Massive concrete construction temperature control and crack prevention integrated system and method

Abstract

The application discloses a mass concrete construction temperature control and crack prevention integrated system and method, which comprises a construction module, a monitoring module, a comparison module and an execution module.The construction module is used for constructing a cooling water pipe fine model based on concrete thermodynamic parameters and construction conditions, solving a heat flow coupling control equation through a heat flow coupling algorithm, and determining a concrete internal temperature field and stress field distribution cloud picture.The monitoring module is used for collecting attribute data of the concrete.The comparison module is used for comparing the attribute data with the concrete internal temperature field and stress field distribution cloud picture, correcting model parameters of the heat flow coupling model according to a comparison result, generating a regulation and control instruction, and sending the regulation and control instruction to the execution module.The execution module is used for receiving the regulation and control instruction and executing the regulation and control instruction.The regulation and control instruction comprises at least one of temperature regulation and pouring timing optimization.The application can accurately predict a temperature field and a stress field, match complex construction conditions, capture mechanical and thermal state changes of the concrete in a whole life cycle in real time, effectively regulate temperature control, and improve construction quality.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology in concrete construction, and in particular to an integrated system and method for temperature control and crack prevention in large-volume concrete construction. Background Technology

[0002] Large-volume concrete, due to the concentrated release of heat during hydration, easily forms a significant temperature gradient between its interior and surface, leading to temperature stress, which is a core contributing factor to the initiation and propagation of cracks in engineering projects. Current temperature control and crack prevention solutions mostly employ a separate strategy of cooling water pipe installation and passive insulation. This results in low accuracy in predicting temperature and stress fields, making it difficult to match complex construction conditions. Furthermore, it fails to capture real-time changes in the mechanical and thermal states of concrete throughout its entire life cycle, hindering effective temperature control and leading to poor construction quality. Summary of the Invention

[0003] This invention aims to at least partially solve one of the technical problems in the aforementioned technologies. Therefore, the purpose of this invention is to propose an integrated system and method for temperature control and crack prevention in large-volume concrete construction, which accurately predicts temperature and stress fields, matches complex construction conditions, captures real-time changes in the mechanical and thermal states of concrete throughout its entire life cycle, effectively regulates temperature, and improves construction quality.

[0004] To achieve the above objectives, embodiments of the present invention propose an integrated temperature control and crack prevention system for large-volume concrete construction, comprising:

[0005] The module is used to build a fine model of cooling water pipes based on concrete thermodynamic parameters and construction conditions. The heat flow coupling control equation is solved by the heat flow coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete.

[0006] The monitoring module is used to collect concrete property data;

[0007] The comparison module is used to compare the attribute data with the temperature field and stress field distribution cloud map inside the concrete, correct the model parameters of the thermal-fluid coupling model based on the comparison results, generate control instructions and send them to the execution module.

[0008] An execution module is used to receive and execute control commands; the control commands include at least one of temperature adjustment and pouring sequence optimization.

[0009] According to some embodiments of the present invention, the building module includes:

[0010] The data acquisition module is used to collect thermophysical parameters of concrete raw materials, heat release rate curves of hydration, and aggregate gradation distribution data, and to construct a concrete microstructure model based on a random aggregate generation algorithm.

[0011] A module is established to obtain the cooling water pipe layout parameters and initial water flow parameters, and input them into the concrete microstructure model to establish a fine model of the cooling water pipe that includes the heat transfer resistance of the water pipe-concrete interface.

[0012] The solver module is used to solve the thermal-fluid coupling control equations of the fine model of the cooling water pipe using a thermal-fluid coupling algorithm, and outputs cloud maps of the internal temperature field and stress field distribution of concrete at different construction stages.

[0013] According to some embodiments of the present invention, the heat-fluid coupling control equation is as follows:

[0014] ;

[0015] in, This refers to the density of concrete. This refers to the specific heat capacity of concrete. The temperature of the concrete; For time; For heat conduction, For gradient operators; It is a divergence operator; The thermal conductivity of concrete; The heat release rate of hydration heat in concrete; The coefficient of thermal expansion of concrete; Porosity of concrete; This refers to the pore water pressure inside the concrete.

[0016] According to some embodiments of the present invention, a monitoring module includes:

[0017] The temperature monitoring module is set along the height of the concrete pouring and is used to collect the temperature data of the concrete.

[0018] The stress monitoring module is deployed at the centroid and edges of the concrete section to collect stress data of the concrete.

[0019] A humidity monitoring module is installed on and inside the concrete surface to collect humidity data of the concrete.

[0020] The first determination module is used to determine the property data of concrete based on temperature data, stress data, and humidity data.

[0021] According to some embodiments of the present invention, the monitoring module further includes: a micro-strain sensing module, which is deployed at the concrete joint and the embedded steel reinforcement, for monitoring the concrete shrinkage strain and the steel reinforcement constraint strain. When the strain difference between the concrete shrinkage strain and the steel reinforcement constraint strain is greater than a preset difference threshold, a constraint release control command is triggered.

[0022] According to some embodiments of the present invention, the comparison module includes:

[0023] The data processing module is used to remove random noise from temperature and stress data using the Kalman filter algorithm and to fill in missing data using linear interpolation to obtain preprocessed data.

[0024] The correction module is used for:

[0025] The temperature data in the preprocessed data is compared with the temperature field to obtain the first deviation parameter;

[0026] The stress data in the preprocessed data is compared with the stress field distribution cloud map to obtain the second deviation parameter;

[0027] When the first deviation parameter is greater than the first deviation threshold and / or the second deviation parameter is greater than the second deviation threshold, the model parameters of the thermal-fluid coupling model are corrected by Bayesian optimization algorithm.

[0028] The first generation module is used to determine the target data based on the modified heat-fluid coupling model, generate graded control instructions based on the target data and the preset database, and send them to the execution module.

[0029] According to some embodiments of the present invention, the execution module includes:

[0030] The receiving module is used to receive control commands;

[0031] Temperature control module, used to regulate the temperature of concrete;

[0032] The optimization module is used to optimize the concrete pouring sequence.

[0033] According to some embodiments of the present invention, a temperature regulation module includes:

[0034] A phase change insulation template includes a phase change material encapsulated inside a hollow template, a thermally conductive reinforcement layer arranged on the inner side of the template, and a thermal insulation layer arranged on the outer side; the phase change temperature range of the phase change material includes a first phase change temperature and a second phase change temperature, wherein the first phase change temperature is lower than the second phase change temperature;

[0035] The second determining module is used to determine that when the temperature of the concrete is less than the first phase change temperature, the phase change material undergoes a solidification phase change to release latent heat and conducts heat to the concrete surface through the thermally conductive reinforcement layer; when the temperature of the concrete is greater than the second phase change temperature, the phase change material undergoes a melting phase change to absorb heat.

[0036] According to some embodiments of the present invention, the optimization module includes:

[0037] The acquisition module is used to acquire meteorological data for future periods and, in conjunction with the predicted results of concrete hydration heat temperature rise, determine the suitable and restricted pouring periods.

[0038] The setting module is used to set constraints based on the maximum internal temperature rise of the concrete and the internal and external temperature difference, thereby optimizing the thickness of the pouring layer and the pouring interval.

[0039] The second generation module is used to perform pouring based on the thickness of the pouring layer and the pouring interval during a suitable pouring period. During the pouring process, when the ambient temperature is higher than the preset temperature threshold, the pouring sequence is automatically adjusted, and the shaded area is poured first.

[0040] According to some embodiments of the present invention, an integrated method for temperature control and crack prevention in large-volume concrete construction includes:

[0041] A fine model of cooling water pipes is constructed based on the thermodynamic parameters of concrete and construction conditions. The thermo-fluid coupling control equation is solved by the thermo-fluid coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete.

[0042] Collect concrete property data;

[0043] The model parameters of the thermal-fluid coupling model are corrected based on the comparison results by comparing the attribute data with the temperature field and stress field distribution cloud map inside the concrete, generating control instructions and sending them to the execution module.

[0044] The execution module receives and executes control commands; the control commands include at least one of temperature adjustment and pouring sequence optimization.

[0045] This invention proposes an integrated system and method for temperature control and crack prevention in large-volume concrete construction. By coupling the heat flow model of concrete microstructure, pore water pressure, and heat of hydration, the accuracy of temperature and stress field predictions is improved. It can capture the coordinated changes in thermal and mechanical states in real time, enhancing the comprehensiveness of monitoring. The monitoring data drives dynamic correction of model parameters, allowing for adjustment based on the actual state of the concrete, thus improving construction quality.

[0046] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0048] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0049] Figure 1 This is a block diagram of an integrated temperature control and crack prevention system for large-volume concrete construction according to an embodiment of the present invention;

[0050] Figure 2 This is a block diagram of a construction module according to an embodiment of the present invention;

[0051] Figure 3 This is a block diagram of a comparison module according to an embodiment of the present invention. Detailed Implementation

[0052] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0053] like Figure 1 As shown in the figure, this invention proposes an integrated temperature control and crack prevention system for large-volume concrete construction, comprising:

[0054] The module is used to build a fine model of cooling water pipes based on concrete thermodynamic parameters and construction conditions. The heat flow coupling control equation is solved by the heat flow coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete.

[0055] The monitoring module is used to collect concrete property data;

[0056] The comparison module is used to compare the attribute data with the temperature field and stress field distribution cloud map inside the concrete, correct the model parameters of the thermal-fluid coupling model based on the comparison results, generate control instructions and send them to the execution module.

[0057] An execution module is used to receive and execute control commands; the control commands include at least one of temperature adjustment and pouring sequence optimization.

[0058] The working principle of the above technical solution is as follows: The construction module collects thermodynamic parameters of concrete, such as thermal conductivity and specific heat capacity, and collects construction conditions, such as cooling water pipe layout and pouring environment. It then constructs a detailed model of the cooling water pipes and solves the control equations coupled with temperature, stress, and pore water pressure using a heat-fluid coupling algorithm. This outputs distribution cloud maps of the internal temperature and stress fields of the concrete, facilitating the prediction of potential temperature gradients and stress concentration areas. The monitoring module collects concrete property data, including temperature, stress, and humidity data. The comparison module compares the real-time collected property data with the temperature and stress field distribution cloud maps obtained from the model, calculating the data deviation. If the deviation exceeds a threshold, such as a temperature deviation > 3℃ or a stress deviation > 0.5MPa, the model parameters of the heat-fluid coupling model are corrected, and control commands are generated and sent to the execution module. The execution module receives and executes the control commands.

[0059] The beneficial effects of the above technical solution are as follows: By coupling the heat flow model of concrete microstructure, pore water pressure, and heat of hydration, the accuracy of temperature and stress field predictions can be improved. Real-time capture of the coordinated changes in thermal and mechanical states enhances the comprehensiveness of monitoring. Dynamic correction of model parameters driven by monitoring data allows for adjustment based on the actual state of the concrete, facilitating improved construction quality.

[0060] like Figure 2 As shown, according to some embodiments of the present invention, the building module includes:

[0061] The data acquisition module is used to collect thermophysical parameters of concrete raw materials, heat release rate curves of hydration, and aggregate gradation distribution data, and to construct a concrete microstructure model based on a random aggregate generation algorithm.

[0062] A module is established to obtain the cooling water pipe layout parameters and initial water flow parameters, and input them into the concrete microstructure model to establish a fine model of the cooling water pipe that includes the heat transfer resistance of the water pipe-concrete interface.

[0063] The solver module is used to solve the thermal-fluid coupling control equations of the fine model of the cooling water pipe using a thermal-fluid coupling algorithm, and outputs cloud maps of the internal temperature field and stress field distribution of concrete at different construction stages.

[0064] The working principle of the above technical solution is as follows: Collect thermophysical parameters of concrete raw materials, such as density, thermal conductivity, hydration heat release rate curve, and aggregate gradation distribution data. Using a random aggregate generation algorithm, recreate the actual distribution of aggregates and mortar within the concrete in the model, constructing a concrete microstructure model. Establish a module to obtain the layout parameters of cooling water pipes, such as spacing, pipe diameter, and burial depth, as well as initial water flow parameters, such as water temperature and flow rate. Input these parameters into the concrete microstructure model to establish a refined cooling water pipe model that includes the heat transfer resistance at the water pipe-concrete interface. Employ a heat-fluid coupling algorithm to solve the heat-fluid coupling control equations in the refined cooling water pipe model, outputting cloud maps of the internal temperature and stress fields of the concrete at different construction stages.

[0065] The beneficial effects of the above technical solution are as follows: A microstructural model is constructed using a random aggregate generation algorithm, realistically reflecting the thermal / mechanical differences between aggregates and mortar within the concrete, thus improving model accuracy. The introduction of heat transfer resistance at the water pipe-concrete interface compensates for the shortcomings of existing models that neglect interfacial heat loss. The heat-fluid coupling algorithm simultaneously considers the mutual influence of temperature, stress, and pore water pressure, improving prediction accuracy.

[0066] According to some embodiments of the present invention, the heat-fluid coupling control equation is as follows:

[0067] ;

[0068] in, This refers to the density of concrete. This refers to the specific heat capacity of concrete. The temperature of the concrete; For time; For heat conduction, For gradient operators; It is a divergence operator; The thermal conductivity of concrete; The heat release rate of hydration heat in concrete; The coefficient of thermal expansion of concrete; Porosity of concrete; This refers to the pore water pressure inside the concrete.

[0069] The working principle and beneficial effects of the above technical solution: It reflects the dynamic fluctuation of temperature over time. It describes the heat conduction process within concrete. Integrating the interactions of thermodynamics, mechanics, and hydraulics, it improves the comprehensiveness of multi-field coupling and facilitates better prediction accuracy.

[0070] According to some embodiments of the present invention, a monitoring module includes:

[0071] The temperature monitoring module is set along the height of the concrete pouring and is used to collect the temperature data of the concrete.

[0072] The stress monitoring module is deployed at the centroid and edges of the concrete section to collect stress data of the concrete.

[0073] A humidity monitoring module is installed on and inside the concrete surface to collect humidity data of the concrete.

[0074] The first determination module is used to determine the property data of concrete based on temperature data, stress data, and humidity data.

[0075] The working principle and beneficial effects of the above technical solution are as follows: The temperature monitoring module is set along the concrete pouring height to collect the concrete temperature data; the stress monitoring module is set at the centroid and edge of the concrete cross section to collect the concrete stress data; the humidity monitoring module is set at the concrete surface and interior to collect the concrete humidity data; the concrete property data are determined based on the temperature data, stress data and humidity data, which facilitates the improvement of the comprehensiveness of the monitoring dimensions.

[0076] According to some embodiments of the present invention, the monitoring module further includes: a micro-strain sensing module, which is deployed at the concrete joint and the embedded steel reinforcement, for monitoring the concrete shrinkage strain and the steel reinforcement constraint strain. When the strain difference between the concrete shrinkage strain and the steel reinforcement constraint strain is greater than a preset difference threshold, a constraint release control command is triggered.

[0077] The working principle and beneficial effects of the above technical solution are as follows: Micro-strain sensors are strategically placed at concrete joints and embedded reinforcing bars to capture strain changes at key risk points. This allows for the acquisition of shrinkage strain caused by the cooling of concrete due to hydration heat and water evaporation, as well as the constraint strain of the embedded reinforcing bars due to concrete shrinkage. The strain difference between the two is calculated. A preset difference threshold is determined based on the tensile strength of concrete, the elastic modulus of reinforcing bars, and engineering experience, such as 300 με. When the strain difference between the concrete shrinkage strain and the reinforcing bar constraint strain exceeds the preset difference threshold, a constraint release control command is triggered, including adjusting curing humidity, optimizing stress release measures for reinforcing bar placement, and initiating local insulation to slow down the shrinkage rate. By triggering the constraint release command through the strain difference threshold, proactive intervention occurs before visible cracks appear in the concrete, resulting in more accurate early warnings.

[0078] like Figure 3 As shown, according to some embodiments of the present invention, the comparison module includes:

[0079] The data processing module is used to remove random noise from temperature and stress data using the Kalman filter algorithm and to fill in missing data using linear interpolation to obtain preprocessed data.

[0080] The correction module is used for:

[0081] The temperature data in the preprocessed data is compared with the temperature field to obtain the first deviation parameter;

[0082] The stress data in the preprocessed data is compared with the stress field distribution cloud map to obtain the second deviation parameter;

[0083] When the first deviation parameter is greater than the first deviation threshold and / or the second deviation parameter is greater than the second deviation threshold, the model parameters of the thermal-fluid coupling model are corrected by Bayesian optimization algorithm.

[0084] The first generation module is used to determine the target data based on the modified heat-fluid coupling model, generate graded control instructions based on the target data and the preset database, and send them to the execution module.

[0085] The working principle and beneficial effects of the above technical solution are as follows: Random noise in temperature and stress data is removed using a Kalman filter algorithm, and missing data is supplemented using linear interpolation to obtain preprocessed data. The temperature data in the preprocessed data is compared with the temperature field to obtain the first deviation parameter. The stress data in the preprocessed data is compared with the stress field distribution cloud map to obtain the second deviation parameter. When the first deviation parameter exceeds the first deviation threshold, or the second deviation parameter exceeds the second deviation threshold, or both exceed the threshold, it indicates that the parameters of the initial thermal-fluid coupling model deviate from the actual working conditions. Using a Bayesian optimization algorithm, with the goal of minimizing the deviation, the optimal value is iteratively searched within the feasible region of the parameters, dynamically correcting the model parameters to make the model prediction results more closely match the actual state of concrete. Based on the corrected thermal-fluid coupling model, target data reflecting the true thermal and mechanical state of concrete is re-solved. The target data is matched with a preset database to generate graded control instructions and send them to the execution module. The preset database stores control strategies corresponding to different deviation levels and working conditions. Based on the judgment logic of dual deviation parameters, the deviation between the model and the actual working conditions is accurately identified; combined with the adaptive correction of the Bayesian optimization algorithm, the heat flow coupling model can adapt to the changes in working conditions during the construction process in real time, which facilitates the accurate determination of target data and thus the accurate determination of graded control instructions.

[0086] According to some embodiments of the present invention, the execution module includes:

[0087] The receiving module is used to receive control commands;

[0088] Temperature control module, used to regulate the temperature of concrete;

[0089] The optimization module is used to optimize the concrete pouring sequence.

[0090] The working principle and beneficial effects of the above technical solution are as follows: The receiving module receives control commands; the temperature regulation module regulates the temperature of the concrete; and the optimization module optimizes the concrete pouring sequence to facilitate the effective execution of control commands and thus improve construction quality.

[0091] According to some embodiments of the present invention, a temperature regulation module includes:

[0092] A phase change insulation template includes a phase change material encapsulated inside a hollow template, a thermally conductive reinforcement layer arranged on the inner side of the template, and a thermal insulation layer arranged on the outer side; the phase change temperature range of the phase change material includes a first phase change temperature and a second phase change temperature, wherein the first phase change temperature is lower than the second phase change temperature;

[0093] The second determining module is used to determine that when the temperature of the concrete is less than the first phase change temperature, the phase change material undergoes a solidification phase change to release latent heat and conducts heat to the concrete surface through the thermally conductive reinforcement layer; when the temperature of the concrete is greater than the second phase change temperature, the phase change material undergoes a melting phase change to absorb heat.

[0094] The working principle of the above technical solution is as follows: The phase change material is a paraffin-expanded graphite composite material. The thermally conductive reinforcement layer is an aluminum foil fiber composite material. The thermal insulation layer is polyurethane foam. The first phase change temperature is 10℃, and the second phase change temperature is 30℃. When the concrete temperature is determined to be lower than the first phase change temperature, the phase change material undergoes a solidification phase change, releasing latent heat. This heat is then conducted to the concrete surface through the thermally conductive reinforcement layer, compensating for heat loss from the concrete surface and preventing excessive temperature gradients caused by excessively low surface temperatures. When the concrete temperature is determined to be higher than the second phase change temperature, the phase change material undergoes a melting phase change, absorbing heat and inhibiting a rapid rise in surface temperature. Simultaneously, the outer thermal insulation layer blocks heat loss, preventing environmental temperature fluctuations from interfering with the internal temperature field of the concrete.

[0095] The beneficial effects of the above technical solution are: the three-layer composite structure and the clearly defined phase change temperature range work together to maintain a stable concrete surface temperature and improve the efficiency and accuracy of temperature regulation.

[0096] According to some embodiments of the present invention, the optimization module includes:

[0097] The acquisition module is used to acquire meteorological data for future periods and, in conjunction with the predicted results of concrete hydration heat temperature rise, determine the suitable and restricted pouring periods.

[0098] The setting module is used to set constraints based on the maximum internal temperature rise of the concrete and the internal and external temperature difference, thereby optimizing the thickness of the pouring layer and the pouring interval.

[0099] The second generation module is used to perform pouring based on the thickness of the pouring layer and the pouring interval during a suitable pouring period. During the pouring process, when the ambient temperature is higher than the preset temperature threshold, the pouring sequence is automatically adjusted, and the shaded area is poured first.

[0100] The working principle of the above technical solution is as follows: Meteorological data for future periods is acquired, and combined with the predicted temperature rise of concrete hydration heat, suitable and restricted pouring periods are determined. The suitable pouring period is characterized by an ambient temperature of 15-28℃ and a wind speed ≤3m / s. The module uses the maximum internal temperature rise of concrete ≤50℃ and the internal-external temperature difference ≤25℃ as core constraints. Combined with the initial setting time of concrete and the capacity of construction equipment, a multi-objective optimization algorithm iteratively calculates the optimal pouring layer thickness and pouring interval to ensure that layered pouring does not cause temperature rise superposition while guaranteeing interlayer bonding quality. During the suitable pouring period, pouring is carried out based on the pouring layer thickness and pouring interval. During the pouring process, when the ambient temperature exceeds a preset temperature threshold (32℃), the pouring sequence is automatically adjusted, prioritizing the pouring of shaded areas, such as those obstructed by buildings or on the shady side of mountains, avoiding areas exposed to direct sunlight or experiencing sudden temperature changes, and simultaneously adjusting the pouring rhythm.

[0101] The beneficial effects of the above technical solution are as follows: By coupling analysis of meteorological data and hydration heat temperature rise prediction, unfavorable periods such as high temperature and severe weather can be avoided in advance. The thickness and interval of the pouring layer are optimized with concrete temperature rise value and internal and external temperature difference as rigid constraints. During the pouring process, the system responds to environmental temperature fluctuations in real time, automatically adjusts the pouring sequence and area, and prioritizes the use of the low temperature environment in the shaded area to avoid the impact of sudden environmental changes on the concrete surface temperature, thereby facilitating the improvement of construction quality.

[0102] According to some embodiments of the present invention, it further includes: an alarm module for monitoring the execution data of the execution module and issuing an alarm when an abnormality is detected.

[0103] The working principle and beneficial effects of the above technical solution are as follows: The alarm module monitors the execution data of the execution module and issues an alarm when an anomaly is detected, so as to facilitate timely adjustment of the execution status of the execution module and avoid losses.

[0104] According to some embodiments of the present invention, an integrated method for temperature control and crack prevention in large-volume concrete construction includes:

[0105] A fine model of cooling water pipes is constructed based on the thermodynamic parameters of concrete and construction conditions. The thermo-fluid coupling control equation is solved by the thermo-fluid coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete.

[0106] Collect concrete property data;

[0107] The model parameters of the thermal-fluid coupling model are corrected based on the comparison results by comparing the attribute data with the temperature field and stress field distribution cloud map inside the concrete, generating control instructions and sending them to the execution module.

[0108] The execution module receives and executes control commands; the control commands include at least one of temperature adjustment and pouring sequence optimization.

[0109] The beneficial effects of the above technical solution are as follows: By coupling the heat flow model of concrete microstructure, pore water pressure, and heat of hydration, the accuracy of temperature and stress field predictions can be improved. Real-time capture of the coordinated changes in thermal and mechanical states enhances the comprehensiveness of monitoring. Dynamic correction of model parameters driven by monitoring data allows for adjustment based on the actual state of the concrete, facilitating improved construction quality.

[0110] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An integrated temperature control and crack prevention system for large-volume concrete construction, characterized in that, include: The module is used to build a fine model of cooling water pipes based on concrete thermodynamic parameters and construction conditions. The heat flow coupling control equation is solved by the heat flow coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete. The monitoring module is used to collect concrete property data; The comparison module is used to compare the attribute data with the temperature field and stress field distribution cloud map inside the concrete, correct the model parameters of the thermal-fluid coupling model based on the comparison results, generate control instructions and send them to the execution module. The execution module is used to receive and execute control commands; The control commands include at least one of temperature regulation and pouring sequence optimization; Build modules, including: The data acquisition module is used to collect thermophysical parameters of concrete raw materials, heat release rate curves of hydration, and aggregate gradation distribution data, and to construct a concrete microstructure model based on a random aggregate generation algorithm. A module is established to obtain the cooling water pipe layout parameters and initial water flow parameters, and input them into the concrete microstructure model to establish a fine model of the cooling water pipe that includes the heat transfer resistance of the water pipe-concrete interface. The solver module is used to solve the thermal-fluid coupling control equations included in the fine model of the cooling water pipe using a thermal-fluid coupling algorithm, and outputs the temperature field distribution cloud map and stress field distribution cloud map inside the concrete at different construction stages. The heat-fluid coupling control equation is: ； in, This refers to the density of concrete. This refers to the specific heat capacity of concrete. The temperature of the concrete; For time; For heat conduction, For gradient operators; It is a divergence operator; The thermal conductivity of concrete; The heat release rate of hydration heat in concrete; The coefficient of thermal expansion of concrete; Porosity of concrete; This refers to the pore water pressure inside the concrete. The monitoring module includes: The temperature monitoring module is set along the height of the concrete pouring and is used to collect the temperature data of the concrete. The stress monitoring module is deployed at the centroid and edges of the concrete section to collect stress data of the concrete. A humidity monitoring module is installed on and inside the concrete surface to collect humidity data of the concrete. The first determination module is used to determine the property data of concrete based on temperature data, stress data, and humidity data. The comparison module includes: The data processing module is used to remove random noise from temperature and stress data using the Kalman filter algorithm and to fill in missing data using linear interpolation to obtain preprocessed data. The correction module is used for: The temperature data in the preprocessed data is compared with the temperature field distribution cloud map to obtain the first deviation parameter; The stress data in the preprocessed data is compared with the stress field distribution cloud map to obtain the second deviation parameter; When the first deviation parameter is greater than the first deviation threshold and / or the second deviation parameter is greater than the second deviation threshold, the model parameters of the thermal-fluid coupling model are corrected by Bayesian optimization algorithm. The first generation module is used to determine the target data based on the modified heat-fluid coupling model, generate graded control instructions based on the target data and the preset database, and send them to the execution module.

2. The integrated temperature control and crack prevention system for large-volume concrete construction as described in claim 1, characterized in that, The monitoring module also includes a micro-strain sensing module, which is deployed at the concrete joint and the embedded steel bars to monitor the concrete shrinkage strain and the steel bar constraint strain. When the strain difference between the concrete shrinkage strain and the steel bar constraint strain is greater than the preset difference threshold, the constraint release control command is triggered.

3. The integrated temperature control and crack prevention system for large-volume concrete construction as described in claim 1, characterized in that, The execution module includes: The receiving module is used to receive control commands; Temperature control module, used to regulate the temperature of concrete; The optimization module is used to optimize the concrete pouring sequence.

4. The integrated temperature control and crack prevention system for large-volume concrete construction as described in claim 3, characterized in that, Temperature regulation module, including: A phase change insulation template includes a phase change material encapsulated inside a hollow template, a thermally conductive reinforcement layer arranged on the inner side of the template, and a thermal insulation layer arranged on the outer side; the phase change temperature range of the phase change material includes a first phase change temperature and a second phase change temperature, wherein the first phase change temperature is lower than the second phase change temperature; The second determining module is used to determine that when the temperature of the concrete is less than the first phase change temperature, the phase change material undergoes a solidification phase change to release latent heat and conducts heat to the concrete surface through the thermally conductive reinforcement layer; when the temperature of the concrete is greater than the second phase change temperature, the phase change material undergoes a melting phase change to absorb heat.

5. The integrated temperature control and crack prevention system for large-volume concrete construction as described in claim 3, characterized in that, The optimization module includes: The acquisition module is used to acquire meteorological data for future periods and, in conjunction with the predicted results of concrete hydration heat temperature rise, determine the suitable and restricted pouring periods. The setting module is used to set constraints based on the maximum internal temperature rise of the concrete and the internal and external temperature difference, thereby optimizing the thickness of the pouring layer and the pouring interval. The second generation module is used to perform pouring based on the thickness of the pouring layer and the pouring interval during a suitable pouring period. During the pouring process, when the ambient temperature is higher than the preset temperature threshold, the pouring sequence is automatically adjusted, and the shaded area is poured first.

6. The integrated method for construction temperature control and crack prevention of the integrated system for temperature control and crack prevention in large-volume concrete construction as described in any one of claims 1-5, characterized in that, include: A fine model of cooling water pipes is constructed based on the thermodynamic parameters of concrete and construction conditions. The thermo-fluid coupling control equation is solved by the thermo-fluid coupling algorithm to determine the temperature field and stress field distribution cloud map inside the concrete. Collect concrete property data; The model parameters of the thermal-fluid coupling model are corrected based on the comparison results by comparing the attribute data with the temperature field and stress field distribution cloud map inside the concrete, generating control instructions and sending them to the execution module. The execution module receives and executes control commands; the control commands include at least one of temperature adjustment and pouring sequence optimization.

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