Mass concrete temperature control construction method and system based on phase change energy storage

Abstract

The invention discloses a mass concrete temperature control construction method and system based on phase change energy storage, and the method comprises the steps: S100, building a BIM model for a concrete member pouring region according to a design size, setting a temperature sensor in a concrete member to monitor data in real time, and predicting a temperature field in combination with the BIM model; s200, the space between the conventional cooling water pipe and the concrete protection layer is filled with phase change microcapsules in a gradient density mode, a phase change energy storage buffer layer is formed, and transfer of heat to the interior of the concrete member is delayed; s300, according to the predicted temperature field, the water inlet flow and the water temperature are dynamically adjusted, the temperature peak is controlled, and the cooling rate is controlled; s400, fiber grating sensors are arranged at the four corners and the midspan of the concrete member, and the strain change rate is detected; and S500, establishing a digital twin temperature control platform, integrating temperature, humidity and strain data, constructing a three-dimensional thermodynamic model, predicting the temperature rise trend of the concrete member, and performing adaptive regulation and control on the temperature. Temperature difference inside and outside the concrete is controlled through phase change temperature control.

Description

Technical Field

[0001] This invention belongs to the field of concrete construction technology, and more specifically, relates to a method and system for temperature control construction of large-volume concrete based on phase change energy storage. Background Technology

[0002] Mass concrete construction is a key technology in modern building engineering, primarily used in projects requiring extremely high structural integrity and durability, such as high-rise building foundations, large equipment foundations, hydraulic dams, and bridge piers. However, a core challenge in this construction is the temperature difference between the internal and external surfaces caused by the heat of cement hydration. The internal temperature of concrete can reach 60-65℃, while the surface dissipates heat more rapidly. If the temperature difference exceeds 25℃, the resulting thermal stress may exceed the tensile strength of the concrete, leading to through-cracks or surface cracks. This not only weakens the structure's waterproofing but may also threaten overall safety. Therefore, the core objective of mass concrete construction is to achieve structural integrity while suppressing crack formation through material selection, processing techniques, and temperature control measures.

[0003] There are three major problems in the construction of large-volume concrete: (1) The conventional cooling water pipe layout is simple. The cooling water pipe only conducts heat on the surface, which is inefficient and easily forms local low temperature zones. The concrete around the water pipe is prone to cracking. (2) Ordinary concrete has a large shrinkage rate, which generates tensile stress under constrained conditions. Excessive cement content aggravates temperature rise shrinkage. Ordinary concrete is not tough enough. Under temperature stress, cracks expand rapidly and it is difficult to achieve self-healing through aggregate interlocking. (3) Concrete temperature data depends on manual monitoring. It usually takes 3 to 5 hours from data recording, manual analysis and control instructions to issuance, which leads to serious delays in intervention measures. At the same time, there is a lack of synchronous monitoring of temperature-stress-humidity. Existing methods can only obtain a single temperature parameter and cannot provide early warning of stress over-limit risks.

[0004] Therefore, there is a need for a large-volume concrete temperature control construction method and system based on phase change energy storage to control the temperature difference between the inside and outside of the concrete and reduce the risk of temperature stress cracks. Summary of the Invention

[0005] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a method and system for temperature control construction of large-volume concrete based on phase change energy storage. By filling phase change microcapsules with a gradient density between conventional cooling water pipes and concrete, these microcapsules undergo a solid-liquid phase change during the peak hydration heat period, absorbing a large amount of heat and delaying heat transfer to the concrete interior. Through phase change temperature control, the temperature difference between the inside and outside of the concrete is controlled, reducing the risk of temperature stress cracking. Simultaneously, by optimizing the concrete mix design and employing intelligent temperature control, the peak concrete temperature is reduced compared to conventional concrete construction temperature control, keeping the temperature difference between the inside and outside of the concrete within specifications, reducing concrete shrinkage, and shortening the construction period.

[0006] To achieve the above objectives, according to a first aspect of the present invention, a method for temperature control construction of large-volume concrete based on phase change energy storage is provided, specifically including the following steps: S100. Establish a BIM model of the concrete component pouring area according to the design dimensions, set up temperature sensors in the concrete component to monitor data in real time, and predict the temperature field in combination with the BIM model. S200, between conventional cooling water pipes and concrete protective layer, phase change microcapsules are filled with gradient density to form a phase change energy storage buffer layer, which delays the transfer of heat to the interior of concrete components. S300: Based on the predicted temperature field, dynamically adjust the inlet water flow and water temperature to control the temperature peak and the cooling rate. S400: Fiber grating sensors are arranged at the four corners and mid-span of the concrete member to detect the strain rate of change. S500 establishes a digital twin temperature control platform, integrates temperature, humidity and strain data, constructs a three-dimensional thermodynamic model, predicts the temperature rise trend of concrete components, and adaptively regulates the temperature.

[0007] Furthermore, in step S100, the model needs to be built in conjunction with the on-site construction environment. Then, based on the BIM model, the location and timing of the maximum temperature rise point are predicted. This specifically includes the following steps: S101. Collect environmental parameters of the construction site, and record information on the construction area including geographical conditions, formwork type and insulation measures, and maintenance methods. Establish a site environmental database and conduct quantitative analysis. S102. Establish an accurate three-dimensional BIM model of the concrete component according to the design dimensions, and integrate the site environmental data, construction parameters, and concrete material properties into the model to ensure that the model contains multi-dimensional data including geometric information, physical properties, and environmental impact. S103. Import the geometric data and integrated information of the BIM model into the analysis software, set boundary conditions according to the site environment, and construct a temperature field analysis model associated with the BIM model. S104. Run the temperature field analysis model to simulate the temperature change process at different time points after concrete pouring, output the temperature field distribution data at each time point and connect the calculation results with the BIM model. S105. Through data interaction technology, the temperature field analysis results are mapped into the BIM model to realize the visualization of temperature distribution at different time points on the model and intuitively present the temperature change trend. S106. Based on visualized temperature field data, analyze the temperature peaks of each area in the BIM model, determine the location with the highest temperature, extract the temperature-time curve of that point, determine the specific time when the maximum temperature rise occurs through the peak value of the curve, and verify the rationality of the prediction results in combination with on-site environmental parameters.

[0008] Furthermore, in step S101, the environmental parameters include ambient temperature, humidity, wind speed, and solar radiation intensity. The geographical conditions of the construction area include its location at the foundation pit and the obstruction caused by surrounding buildings. In step S103, the boundary conditions include the ambient temperature change curve over time, the template heat transfer coefficient, and the solar radiation coefficient.

[0009] Furthermore, step S200 specifically includes the following steps: S201. Based on the design dimensions of the concrete components, the spacing of the cooling water pipes, and the thickness of the protective layer, determine the phase change temperature, particle size, and specific parameters for different density gradients of the phase change microcapsules. S202. Clean the surface of the cooling water pipes and the inside of the concrete protective layer of debris and dust to ensure that the contact surface is flat and clean. Check the installation position of the cooling water pipes and apply release agent to the inside of the protective layer formwork. S203. In the space between the cooling water pipe and the protective layer, according to the preset density gradient parameters, divide several filling areas parallel to the cooling water pipe, and use a marker pen or special separator strip to mark the partition boundaries on the inside of the template or the surface of the cooling water pipe. S204. Start filling from the first gradient zone near the cooling water pipe. Mix the phase change microcapsules of the corresponding density with the binder in proportion and stir evenly. Inject the mixture into the area. During the filling process, tap the template lightly or use a vibrating tool to ensure that the material is compacted until the first gradient zone is filled and the surface is smoothed. S205. Fill the subsequent gradient regions in the order of the marked partitions. After each gradient region is filled, check whether the connection with the previous gradient region is tight. S206. After all gradient zones are filled, cover the phase change energy storage buffer layer with a moisturizing film for curing. Control the temperature and humidity of the curing environment according to the characteristics of the adhesive to ensure that the material is fully cured and forms a structurally stable buffer layer. S207. After the buffer layer has cured, check its thickness and density in each gradient zone to ensure they meet the preset parameters. Simulate the ambient temperature change before concrete pouring, test the buffer layer's heat transfer blocking effect, and verify its compatibility with cooling water pipes and concrete protective layer.

[0010] Furthermore, after step S200 is completed, the concrete components should be poured in layers. Before pouring, the gel material needs to be pre-cooled and homogenized, specifically as follows: Cement is stored in warehouses 7 days in advance, with the temperature inside the warehouses kept constant at ≤25℃ to prevent moisture absorption and clumping, which would reduce its activity; fly ash is produced using an ultrafine grinding process. Coarse aggregates are cooled to a temperature of 3-7℃ by liquid nitrogen spraying; Fine aggregate is protected from the sun by building a canopy and sprayed with cold water until the temperature reaches 15℃; A water pressure test is also required for the cooling water pipes, and a flow meter is used to test the water flow rate of each circuit to ensure that the error with the design is within the allowable range.

[0011] Furthermore, step S300 specifically includes the following steps: S301. Import the temperature field data predicted by the BIM model into the dynamic control system, and set the temperature control threshold for each monitoring point in accordance with the concrete temperature control specifications to establish a data association model. S302. By using temperature sensors embedded in concrete components, the actual temperature data of each monitoring point is collected in real time and transmitted synchronously to the control system. The data is then compared in real time with the temperature field predicted by the BIM model to analyze the deviation between the actual temperature and the predicted value. S303. Based on the predicted initial temperature field distribution and the location of the cooling water pipes, set the initial inlet flow rate and water temperature of the cooling water pipes to ensure that the water flow evenly covers each area. S304. When the monitoring data shows that the temperature in a certain area is close to the preset temperature peak threshold, the system automatically analyzes the corresponding cooling water pipe section in that area, prioritizes increasing the inlet water flow rate of that section of water pipe, and at the same time reduces the inlet water temperature. S305. When the temperature at the monitoring point reaches its peak and begins to decrease, the system switches to the cooling rate control mode, calculates the cooling rate of each point in real time, and if the cooling rate exceeds the safety threshold, gradually reduces the inlet water flow of the cooling water pipe in the corresponding area or increases the inlet water temperature. S306. When multiple areas experience temperature anomalies simultaneously, the system optimizes the flow distribution of the cooling water pipe network through algorithms, prioritizing the cooling needs of high-risk areas, while fine-tuning the parameters of secondary areas through valves. S307. After each dynamic adjustment, continuously monitor the temperature change of the corresponding area to verify the effectiveness of the adjustment measures. If the effect does not meet expectations, re-analyze the cause of the temperature field deviation, correct the inlet water flow rate, water temperature parameters, or adjust the cooling strategy until the temperature control requirements are met. S308 records the inlet flow rate of the cooling water pipe, the water temperature adjustment curve, and the temperature change data of each monitoring point throughout the process, and forms a comparative report with the temperature field prediction results of the BIM model.

[0012] Furthermore, in step S301, historical engineering data is used to predict the critical temperature peak threshold for different regions through multi-feature nonlinear mapping, replacing the traditional empirical threshold, to obtain the temperature peak threshold, safe cooling rate threshold, and regional temperature difference threshold for each monitoring point.

[0013] Furthermore, in step S302, when the actual temperature data is collected, the nonlinear temperature field is processed by EKF. Specifically, the temperature change of concrete is affected by nonlinear factors such as heat of hydration and heat dissipation from the environment. EKF outputs high-precision real-time temperature by filtering the linearized state equation. Then, anomalies are detected through isolated forests. Specifically, for sensor malfunctions, the isolated forest algorithm is used to cluster the temperature series, identify outliers that deviate from the normal distribution, and mark them.

[0014] Furthermore, the specific steps include: S401. Select a fiber optic strain sensor with suitable range and accuracy, and establish a multi-dimensional calibration relationship of wavelength-strain-temperature in advance through a calibration bench. S402. Plan measurement points at the four corners and mid-span, use the BIM model for three-dimensional positioning, and output the coordinates and layout of the measurement points. S403. Grind and clean the marking mounting surface, then wipe it with anhydrous ethanol to remove oil and dust; S404. Lead the sensor out to the end of the component or the reserved detection port, connect it to the fiber optic patch cord, and mark the corresponding sensor number for the fiber optic channel. S405. Connect the fiber optic grating demodulator, set the demodulator parameters, apply simulated strain to each sensor, verify the correspondence between the sensor reflection wavelength change and the strain, and compare the calibration curves. S406. Assign dedicated personnel to monitor the sensor status. If sensor displacement or fiber breakage is found, stop pouring immediately and repair the damage. S407. During concrete curing and structural use, the sensor wavelength data is collected by a demodulator at the set sampling frequency, and the strain value is converted using the calibration relationship to calculate the strain change rate. S408: Real-time analysis of strain change rate. When it exceeds the warning threshold, an alarm is triggered. Combined with temperature field data, it distinguishes between temperature strain and load strain to help determine the stress state and cracking risk of concrete components.

[0015] According to a second aspect of the present invention, a large-volume concrete temperature control construction system based on phase change energy storage is provided, comprising: Preliminary prediction module: used to create a BIM model of the concrete component pouring area according to the design dimensions, set temperature sensors in the concrete component to monitor data in real time, and combine the BIM model to predict the temperature field; Phase change buffer module: used to fill phase change microcapsules with gradient density between conventional cooling water pipes and concrete protective layer to form a phase change energy storage buffer layer, delaying the transfer of heat to the interior of concrete components; Inlet water regulation module: used to dynamically adjust the inlet water flow and water temperature according to the predicted temperature field, control the temperature peak and control the cooling rate; Strain detection module: used to place fiber optic grating sensors at the four corners and mid-span of concrete members to detect the rate of strain change; Trend prediction module: Used to establish a digital twin temperature control platform, integrate temperature, humidity and strain data, construct a three-dimensional thermodynamic model, predict the temperature rise trend of concrete components, and adaptively regulate the temperature.

[0016] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: 1. The large-volume concrete temperature-controlled construction method of the present invention involves filling phase change microcapsules with a gradient density between conventional cooling water pipes and concrete. During the peak hydration heat period, the phase change microcapsules undergo a solid-liquid phase change, absorbing a large amount of heat and delaying heat transfer to the interior of the concrete. Through phase change temperature control, the temperature difference between the inside and outside of the concrete is controlled, reducing the risk of temperature stress cracking. Simultaneously, by optimizing the concrete mix design and using intelligent temperature control, the peak concrete temperature is reduced compared to conventional concrete construction temperature control, keeping the temperature difference between the inside and outside of the concrete within the specified requirements, reducing concrete shrinkage, and shortening the construction period.

[0017] 2. In the large-volume concrete temperature control construction method of the present invention, in step S100, modeling and prediction serve as the initial stage of basic prediction. Based on design parameters and historical data, the possible temperature change range of the concrete component is initially predicted, providing a basis for sensor deployment and the division of key monitoring areas. This is used as a basis to control the cooling parameters, with the final data results serving as a reference. In step S500, combining the data from the initial prediction and the data obtained after the initial prediction operation, based on multi-source real-time data integrated by the digital twin platform and combined with a three-dimensional thermodynamic model, the temperature rise trend is accurately predicted, providing decision support for adaptive temperature control. Dynamic optimization is achieved through real-time data feedback, forming a progressive relationship of "initial prediction—real-time correction—accurate prediction," jointly supporting the accuracy of the entire process of concrete component temperature control, thereby achieving better temperature control results.

[0018] 3. The large-volume concrete temperature control construction method of the present invention establishes a digital twin temperature control platform to achieve integrated automatic control, avoiding the problem of long manual monitoring and control command cycles, and simultaneously realizing synchronous monitoring of temperature, humidity and stress, improving the early warning of the risk of stress exceeding limits. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a method for temperature control construction of large-volume concrete based on phase change energy storage according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the cooling water pipe and the gradient filling of phase change microcapsules in a large-volume concrete temperature control construction method based on phase change energy storage according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the phase change microcapsule heat absorption buffer principle of a large-volume concrete temperature control construction method based on phase change energy storage according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the heat of hydration model of a concrete component in a large-volume concrete temperature control construction method based on phase change energy storage, according to an embodiment of the present invention. Figure 5 This is a schematic diagram of a digital twin temperature control platform for a large-volume concrete temperature control construction method based on phase change energy storage, according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0021] Example 1 like Figure 1-5 As shown, this embodiment of the invention provides a method for temperature control construction of large-volume concrete based on phase change energy storage, specifically including the following steps: S100. Establish a BIM model of the concrete component pouring area according to the design dimensions, set up temperature sensors in the concrete component to monitor data in real time, and predict the temperature field in combination with the BIM model. S200, between conventional cooling water pipes and concrete protective layer, phase change microcapsules are filled with gradient density to form a phase change energy storage buffer layer, which delays the transfer of heat to the interior of concrete components. S300: Based on the predicted temperature field, dynamically adjust the inlet water flow and water temperature to control the temperature peak and the cooling rate. S400: Fiber grating sensors are arranged at the four corners and mid-span of the concrete member to detect the strain rate of change. S500 establishes a digital twin temperature control platform, integrates temperature, humidity and strain data, constructs a three-dimensional thermodynamic model, predicts the temperature rise trend of concrete components, and adaptively regulates the temperature.

[0022] By filling phase change microcapsules with a gradient density between conventional cooling water pipes and concrete, the microcapsules undergo a solid-liquid phase change during the peak of hydration heat, absorbing a large amount of heat and delaying heat transfer to the interior of the concrete. Phase change temperature control manages the temperature difference between the inside and outside of the concrete, reducing the risk of temperature stress cracking. Simultaneously, by optimizing the concrete mix design and using intelligent temperature control, the peak concrete temperature is reduced compared to conventional construction methods, keeping the temperature difference between the inside and outside of the concrete within specifications, reducing concrete shrinkage, and shortening the construction period.

[0023] In step S100, the model needs to be built in conjunction with the on-site construction environment. Then, based on the BIM model, the location and timing of the maximum temperature rise point are predicted. This specifically includes the following steps: S101. Collect environmental parameters of the construction site, and record information on the construction area including geographical conditions, formwork type and insulation measures, and maintenance methods. Establish a site environmental database and conduct quantitative analysis. S102. Establish an accurate three-dimensional BIM model of the concrete component according to the design dimensions, and integrate the site environmental data, construction parameters, and concrete material properties into the model to ensure that the model contains multi-dimensional data including geometric information, physical properties, and environmental impact. S103. Import the geometric data and integrated information of the BIM model into the analysis software, set boundary conditions according to the site environment, and construct a temperature field analysis model associated with the BIM model. S104. Run the temperature field analysis model to simulate the temperature change process at different time points after concrete pouring, output the temperature field distribution data at each time point and connect the calculation results with the BIM model. S105. Through data interaction technology, the temperature field analysis results are mapped into the BIM model to realize the visualization of temperature distribution at different time points on the model and intuitively present the temperature change trend. S106. Based on visualized temperature field data, analyze the temperature peaks of each area in the BIM model, determine the location with the highest temperature, extract the temperature-time curve of that point, determine the specific time when the maximum temperature rise occurs through the peak value of the curve, and verify the rationality of the prediction results in combination with on-site environmental parameters.

[0024] In step S101, the environmental parameters include ambient temperature, humidity, wind speed, and solar radiation intensity. The geographical conditions of the construction area include its location at the foundation pit and the obstruction from surrounding buildings.

[0025] In step S103, the boundary conditions include the ambient temperature change curve over time, the template heat transfer coefficient, and the solar radiation coefficient.

[0026] Step S200 specifically includes the following steps: S201. Based on the design dimensions of the concrete components, the spacing of the cooling water pipes, and the thickness of the protective layer, determine the phase change temperature, particle size, and specific parameters for different density gradients of the phase change microcapsules. S202. Clean the surface of the cooling water pipes and the inside of the concrete protective layer of debris and dust to ensure that the contact surface is flat and clean. Check the installation position of the cooling water pipes and apply release agent to the inside of the protective layer formwork. S203. In the space between the cooling water pipe and the protective layer, according to the preset density gradient parameters, divide several filling areas parallel to the cooling water pipe, and use a marker pen or special separator strip to mark the partition boundaries on the inside of the template or the surface of the cooling water pipe. S204. Start filling from the first gradient zone near the cooling water pipe. Mix the phase change microcapsules of the corresponding density with the binder in proportion and stir evenly. Inject the mixture into the area. During the filling process, tap the template lightly or use a vibrating tool to ensure that the material is compacted until the first gradient zone is filled and the surface is smoothed. S205. Fill the subsequent gradient regions in the order of the marked partitions. After each gradient region is filled, check whether the connection with the previous gradient region is tight. S206. After all gradient zones are filled, cover the phase change energy storage buffer layer with a moisturizing film for curing. Control the temperature and humidity of the curing environment according to the characteristics of the adhesive to ensure that the material is fully cured and forms a structurally stable buffer layer. During the curing period, regularly check whether the buffer layer has cracks or hollows and repair them in time. S207. After the buffer layer has cured, check its thickness and density in each gradient zone to ensure they meet the preset parameters. Simulate the ambient temperature change before concrete pouring, test the buffer layer's heat transfer blocking effect, and verify its compatibility with cooling water pipes and concrete protective layer.

[0027] After step S200 is completed, the concrete components should be poured in layers. Before pouring, the gel material needs to be pre-cooled and homogenized. Specifically: cement should be stored in a warehouse 7 days in advance, with the temperature inside the warehouse controlled at ≤25℃ to avoid moisture absorption and clumping, which would reduce its activity; fly ash should be ground using an ultrafine grinding process; coarse aggregate should be cooled to 3-7℃ by liquid nitrogen spraying; fine aggregate should be protected from the sun by a canopy and sprayed with cold water to a temperature of 15℃. A water pressure test should also be conducted on the cooling water pipes, and the flow rate of each loop should be tested using a flow meter to ensure that the error with the design is within the allowable range.

[0028] Step S300 specifically includes the following steps: S301. Import the temperature field data predicted by the BIM model into the dynamic control system, and set the temperature control threshold for each monitoring point in accordance with the concrete temperature control specifications to establish a data association model. S302. By using temperature sensors embedded in concrete components, the actual temperature data of each monitoring point is collected in real time and transmitted synchronously to the control system. The data is then compared in real time with the temperature field predicted by the BIM model to analyze the deviation between the actual temperature and the predicted value. S303. Based on the predicted initial temperature field distribution and the location of the cooling water pipes, set the initial inlet flow rate and water temperature of the cooling water pipes to ensure that the water flow evenly covers each area. S304. When the monitoring data shows that the temperature in a certain area is close to the preset temperature peak threshold, the system automatically analyzes the corresponding cooling water pipe section in that area, prioritizes increasing the inlet water flow rate of that section of water pipe, and at the same time reduces the inlet water temperature. S305. When the temperature at the monitoring point reaches its peak and begins to decrease, the system switches to the cooling rate control mode, calculates the cooling rate of each point in real time, and if the cooling rate exceeds the safety threshold, gradually reduces the inlet water flow of the cooling water pipe in the corresponding area or increases the inlet water temperature. S306. When multiple areas experience temperature anomalies simultaneously, the system optimizes the flow distribution of the cooling water pipe network through algorithms, prioritizing the cooling needs of high-risk areas, while fine-tuning the parameters of secondary areas through valves. S307. After each dynamic adjustment, continuously monitor the temperature change of the corresponding area to verify the effectiveness of the adjustment measures. If the effect does not meet expectations, re-analyze the cause of the temperature field deviation, correct the inlet water flow rate, water temperature parameters, or adjust the cooling strategy until the temperature control requirements are met. S308 records the inlet flow rate of the cooling water pipe, the water temperature adjustment curve, and the temperature change data of each monitoring point throughout the process, and forms a comparative report with the temperature field prediction results of the BIM model.

[0029] In step S301, historical engineering data is used to predict the critical temperature peak threshold for different regions through multi-feature nonlinear mapping, replacing the traditional empirical threshold, and obtaining the temperature peak threshold, safe cooling rate threshold, and regional temperature difference threshold for each monitoring point.

[0030] In step S302, when the actual temperature data is collected, the nonlinear temperature field is processed using EKF. Specifically, concrete temperature changes are affected by nonlinear factors such as heat of hydration and environmental heat dissipation. EKF outputs high-precision real-time temperature through filtering of the linearized state equation. Then, anomalies are detected using isolated forest. Specifically, for sensor faults, the temperature sequence is clustered using the isolated forest algorithm to identify and mark outliers that deviate from the normal distribution. The state equation of EKF is: ; in, Let k be the temperature at time k. Let the flow rate be at time k-1. Water temperature The sampling interval is... This is process noise.

[0031] In step S303, the temperature field data predicted by the BIM model in step S301 is used as input. Combined with the spatial relationship between the cooling water pipes and the high-temperature zone, the initial flow rate and water temperature of each water pipe are calculated through a weighted and corrected Nusselt number model to ensure that the cooling intensity matches the regional heat load.

[0032] The heat that the k-th water pipe needs to remove is equal to the regional hydration heat power. Calculated according to the heat balance equation, specifically: ; in, Let be the heat exchange area of ​​the k-th water pipe. Let K be the core temperature of the region where the k-th water pipe is located. Let be the initial inlet water temperature of the k-th water pipe. Let k be the heat load coefficient of the area corresponding to the k-th water pipe. Let K be the temperature field volume of the area covered by the k-th water pipe. The convective heat transfer coefficient is... The initial hydration heat release rate per unit volume of concrete.

[0033] Based on the relationship between flow rate and flow velocity, the initial flow rate of the k-th water pipe is derived as follows: ; in, Let k be the length of the k-th water pipe. For Nusselt numbers, The thermal conductivity of water, This refers to the inner diameter of the water pipe.

[0034] The heat load coefficient of the area corresponding to the kth water pipe Specifically: ; in, The characteristic distance is half of the average spacing between water pipes. This represents the shortest distance between the k-th water pipe and the high-temperature core area. This is a distance decay factor; the closer to the core area, the higher the weight. For temperature gradient.

[0035] The temperature gradient for: ; in, The initial temperature of the region.

[0036] The shortest distance between the k-th water pipe and the high-temperature core area for: ; The Nusel The base Nusselt number is obtained by correcting it with a heat load correction term, specifically: ; in, Based on the Nusel number, This is the heat load correction factor.

[0037] The convective heat transfer coefficient for: ; This refers to the diameter of the cooling water pipe.

[0038] In step S304, the predicted temperature trajectory for the next 6-12 hours is used as a constraint. Rolling optimization is employed to calculate the flow rate and water temperature adjustment amounts for the current moment, ensuring that the temperature does not exceed the control threshold while avoiding over-adjustment. The objective function determines the control parameters, specifically: ; in, Adjust the weight for traffic. For initial traffic, The rate of heat release during hydration, and , The attenuation coefficient is... To predict the time domain, This is the peak temperature threshold.

[0039] In step S304, during the heating process, a double layer of geotextile is laid on the surface of the concrete component, and a high-pressure micro-mist device is used to spray it while keeping the covered surface free of standing water.

[0040] In step S305, during the cooling process, a curing agent is sprayed to form a film after the side membrane is removed, by storing water at a depth of more than 10 cm and the water level at the location is greater than 15℃.

[0041] Step S400 specifically includes the following steps: S401. Based on the size of the concrete component and the design strain range, select a fiber optic strain sensor with suitable range and accuracy, and establish a multi-dimensional calibration relationship of wavelength-strain-temperature in advance through a calibration bench. S402. Based on the structural type of the concrete component, plan the measuring points at the four corners and mid-span, use the BIM model for three-dimensional positioning, output the coordinates and layout of the measuring points, and mark the sensor number and installation direction with paint or labels at the corresponding positions of the formwork / reinforcing steel skeleton. S403. Before pouring concrete, grind and clean the marking installation surface, then wipe it with anhydrous ethanol to remove oil and dust, ensuring that the base layer is dry and clean, and then attach the fiber optic grating sensor to the marking position. S404. Lead the sensor out of the optical fiber and arrange it in an orderly manner along the surface of the component. Use cable trays and conduits for protection. Lead the optical fiber to the end of the component or reserve the detection port, connect it to the optical fiber jumper, protect the joint, and mark the corresponding sensor number of the optical fiber channel. S405. After the sensor is installed, connect the fiber optic grating demodulator, power it on, set the demodulator parameters, apply simulated strain to each sensor, verify the correspondence between the sensor's reflected wavelength change and the strain, and compare the calibration curves. S406. Assign a dedicated person to monitor the sensor status and avoid direct contact between the vibrator and the sensor and optical fiber. If sensor displacement or optical fiber breakage is found, stop pouring immediately and repair the damage. S407. During concrete curing and structural use, the sensor wavelength data is collected by a demodulator at the set sampling frequency, and the strain value is converted using the calibration relationship to calculate the strain change rate. S408: Real-time analysis of strain change rate. When it exceeds the warning threshold, an alarm is triggered. Combined with temperature field data, it distinguishes between temperature strain and load strain to help determine the stress state and cracking risk of concrete components.

[0042] Step S500 specifically includes the following steps: S501, connects to the real-time data streams of temperature, humidity and strain sensors, unifies the data format and sampling frequency, and imports BIM model geometric parameters, material properties and historical construction environment data; S502. Construct a high-precision geometric twin based on the BIM model, bind the spatial coordinates of monitoring points, overlay concrete thermodynamic parameters, environmental parameters and construction parameters, establish a dynamic mapping rule between the entity and the twin, and realize real-time data synchronization. S503. Construct a three-dimensional transient thermodynamic model, couple the heat of hydration heat generation rate with the environmental heat transfer term, correlate the strain-temperature model, and use the strain feedback as the boundary condition correction term of the thermodynamic model. S504: Integrate multi-source data, dynamically correct model parameters, establish an error feedback mechanism, and automatically trigger parameter recalibration when deviation exceeds the limit; S505. Based on the spatiotemporal attention mechanism LSTM model, the temperature rise trend is predicted, and the temperature cloud map, strain contour lines and humidity gradient field are displayed using three-dimensional visualization. S506 integrates multi-objective reinforcement learning algorithms to generate control strategies, realizing closed-loop control of control command issuance and execution result feedback.

[0043] Understandable, Example 2 This invention provides a large-volume concrete temperature control construction system based on phase change energy storage, specifically including: Preliminary prediction module: used to create a BIM model of the concrete component pouring area according to the design dimensions, set temperature sensors in the concrete component to monitor data in real time, and combine the BIM model to predict the temperature field; Phase change buffer module: used to fill phase change microcapsules with gradient density between conventional cooling water pipes and concrete protective layer to form a phase change energy storage buffer layer, delaying the transfer of heat to the interior of concrete components; Inlet water regulation module: used to dynamically adjust the inlet water flow and water temperature according to the predicted temperature field, control the temperature peak and control the cooling rate; Strain detection module: used to place fiber optic grating sensors at the four corners and mid-span of concrete members to detect the rate of strain change; Trend prediction module: Used to establish a digital twin temperature control platform, integrate temperature, humidity and strain data, construct a three-dimensional thermodynamic model, predict the temperature rise trend of concrete components, and adaptively regulate the temperature.

[0044] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A temperature control construction method for mass concrete based on phase change energy storage, characterized in that, Specifically comprising the following steps: S100, a BIM model is established for a concrete member pouring area according to a design size, a temperature sensor is arranged in the concrete member to monitor data in real time, and a temperature field is predicted in combination with the BIM model; S200, phase change microcapsules are filled between a conventional cooling water pipe and a concrete protective layer at a gradient density to form a phase change energy storage buffer layer to delay heat transfer to the inside of the concrete member; S300, the water inflow and water temperature are dynamically adjusted according to the predicted temperature field to control the temperature peak and the cooling rate; S400, fiber grating sensors are arranged at four corners and in the middle of the concrete member to detect a strain change rate; S500, a digital twin temperature control platform is established, data of temperature, humidity and strain are integrated, a three-dimensional thermodynamic model is constructed, a temperature rise trend of the concrete member is predicted, and the temperature is adaptively adjusted and controlled.

2. The temperature control construction method of phase change energy storage mass concrete according to claim 1, characterized in that, In step S100, the model needs to be established in combination with the construction site environment, and then the position of the maximum temperature rise point and the time of occurrence are predicted according to the BIM model, specifically comprising the following steps: S101, environmental parameters of the construction site are collected, information of the construction area including geographical conditions, template type and insulation measures, curing methods and the like is recorded, a site environment database is established and quantitative analysis is performed; S102, a precise three-dimensional BIM model of the concrete member is established according to the design size, the site environment data and construction parameters, and concrete material properties are integrated into the model to ensure that the model contains multi-dimensional data including geometric information and physical properties, environmental influences and the like; S103, the geometric data and integrated information of the BIM model are imported into an analysis software, boundary conditions are set according to the site environment, and a temperature field analysis model associated with the BIM model is constructed; S104, the temperature field analysis model is run, the temperature change process of the concrete after pouring at different time periods is simulated, temperature field distribution data at each time node are output, and the calculation results are data-connected with the BIM model; S105, the temperature field analysis results are mapped into the BIM model through data interaction technology, visual display of the temperature distribution at different time points on the model is realized, and the temperature change trend is intuitively presented; S106, based on the visual temperature field data, the temperature peak of each region in the BIM model is analyzed, the position of the highest temperature is determined, the temperature-time curve of the point is extracted, the specific time of the maximum temperature rise is determined through the peak value of the curve, and the rationality of the prediction result is verified in combination with the site environmental parameters.

3. The temperature control construction method of phase change energy storage mass concrete according to claim 2, characterized in that, In step S101, the environmental parameters include environmental temperature, humidity, wind speed and solar intensity; The geographical conditions of the construction area include the position in the foundation pit and the shielding condition of the surrounding buildings; In step S103, the boundary conditions include an environmental temperature curve changing with time, a template heat transfer coefficient and a solar radiation coefficient.

4. The temperature control construction method of phase change energy storage mass concrete according to claim 3, characterized in that, In step S200, specifically comprising the following steps: S201, the phase change temperature, particle size specification and specific parameters of different density gradients of the phase change microcapsules are determined according to the design size of the concrete member, the cooling water pipe arrangement interval and the protective layer thickness; S202, clean up the cooling water pipe surface and the inside of the concrete protective layer of sundries, floating dust, ensure the contact surface is smooth and clean, check the cooling water pipe installation position, and brush release agent on the inside of the protective layer formwork; S203, in the space between the cooling water pipe and the protective layer, according to the preset density gradient parameters, divide several filling areas parallel to the cooling water pipe, mark the partition boundaries on the inside of the formwork or the surface of the cooling water pipe using a marker pen or special partition strip; S204, start filling from the first gradient zone close to the cooling water pipe, mix the phase change microcapsules corresponding to the density with the binder in proportion, stir uniformly, inject the mixture into the area, tap the formwork or use a vibrating tool to ensure material compaction during the filling process, until the first gradient zone is filled and the surface is scraped flat; S205, according to the marked partition order, fill the subsequent gradient zones in turn, and check whether the connection with the last gradient zone is tight after completing the filling of each gradient zone; S206, after filling all the gradient zones, cover the moisture-proof film to maintain the phase change energy storage buffer layer, control the temperature and humidity of the maintenance environment according to the characteristics of the binder, and ensure that the material is fully cured to form a stable buffer layer structure; S207, after the buffer layer is cured, detect its thickness and the density of each gradient zone to reach the preset parameters, simulate the temperature change of the environment before concrete pouring, test the heat transfer resistance effect of the buffer layer, and verify its adaptability to the cooling water pipe and the concrete protective layer.

5. The temperature control construction method of phase change energy storage mass concrete according to claim 4, characterized in that, After step S200 is completed, the concrete member should also be poured in layers. Before pouring, the gel material needs to be pre-cooled and homogenized. Specifically: Cement is stored in the warehouse for 7 days in advance, and the temperature in the warehouse is controlled at ≤25℃ to avoid moisture absorption and clumping, which may cause activity decline; superfine grinding process is adopted for fly ash; Coarse aggregate is cooled to a temperature of 3-7℃ by liquid nitrogen spraying; Fine aggregate is shaded under a shed and sprayed with cold water to a temperature of 15℃; Water pressure test should also be conducted on the cooling water pipe, and flow meter is used to test the water flow of each circuit to ensure that the error is within the allowable range.

6. The phase change energy storage-based temperature control construction method for mass concrete according to claim 5, characterized in that, In step S300, the following steps are included: S301, import the temperature field data predicted by the BIM model into the dynamic control system, set the temperature control threshold of each monitoring point according to the concrete temperature control specification, and establish a data correlation model; S302, real-time collect the actual temperature data of each monitoring point through the temperature sensor embedded in the concrete member, and synchronously transmit the data to the control system for real-time comparison with the temperature field predicted by the BIM model, and analyze the deviation between the actual temperature and the predicted value; S303, according to the predicted initial temperature field distribution, set the initial water flow and water temperature of the cooling water pipe according to the arrangement position of the cooling water pipe to ensure that the water flow uniformly covers each area; S304, when the monitoring data shows that the temperature of a certain area approaches the preset temperature peak threshold, the system automatically analyzes the corresponding cooling water pipe section of the area, preferentially increases the water flow of the section, and at the same time, reduces the water temperature; S305、When the monitoring point temperature reaches the peak value and starts to decline, the system switches to the cooling rate control mode, and the cooling rate of each point is calculated in real time. If the cooling rate exceeds the safety threshold, gradually reduce the water inflow of the corresponding area cooling water pipe, or increase the water temperature; S306、When multiple areas have temperature abnormalities at the same time, the system optimizes the flow distribution of the cooling water pipe network through algorithms, prioritizes the cooling needs of high-risk areas, and adjusts the parameters of secondary areas through valve fine-tuning; S307、After each dynamic adjustment, the temperature change of the corresponding area is continuously monitored to verify the effectiveness of the adjustment measures. If the effect is not as expected, re-analyze the temperature field deviation reasons, modify the water inflow, water temperature parameters or adjust the cooling strategy until the temperature control requirements are met; S308、Record the water inflow and water temperature adjustment curve of the cooling water pipe throughout the process, as well as the temperature change data of each monitoring point, and compare the results with the temperature field prediction results of the BIM model to form a comparison report.

7. The phase change energy storage-based temperature control construction method for mass concrete according to claim 6, characterized in that, In step S301, historical engineering data is used to predict the critical temperature peak threshold of different areas through multi-feature nonlinear mapping, replacing the traditional empirical threshold, to obtain the temperature peak threshold, safe cooling rate threshold and regional temperature difference threshold of each monitoring point.

8. The phase change energy storage-based temperature control construction method for mass concrete according to claim 7, characterized in that, In step S302, when the actual temperature data is collected, the nonlinear temperature field is processed through EKF, specifically: the temperature change of concrete is affected by nonlinear factors such as hydration heat and environmental heat dissipation. EKF filters the linearized state equation to output high-precision real-time temperature; Then detect the anomaly through Isolation Forest, specifically: for sensor failure, cluster the temperature sequence through Isolation Forest algorithm, identify abnormal values deviating from normal distribution and mark.

9. A phase change material-based temperature control method for mass concrete construction according to any one of claims 6-8, characterized in that, Specifically includes the following steps: S401、Select a fiber Bragg grating strain sensor with appropriate range and accuracy, and establish a multi-dimensional calibration relationship between wavelength, strain and temperature in advance through a calibration table; S402、Plan the measurement points at the corners and across the middle, use the BIM model for three-dimensional positioning, and output the measurement point coordinates and layout diagram; S403、Grind and clean the marked installation surface, then wipe it with anhydrous ethanol to remove oil and dust; S404、Lead the sensor to the end of the component or the reserved detection port, connect it with the fiber jumper, and mark the corresponding sensor number on the fiber channel; S405、Connect the fiber Bragg grating demodulator, set the demodulator parameters, apply simulated strain to each sensor, verify the correspondence between the change of sensor reflected wavelength and strain, and compare the calibration curve; S406、Arrange a person to monitor the sensor state, if the sensor is found to be displaced or the fiber is broken, stop pouring in time and repair; S407、During concrete curing and structure use stage, collect sensor wavelength data through demodulator at set sampling frequency, convert strain value using calibration relationship, and calculate strain change rate; S408、Real-time analysis of strain change rate, when exceeding the warning threshold, trigger alarm, combined with temperature field data, distinguish temperature strain and load strain, assist to judge the stress state and cracking risk of concrete components.

10. A phase change energy storage based mass concrete temperature control construction system for implementing a phase change energy storage based mass concrete temperature control construction method according to any one of claims 1-9, characterized in that, Including: The preliminary prediction module is used to establish a BIM model according to the design size of the concrete member pouring area, set a temperature sensor in the concrete member to monitor real-time data, and predict a temperature field in combination with the BIM model; The phase change buffer module is used to fill phase change microcapsules with gradient density between the conventional cooling water pipe and the concrete protective layer, form a phase change energy storage buffer layer, and delay the heat transfer to the inside of the concrete member; The water inlet adjusting module is used to dynamically adjust the water inlet flow and water temperature according to the predicted temperature field, control the temperature peak and control the cooling rate; The strain detection module is used to arrange a fiber grating sensor at the four corners and the midspan of the concrete member to detect the strain change rate; The trend prediction module is used to establish a digital twin temperature control platform, integrate temperature, humidity and strain data, construct a three-dimensional thermodynamic model, predict the temperature rise trend of the concrete member, and adaptively control the temperature.

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