A bridge concrete pouring process quality data analysis method and system

Abstract

The application relates to the technical field of engineering quality control, in particular to a bridge concrete pouring process quality data analysis method and system. The method comprises the following steps: intelligent precooling management and temperature collection are carried out on aggregates to generate pouring source temperature control basic data set; based on the data set, concrete mixing, conveying and mold feeding whole process temperature collaborative management and deviation correction are carried out to generate mold feeding quality stable data set; based on the mold feeding data, concrete internal temperature field real-time solving and cooling water flow dynamic adjustment are carried out to generate internal precise temperature control data set; based on the internal data, hot water circulation maintenance and internal and external temperature difference collaborative control are carried out to generate a concrete crack prevention quality analysis report. The application can realize whole-chain data driving and closed-loop control from raw material pretreatment to later maintenance, effectively solve the problems of excessive internal and external temperature difference and temperature cracks caused by hydration heat accumulation of mass concrete, and improve the traceability and structural durability of construction quality.

Description

Technical Field

[0001] This application relates to the field of engineering quality control technology, and in particular to a method and system for analyzing quality data during the concrete pouring process of bridges. Background Technology

[0002] With the rapid development of transportation infrastructure construction in my country, the application of large-volume concrete structures such as abutments and piers in large bridge projects is becoming increasingly widespread. During the construction of large-volume concrete, the heat released by the cement hydration reaction causes a significant increase in the internal temperature of the concrete, while the surface dissipates heat more quickly, resulting in a large temperature difference between the inside and outside. To control temperature cracks, existing technologies typically employ a series of temperature control measures, including spraying aggregates for cooling or constructing simple sheds for natural cooling, adding ice or using cold water during the concrete mixing stage, layering the concrete during pouring and installing cooling water pipes, and covering it with geotextile and sprinkling or storing water during the curing stage. These technical solutions attempt to reduce the initial temperature and maximum internal temperature of the concrete through physical means, and to a certain extent regulate the temperature difference between the inside and outside, and are currently the commonly used operating modes in the construction of large-volume concrete.

[0003] However, in existing technologies, due to the lack of systematic correlation analysis and dynamic feedback mechanisms for temperature data throughout the entire construction process, it is often difficult to accurately control the real-time evolution of the internal temperature field of concrete. Existing temperature control measures mostly rely on manual experience to set fixed cooling parameters or make delayed manual interventions. This leads to problems such as local overcooling, uncontrolled cooling rate, or excessive internal and external temperature differences when facing complex and variable environmental conditions and the nonlinear release characteristics of concrete hydration heat. As a result, it is difficult to fundamentally ensure the crack resistance quality of large-volume concrete structures throughout their entire lifespan. Summary of the Invention

[0004] This application provides a method and system for analyzing quality data during the concrete pouring process of bridges to solve the above-mentioned problems.

[0005] In a first aspect, this application provides a method for analyzing quality data during the concrete pouring process of a bridge, the method comprising: Intelligent pre-cooling control and temperature acquisition of aggregates are carried out to establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset of temperature control at the casting source. Based on the basic dataset of temperature control at the source of pouring, we carried out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying and placement, and generated a dataset of stable placement quality. Based on the stable data set of concrete entry quality, we carried out real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow to generate a precise internal temperature control data set. Based on the internal precise temperature control dataset, hot water circulation curing and coordinated control of internal and external temperature differences are carried out to generate a concrete crack prevention quality analysis report.

[0006] In one optional embodiment, intelligent pre-cooling control and temperature acquisition of aggregates are implemented, including: An insulated and enclosed silo was constructed and an air curtain machine was installed to block heat exchange between the inside and outside of the silo. Cold air was delivered into the silo through a linkage between an evaporative air cooler and a refrigeration unit. Temperature sensors are installed in the upper, middle, and lower layers of the aggregate stockpile, as well as at the center and edges, to collect the actual temperature of the aggregate and the ambient temperature of the silo in real time. The aggregate temperature is stably controlled within 15℃, and the temperature difference between aggregates in different locations is controlled within 3℃, thus forming aggregate raw materials that meet the low temperature requirements. The collected data on actual aggregate temperature, silo ambient temperature, and refrigeration equipment operation are integrated and stored to obtain a basic dataset for temperature control at the casting source. This dataset is then used to implement comprehensive temperature control management of raw materials.

[0007] In one optional embodiment, comprehensive temperature control management of raw materials is implemented based on the temperature control dataset at the pouring source, including: The cementitious materials are brought to the site in advance and allowed to stand to dissipate heat. The powder tank is also sprayed to cool it down, so that the material temperature is controlled below 45℃. The mixing water is cooled by a chiller unit and ice is added to the water tank to continuously reduce the temperature of the mixing water, while real-time temperature data of various raw materials are collected simultaneously. The real-time temperature data of raw materials is matched and calculated with the preset pre-cooling data of aggregates to form a basic dataset for temperature control at the pouring source, which serves to predict the temperature of concrete exiting the mixer.

[0008] In one optional embodiment, temperature control and deviation correction are implemented throughout the entire process of concrete mixing, conveying, and placement, including: Mix the aggregates in the order of cooling them first and then adding the cementitious materials, and extend the mixing time to ensure that the concrete is mixed evenly and the temperature is stable. The concrete discharge temperature is monitored in real time at the mixer discharge port, and the pouring temperature is collected at multiple points on the pouring surface to keep the pouring temperature stable below 28℃. By comparing the deviation between the concrete discharge temperature and the pouring temperature, the influence of temperature fluctuations in the mixing and transportation stages is corrected, and the pouring process is precisely controlled according to preset rules to obtain a stable dataset of pouring quality.

[0009] In one optional embodiment, precise control of the pouring process is performed according to preset rules, including: Concrete pouring is carried out in a layered and sequential manner, with the thickness of each layer controlled between 30cm and 50cm, thus forming pouring layer information. During the pouring process, environmental parameters and real-time temperature data of the mold are continuously monitored to maintain a stable temperature of the mold without sudden changes. The information on layered pouring, environmental parameters, and real-time temperature upon entering the mold are stored in a unified manner to provide stable data support for internal temperature control.

[0010] In one optional embodiment, real-time calculation of the internal temperature field of the concrete and dynamic adjustment of the cooling water flow rate are performed, including: The internal cooling water pipes of the concrete were laid out and pressure tested according to the preset layout specifications. Several layers of temperature sensors were also installed to collect data on the highest internal temperature, surface temperature, and corner temperature of the concrete in real time. The system automatically calculates the internal surface temperature difference and cooling rate, keeping the maximum internal temperature below 75℃, the internal surface temperature difference below 25℃, and the cooling rate below 2℃ / day. Based on the calculation results, the cooling water flow rate of each cooling circuit is adjusted independently, with the flow rate increased in high-temperature areas and decreased in areas with stable cooling, thus forming an internal precise temperature control dataset.

[0011] In one optional embodiment, the installation and pressure testing of the internal cooling water pipes in the concrete are completed according to a preset layout specification, including: Cooling water pipes are laid out in a serpentine coil pattern inside the concrete, with the horizontal spacing controlled between 0.9m and 1.2m, and the vertical spacing matched to the thickness of each pouring layer. Perform a water pressure test on the cooling water pipes to ensure that there are no leaks and that the water flows smoothly, and record the pipe distribution information; By integrating cooling water pipe layout parameters, pressure test qualification information, and measurement point distribution information, the basic configuration information of the internal precise temperature control dataset is obtained.

[0012] In one optional embodiment, hot water circulation maintenance and coordinated control of internal and external temperature differences are carried out, including: The warm water discharged from the cooling water pipes is collected as a curing water source, and a cofferdam is constructed on the top surface of the concrete to form a water storage and curing area. The curing water temperature is controlled between 30℃ and 35℃, and the water depth is kept stable at 10cm to 15cm to reduce the cold impact stress on the concrete surface. The system collects maintenance water temperature, surface temperature, and internal temperature in real time, dynamically adjusts the hot water supply, continuously reduces the temperature difference between the internal and external surfaces, and determines the maintenance process and termination conditions based on changes in temperature control data.

[0013] In one optional embodiment, the maintenance process and termination conditions are determined based on changes in temperature control data, including: When the temperature difference between the inner surface and the outer surface is less than 20°C for 24 consecutive hours and the internal temperature continues to drop steadily, the maintenance termination conditions are automatically met. All data on aggregate precooling, mold temperature, internal temperature control, and hot water curing are recorded throughout the process to form a complete and traceable quality ledger; Based on a complete quality record, the temperature control indicators are assessed to determine compliance, the absence of harmful temperature cracks is identified, and a crack prevention quality analysis report is generated.

[0014] Secondly, this application provides a quality data analysis system for bridge concrete pouring process, the system comprising: The source precooling module is used to carry out intelligent precooling control and temperature acquisition of aggregates, establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset of casting source temperature control. The concrete placement module is used to carry out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, transportation and placement, based on the aforementioned temperature control dataset at the pouring source, and to generate a stable data set of placement quality. The internal temperature control module is used to perform real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow based on the stable data set of the molded concrete quality, and generate an internal precise temperature control data set. The maintenance collaboration module is used to carry out hot water circulation maintenance and coordinated control of internal and external temperature differences based on the internal precise temperature control dataset, and generate a concrete crack prevention quality analysis report.

[0015] This application provides a method and system for quality data analysis during bridge concrete pouring. This method intelligently manages and collects the temperature of aggregates, establishing a correlation between aggregate temperature and initial heat release, generating a basic dataset for temperature control at the pouring source, thus reducing the initial temperature rise of the concrete from the outset. Based on this dataset, it conducts coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying, and placement, generating a stable quality dataset for placement. This ensures that the concrete has a stable temperature before entering the structure, effectively suppressing temperature fluctuations during transportation and operation. Furthermore, based on this stable quality dataset for placement, it... This system utilizes real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow to generate a precise internal temperature control dataset. By automatically calculating the internal surface temperature difference and cooling rate and independently adjusting the flow rate of each cooling loop, it achieves targeted cooling of high-temperature zones and energy-saving insulation of low-temperature zones within the concrete, thus avoiding shrinkage cracks caused by localized overcooling or excessively rapid cooling rates. Furthermore, based on this precise internal temperature control dataset, it implements hot water circulation curing and coordinated control of internal and external temperature differences. Recycled warm water is used for water storage curing, reducing cold impact stress on the concrete surface. The system automatically determines the curing progress and termination conditions based on temperature control data changes, ultimately generating a concrete crack prevention quality analysis report. This solves the problem of excessive internal and external temperature differences and temperature cracks caused by the accumulation of hydration heat in large-volume concrete. It achieves full-chain data-driven and closed-loop control from raw material pretreatment to post-curing, improving the integrity, durability, and traceability of bridge concrete structures, ensuring the long-term safety and reliability of the project.

[0016] In summary, this application constructs a four-stage progressive temperature control logic chain—from initial precooling to process temperature stabilization, internal temperature regulation, and final curing—transforming discrete construction processes into continuous data and control flows, thus forming a robust technical closed loop. This solution not only achieves precise perception and proactive intervention in the spatiotemporal evolution of the temperature field but also significantly reduces energy consumption and reliance on manual labor through waste heat utilization and intelligent decision-making. It demonstrates the advantages of systematic, intelligent, and green technologies, providing a scientifically sound and comprehensive quality assurance system for crack-resistant construction of large-volume concrete. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram illustrating an application scenario provided in one embodiment of this application; Figure 2A flowchart of a method for analyzing quality data during bridge concrete pouring process, provided as an embodiment of this application; Figure 3 This is a structural schematic diagram of a quality data analysis system for bridge concrete pouring process provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0021] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0022] Figure 1 This application provides an application scenario diagram. In the process of bridge concrete pouring, the method provided in this application can realize full-chain data-driven and closed-loop control from raw material pretreatment to post-curing, effectively solving the problem of excessive internal and external temperature difference and temperature cracks caused by the accumulation of hydration heat in large-volume concrete, and improving the traceability of construction quality and structural durability.

[0023] Specifically, the method provided in this application can be applied to any server, where the server interacts with the intelligent temperature control system to obtain the basic dataset of temperature control at the pouring source provided by the intelligent temperature control system, and finally outputs the concrete crack prevention quality analysis report to relevant personnel.

[0024] The specific implementation method can be referred to in the following embodiments, wherein the data mentioned in the embodiments are only for reference and examples, so that relevant personnel can better understand them.

[0025] Figure 2 This document presents a flowchart illustrating a method for analyzing quality data during bridge concrete pouring, as provided in one embodiment of this application. The method described in this embodiment can be applied to servers in the aforementioned scenarios. (See also...) Figure 2 The process, specifically the implementation steps, are as follows:

[0026] Example 1:

[0027] In the construction of large-volume concrete bridge structures, the enormous heat released by the cement hydration reaction causes a rapid rise in the internal temperature of the concrete, while the external temperature dissipates heat more quickly, resulting in a significant temperature difference between the inside and outside. This uneven temperature field generates enormous thermal stress. When the tensile stress exceeds the early tensile strength of the concrete, it can easily trigger temperature cracks, especially penetrating cracks, which will severely damage the structure's integrity, load-bearing capacity, and durability. Existing temperature control measures often suffer from low control precision, reliance on manual experience, slow response, and high energy consumption, making it difficult to achieve precise closed-loop control of the temperature field throughout the entire life cycle of concrete and failing to meet the stringent requirements of high-quality and green construction in modern large-scale infrastructure projects.

[0028] To address the aforementioned problems, this application provides a method for analyzing quality data during bridge concrete pouring, comprising the following steps: Step 1: Conduct intelligent pre-cooling control and temperature acquisition of aggregates, establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset for temperature control at the casting source; Intelligent pre-cooling control of aggregates refers to the forced reduction of aggregate temperature in an insulated, enclosed environment using refrigeration equipment, thereby reducing the initial heat of the concrete at its source. Specifically, this involves constructing an insulated, enclosed silo and configuring an air curtain to block heat exchange between the inside and outside of the silo. An evaporative air cooler, linked to a refrigeration unit, delivers cold air into the silo, maintaining the aggregate stockpile in a low-temperature, constant-temperature environment. Temperature sensors are installed at the upper, middle, and lower layers of the aggregate stockpile, as well as at the center and edges, to collect real-time data on the actual aggregate temperature and the ambient temperature of the silo. This ensures that the temperature difference between aggregates at different locations is controlled within a preset range (e.g., within 3°C) and that the aggregate temperature is stably controlled within a target value (e.g., 15°C). Establishing a correlation between aggregate temperature and initial heat release involves analyzing multi-point temperature data, combined with aggregate specific heat capacity and mass parameters, to calculate the total sensible heat brought into the concrete system by the aggregate, thus quantifying its contribution to the initial temperature rise of the concrete. For example, when the temperature at the center of the aggregate exceeds a set threshold by more than the edge temperature, the system automatically adjusts the airflow direction of the cooling fan or increases the cooling power in that area until the temperature distribution is uniform. The collected actual aggregate temperature, silo ambient temperature, and refrigeration equipment operating data are integrated and stored to obtain a basic dataset for temperature control at the pouring source. This dataset not only contains real-time temperature values ​​but also metadata such as the energy efficiency ratio of the refrigeration equipment and the start / stop status of the air curtain, providing a validated basis for comprehensive temperature control of raw materials in subsequent stages. This step effectively lowers the initial temperature of the concrete exiting the mixer, preventing temperature control failure in subsequent stages due to excessive initial heat.

[0029] Step 2: Based on the basic dataset of temperature control at the pouring source, carry out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying and placement, and generate a dataset of stable placement quality. The integrated temperature control throughout the concrete mixing, transportation, and placement process refers to using source temperature control data generated in previous steps to guide temperature regulation strategies during concrete production and transportation. Specifically, mixing is carried out in the order of cooling aggregates before adding cementitious materials, extending the mixing time to ensure uniform mixing and stable temperature. Simultaneously, cementitious materials are allowed to cool down beforehand or powder tanks are sprayed with water to cool them. Chillers are used to cool the mixing water, and ice is even added to further reduce the temperature of the mixture. The concrete outlet temperature is monitored in real-time at the mixer discharge port, and the placement temperature is collected at multiple points on the pouring surface, ensuring the placement temperature is stably controlled within the target value (e.g., 28℃). Deviation correction involves comparing the deviation between the concrete outlet temperature and the placement temperature, analyzing the temperature rise caused by environmental radiation, frictional heat generation, and other factors during transportation. If the deviation exceeds the preset limit, the outlet temperature setting for the next batch is dynamically adjusted, or the transportation route and insulation measures are optimized. For example, if the system detects that the temperature rise of a batch of concrete exceeds 2°C after 30 minutes of transportation, it automatically determines that the insulation layer during transportation has failed or the route has been severely overheated. It then instructs the mixing plant to reduce the outlet temperature compensation value for subsequent batches or dispatches transport vehicles equipped with shading facilities. The corrected mixing parameters, transportation trajectory temperature records, and final placement temperature data are stored uniformly to form a stable placement quality dataset. This step, through closed-loop feedback throughout the entire process, eliminates temperature fluctuation interference in intermediate stages, ensuring that the concrete entering the formwork possesses homogeneous and stable low-temperature characteristics, laying a solid foundation for internal temperature control.

[0030] Step 3: Based on the stable data set of the concrete pouring quality, perform real-time calculation of the internal temperature field of the concrete and dynamic adjustment of the cooling water flow rate to generate an internal precise temperature control data set; The real-time calculation of the internal temperature field of concrete refers to using a heat transfer model to invert the distribution of the three-dimensional temperature field inside the concrete based on the initial temperature boundary conditions at the time of placement and the real-time feedback data from pre-embedded temperature sensors. Specifically, cooling water pipes are laid out and pressure tested inside the concrete according to preset layout specifications, and several layers of temperature sensors are installed to collect data on the highest internal temperature, surface temperature, and corner temperature of the concrete in real time. The system automatically calculates the internal surface temperature difference and cooling rate, and compares the highest internal temperature, internal surface temperature difference, and cooling rate with preset thresholds (e.g., highest internal temperature <75℃, internal surface temperature difference <25℃, cooling rate <2℃ / day). Dynamic adjustment of cooling water flow rate refers to independently adjusting the cooling water flow rate of each cooling loop based on the calculation results to achieve precise temperature control based on spatial differences. For areas with higher temperatures or faster temperature rise rates, the cooling water flow rate of the corresponding loop is automatically increased to enhance heat dissipation; for areas with stable temperatures or those that have passed their peak, the flow rate is reduced to avoid excessive cooling that could lead to shrinkage cracks. For example, when the temperature in the central area of ​​the pier is detected to be close to 70℃ and rising rapidly, the system increases the opening of the electric regulating valve in the corresponding serpentine coil loop, raising the flow rate from 1.0 m³ / h to 1.5 m³ / h to accelerate heat removal. Conversely, when the temperature difference in the corner areas is less than 15℃, a low-flow insulation mode is maintained. The resulting dataset, containing the temperature time sequence at each measuring point, flow rate adjustment records for each loop, and the trend of temperature difference evolution, constitutes the internal precise temperature control dataset. This step represents a shift from passive water flow to active intervention, effectively suppressing internal temperature peaks and controlling the temperature gradient.

[0031] Step 4: Based on the internal precise temperature control dataset, carry out hot water circulation curing and coordinated control of internal and external temperature differences to generate a concrete crack prevention quality analysis report.

[0032] Hot water circulation curing refers to recycling the warm water discharged from the internal temperature control system after heat absorption as the curing water source, avoiding the surface cooling shock effect caused by traditional cold water curing. Specifically, warm water discharged from cooling water pipes is collected, and a dike is constructed on the top surface of the concrete to form a water storage curing area. The curing water temperature is controlled within a suitable range (e.g., between 30℃ and 35℃), and the water storage depth is maintained stable (e.g., 10cm to 15cm). Coordinated control of internal and external temperature differences involves real-time collection of curing water temperature, concrete surface temperature, and internal temperature, dynamically adjusting the hot water supply to continuously reduce the internal-to-surface temperature difference. Based on the changing trends of temperature control data, the system automatically determines each stage of the curing process and the termination conditions. For example, when the internal-to-surface temperature difference is less than 20℃ for 24 consecutive hours and the internal temperature shows a continuous and stable downward trend, the system automatically determines that the curing termination conditions are met, gradually reducing the hot water supply and eventually stopping the water flow. All key data related to aggregate precooling, mold placement temperature, internal temperature control, and hot water curing are recorded throughout the process, forming a complete and traceable quality ledger. Based on a complete quality log, the system comprehensively assesses the compliance of various temperature control indicators, identifies the potential for harmful temperature cracks, and ultimately generates a concrete crack prevention quality analysis report. This report not only includes the final conclusions but also covers temperature curves, flow regulation logs, and abnormal event records throughout the entire process, providing detailed data support for project quality acceptance and subsequent operation and maintenance.

[0033] This application constructs a closed-loop temperature control system covering the entire chain, from aggregate source cooling to mixing and conveying temperature stabilization, internal dynamic temperature adjustment, and finally to terminal hot water curing, through the close connection and synergistic effect of the above four steps. The intelligent pre-cooling significantly reduces the initial enthalpy of the concrete from the physical source, avoiding excessive subsequent temperature control pressure caused by a high starting point. The use of source data for full-process deviation correction eliminates random thermal disturbances during transportation and operation, ensuring the homogeneity of the temperature upon entering the formwork. Real-time calculation of the temperature field based on the data entering the formwork and dynamic adjustment of the cooling water flow rate achieves refined peak shaving and valley filling of the internal temperature gradient, preventing structural damage caused by local overheating or excessively rapid cooling. Furthermore, the innovative use of internally discharged waste heat for surface curing eliminates surface cold impact stress and promotes continuous cement hydration, creating a synergistic effect with the internal temperature control. The combined effect of these technologies has significantly improved the accuracy and stability of temperature field control in large-volume concrete, effectively solving the problem of temperature cracks caused by excessive internal and external temperature differences, and ensuring the durability and safety of bridge concrete structures.

[0034] Example 2: In another optional embodiment, a method for intelligent precooling control and temperature acquisition of aggregates is provided for the embodiments of this application. The method includes specific steps for intelligent precooling control and temperature acquisition of aggregates.

[0035] Step 1: Construct an insulated and enclosed silo and configure an air curtain machine to block heat exchange between the inside and outside of the silo. Use an evaporative air cooler and a refrigeration unit to deliver cold air into the silo. Insulated enclosed silos refer to sealed storage spaces constructed using high-performance insulation panels. Their main frame is typically made of light steel, and the enclosure system uses polyurethane sandwich panels or rock wool sandwich panels with a thermal conductivity λ≤0.022W / (m·K), with a panel thickness of not less than 100mm to form an efficient thermal barrier. Air curtains are installed above the silo inlet and outlet on the inner side to create a high-speed airflow barrier when the silo door is opened, physically isolating air convection between the inside and outside of the silo and preventing cold air leakage and hot air intrusion. Evaporative air coolers and refrigeration units form a linked cooling system. The evaporative air cooler provides basic cooling capacity using the principle of water evaporation heat absorption, while the refrigeration unit (such as a screw condenser unit) serves as the core cold source for deep cooling. The two work together to maintain a constant low-temperature environment within the silo. For example, when the ambient temperature reaches 35°C, the air curtain machine is activated, and after the silo door is closed, the refrigeration unit and multiple air coolers installed on the silo roof are simultaneously turned on, rapidly reducing the ambient temperature inside the silo to around 5°C. This also prevents condensation from forming on the aggregate surface due to contact with the excessively cold air cooler fins. Through this synergistic architecture of thermal insulation sealing + air curtain barrier + dual-mode refrigeration, external thermal disturbances are effectively blocked, significantly reducing energy loss during the pre-cooling process.

[0036] Step 2: Install temperature sensors in the upper, middle, and lower layers of the aggregate stockpile, as well as at the center and edges, to collect the actual temperature of the aggregate and the ambient temperature of the silo in real time. The preferred temperature sensor is the PT100 platinum resistance temperature sensor, which features high measurement accuracy (up to ±0.1℃), good stability, and strong anti-interference capability. The deployment locations cover key nodes in the three-dimensional space of the aggregate pile: the upper, middle, and lower layers vertically, and the center and edge points horizontally, thus constructing a five-dimensional global sensing network. These sensors are directly buried or tied to different depths within the aggregate pile, with the sensing end in full contact with the aggregate to accurately reflect the differences in thermal inertia in each area. For example, in a 2000 cubic meter silo, measuring points can be set at 0.5 meters below the top, 1.5 meters in the middle, and 2.5 meters below the bottom of the pile, with additional measuring points at the geometric center of the pile and at the edge 0.5 meters from the silo wall, forming multiple monitoring sections. This step, through high-density spatial sampling, eliminates the blind spots of traditional single-point temperature measurement, providing comprehensive data support for subsequent precise control.

[0037] Step 3: Stabilize the aggregate temperature below 15℃ and ensure that the temperature difference between aggregates in different locations is controlled within 3℃ to form aggregate raw materials that meet the low-temperature requirements; The control process involves dynamic adjustments based on the aforementioned collected temperature data. The intelligent control system compares the real-time monitored temperatures at each measuring point with preset target values ​​(≤15℃) and temperature difference thresholds (≤3℃). If the temperature in a certain area is too high or the temperature difference exceeds the standard, the system automatically adjusts the operating power of the air cooler above the corresponding area or increases the output load of the refrigeration unit, guiding the directional flow of cold air to eliminate local hot spots. Aggregate raw materials that meet the low-temperature requirements can refer to building materials that, after uniform cooling, have a consistent overall temperature field distribution and are in a low-energy state. For example, when the temperature at the edge of the silo is 16.5℃ while the temperature in the central area is 13.0℃, the system determines that the temperature difference of 3.5℃ exceeds the limit, and then instructs the air cooler in the edge area to increase the air volume and extend the operating time until the temperature at all measuring points in the entire silo drops below 15℃ and the maximum temperature difference is reduced to 2.8℃. Through this closed-loop feedback mechanism, the homogeneity of the aggregate raw materials is ensured, avoiding the risk of abnormal accumulation of local hydration heat in concrete caused by aggregate temperature dispersion from the source.

[0038] Step 4: Integrate and store the collected data on actual aggregate temperature, silo ambient temperature, and refrigeration equipment operation to obtain a basic dataset for temperature control at the casting source, and carry out full-domain temperature control management of raw materials based on the basic dataset for temperature control at the casting source.

[0039] The basic dataset for temperature control at the pouring source is a structured information collection formed by fusing heterogeneous data from multiple sources. Specifically, it includes time-series data on actual aggregate temperature, silo ambient temperature and humidity, and operating parameters of refrigeration equipment (such as compressor current, evaporation temperature, and fan start / stop status). Integrated storage is achieved by converting sensor signals into digital signals using a data acquisition device, which then uploads them to a cloud server or local database via a transmission layer. Comprehensive temperature control of raw materials refers to the correlation analysis and collaborative scheduling of temperature management for other raw materials such as cementitious materials and mixing water based on this dataset. For example, if the system records an average aggregate temperature of 14.2℃, an ambient temperature of 6.5℃, and a refrigeration unit load rate of 75% during a certain period, this data is packaged, timestamped, and stored in the database. Subsequently, during the concrete mix design stage, the aggregate temperature parameters from this dataset are used, combined with powder tank spray cooling data and chiller outlet water temperature, to predict the theoretical outlet temperature of the concrete. The construction and application of this dataset has enabled the extension from single aggregate temperature control to whole-chain raw material temperature control, laying a solid data foundation for the precise control of subsequent concrete mixing and placement temperature.

[0040] This application constructs a highly efficient aggregate precooling system through the synergistic effect of the aforementioned technical features. Physical isolation between the insulated, enclosed silo and the air curtain significantly reduces the erosion of the low-temperature environment inside the silo by external heat. Combined with the coordinated cooling of the evaporative air cooler and the refrigeration unit, it utilizes the high efficiency of latent heat exchange while ensuring the stability of deep cooling. Based on this, a five-dimensional temperature sensor network achieves comprehensive sensing of the aggregate temperature field, enabling precise control of the target temperature (≤15℃) and temperature difference (≤3℃). Finally, the integrated multi-dimensional sensing data generates a basic dataset for temperature control at the casting source, which not only records the entire precooling process but also serves as a key input variable for subsequent comprehensive temperature control. This effectively solves the problem of large aggregate temperature dispersion and difficulty in achieving stable targets in traditional processes, significantly improving the source quality of crack prevention control in large-volume concrete.

[0041] Example 3:

[0042] One embodiment of this application provides a process for comprehensive temperature control of raw materials, which includes the following steps: Step 1: Allow the cementitious material to stand and dissipate heat before it is brought to the site, and spray the powder tank to cool it down, so that the material temperature is controlled below 45℃. This step refers to reducing the initial temperature of cementitious materials such as cement, fly ash, and slag powder before they are added to the mixing process, using a combination of time and natural / forced heat exchange. The cementitious materials are obtained by organizing their arrival at least 7 days in advance. During their settling time in the powder tank, they slowly release heat through natural convection and thermal radiation on the tank surface. Spray cooling of the powder tank involves activating an automatic spray system installed on the outer surface of the powder tank during high-temperature periods (e.g., 10:00 to 18:00 daily) to intermittently spray cold water onto the tank surface. The water evaporates and absorbs heat on the tank surface, creating forced convection heat exchange, further removing heat from the powder inside the tank. The purpose of this step is to keep the operating temperature of the cementitious materials below 45℃, preventing the release of large amounts of hydration heat during mixing and thus reducing the peak adiabatic temperature rise of the concrete from the source. For example, when the ambient temperature reaches 35℃, the powder temperature may reach over 50℃ if left to stand naturally. However, by spraying for 5 minutes every half hour, the powder temperature can be stably controlled at around 42℃. This dual-path heat dissipation mechanism of standing + spraying effectively offsets the impact of high summer temperatures on cementitious materials, ensuring that the cementitious materials entering the mixer are at a low temperature, laying the foundation for subsequent control of the concrete outlet temperature.

[0043] Step 2: Use a chiller to cool the mixing water and add ice to the water tank to continuously lower the temperature of the mixing water, while simultaneously collecting real-time temperature data of various raw materials. This step involves employing a combined approach of mechanical refrigeration and phase change heat absorption to lower the temperature of the mixing water to extremely low levels and establish a comprehensive temperature sensing network. The mixing water is obtained through a circulating cooling system, which maintains the water temperature in the tank at approximately 9°C. In extreme heat or when mechanical refrigeration alone cannot meet temperature control requirements, food-grade flake ice or crushed ice is added to the water tank. The latent heat of phase change during the ice melting process absorbs a large amount of heat, further rapidly lowering the water temperature to 5°C or even lower. Synchronous data acquisition utilizes PT100 temperature sensors embedded in the water tank, aggregate bins, and powder silos to acquire real-time instantaneous temperature data of water, aggregates, and cementitious materials. The purpose of this step is to significantly lower the liquid phase temperature baseline in the concrete mix design, using a low-temperature water-ice mixture as a cold source to absorb heat from the aggregates and cementitious materials during the mixing process. For example, when preparing 1 cubic meter of concrete, if the water temperature needs to be lowered from 25℃ to 5℃, this can be achieved by adding approximately 30 kg of crushed ice. In this case, the temperature of the ice-water mixture can be precisely maintained within the range of 0℃ to 2℃. This redundant design of mechanical refrigeration + ice addition not only improves cooling efficiency but also ensures that the water temperature control accuracy reaches ±0.5℃, effectively avoiding the risk of excessive concrete outlet temperature due to water temperature fluctuations.

[0044] Step 3: Match and calculate the real-time temperature data of raw materials with the preset pre-cooling data of aggregates to form a basic dataset for temperature control at the pouring source, which serves to predict the temperature of concrete leaving the mixer.

[0045] This step can refer to constructing a multivariate regression model based on the principle of thermal balance, integrating scattered raw material temperature data into a structured dataset with predictive capabilities. The real-time raw material temperature data comes from the collected water temperature, the monitored powder temperature, and the aggregate temperature obtained in the previous embodiment. The preset aggregate pre-cooling data can refer to the ideal aggregate temperature value (e.g., ≤15℃) and its corresponding heat capacity parameters set according to the engineering objectives. The matching calculation is performed by the algorithm module of the intelligent temperature control system, substituting the aforementioned multi-source temperature data into the concrete discharge temperature prediction formula. (Where m is mass, c is specific heat capacity, T is temperature, and i is the i-th raw material) A weighted calculation is performed. The resulting basic dataset for temperature control at the pouring source includes the measured temperature of each raw material, the predicted theoretical discharge temperature, and the deviation correction coefficient. This dataset serves to predict the discharge temperature of concrete; that is, before actual concrete mixing, it pre-determines whether the discharge temperature under the current raw material combination meets the control target of ≤28℃. For example, when the system detects that the aggregate temperature is 16℃ (slightly higher than the preset 15℃) and the water temperature is 6℃, the algorithm automatically calculates the theoretical discharge temperature to be 27.5℃, determines it as qualified, and generates the corresponding mixing instruction; if the calculation result is 29℃, the dataset will mark it as abnormal and prompt an increase in the amount of ice added. Through this data matching and feedforward prediction mechanism, a shift from post-event detection to pre-event prediction is achieved, ensuring that the discharge temperature of each batch of concrete is under control.

[0046] This application constructs a comprehensive raw material temperature control system through the synergistic effect of the aforementioned technical features. By combining the pre-arrival and static setting of cementitious materials with powder tank spray cooling, and utilizing the complementary effects of natural heat dissipation and forced evaporation heat exchange, the temperature of the cementitious materials is successfully controlled below 45℃, eliminating the additional heat source from the high-temperature powder. Furthermore, with the dual guarantee of chiller cooling and ice addition to the water tank, the high efficiency of mechanical refrigeration and the rapid phase change heat absorption are utilized to precisely lock the temperature of the mixing water at a low level, significantly reducing the initial enthalpy of the concrete mixture. Moreover, by matching and calculating real-time multi-source raw material temperature data with preset aggregate pre-cooling data, the system can dynamically construct a source temperature control basic dataset reflecting the true thermal state. This dataset not only records the current temperature distribution but also achieves accurate prediction of the concrete discharge temperature through a thermal model. This progressive approach, from cooling a single material to multi-source data fusion prediction, effectively solves the systemic temperature control mismatch problem caused by the lack of coordinated control between cementitious materials and water temperature in traditional construction. It significantly improves the accuracy of the outlet temperature prediction and provides reliable data support for the parameter optimization of the subsequent concrete mixing process, thereby ensuring that large-volume concrete has excellent crack resistance from the source.

[0047] Example 4:

[0048] In one possible implementation, a method for coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying, and placement, as provided in this application embodiment, includes the following steps: Step 1: Mix the aggregates in the order of cooling them first and then adding the cementitious materials, extending the mixing time to ensure that the concrete is mixed evenly and the temperature is stable. The practice of cooling aggregates before adding cementitious materials can be described as altering the traditional concrete feeding sequence by using low-temperature aggregates, which have undergone intelligent pre-cooling control, as the first material added. Specifically, coarse and fine aggregates with temperatures controlled below 15°C are first added to the mixer, along with some mixing water or ice for a brief wet mix. This utilizes the high heat capacity of the cold aggregates to absorb the sensible heat of the water and the heat released from the initial hydration of the subsequent cementitious materials, forming a low-temperature aggregate slurry coating layer. Cement, fly ash, slag powder, and other cementitious materials, along with remaining admixtures and water, are then added. This feeding sequence effectively delays the onset of the overall concrete temperature rise inflection point, reducing the outlet temperature from the source. Extending the mixing time can refer to adding 15 to 30 seconds to the conventional mixing time, for example, setting the total mixing time to 90 to 120 seconds. The extended mixing time ensures sufficient diffusion and homogenization of the cold energy in the concrete slurry, eliminating localized hot spots, resulting in more uniform mixing of the concrete components, consistent color, and no bleeding or segregation. By optimizing the feeding sequence and extending the mixing time, the concrete outlet temperature can be significantly reduced by approximately 1.8°C to 2.5°C, and a temperature buffer space is reserved for subsequent transportation.

[0049] Step 2: Monitor the concrete discharge temperature at the mixer outlet in real time, and collect the pouring temperature at multiple points on the pouring surface, keeping the pouring temperature stable below 28℃. Real-time monitoring of concrete outlet temperature at the mixer discharge port can refer to setting up online temperature measurement points or using calibrated portable thermometers to sample and test the concrete flow at the mixer discharge port after concrete production is completed. The testing frequency is once per shift, per 100 cubic meters of concrete, or at least once every 2 hours to obtain accurate outlet temperature data T_out. Multi-point collection of pouring temperature at the pouring site can refer to deploying multiple temperature acquisition terminals at different locations (such as the center, edge, and corners) for each pouring section when the concrete arrives at the pouring point on the construction site, and measuring the pouring temperature T_in for each truckload or per 100 cubic meters of concrete to ensure data representativeness. Maintaining the pouring temperature stably below 28℃ is a set hard quality threshold, requiring the pouring temperature T_in at all measuring points to be ≤28℃. If the temperature at any point exceeds this threshold, the system will immediately trigger an alarm. By constructing a temperature sensing network covering the entire chain from production to construction, it is possible to monitor the temperature change trajectory of concrete during transportation in real time, preventing temperature exceedances caused by high ambient temperature or long transportation time.

[0050] Step 3: Compare the deviation between the concrete discharge temperature and the pouring temperature, correct for the influence of temperature fluctuations in the mixing and transportation stages, and implement precise control of the pouring process according to preset rules to obtain a stable dataset of pouring quality.

[0051] The deviation between the concrete discharge temperature and the formwork temperature can be calculated as ΔT = T_in - T_out. This difference reflects the temperature rise of the concrete during transportation, waiting, and pumping, and is a key indicator for evaluating the effectiveness of thermal insulation during transportation and the standardization of on-site operations. Under normal circumstances, this temperature difference should be controlled within a certain range (e.g., 3℃-5℃) during hot seasons. If ΔT increases abnormally, it indicates that the insulation measures of the transport tanker have failed or the on-site dwell time is too long. Correcting the impact of temperature fluctuations in the mixing and transportation stages can refer to dynamically adjusting the parameters of the preceding stages based on the feedback results of ΔT. For example, when ΔT remains high, the system automatically instructs to lower the target discharge temperature of the next batch of concrete, or schedules additional transport vehicles with thermal insulation jackets, or optimizes the driving route to reduce travel time. Precise control of the pouring process according to preset rules refers to actions executed based on a preset control strategy library. These actions include: automatically activating a spray cooling device to assist in heat dissipation from the transport tank when the temperature upon entering the formwork approaches the critical value of 28℃; pausing pouring and investigating the cause when temperature fluctuations exceed the allowable range; and simultaneously recording pouring layer information, environmental parameters, and real-time temperature data. The stable concrete entry quality dataset is a structured data set that integrates and stores the corrected outlet temperature, entry temperature, temperature difference deviation, correction measures records, and environmental data. Through a deviation-driven closed-loop correction mechanism, the response time for temperature loss compensation during transportation can be shortened to less than 5 minutes, reducing the rate of exceeding the limit for entry temperature from the traditional 12.7% to below 0.9%, ensuring an entry temperature stability of 99.2%, thus providing a high-quality data foundation for the subsequent accurate calculation of the internal temperature field of the concrete.

[0052] This application constructs a comprehensive temperature control system for concrete from production to placement through the synergistic effect of the aforementioned technical features. By optimizing the aggregate-before-cementation feeding sequence and extending the mixing time, the initial discharge temperature of the concrete is effectively reduced, providing sufficient cooling capacity to resist environmental heat intrusion during transportation. Furthermore, by utilizing real-time monitoring of both discharge and placement temperatures, the temperature variation characteristics during transportation are quantified, and deviation analysis enables dynamic correction of mixing parameters and transportation strategies. This dual mechanism of source cooling and process correction not only solves the problem of uncontrolled placement temperature caused by improper sequence and lack of monitoring in traditional construction, but also ensures that the placement temperature remains strictly stable below 28℃, significantly reducing the accumulation of early hydration heat in concrete, suppressing the risk of temperature cracks in large-volume concrete from the source, and achieving refined and intelligent control of the construction process.

[0053] Example 5:

[0054] One embodiment of this application provides a process for precise control of the pouring process, which includes specific steps for precise control of the pouring process according to preset rules.

[0055] Step 1: Pour concrete in layers and proceed in sequence, controlling the thickness of each layer to be between 30cm and 50cm, thus forming pouring layer information; The layered and sequential approach involves dividing the large-volume concrete pouring area into several pouring sections and pouring them sequentially according to a predetermined order. This ensures that the lower layer of concrete is covered by the upper layer before initial setting, thus avoiding cold joints. The thickness of each layer refers to the vertical height of the concrete in a single pouring operation. This thickness is determined based on the vertical spacing of the cooling water pipes, the density of temperature measuring points, and the rate of heat release from concrete hydration. By strictly controlling the pouring thickness between 30cm and 50cm, the length of the heat conduction path within the concrete is kept within a controllable range, effectively reducing the internal peak temperature. For example, when the foundation design thickness is 6.5m, if a 40cm layer thickness is used, the entire pouring process can be divided into approximately 17 layers. The pouring time of each layer is matched with the spacing of the cooling water pipes, ensuring that heat can be promptly discharged through the pre-embedded pipes. If the layer thickness is too large, exceeding 60cm, it will cause internal heat to accumulate too quickly, exceeding the cooling system's heat dissipation capacity. If the layer thickness is too thin, less than 20cm, it will increase the number of construction joints, affecting the overall structural integrity and prolonging the construction period. The layering information includes the start and end elevations of each layer, pouring time, pouring volume, and corresponding spatial coordinates. This information constitutes the structured input data for the subsequent internal temperature control model. This layered control method ensures a deterministic match between the vertical spacing of the cooling water pipes and the pouring layer thickness, providing precise geometric boundary conditions for real-time calculation of the internal temperature field.

[0056] Step 2: During the pouring process, continuously monitor environmental parameters and real-time temperature data of the mold to maintain a stable temperature without sudden changes. Environmental parameters include meteorological indicators such as air temperature, relative humidity, wind speed, and solar radiation intensity at the construction site. These data directly affect the heat dissipation rate of the concrete surface and the temperature rise trend after placement in the formwork. Real-time placement temperature data refers to the temperature value of the concrete at the moment it enters the formwork. This data is a key indicator for measuring the effectiveness of temperature control at the source and the thermal insulation performance during transportation. During the pouring process, environmental parameters are collected in real time by meteorological stations deployed around the pouring surface, and the placement temperature is frequently detected using pre-embedded or handheld temperature sensors to quantify the weight of meteorological factors on temperature control. For example, in a high-temperature and high-humidity environment, if the ambient temperature reaches 35℃ and the relative humidity is greater than 80%, the temperature rise rate of the concrete upon placement may be 40% faster than under standard conditions. In this case, the system needs to dynamically adjust the temperature control threshold and increase the cooling water flow rate in advance to offset the environmental heat load. Maintaining a stable placement temperature without sudden changes means that during continuous pouring, the temperature difference between adjacent truckloads of concrete should be controlled within the allowable range (e.g., ±2℃) to prevent initial temperature stress caused by excessive local temperature differences. Specifically, when abnormal fluctuations in the temperature at the bottom of the mold are detected, the temperature at the outlet of the mixing plant or the transportation time is immediately traced, and emergency measures such as shading and misting for cooling are taken. The joint analysis of environmental parameters and the temperature at the bottom of the mold significantly improves the environmental adaptability of the temperature control model, ensuring that the temperature control compliance rate remains at a high level even under extreme weather conditions.

[0057] Step 3: Store the pouring layer information, environmental parameter data, and real-time temperature data of the mold in a unified manner to provide stable data support for internal temperature control.

[0058] Unified storage refers to integrating the three types of heterogeneous data mentioned above into a cloud database or local server according to a unified timestamp and spatial coordinate index, constructing a spatiotemporally coupled quality ledger. Layered pouring information provides geometric constraints in the spatial dimension, environmental parameter data provides thermal loads at the external boundary, and real-time mold-entry temperature data provides the initial temperature field distribution. The integrated storage of these three types of data solves the information loss and untraceability problems caused by data silos in traditional construction, providing crucial boundary conditions and initial field data support for the real-time calculation of the internal temperature field in the above embodiment. For example, when performing internal temperature field inversion calculations, the system can directly call the stored layered information to determine the node positions of the computational grid, read the environmental parameters for the corresponding time period to set the convective heat transfer coefficient, and load the mold-entry temperature as the initial condition, thereby achieving high-precision temperature field prediction. Furthermore, the unified data format meets the archival management standards, achieving 100% traceability of quality data throughout the entire process, facilitating the subsequent generation of crack-resistant quality analysis reports and project acceptance. This data integration mechanism ensures the continuity of data across the entire chain from the pouring source to internal curing, laying a solid foundation for the accurate operation of the intelligent decision-making system.

[0059] This application achieves refined control and data-driven support for the pouring process through the synergistic effect of the aforementioned technical features. By employing a layered, sequential pouring method and a thickness limit of 30cm to 50cm, not only is the heat conduction path of the concrete optimized, reducing the internal peak temperature, but it also achieves precise spatial matching with the layout of cooling water pipes. Furthermore, by combining real-time monitoring of environmental parameters and the temperature at the time of placement, the impact of external environmental disturbances on the concrete temperature rise can be dynamically quantified, allowing for timely adjustments to the temperature control strategy and avoiding temperature runaway caused by response lag in traditional methods. Moreover, by uniformly storing the three key data types—pouring layer information, environmental parameters, and the temperature at the time of placement—a complete spatiotemporal coupled database is constructed, eliminating data silos and providing accurate geometric boundaries, thermal loads, and initial conditions for subsequent real-time calculation of the internal temperature field. This closed-loop system, from physical construction control to data acquisition and integration, significantly improves the predictive accuracy and environmental adaptability of the temperature control model, ensuring the crack prevention effect of large-volume concrete under complex working conditions, and ultimately achieving intelligent and traceable management of construction quality.

[0060] Example 6:

[0061] One embodiment of this application provides a method for real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow rate. The method includes the following steps: Step 1: Complete the layout and pressure test of the internal cooling water pipes of the concrete according to the preset layout specifications, and install several layers of temperature sensors to collect data on the highest internal temperature, surface temperature, and corner temperature of the concrete in real time. The "pre-defined layout specifications" refers to developing a spatial distribution plan for cooling water pipes based on the thermal calculations and geometric dimensions of the concrete structure. Specifically, the cooling water pipes are typically seamless steel pipes or hot-rolled black iron pipes with excellent thermal conductivity, laid out in a serpentine coil pattern within the concrete. The horizontal spacing is controlled between 0.9m and 1.2m, while the vertical spacing matches the thickness of each concrete layer, ensuring comprehensive cooling coverage. After installation, the cooling water pipe system undergoes a pressure test, increasing the network pressure to 1.5 times the working pressure (usually not less than 0.6MPa) and maintaining this pressure for at least 30 minutes to confirm no leaks, deformations, and smooth water flow. This serves as the basis for subsequent cooling system configuration. Simultaneously, the installation of several layers of temperature sensors refers to embedding high-precision PT100 platinum resistance temperature sensors between cooling water pipe layers, at the geometric center of the concrete, at a distance of 0.5m to 1.0m from the surface, and in areas of stress concentration at the corners. These sensors, together with the cooling water pipes, form a three-dimensional monitoring network for real-time acquisition of data on the highest internal temperature, surface temperature, and corner temperatures of the concrete. For example, in the construction of a 6.5m thick foundation, 3 to 4 layers of measuring points can be arranged vertically, and measuring points can be arranged at the center and four corners in the horizontal direction, forming a dense temperature sensing matrix. Through this deployment and data acquisition, a digital twin of the internal temperature field of the concrete can be constructed, providing accurate data input for subsequent real-time calculations.

[0062] Step 2: Automatically calculate the internal surface temperature difference and cooling rate, and control the maximum internal temperature to within 75℃, the internal surface temperature difference to within 25℃, and the cooling rate to within 2℃ / day. The automatic calculation refers to the intelligent temperature control system using a heat transfer theory model and the collected real-time temperature data to instantly calculate the internal thermal state characteristics of the concrete. Specifically, the system compares the values ​​of the highest internal temperature measurement point with the surface temperature measurement point to obtain the internal-to-surface temperature difference in real time; and calculates the current cooling rate by differentiating the temperature changes over a continuous time series. Triple threshold control involves comparing the calculated characteristic values ​​with preset safety limits: the internal highest temperature threshold is set at 75℃ to prevent strength loss or delayed cracking due to overheating; the internal-to-surface temperature difference threshold is set at 25℃ to avoid tensile stress exceeding the early tensile strength of the concrete caused by uneven internal and external shrinkage; and the cooling rate threshold is set at 2℃ / day to prevent cracking due to rapid volume shrinkage caused by excessive cooling. For example, if the system detects a maximum internal temperature of 72℃ and a surface temperature of 50℃ at a certain moment, the internal-to-surface temperature difference is 22℃, which, while not exceeding the limit, is close to the warning line; if the calculated cooling rate at this time is 2.5℃ / day, then the cooling rate is deemed to be exceeding the limit. This step aims to transform the abstract temperature field into specific control instructions through quantitative indicators, ensuring that the concrete is always within a safe temperature control range.

[0063] Step 3: Adjust the cooling water flow rate of each cooling circuit independently based on the calculation results. Increase the flow rate in high-temperature areas and decrease the flow rate in areas with stable cooling to form an internal precise temperature control dataset.

[0064] Independent regulation refers to the intelligent control system dividing the cooling water pipe network into several loops with independent valve control. Based on the calculated temperature field distribution differences, a differentiated flow regulation strategy is implemented for each loop. Specifically, for high-temperature areas with high monitored temperatures and large internal-to-surface temperature differences, the system automatically increases the opening of the corresponding loop's electric regulating valve, increasing the cooling water flow rate (e.g., from 1.0 m³ / h to 1.8 m³ / h) to enhance heat exchange efficiency and quickly remove accumulated heat of hydration. For stable cooling areas where the temperature has stabilized or is in a low-temperature zone, the system automatically reduces the flow rate or even stops water flow, implementing a heat preservation and slow cooling strategy to avoid excessive cooling and the creation of new temperature gradients. This dynamic regulation mechanism of high flow rate in high-temperature areas and low flow rate in low-temperature areas achieves a shift from uniform cooling to precise targeted cooling. For example, during the peak temperature rise of concrete, the loops targeting the central high-temperature zone operate at full speed, while the loops in the peripheral areas maintain a low flow rate. After entering the cooling period, as the central temperature drops, the system gradually and synchronously reduces the flow rate of all loops, strictly controlling the cooling rate. Ultimately, the system integrates and stores the flow setpoints, actual feedback values, corresponding temperature field data, and adjustment action records for each loop at every moment, generating an internal precise temperature control dataset containing spatiotemporal evolution information, providing data support for subsequent maintenance decisions.

[0065] This application constructs a closed-loop temperature control system encompassing sensing, calculation, and execution through the synergistic effect of the aforementioned technical features. By deploying cooling water pipes and multi-layered sensors according to preset specifications, it achieves comprehensive real-time sensing of the three-dimensional temperature field inside the concrete, solving the problem of insufficient representativeness in traditional single-point monitoring. Based on the sensed data, it automatically calculates the internal surface temperature difference and cooling rate, and sets triple dynamic thresholds of 75℃, 25℃, and 2℃ / day, transforming empirical qualitative judgment into quantitative automated decision-making logic. Furthermore, based on the calculation results, it implements independent dynamic flow adjustment for each cooling loop, effectively eliminating the non-uniformity of the internal temperature field of the concrete by utilizing a differentiated strategy of strong cooling in high-temperature zones and weak cooling in low-temperature zones. This synergistic mechanism not only ensures that the internal maximum temperature, internal surface temperature difference, and cooling rate are strictly controlled within a safe range, significantly reducing the risk of cracks caused by temperature stress concentration, but also avoids the energy waste and local overcooling phenomena caused by traditional constant flow cooling, achieving refined, intelligent, and green temperature control for large-volume concrete.

[0066] Example 7:

[0067] In one optional implementation, a cooling water pipe laying and pressure testing process provided in this application includes: Step 1: Lay cooling water pipes inside the concrete in a serpentine coil pattern, controlling the horizontal spacing between 0.9m and 1.2m, and the vertical spacing matching the thickness of each pouring layer; The serpentine coil method refers to arranging cooling water pipes in a continuous, reciprocating bend within the concrete structure, forming a long, snake-like flow loop. This arrangement significantly extends the flow path of the cooling water within the concrete, increasing the contact area between the concrete and the cooling pipes per unit volume, thereby improving heat dissipation efficiency. Horizontal spacing refers to the distance between the centerlines of two adjacent parallel cooling water pipes; this parameter directly determines the uniformity of the temperature field. By strictly controlling the horizontal spacing between 0.9m and 1.2m, it is possible to ensure comprehensive cooling coverage while avoiding construction interference or cost waste caused by excessively close pipe spacing. For example, for a large-volume foundation with a thickness of 3.5m, a horizontal spacing of 1.0m, combined with vertical layering, ensures that the distance from any point inside the concrete to the nearest cooling pipe does not exceed 0.6m, effectively suppressing the formation of localized high-temperature zones. Vertical spacing refers to the vertical distance between upper and lower layers of cooling water pipes, and its setting must match the layer thickness of the poured concrete. Specifically, if the concrete is poured in layers with each layer being 0.5m thick, the vertical spacing can be set to 1.0m or adjusted to 0.7m based on thermal calculations to ensure that each layer is effectively covered by the cooling pipe network. By using serpentine coils in conjunction with precise spacing control, an efficient internal heat dissipation network is constructed, providing a stable physical basis for subsequent temperature field calculations.

[0068] Step 2: Conduct a water pressure test on the cooling water pipes to ensure that there are no leaks and that the water flows smoothly, and record the pipe distribution information; Herein, the water pressure test may refer to the process of injecting clean water into the cooling water pipes and pressurizing it to a specified value after the installation of the cooling water pipes is completed and before concrete pouring, so as to inspect the sealing performance and pressure bearing capacity of the pipeline system. This step is a critical quality control link to prevent pipe burst and water leakage accidents after concrete pouring. In specific implementation, connect all circuits in series or in parallel to a pressure test pump, and slowly raise the pressure to 1.5 times the working pressure (usually not less than 0.6 MPa), with the pressure holding and stabilizing time not less than 30 minutes. During this period, if the reading drop of the pressure gauge is no more than 0.02 MPa, and visual inspection shows no leakage or no visible deformation on all joints and pipe bodies, the pressure test is judged to be qualified. Smooth water flow may refer to confirming that there is no foreign blockage in the pipes and no dead folds at the elbows by observing the flow rate and pressure stability at the water outlet. The pipeline distribution information may refer to recording the spatial position data of the cooling water pipes in the concrete structure, including the coordinates of the start and end points of each circuit, the positions of elbows, the positions of valves, and the relative relationship with the temperature measuring points. For example, if an abnormal pressure drop in a certain circuit is found during the pressure test, the leakage point can be located and repaired immediately, and the repair record of this circuit is incorporated into the pipeline distribution information. Through the coordination of the water pressure test and information recording, not only the hidden danger of pipeline failure is eliminated, but also accurate physical topology data is provided for the subsequent intelligent temperature control system, ensuring that the flow regulation instruction can be accurately mapped to a specific spatial area.

[0069] Step 3: Integrate the layout parameters of the cooling water pipes, the pressure test qualification information, and the measuring point distribution information to obtain the basic configuration information of the internal precise temperature control dataset.

[0070] Herein, the layout parameters of the cooling water pipes include geometric and hydraulic characteristic data such as pipe specification, horizontal spacing, vertical spacing, circuit length, and designed flow velocity value; the pressure test qualification information includes quality verification data such as pressure test time, test pressure value, pressure stabilizing duration, pressure drop value, and acceptance conclusion; the measuring point distribution information may refer to the precise three-dimensional coordinates of the embedded temperature sensors and the numbers of the cooling circuits they belong to. The basic configuration information is a structured dataset formed by standardizing, cleaning, correlating and fusing the above multi-source heterogeneous data, which constitutes the digital base map of the internal temperature control system. The function of this information is to provide a spatial coordinate mapping basis for the subsequent real-time temperature field solution, so that the intelligent algorithm can logically bind the measured temperature data with the specific cooling circuits and concrete areas. For example, when the system monitors that the temperature in a certain area rises abnormally, it can quickly retrieve the number of the cooling circuit corresponding to this area and the valve state according to the basic configuration information, and then perform a targeted flow increasing operation. By integrating the layout parameters, pressure test information and measuring point information, the precise alignment between physical entities and digital models is realized, the integrity and traceability of the internal precise temperature control dataset are ensured, and reliable data support is provided for the implementation of the dynamic regulation strategy.

[0071] This application maximizes the heat exchange efficiency of cooling water pipes by employing a serpentine coiling method and strictly controlling the horizontal spacing between 0.9m and 1.2m, combined with vertical spacing matching the thickness of the poured layers. This effectively solves the problems of numerous cooling blind spots and difficulty in temperature difference control under traditional layout methods. Furthermore, a rigorous water pressure testing process eliminates the risk of pipe leakage and blockage in advance, ensuring the reliability of the cooling system during long-term service. Further, the layout parameters, pressure test qualification information, and measuring point distribution information are deeply integrated to construct high-precision basic configuration information, enabling the intelligent temperature control system to perform real-time calculations and decisions based on an accurate physical model. This collaborative mechanism of optimized layout + rigorous pressure testing + data integration not only significantly improves the control accuracy of the internal temperature field of large-volume concrete, reducing the pipe burst accident rate to zero, but also greatly shortens the commissioning cycle of the temperature control system, realizing a closed-loop data chain from construction to intelligent operation and maintenance, ultimately ensuring the crack-resistant quality of the concrete structure.

[0072] Example 8:

[0073] In another optional embodiment, a process for hot water circulation maintenance and coordinated control of internal and external temperature difference provided in this application embodiment includes the following steps: Step 1: Collect the warm water discharged from the cooling water pipes as the curing water source, and construct a cofferdam on the top surface of the concrete to form a water storage and curing area; The collection of warm water discharged from the cooling water pipes refers to the recovery of circulating water flowing out after heat exchange in the internal temperature control system of the concrete. This warm water originates from the cooling water pipe loops installed inside the concrete, and its temperature is usually higher than the ambient temperature, carrying some of the hydration heat from within the concrete. Constructing a cofferdam refers to setting up a water-retaining structure around the top surface of the concrete pouring structure. This cofferdam can be made by extending the edge of the formwork above the concrete surface or by installing reusable lightweight steel water-retaining strips. Its function is to form a closed water storage space, preventing the loss of curing water and ensuring uniform water depth. By combining the recovery of warm water with the construction of a cofferdam, the waste heat is utilized in a tiered manner, avoiding surface cold impact caused by direct spraying of low-temperature water, and providing a stable constant-temperature water bath environment for the concrete surface. For example, when the outlet temperature of the cooling water inside the foundation concrete reaches 32℃, the system automatically guides the water flow into a collection well for filtration, and then pumps it to the top cofferdam area, utilizing the closed space formed by the cofferdam to evenly spread the warm water on the top surface. This significantly improves the utilization rate of curing water and effectively isolates the direct impact of external temperature fluctuations on the concrete surface.

[0074] Step 2: Control the curing water temperature between 30℃ and 35℃, and maintain the water depth at a stable level of 10cm to 15cm to reduce the cold impact stress on the concrete surface. The curing water temperature refers to the temperature of the water stored within the cofferdam on top of the concrete. This temperature is dynamically set by adjusting the flow rate and speed of the replenishing hot water, aiming to ensure that the difference between the curing water temperature and the surface temperature of the concrete after initial setting is less than 7°C, thereby avoiding the critical threshold of cold shock. The water depth refers to the vertical height of the water layer within the cofferdam. This depth is calculated based on the concrete surface area and heat dissipation requirements, ensuring sufficient heat capacity to buffer temperature fluctuations. Maintaining the curing water temperature between 30°C and 35°C and the water depth between 10cm and 15cm ensures that the concrete surface is in a mild, humid environment, preventing tensile stress caused by rapid surface shrinkage due to excessive temperature differences. Specifically, when the water temperature in the storage tank is detected to be below 30°C, the system increases the supply of high-temperature drainage from the internal cooling circuit; when the water level drops below 10cm due to evaporation, the water replenishment pump is automatically activated to maintain the liquid level. For example, in high-temperature summer environments, by continuously replenishing 34°C circulating warm water and maintaining a water depth of 12cm, the temperature fluctuation range of the concrete surface can be reduced to within ±0.8°C. This constant temperature and depth control method can reduce surface cold impact stress by 83%, effectively preventing the formation of surface cracks.

[0075] Step 3: Real-time collection of maintenance water temperature, surface temperature, and internal temperature; dynamic adjustment of hot water supply; continuous reduction of internal and external temperature difference; and determination of maintenance progress and termination conditions based on changes in temperature control data.

[0076] Real-time data acquisition refers to periodically obtaining thermal state data of different parts of the concrete through a pre-embedded temperature sensor network, including the water temperature in the reservoir, the surface temperature 5cm below the concrete surface, and the internal temperature of the core area. Dynamic adjustment of hot water supply refers to the intelligent control system automatically adjusting the speed of the hot water circulation pump or the opening of the water supply valve based on the real-time collected internal surface temperature difference data, thereby changing the flow rate of hot water injected into the cofferdam per unit time. Determining the curing progress and termination conditions refers to logically judging whether the criteria for stopping water supply for curing are met based on the temperature difference trend and the rate of internal temperature decrease over a continuous time period. Through the synergistic effect of real-time acquisition of multi-source temperature data and dynamic adjustment of supply, a closed-loop control mechanism of monitoring-analysis-execution is constructed, ensuring that the internal surface temperature difference is always controlled within a safe range (e.g., less than 25℃), and that curing is terminated in a timely manner when the temperature field tends to stabilize to save energy. For example, when the system detects that the internal surface temperature difference is close to 24°C, it automatically increases the supply ratio of high-temperature hot water to raise the surface temperature and reduce the temperature difference. When the internal surface temperature difference is less than 20°C for 24 consecutive hours and the internal temperature shows a steady downward trend, the system automatically determines that the termination condition has been met and gradually stops the hot water supply. This achieves refined control of the curing process, ensuring that no harmful temperature cracks occur on the surface or inside the concrete.

[0077] This application utilizes warm water discharged from cooling water pipes as a curing water source and constructs a cofferdam on the top surface of the concrete to form a water-storage curing area. This achieves resource utilization of internal heat dissipation and avoids the thermal shock risks associated with traditional cold water curing. Furthermore, by strictly controlling the curing water temperature between 30℃ and 35℃ and maintaining a stable water depth of 10cm to 15cm, a stable surface constant-temperature layer is constructed using the high specific heat capacity of water, significantly reducing cold impact stress on the concrete surface. Moreover, by real-time acquisition of curing water temperature, surface temperature, and internal temperature data, the system can dynamically adjust the hot water supply, forming an active control mechanism for the internal and external temperature differences, ensuring a continuous reduction in the internal and external temperature gradient. Finally, based on the real-time trend of temperature control data, the curing process and termination conditions are scientifically determined, ensuring not only the healthy development of concrete strength but also significantly reducing curing energy consumption, achieving a dual improvement in crack prevention and green construction.

[0078] Example 9:

[0079] In one optional implementation, a process for determining the maintenance process and termination conditions is provided in the embodiments of this application. The method includes specific steps for determining the maintenance process and termination conditions based on changes in temperature control data.

[0080] Step 1: When the temperature difference between the inner surface and the outer surface is less than 20°C for 24 consecutive hours and the internal temperature continues to drop steadily, the maintenance termination condition is automatically met. Among them, the internal surface temperature difference refers to the difference between the highest measuring point temperature inside the concrete and the temperature of a representative measuring point on the surface. This indicator directly reflects the temperature gradient within the concrete section and the resulting tensile stress risk. The continuous 24-hour period is a stability criterion in the time dimension, used to eliminate transient temperature interference caused by fluctuations in ambient temperature, rainfall, or short-term water supply, ensuring the robustness of the judgment results. The continuous and stable decrease in internal temperature can refer to the highest internal temperature showing a monotonically decreasing trend over time, and the cooling rate being controlled within a preset safety threshold (such as 2℃ / day), indicating that the peak of cement hydration heat release has passed and the structure has entered a stable heat dissipation and contraction period.

[0081] Specifically, the intelligent temperature control system collects and calculates the internal surface temperature difference data at each temperature measurement point in real time. When the internal surface temperature difference value of any key section is detected to be below the safety threshold of 20℃, and this state is not broken within 24 consecutive sampling cycles (sampling once per hour), and the slope of the highest internal temperature curve is negative and there is no rebound, the system automatically triggers the curing termination logic. For example, if the internal surface temperature difference of a certain foundation center area remains in the range of 15℃~18℃ from 08:00 on day 10 to 08:00 on day 11, and the internal temperature steadily drops from 45℃ to 41℃ without any temperature fluctuation, the system determines that the tensile strength of the concrete is sufficient to resist the remaining temperature stress, meeting the conditions for stopping active water cooling and hot water circulation. Through this automatic judgment mechanism based on dual conditions (temperature difference threshold + time duration + temperature trend), the subjectivity and lag of human experience judgment are effectively avoided, preventing delayed cracks caused by stopping curing too early or waste of water and energy resources caused by stopping too late.

[0082] Step 2: Record all data on aggregate precooling, mold temperature, internal temperature control, and hot water curing throughout the process to form a complete and traceable quality ledger; The data collection system comprehensively records the entire lifecycle of concrete, from raw material pre-cooling upon arrival, through mixing, transportation, pouring, internal cooling, and surface curing. Aggregate pre-cooling data includes source temperature control information such as silo ambient temperature, measured temperatures of each aggregate layer, and refrigeration unit operating parameters. Formwork temperature data includes process control information such as mixer outlet temperature, temperature rise during transportation, and multi-point formwork temperature at the pouring surface. Internal temperature control data involves core monitoring information such as cooling water pipe layout parameters, inlet and outlet water temperatures and flow rates for each loop, three-dimensional temperature field distribution within the concrete, internal and external temperature differences, and cooling rates. Hot water curing data includes terminal drainage information such as reservoir water temperature, water level depth, water replenishment volume, and curing duration. Furthermore, the data acquisition and control system standardizes, cleans, and structures the aforementioned multi-source heterogeneous data, establishing a complete quality ledger indexed by time and spatial measurement points. For example, the ledger not only records the average temperature for a specific period but also links it to corresponding cooling water flow adjustment commands, environmental meteorological parameters, and equipment operation status logs. This comprehensive, real-time data archiving method enables digital traceability of construction process quality, allowing any temperature anomaly to be traced back to the specific batch of raw materials, equipment condition, or operational step. This provides solid data support for subsequent quality responsibility tracing and also meets the stringent requirements of modern engineering for the integrity and searchability of electronic archives.

[0083] Step 3: Based on the complete quality record, determine whether the temperature control indicators meet the standards, identify the quality conclusion that there are no harmful temperature cracks, and generate a crack prevention quality analysis report.

[0084] Among them, the temperature control index compliance status is a process of comparing the measured data in the quality log with the design specifications and preset control targets (such as internal maximum temperature <75℃, internal surface temperature difference <25℃, cooling rate <2℃ / day, etc.) item by item; the quality conclusion of no harmful temperature cracks is a qualitative evaluation based on the temperature control compliance rate, temperature stress evolution trend and on-site visual inspection results, which aims to confirm that the concrete structure has not produced penetrating temperature cracks or temperature cracks that affect durability; the crack prevention quality analysis report is the final documented output, which integrates data statistics charts, over-standard early warning records, review of treatment measures and final quality assessment conclusions.

[0085] Specifically, the system automatically traverses the complete quality log, calculates the pass rate of various temperature control indicators, and if all key indicators are within the allowable deviation range and the temperature field evolution conforms to the expected pattern, it automatically generates a preliminary conclusion that there are no harmful temperature cracks. This conclusion is then combined with surface crack observation records (if any) entered during manual inspections for final verification. For example, the report can generate a temperature-time history curve, visually displaying the time of the internal temperature peak and its downward trend, and marking the periods when the internal surface temperature difference exceeds the warning value and the corresponding flow regulation response records, proving the effective intervention of the temperature control system. The final report not only serves as the core quality certificate for project completion acceptance but also provides valuable data assets for mix ratio optimization and temperature control strategy improvement in similar projects.

[0086] This application establishes dual automatic termination conditions: a continuous internal surface temperature difference of less than 20°C for 24 hours and a steady decrease in internal temperature. By utilizing the continuity of time, it filters out instantaneous interference, ensuring the scientific and safe selection of the curing termination time and fundamentally eliminating the risk of secondary cracking caused by premature removal of curing measures. Based on this, a traceable quality ledger is constructed through complete recording and structured archiving of data from aggregate pre-cooling, mold placement temperature, internal temperature control, and hot water curing, achieving a closed-loop data chain from source to end. Furthermore, automated indicator comparison and quality conclusion identification based on this ledger transform scattered monitoring data into a legally valid crack-prevention quality analysis report. This not only objectively verifies the quality of the engineering entity free of harmful temperature cracks but also significantly improves the informatization level of quality management and the efficiency of accountability traceability, ensuring the long-term durability and service safety of large-volume concrete structures in large bridges.

[0087] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0088] Figure 3 A schematic diagram of a quality data analysis system for bridge concrete pouring process provided in an embodiment of this application is shown below. Figure 3 As shown, the bridge concrete pouring process quality data analysis system 300 of this embodiment includes: a source precooling module 301, a concrete pouring module 302, an internal temperature control module 303, and a curing coordination module 304.

[0089] The source precooling module 301 is used to carry out intelligent precooling control and temperature acquisition of aggregates, establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset of casting source temperature control. The concrete placement module 302 is used to carry out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying and placement, based on the temperature control basic dataset at the pouring source, and to generate a stable data set of placement quality. The internal temperature control module 303 is used to perform real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow based on the stable data set of the mold entry quality, and generate an internal precise temperature control data set. The maintenance collaboration module 304 is used to carry out hot water circulation maintenance and coordinated control of internal and external temperature differences based on the internal precise temperature control dataset, and generate a concrete crack prevention quality analysis report.

[0090] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A method for analyzing quality data during the concrete pouring process of bridges, characterized in that, include: Intelligent pre-cooling control and temperature acquisition of aggregates are carried out to establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset of temperature control at the casting source. Based on the aforementioned basic dataset of temperature control at the pouring source, we carry out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying and placement, and generate a dataset of stable placement quality. Based on the aforementioned stable data set of concrete injection quality, real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow are carried out to generate a precise internal temperature control data set. Based on the aforementioned internal precise temperature control dataset, hot water circulation curing and coordinated control of internal and external temperature differences are carried out to generate a concrete crack prevention quality analysis report. The aforementioned implementation of coordinated temperature control and deviation correction throughout the entire process of concrete mixing, conveying, and placement includes: Mix the aggregates in the order of cooling them first and then adding the cementitious materials, and extend the mixing time to ensure that the concrete is mixed evenly and the temperature is stable. The concrete discharge temperature is monitored in real time at the mixer discharge port, and the pouring temperature is collected at multiple points on the pouring surface to keep the pouring temperature stable below 28℃. By comparing the deviation between the concrete discharge temperature and the concrete placement temperature, the influence of temperature fluctuations in the mixing and transportation stages is corrected, and the pouring process is precisely controlled according to preset rules to obtain the stable data set of placement quality. The aforementioned real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow include: The internal cooling water pipes of the concrete were laid out and pressure tested according to the preset layout specifications. Several layers of temperature sensors were also installed to collect data on the highest internal temperature, surface temperature, and corner temperature of the concrete in real time. The system automatically calculates the internal surface temperature difference and cooling rate, keeping the maximum internal temperature below 75℃, the internal surface temperature difference below 25℃, and the cooling rate below 2℃ / day. The cooling water flow rate of each cooling circuit is adjusted independently based on the calculation results. The flow rate is increased in the high-temperature area and decreased in the stable cooling area to form the internal precise temperature control dataset. The aforementioned implementation of hot water circulation maintenance and coordinated control of internal and external temperature differences includes: The warm water discharged from the cooling water pipes is collected as a curing water source, and a cofferdam is constructed on the top surface of the concrete to form a water storage and curing area. The curing water temperature is controlled between 30℃ and 35℃, and the water depth is kept stable at 10cm to 15cm to reduce the cold impact stress on the concrete surface. The system collects maintenance water temperature, surface temperature, and internal temperature in real time, dynamically adjusts the hot water supply, continuously reduces the temperature difference between the internal and external surfaces, and determines the maintenance process and termination conditions based on changes in temperature control data.

2. The method according to claim 1, characterized in that, The intelligent pre-cooling control and temperature acquisition of aggregates includes: An insulated and enclosed silo was constructed and an air curtain machine was installed to block heat exchange between the inside and outside of the silo. Cold air was delivered into the silo through a linkage between an evaporative air cooler and a refrigeration unit. Temperature sensors are installed in the upper, middle, and lower layers of the aggregate stockpile, as well as at the center and edges, to collect the actual temperature of the aggregate and the ambient temperature of the silo in real time. The aggregate temperature is stably controlled within 15℃, and the temperature difference between aggregates in different locations is controlled within 3℃, thus forming aggregate raw materials that meet the low temperature requirements. The actual temperature of the aggregate, the ambient temperature of the silo, and the operating data of the refrigeration equipment are integrated and stored to obtain the basic dataset for temperature control at the casting source. The raw material temperature control is then managed and controlled across the entire range using the basic dataset for temperature control at the casting source.

3. The method according to claim 2, characterized in that, The process of implementing comprehensive temperature control management of raw materials based on the basic dataset for temperature control at the pouring source includes: The cementitious materials are brought to the site in advance and allowed to stand to dissipate heat. The powder tank is also sprayed to cool it down, so that the material temperature is controlled below 45℃. The mixing water is cooled by a chiller unit and ice is added to the water tank to continuously reduce the temperature of the mixing water, while real-time temperature data of various raw materials are collected simultaneously. The real-time temperature data of the raw materials is matched and calculated with the preset pre-cooling data of aggregates to form the basic dataset for temperature control at the pouring source, which serves to predict the temperature of concrete exiting the machine.

4. The method according to claim 1, characterized in that, The precise control of the pouring process according to preset rules includes: Concrete pouring is carried out in a layered and sequential manner, with the thickness of each layer controlled between 30cm and 50cm, thus forming pouring layer information. During the pouring process, environmental parameters and real-time temperature data of the mold are continuously monitored to maintain a stable temperature of the mold without sudden changes. The pouring layer information, the environmental parameter data, and the real-time temperature data of the mold entry are stored in a unified manner to provide stable data support for internal temperature control.

5. The method according to claim 4, characterized in that, The installation and pressure testing of the internal cooling water pipes of the concrete according to the preset layout specifications includes: Cooling water pipes are laid out in a serpentine coil pattern inside the concrete, with the horizontal spacing controlled between 0.9m and 1.2m, and the vertical spacing matched to the thickness of each pouring layer. Perform a water pressure test on the cooling water pipes to ensure that there are no leaks and that the water flows smoothly, and record the pipe distribution information; By integrating the cooling water pipe layout parameters, pressure test qualification information, and measuring point distribution information, the basic configuration information of the internal precise temperature control dataset is obtained.

6. The method according to claim 1, characterized in that, The method of determining the maintenance process and termination conditions based on changes in temperature control data includes: When the temperature difference between the inner surface and the outer surface is less than 20°C for 24 consecutive hours and the internal temperature continues to drop steadily, the maintenance termination conditions are automatically met. All data on aggregate precooling, mold temperature, internal temperature control, and hot water curing are recorded throughout the process to form a complete and traceable quality ledger; Based on the complete quality ledger, the temperature control indicators are determined to meet the standards, the conclusion that there are no harmful temperature cracks is identified, and the crack prevention quality analysis report is generated.

7. A quality data analysis system for bridge concrete pouring process, characterized in that, The method applied to any one of claims 1-6 includes: The source precooling module is used to carry out intelligent precooling control and temperature acquisition of aggregates, establish the correlation characteristics between aggregate temperature and initial heat release, and generate a basic dataset of casting source temperature control. The concrete placement module is used to carry out coordinated temperature control and deviation correction throughout the entire process of concrete mixing, transportation and placement, based on the aforementioned temperature control dataset at the pouring source, and to generate a stable data set of placement quality. The internal temperature control module is used to perform real-time calculation of the internal temperature field of concrete and dynamic adjustment of cooling water flow based on the stable data set of the molded concrete quality, and generate an internal precise temperature control data set. The maintenance collaboration module is used to carry out hot water circulation maintenance and coordinated control of internal and external temperature differences based on the internal precise temperature control dataset, and generate a concrete crack prevention quality analysis report.

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