renovation" strategy is adopted; if the remaining bearing capacity is lower than a second threshold ratio of the initial planned bearing capacity, a "complete demolition" strategy is adopted.

5. A green building life cycle assessment system based on pile foundation data, applied to the method described in any one of claims 1-4, characterized in that, Includes the following modules: The analysis module is used to acquire material and energy consumption data during the building construction phase, including pile foundations, and to calculate the building's inherent environmental load by combining it with an environmental impact factor database. During the building's service life, structural response monitoring data of the pile foundation is collected, and inversion analysis is performed through the structure-foundation correlation model to solve the equivalent load time series of the superstructure that reflects the actual use state of the building. The first calculation module is used to input the equivalent load time series of the superstructure into the pile foundation performance degradation model, predict the performance evolution trend of the pile foundation, generate a maintenance plan, and calculate the corresponding maintenance environmental load. Furthermore, the actual usage patterns of the building are identified based on the time sequence of the equivalent load of the superstructure, and the building energy consumption model is calibrated according to the actual usage patterns to calculate the operating environment load. The second calculation module is used to assess the remaining bearing capacity of the pile foundation based on the predicted state of the pile foundation performance degradation model at the end of the planned life, determine the scrapping strategy of demolishing, renovating or reusing the entire building based on the remaining bearing capacity, and calculate the environmental load of scrapping. The summary module is used to summarize the environmental loads contained in the building, the environmental loads of maintenance, the environmental loads of operation, and the environmental loads of decommissioning, so as to obtain the environmental load assessment results of the building's entire life cycle.

6. The system according to claim 5, characterized in that, During the building's service life, structural response monitoring data of the pile foundation is collected, including: fiber Bragg grating strain sensors are uniformly distributed and fixed along the circumference at different depths in the pile foundation's reinforcement cage, including the pile top, the middle of the pile body, and the pile bottom; during the building's service life, the strain readings of each sensor are continuously acquired at a preset acquisition frequency using a fiber optic demodulator to obtain the time-series data of the pile body strain.

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