Method for preventing early cracking of mass concrete

Abstract

The embodiment of the invention provides a method for preventing early cracking of mass concrete. The method comprises the following steps: selecting high-performance cement, reasonably controlling the water-cement ratio, doping 10%-20% of a high-activity mineral admixture, adding 0.5%-1% of high-strength fibers and a proper amount of an early strength agent; concrete is sprayed in a reasonable pouring mode, micro-prestressed steel bars are arranged, temperature sensors are embedded to monitor temperature changes in real time so as to obtain the temperature gradient, and the construction environment is controlled to avoid extreme temperature; constant-temperature wet curing is adopted for not less than 14 days, and the surface of the concrete is covered with a moisturizing material; and optimizing the range and priority of the temperature regulation and control region based on the temperature gradient distribution. According to the scheme of the embodiment of the invention, early cracking of mass concrete caused by overlarge temperature gradient due to hydration heat accumulation and environment temperature change in the construction process can be prevented.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building construction, in particular to a method for preventing early cracking of mass concrete. BACKGROUND

[0002] In the field of building construction, mass concrete structures have attracted much attention due to their wide application in many important projects such as large infrastructure and high-rise building foundations. However, the problem of early cracking of mass concrete has been a major challenge for the engineering community, posing a serious threat to the durability, safety and functionality of structures, and urgently needs in-depth research and effective solutions.

[0003] Mass concrete structures usually have large dimensions and generate a significant amount of internal hydration heat. During the early stage after concrete pouring, the cement hydration reaction proceeds rapidly, releasing a large amount of heat. Due to the difference in heat dissipation conditions between the interior and surface of the concrete, the internal temperature rises significantly, while the surface temperature is relatively low, resulting in the generation of internal and external temperature difference. When the internal and external temperature difference reaches a certain level, the internal concrete will generate expansion stress, while the surface will generate shrinkage stress. If these stresses exceed the tensile strength of the concrete itself, early cracking is likely to occur.

[0004] In addition, mass concrete also faces the problem of drying shrinkage in the early stage. During the hardening process of concrete, internal moisture gradually evaporates, and the cement stone structure shrinks. Due to the relatively long internal evaporation path of mass concrete, the internal shrinkage is inconsistent with the surface shrinkage, further increasing the risk of cracking. Moreover, factors such as the quality of concrete raw materials, mix proportion design and construction technology also have important influence on early cracking. For example, the use of low-quality cement, aggregate or admixture may lead to an increase in internal structural defects of concrete, reducing its crack resistance; unreasonable mix proportion design, such as excessive water-cement ratio or improper sand ratio, will reduce the strength and durability of concrete, increasing the possibility of early cracking; and insufficient compaction during construction process and inadequate curing measures, etc., also create conditions for the occurrence of cracks.

[0005] Once early cracking occurs, it not only affects the appearance quality of the concrete structure, but more importantly, it destroys the integrity and compactness of the structure. This makes it easier for harmful substances such as moisture and chloride ions to enter the interior of the concrete, accelerating the corrosion of steel bars, reducing the load-carrying capacity and durability of the structure, shortening the service life of the project, and causing huge economic losses and safety hazards to the construction project. SUMMARY

[0006] Therefore, the present application provides a method for preventing early cracking of mass concrete, at least partially solving the problems existing in the prior art.

[0007] A method for preventing early cracking of mass concrete according to the present application comprises the following steps:

[0008] Selecting high-performance cement, reasonably controlling water-cement ratio, adding 10%-20% of high-activity mineral admixtures, adding 5%-1% of high-strength fibers, and adding appropriate early strength agent;

[0009] Spraying concrete with reasonable pouring method, setting up micro-prestressed steel bars, burying temperature sensors to monitor temperature changes in real time to obtain temperature gradient, and controlling construction environment to avoid extreme temperature;

[0010] Using constant temperature and humidity curing for no less than 14 days, and covering moisture-retaining materials on the surface of the concrete;

[0011] Optimizing the range and priority of the temperature regulation area based on the temperature gradient distribution.

[0012] Preferably, the step of optimizing the range and priority of the temperature regulation area based on the temperature gradient distribution further comprises:

[0013] Generating a temperature gradient distribution map according to real-time temperature sensor data;

[0014] Dividing key regulation areas based on the size of the temperature gradient, the larger the gradient, the smaller the area range;

[0015] Setting area priority, the higher the gradient, the higher the priority;

[0016] If the maximum temperature gradient G_max is greater than the critical threshold G_th, mark the area as the highest priority and prioritize regulation; wherein G_max represents the maximum temperature gradient value monitored, and G_th represents the preset safety temperature gradient critical value.

[0017] Preferably, the step of dividing key regulation areas based on the size of the temperature gradient further comprises:

[0018] Calculating the average temperature gradient G_avg of each area;

[0019] Determining the area boundary based on the relationship between G_avg and the overall distribution;

[0020] Defining the area with G_avg greater than the overall average as a key regulation area;

[0021] If G_avg > G_overall × f, then reduce the area range to focus on regulation, wherein G_avg represents the average temperature gradient of the area, G_overall represents the overall average temperature gradient, f represents an adjustment factor, and f > 1.

[0022] Preferably, the step of determining the region boundary based on the relationship between G_avg and the overall distribution further comprises:

[0023] analyzing the standard deviation σ of the temperature gradient distribution;

[0024] adjusting the region division precision based on the size of σ;

[0025] setting the region boundary as G_avg ± k × σ, where k is a range coefficient;

[0026] if σ > σ_th, increasing the value of k to expand the boundary range; where σ represents the standard deviation of the temperature gradient distribution, σ_th represents the threshold of the standard deviation, and k represents the dynamically adjusted range coefficient.

[0027] Preferably, the step of adjusting the region division precision based on σ further comprises:

[0028] obtaining the value of σ and the current division precision P;

[0029] updating P based on the rate of change of σ R_σ;

[0030] calculating the new precision P_new = P × (1 + m × R_σ), where m is a sensitivity coefficient;

[0031] if R_σ > 0 and σ > σ_min, increasing the value of m, where R_σ represents the rate of change of the standard deviation, σ_min represents the minimum standard deviation reference value, and m is used to adjust the precision adjustment amplitude.

[0032] Preferably, the step of updating P based on the rate of change of σ R_σ further comprises:

[0033] monitoring the change of σ over time;

[0034] calculating R_σ = (σ_current-σ_previous) / Δt based on historical σ data;

[0035] adjusting the division precision P according to the positive or negative of R_σ;

[0036] if R_σ > R_max, preferentially increasing the division precision P to improve the response speed, where R_σ represents the rate of change of the standard deviation, R_max represents the maximum allowed rate of change, and Δt represents the time interval.

[0037] Preferably, the step of setting the region priority, with the region having a higher gradient having a higher priority, further comprises:

[0038] a priority score S = a × G + b × A is assigned to each zone, where G represents the zone temperature gradient value, A represents the zone area, and a and b are weight coefficients;

[0039] The zone priority is ranked based on the S value;

[0040] The regulation resources are preferentially allocated to the zones with high S values;

[0041] If S > S_th, the instant regulation measure is started; wherein S_th represents the priority score threshold value.

[0042] Preferably, the step of ranking the zone priority based on the S value further comprises:

[0043] The S values of all zones are collected;

[0044] The ranking threshold value T_sort is calculated based on the S value distribution;

[0045] The zones are ranked from high to low S value;

[0046] If S_max-S_min > D, the T_sort is set as a dynamic value, wherein S_max represents the highest priority score, S_min represents the lowest priority score, and D represents the score difference threshold value.

[0047] Preferably, the step of calculating the ranking threshold value T_sort based on the S value distribution further comprises:

[0048] The average value S_avg and the variance V of the S values are analyzed;

[0049] The T_sort = S_avg + c × √V is determined based on the size of V, wherein c is an adjustment coefficient;

[0050] The high priority zones are screened by applying the T_sort;

[0051] If V > V_th, the c value is increased, wherein V represents the priority score variance, V_th represents the variance threshold value, and c is used to amplify the threshold value range.

[0052] Preferably, the step of determining the T_sort based on the size of V further comprises:

[0053] The V value and the current c are obtained;

[0054] The c is adjusted based on the environmental temperature T_env;

[0055] The T_sort = S_avg + c × √V is calculated;

[0056] If T_env > T_ref, set c as c_high, where T_env represents an environmental temperature, T_ref represents a reference temperature, and c_high represents an adjustment coefficient at a high temperature.

[0057] The method for preventing early cracking of mass concrete provided by the embodiments of the present disclosure includes the following steps: selecting high-performance cement, reasonably controlling water-cement ratio, adding 10%-20% of high-activity mineral admixture, adding 5%-1% of high-strength fiber, and adding an appropriate amount of early strength agent; spraying concrete by using a reasonable pouring method, setting micro-prestressed steel bars, burying temperature sensors to monitor temperature changes in real time to obtain a temperature gradient, and controlling a construction environment to avoid extreme temperatures; adopting constant temperature and humidity curing for no less than 14 days, and covering a moisture-retaining material on a concrete surface; and optimizing the range and priority of a temperature regulation area based on the temperature gradient distribution. Through the scheme of the embodiments of the present disclosure, early cracking of mass concrete caused by excessive temperature gradient due to accumulation of hydration heat and changes in environmental temperature during the construction process can be prevented. BRIEF DESCRIPTION OF DRAWINGS

[0058] In the drawings, like reference numerals designate like or similar parts throughout the several views, and the reference numerals with altered alphabetic suffixes designate variations among like parts unless otherwise specified. The drawings are not necessarily to scale, and the various depicted geometric shapes are meant to be idealized representations that can not be drawn to scale. It is to be understood that the drawings only depict some embodiments in accordance with the present disclosure and should not be considered to be limiting of the scope of the present disclosure.

[0059] Figure 1 is a flowchart of a method for preventing early cracking of mass concrete;

[0060] Figure 2 is a flowchart of optimizing the range and priority of a temperature regulation area based on a temperature gradient distribution;

[0061] Figure 3 is a flowchart of dividing a key regulation area based on the size of a temperature gradient;

[0062] Figure 4 is a flowchart of determining the boundary of an area based on the relationship between G_avg and the overall distribution;

[0063] Figure 5 is a flowchart of adjusting the accuracy of area division based on the size of σ;

[0064] Figure 6 is a flowchart of updating P based on the change rate R_σ of σ;

[0065] Figure 7 is a flowchart of setting the priority of an area, with a higher priority for an area with a higher gradient;

[0066] Figure 8is a flow chart based on S value ranking region priority;

[0067] Figure 9 is a flow chart based on S value distribution calculation ranking threshold T_sort;

[0068] Figure 10 is a flow chart based on V size to determine T_sort. DETAILED DESCRIPTION

[0069] For the purposes of the present disclosure embodiments, the technical solutions and advantages are more clearly and clearly understood, the present disclosure embodiments are further described below in conjunction with examples and drawings, the illustrative embodiments of the present disclosure and its description are only used to explain the present disclosure embodiments, and are not as a limitation of the present disclosure embodiments.

[0070] Next, referring to Figure 1 , a method for preventing early cracking of mass concrete is described, which includes four key steps that specifically address the problem of excessive temperature gradient caused by accumulated hydration heat and environmental temperature changes during construction of mass concrete, thereby effectively preventing early cracking.

[0071] S101: Select high-performance cement, reasonably control water-cement ratio, mix in 10%-20% high-activity mineral admixture, add 0.5%-1% high-strength fiber, and appropriate early strength agent; in specific operation, first select high-performance cement such as 52.5 grade Portland cement, control water-cement ratio in the range of 0.35-0.45 (mass ratio) to reduce porosity, then mix in silica fume or mineral powder as high-activity mineral admixture to enhance the activity of cementitious materials; then add high-strength fibers such as polypropylene fibers or basalt fibers, mix evenly to improve the tensile toughness of concrete; finally, mix in an appropriate amount of early strength agent such as calcium chloride or sulphoaluminate to accelerate the initial hydration reaction.

[0072] For example, in a large bridge foundation construction example, high-performance cement can be selected to control the water-cement ratio to 0.4, mix in 15% silica fume to improve activity, add 0.8% polypropylene fiber to enhance tensile performance, and add 0.3% calcium chloride early strength agent; this operation significantly improves the early tensile strength of concrete, reduces the volume shrinkage caused by the accumulation of hydration heat, and directly improves the initial crack resistance of concrete by optimizing the material mix ratio, thereby alleviating the stress concentration problem caused by temperature gradient.

[0073] S102: Pouring concrete with reasonable pouring method, setting up micro-prestressed reinforcement, burying temperature sensors to monitor temperature changes in real time to obtain temperature gradient, and controlling construction environment to avoid extreme temperature; Specific operations include using, for example, jet pouring technique to ensure uniform and dense concrete and avoid stratification; Arranging micro-prestressed reinforcement such as low-carbon steel reinforcement with a diameter of 6 mm before pouring to apply a prestress of 5-10 MPa to enhance the tensile capacity; At the same time, burying temperature sensors in the interior and surface of the concrete and connecting a monitoring system to collect temperature data in real time to obtain temperature gradient data; Specifically, during the pouring process of the concrete, multiple temperature sensors (such as thermocouples or optical fiber sensors) can be pre-buried at key positions (such as different depths or regions) of the structure and connected to a real-time data acquisition system (such as a wireless transmission module or a data logger) for continuous sampling and transmission of temperature data; Real-time analysis of these data through monitoring software, comparison of temperature values of different sensor points, calculation of temperature gradient (i.e. the rate of change of temperature with position), and thus dynamic tracking of the temperature distribution inside the concrete; And controlling the construction environment, maintaining the temperature in the range of 10-30°C by building sunshades or using a cooling water circulation system.

[0074] Specifically, in one dam construction embodiment, the concrete can be poured in a jetting manner to ensure overall density without gaps; A network of micro-prestressed reinforcement is set up to apply a prestress of 8 MPa to compensate for shrinkage stress; Multiple temperature sensors are buried, data is read every 2 hours, and temperature retention measures are adjusted through software; In terms of environmental control, construction is avoided during the high-temperature period of summer; These measures directly reduce the excessive temperature gradient caused by hydration heat accumulation and environmental temperature changes through real-time monitoring and prestress compensation, and reduce the risk of thermal stress concentration and early cracking.

[0075] S103: Adopting constant temperature and humidity curing for no less than 14 days, and covering moisture-retaining materials on the surface of the concrete. In specific operation, constant temperature and humidity curing is implemented, the temperature is maintained at 20±2°C, the humidity is greater than 90%, and the duration is at least 14 days to ensure uniform hydration reaction; At the same time, moisture-retaining materials such as wet burlap or plastic film are covered, and water is sprayed regularly to maintain surface moisture.

[0076] For example, in one tunnel lining project, the temperature is controlled at 20°C during the curing stage, the humidity is 95%, double-layer wet burlap is covered, and water is sprayed every 4 hours; This operation ensures uniform hydration inside the concrete, reduces internal stress caused by water loss shrinkage, and effectively prevents crack propagation caused by temperature fluctuations by maintaining a stable environment. Overall, this method solves the early cracking problem of mass concrete by optimizing materials to enhance early tensile strength, controlling thermal stress during construction, and ensuring uniform hydration through curing.

[0077] In the present application, the high-activity mineral admixture can be silica fume or fly ash. The addition of mineral materials with high reactivity in concrete, specifically silica fume or fly ash, accelerates the hydration process and improves the early tensile strength of concrete, thereby reducing the risk of cracking due to temperature gradients. These admixtures enhance the activity of cementitious materials, optimize the microstructure, and improve the overall durability of concrete. Specifically, in one embodiment, for example, when constructing large infrastructure such as dams, the addition of 10%-20% silica fume to the concrete mix can significantly improve the early tensile strength and prevent shrinkage cracking caused by the accumulation of hydration heat.

[0078] In addition, the high-strength fibers can be polypropylene fibers or basalt fibers. By incorporating these fiber materials, the tensile properties of concrete are enhanced, internal stresses are dispersed, thereby inhibiting crack formation and improving the durability and overall stability of the structure. For example, in one embodiment, basalt fibers are added to the mixture at a rate of 0.7% by weight before concrete spraying construction to prevent early cracking in mass concrete bridge foundations. The fiber length is controlled within the range of 12-18 mm, with an optimal value of 15 mm. During the spraying process, the fibers are uniformly distributed to absorb temperature shrinkage stress and reduce the risk of cracking caused by hydration heat.

[0079] In addition, calcium chloride or sulphoaluminate can also be used as an early strength agent to accelerate the initial hydration reaction of concrete and improve the early tensile strength, thereby reducing the risk of shrinkage cracking caused by temperature gradients. These early strength agents promote cement hydration, shorten the setting time, and enhance the initial strength stability of concrete. For example, in one embodiment, the addition of 1% calcium chloride early strength agent during the construction of mass concrete bridge foundations can ensure rapid hardening of the concrete within 24 hours after pouring, reduce early cracking caused by environmental temperature fluctuations, and improve structural durability.

[0080] In addition, in the present application, the dosage of early strength agent is controlled within an appropriate range to balance the acceleration of hydration and avoid side effects (such as chloride ion corrosion), ensuring the optimization of concrete performance. Specifically, the dosage range is typically 0.5%-2% of the weight of cementitious materials, with an optimal value of 1%, which maximizes the early strength improvement while preventing the increase in brittleness caused by excessive reaction. For example, in dam concrete construction, the use of 1% sulphoaluminate early strength agent, combined with temperature monitoring, effectively reduces internal stress caused by the accumulation of hydration heat and prevents cracking.

[0081] Additionally, the mineral admixture is incorporated in an amount of 10-20% to increase the cementitious material activity and early tensile strength, thereby reducing the risk of cracking due to hydration heat. Specifically, the meaning of the incorporation amount parameter is the weight percentage of the mineral admixture in the cementitious material (including cement and admixture), and the range is set to 10-20%, and the optimal value is usually around 15% to balance the enhancement effect and the workability of the concrete. The range is set in this way because less than 10% may not be able to fully activate the hydration reaction to improve the early strength, and more than 20% may reduce the flowability of the concrete or increase the cost, so the range ensures effective inhibition of early cracking while maintaining construction feasibility. For example, in one embodiment, when used for dam foundation construction, 15% of silica fume is added to the high-performance cement-based cementitious material, and the water-cement ratio is controlled to be 0.4, which can significantly improve the 7-day tensile strength of the concrete to more than 2.5 MPa, reducing shrinkage cracks caused by temperature gradient.

[0082] Additionally, in the present application, the added high-strength fiber is added in an amount of 0.5-1%. By incorporating a specific proportion of high-strength fiber, such as polypropylene fiber or basalt fiber, in the concrete, the tensile capacity of the concrete is enhanced, and the internal stress is dispersed, thereby reducing the risk of early cracking; too low (less than 0.5%) cannot effectively improve the tensile strength, and too much (more than 1%) may cause the flowability of the concrete to decrease or the cost to increase, so the range of 0.5-1% ensures the balance between the anti-cracking effect and the construction feasibility, and the optimal value can be 0.8% to achieve the best performance. For example, in one embodiment, when applied to mass concrete construction for large bridge foundation, 0.8% of basalt fiber is added, and other measures such as optimizing the water-cement ratio and constant temperature curing are taken, which significantly improves the early tensile strength and reduces cracks caused by temperature shrinkage.

[0083] Additionally, during the curing process of the concrete, wet burlap or plastic film is covered on the surface of the concrete to prevent early water loss from causing shrinkage cracking and to maintain the uniformity of the hydration reaction, thereby reducing thermal stress concentration and cracking risk. The meaning of this step is to reduce water evaporation through a physical barrier to ensure that the internal hydration process of the concrete proceeds stably, avoid volume shrinkage and stress accumulation caused by drying, and ultimately improve the early tensile strength and overall durability of the concrete. For example, in one embodiment, after the mass concrete construction for large bridge foundation, plastic film is immediately laid on the surface of the concrete to cover it evenly to avoid local drying; specifically, when the ambient temperature is high, the plastic film can effectively isolate the external air and maintain a constant humidity, combined with constant temperature and humidity curing for no less than 14 days, which significantly reduces the early cracking phenomenon and improves the structural stability.

[0084] In addition, in the present application, during the concrete construction process, the temperature difference between the inside and outside of the concrete is adjusted by using thermal insulation or cooling means to reduce the thermal stress concentration caused by temperature changes, thereby preventing early cracking. Specifically, the thermal insulation measure refers to covering thermal insulation materials to slow down heat loss, and the cooling measure refers to introducing cooling medium to reduce the temperature rise rate, the purpose is to maintain the temperature gradient within a safe range and avoid excessive concrete volume shrinkage.

[0085] For example, in one embodiment, when applied to mass concrete foundation construction, the internal temperature is monitored in real time after pouring concrete. If the temperature gradient exceeds 20°C, thermal insulation is performed by covering thermal insulation blankets, or cooling is performed by pre-embedding cooling water pipes in the concrete to circulate cold water. This effectively controls the accumulation of hydration heat and reduces the risk of cracking.

[0086] S104: optimizing the range and priority of the temperature regulation area based on the temperature gradient distribution, which aims to solve the problem of excessive temperature gradient caused by hydration heat accumulation and environmental temperature changes. The specific operation involves using the sensor data buried in step S102 to draw a temperature gradient distribution map in real time, identifying high gradient areas (such as core areas or edges with a temperature difference exceeding 20°C / m); then, according to the gradient size, the priority is divided, and the high gradient area is listed as the first priority, and active regulation such as increasing the cooling water flow rate or covering the thermal insulation layer is implemented; when optimizing the range, the structure is divided into small areas (such as 1m x 1m grid), and the measures are adjusted accordingly to avoid resource waste in global regulation; at the same time, combined with environmental changes (such as diurnal temperature difference), the priority is dynamically adjusted, for example, the surface area is given priority when the environmental temperature drops suddenly to prevent thermal stress concentration. This solves the cracking problem caused by hydration heat accumulation and environmental factors, because the optimization process responds to temperature changes in real time, reducing the gradient difference to a safe threshold (such as <15°C / m), thereby balancing the internal stress and preventing crack generation. For example, in a large underground parking lot foundation construction, the temperature sensor shows that the core area gradient reaches 25°C / m, and the engineer optimizes the regulation based on the distribution map: first, lay the circulating water cooling pipe in the high gradient core area, and increase the water flow rate; the low gradient surface area is only covered with thermal insulation materials; after range optimization, resources are concentrated only on 30% of the high-risk areas, and the result is that the gradient is reduced to 12°C / m within 48 hours, avoiding the risk of early cracking, while improving the construction efficiency. Overall, this method significantly reduces the temperature stress through multi-step coordination, ensuring the durability of mass concrete.

[0087] Next, referring to Figure 2 , the step of optimizing the range and priority of the temperature regulation area based on the temperature gradient distribution of one embodiment of the present application is further described, which specifically includes:

[0088] S201: Generate temperature gradient distribution map according to real-time temperature sensor data. This step collects temperature data through a sensor network deployed in the concrete structure and generates a visual temperature gradient distribution map using software processing to intuitively display temperature changes. For example, in one embodiment, during the pouring of a mass concrete bridge pier, sensors are placed inside and on the surface, and a distribution map is generated in real time to identify a high temperature gradient (e.g., 20°C / m) in the central region.

[0089] S202: Divide key control regions based on the size of the temperature gradient, where the larger the gradient, the smaller the region. This step subdivides high-gradient regions into smaller sub-regions to facilitate precise control and avoid resource waste. Specifically, the term "key control region" can refer to a region with a gradient exceeding a predetermined threshold. In addition, for example, a region with a gradient exceeding 25°C / m can be divided into 0.5m x 0.5m blocks, while a region with a gradient of 15°C / m can be divided into a 2m x 2m range. This ensures that hot spot regions are isolated and treated. It should be understood that when dividing the range of key control regions according to the gradient, regions with temperature gradients within a certain deviation range can be considered to have the same temperature gradient. For example, regions with a gradient of 15 ± 0.5C / m can be considered to have the same temperature gradient, and the range can be divided within this range. In other words, the larger the temperature gradient, the smaller the region. Since a larger internal temperature gradient in concrete results in more concentrated thermal stress and a sharp increase in cracking risk, dividing the range of regions with large gradients into smaller regions allows for precise positioning of the risk core region, and the limited cooling, insulation, and other control resources (such as cooling water flow, sensor monitoring density) are highly concentrated on these most dangerous small range regions, maximizing resource utilization efficiency, quickly suppressing local temperature abnormalities, and effectively reducing the cracking risk in high stress areas.

[0090] S203: Set region priority, with high gradient regions having high priority. This step assigns control sequences based on gradient values, with high-gradient regions receiving cooling or insulation resources first. For example, in one embodiment, regions with a gradient > 30°C / m are assigned priority 1, regions with a gradient of 20-30°C / m are assigned priority 2, and regions with a gradient < 20°C / m are assigned priority 3 to quickly respond to hydration heat accumulation risks.

[0091] S204: If the maximum temperature gradient G max is greater than the critical threshold G th, mark the region as the highest priority and prioritize the regulation. Wherein, G max represents the maximum temperature gradient value (unit: °C / m) monitored, G th represents the preset safety temperature gradient critical value (unit: °C / m), the range is set based on the type of concrete (such as 20-30°C / m). The meaning of the formula G max > G th is that when the measured gradient exceeds the safety threshold, the highest priority regulation is triggered immediately to prevent temperature stress from causing cracks. In this way, resources can be dynamically focused on high-risk points to avoid cracking caused by changes in ambient temperature or uncontrolled hydration heat. For example, specifically, in large foundation construction, when G max = 28°C / m exceeds G th = 25°C / m, the region is marked as the highest priority, and the water pipe cooling system is started preferentially.

[0092] Next, with reference to Figure 3 , the steps of dividing the key regulation region based on the size of the temperature gradient in an embodiment of the present application are described. In the above description with reference to Figure 2 , the key regulation region is divided based on the size of the temperature gradient, and the larger the gradient, the smaller the region range. In the embodiment described below with reference to Figure 3 , how to determine the key regulation region is specifically described. The steps specifically include:

[0093] S301: Calculate the temperature gradient average value G avg of each region;

[0094] S302: Determine the region boundary based on the relationship between G avg and the overall distribution;

[0095] S303: Define the region with G avg greater than the overall average value as the key regulation region;

[0096] S304: If G avg > G_overall x f, reduce the region range to focus on regulation, wherein G avg represents the average value of the temperature gradient of the region, G_overall represents the overall average value of the temperature gradient, and f represents an adjustment factor, and f > 1.

[0097] Step S301 provides basic data for evaluating cracking risk by quantifying the average intensity of temperature change in the region. Step S302 uses the statistical distribution of G_avg (such as cluster analysis) to accurately divide the region boundaries, ensuring that the division is reasonable and reflects the gradient difference. In a specific embodiment, first, the average temperature gradient value (G_avg) of the current evaluation region is calculated. In actual operation, the current evaluation region can be a region preliminarily divided according to the temperature gradient, for example, it can be divided into a region with the same temperature gradient. In another embodiment, the entire mass concrete structure can be divided into a 1m x 1m grid, and each grid can be divided into a region. Then, the G_avg value is compared and analyzed with the statistical characteristic value (such as the overall average G_overall, specific percentile, or standard deviation multiple, etc.) representing the overall distribution of the temperature gradient of the entire mass concrete structure. Based on this comparison relationship (such as determining whether G_avg is significantly higher than the overall average level or located in the upper tail region of the overall distribution), the physical boundary range of the region is dynamically and iteratively adjusted or precisely defined (such as when G_avg is significantly higher than the overall level, the boundary may need to be narrowed to focus on the core sub-region with the highest gradient, otherwise the range may be expanded to include the relevant affected area), so as to ensure that the finally divided region boundary can objectively reflect the abnormal degree of the local region temperature gradient relative to the overall structure. Step S303 identifies regions with high potential cracking risk for priority regulation. Specifically, regions with G_avg greater than the overall average value are defined as key regulation regions. Step S304 narrows the range for extreme high gradient regions to concentrate resources (such as cooling measures) and improve regulation efficiency. Specifically, if G_avg > G_overall x f, then the range of the region is narrowed to focus on regulation, where G_avg represents the average temperature gradient of the region, G_overall represents the overall average temperature gradient, and f represents the adjustment factor, and f > 1.

[0098] In the formula G_avg > G_overall x f, G_avg is the average temperature gradient of the region, representing the local temperature change rate; G_overall is the overall average temperature gradient, reflecting the global average change; f is the adjustment factor (amplification factor), f > 1, usually ranging from 1.2 to 1.5, and the optimal value is based on experience (such as f = 1.3) to balance sensitivity and false positives. The formula means to identify regions significantly higher than the average level, amplify the overall average value by f to enhance detection sensitivity and avoid missing real high-risk points. This setting is because in mass concrete, small gradient changes can easily lead to cracking, and the amplification factor enhances the identification accuracy of high gradient regions.

[0099] In one embodiment, for a mass concrete foundation slab anti-cracking project, first divide the structure into multiple sub-regions (e.g., based on grid division), calculate G_avg of each sub-region using temperature sensor data (e.g., G_avg of region A = 8°C / m). Based on the distribution of all G_avg (e.g., statistical standard deviation), determine the boundary (e.g., merge gradient similar regions). Then, define the region with G_avg > G_overall (set G_overall = 6°C / m) as the key regulation region (e.g., G_avg of region B = 7°C / m). Specifically, if G_avg of region C = 9°C / m > G_overall x f (f = 1.3, i.e., 7.8°C / m), then narrow down the region range (e.g., focus only on the core high gradient point) to implement precise cooling to prevent early cracking. In one specific embodiment, for a region with G_avg > G_overall x f, all measurement points in the region with temperature greater than G_overall x f can be connected, and the overall profile of these measurement points (which includes all measurement points with temperature higher than G_overall x f) can be obtained, and the overall profile is taken as the narrowed-down region. In this way, the region boundary contains more high-temperature points, and by prioritizing the regulation of this region, the possibility of cracking in this region can be reduced.

[0100] Next, with reference to Figure 4 , the step of determining the region boundary based on the relationship between G_avg and the overall distribution of the present application is described.

[0101] S401: analyze the standard deviation σ of the temperature gradient distribution to quantify the degree of dispersion of the temperature gradient; S402: adjust the region division accuracy based on the size of σ to ensure that the boundary setting adapts to data variability;

[0102] S403: set the region boundary to G_avg ± k x σ, where k is a range coefficient used to define the boundary width;

[0103] S404: If σ > σ th, increase k value to expand the boundary range to cover potential hotspots. Specifically, σ represents the standard deviation of the temperature gradient distribution, which is a non-negative real number, and is usually greater than zero in practical applications; σ th represents the standard deviation threshold, which is a positive value, and the optimal value is set according to historical cracking data (such as 0.5°C / m), which is used to judge whether the dispersion degree exceeds the safety level; k is a dynamically adjusted range coefficient, which is a real number greater than 1, and the optimal value is initially set to 2, but can be adjusted with σ. The meaning of the formula G avg ± k × σ is to scale the boundary by the standard deviation, and to expand the range to capture abnormal gradients when σ is large to prevent missing hotspots. This setting is because when the temperature gradient dispersion is high (σ is large), the stress distribution inside the concrete is uneven, the risk increases, and k needs to be dynamically adjusted to ensure that the boundary covers the high-risk area.

[0104] For example, in one embodiment, during the construction of a mass concrete bridge pier, the temperature gradient data is monitored: G avg is the average gradient 10°C / m, and σ is calculated to be 0.6°C / m. If the preset σ th is 0.5°C / m, and σ > σ th, k increases from 2 to 3, then the boundary is set to 10 ± 3 × 0.6, i.e. 7.2°C / m to 12.8°C / m. This range covers the discrete hotspots and avoids local overheating cracking.

[0105] Specifically, in the formula parameters, σ is calculated in real time based on sensor data; the optimal value of σ th is determined through laboratory tests (such as 0.4-0.6°C / m) to ensure that the threshold reflects the safety threshold; and the initial optimal value of k is 2, which is derived from statistical experience (covering 95% of the data), but after increasing to 3, the boundary is wider, which enhances the prevention of concrete surface cracking.

[0106] It should be noted that in the above reference Figure 3 described, the range is reduced when the average value of the temperature gradient G avg is greater than the predetermined threshold, and in this embodiment, the standard deviation σ of the temperature gradient distribution of the region is also considered, and if σ > σ th, the value of k is increased to expand the boundary range. It can be seen that in the present application, not only the temperature gradient itself is considered, but also the dispersion type of the temperature gradient is considered to divide the region, so as to realize the compromise between the control accuracy and the range.

[0107] Next, with reference to Figure 5 , the step of adjusting the accuracy of the region division based on σ of the present application is described.

[0108] S501: Obtain a value of σ and a current partitioning precision P, where σ represents a standard deviation of temperature gradient inside the concrete, used to monitor cracking risk, and P represents a current regional partitioning precision, such as 1 m x 1 m (partitioning according to size), or ±0.2 °C / m (partitioning according to temperature gradient), that is, in the present application, the regional partitioning precision can be partitioned according to physical size or temperature gradient.

[0109] S502: Update P based on a rate of change of σ, R_σ, which is a rate of change of the standard deviation over time, reflecting the stability of the concrete state. Specifically, R_σ is calculated as (current σ - previous σ) / previous σ, which is used to adjust the precision. For example, if R_σ is 0.1 (indicating a 10% increase in the standard deviation), the update process is triggered. Then, the new precision P_new = P x (1 + m x R_σ) is calculated, where m is a sensitivity coefficient used to adjust the adjustment amplitude. Where m typically ranges from 0.1 to 5 (optimal value 2.0, calibrated by experiment), the formula means that the precision is dynamically scaled by a multiplication factor, ensuring that the partitioning precision is increased when R_σ > 0 to avoid missing critical areas that need to be regulated in time. In the present application, the partitioning precision P can refer to the size of the grid or the size of the temperature gradient deviation. This formula is set in this way because it responds to fluctuations simply and efficiently, avoiding excessive adjustment: for example, when R_σ = 0.1 and m = 1.0, P_new increases by 10%, which is suitable for quickly adapting to temperature gradients in concrete monitoring. Finally, if R_σ > 0 and σ > σ_min, set m to a high value (e.g. 3.0 to 5.0), i.e. increase the value of m, where σ_min is a minimum standard deviation benchmark value (e.g. 1.0 °C), ensuring that the adjustment intensity is enhanced only when the standard deviation increases and exceeds the safety threshold, preventing unnecessary waste of resources. For example, in one embodiment, σ = 3.0 (> σ_min = 1.0) and R_σ = 0.2, then set m = 4.0, significantly increasing the precision to P_new = P x 1.8 (for example, the partitioning precision from P from 1 m x 1 m to 0.55 m x 0.55 m), to fine-tune the monitoring of high-risk areas and reduce early cracking.

[0110] It should be noted that in the present application, the partitioning precision P can refer to the regulation precision of the regulation area (e.g. 1 m x 1 m, or ±0.2 °C / m), that is, the original size of the individual regulation area is also adjusted according to the rate of change of σ in the present application, and the partitioning precision P represents the regulation grid size or the regulation temperature gradient size. In a more general case, it is preferred to use the temperature gradient size as the regulation precision.

[0111] Next, with reference to Figure 6 , the step of updating P based on the rate of change of σ R_σ of the present application is described.

[0112] S601: Monitor the change of σ over time;

[0113] S602: Calculate R_σ = (σ_current - σ_previous) / Δt based on historical σ data;

[0114] S603: Adjust P according to the positive or negative of R_σ;

[0115] S604: If R_σ > R_max, prefer to reduce P to improve response speed.

[0116] The meaning of step S601 is to continuously monitor the change of standard deviation σ of internal temperature gradient distribution over time to capture potential cracking risks in real time. The meaning of step S602 is to calculate the change rate R_σ using historical stress data, which represents the rate of change of standard deviation, for quantifying abnormal fluctuations. The meaning of step S603 is to adjust the control parameter P (division precision) according to the positive or negative value of R_σ, where positive R_σ indicates an increase in standard deviation, requiring an increase in division precision P to cover points with larger fluctuations, and a negative value may moderately reduce the division precision P to avoid excessive regulation. The meaning of step S604 is to prefer to quickly increase the division precision when R_σ exceeds the maximum allowed change rate R_max, to enhance the system response speed and prevent stress accumulation from causing cracking.

[0117] For the formula R_σ = (σ_current - σ_previous) / Δt, the parameter σ_current is the current temperature gradient standard deviation, σ_previous is the temperature gradient standard deviation of the previous period, and Δt is the sampling time interval (unit: minutes, range: 1-30 minutes, optimal value: 5-10 minutes to balance response and timeliness and data stability). The formula calculates the instantaneous rate of stress change to detect abnormal trends.

[0118] In one embodiment, specifically, assuming that the internal thermal stress is monitored during the early stage after mass concrete placement, for example, Δt = 10 minutes, σ_previous is 2.0 MPa, and σ_current increases to 3.0 MPa, then R_σ = (3.0 - 2.0) / 10 = 0.1 MPa / min. If R_max is set to 0.15 MPa / min, since R_σ does not exceed the standard, the system slightly increases the division precision P according to the positive R_σ (because the standard deviation increases, the regulation range needs to be expanded). However, if σ_current suddenly increases to 4.5 MPa, R_σ = (4.5 - 3.0) / 10 = 0.15 MPa / min, which exceeds R_max, then P is preferentially increased significantly to cool down the areas with large temperature gradients and larger ranges through methods such as water flushing to prevent early cracking.

[0119] Next, refer toFigure 7 , describes the step of setting the priority of each region, the higher the gradient, the higher the priority.

[0120] S701: Assign a priority score S = a × G + b × A to each region, where G represents the regional temperature gradient value, A represents the regional area, and a and b are weight coefficients;

[0121] S702: Sort the region priority based on the S value;

[0122] S703: Prioritize the allocation of control resources to regions with high S values;

[0123] S704: If S > S_th, start immediate control measures.

[0124] The meaning of step S701 is to calculate a risk score for different regions of the concrete structure to quantify the cracking risk. Step S702 determines the priority order by sorting the S values to ensure that high-risk regions are given priority. Step S703 prioritizes the allocation of cooling equipment or materials to high-S-value regions when resources are limited. Step S704 immediately implements measures such as water spraying to prevent cracking from spreading when the score exceeds the threshold.

[0125] For the formula S = a × G + b × A, G represents the regional temperature gradient value (unit: °C / m, which can be the average temperature gradient in specific operations), usually ranging from 5-30°C / m; A represents the regional area (unit: m²), for example, ranging from 10-1000m²; a and b are weight coefficients (range 0-1, a usually 0.6-0.8, b 0.2-0.4, optimal values a=0.7, b=0.3 to emphasize the gradient dominant risk, i.e. the value of a is greater than the value of b); S_th is the threshold value (range 30-60, optimal value 40-50). The formula means that the risk score S is calculated by combining the temperature gradient (G) and the area (A), high gradient indicates large temperature difference prone to cracking, large area indicates wide impact range, and the weights a and b balance the importance of the two. The formula is set in this way because the temperature gradient is a direct driving factor for cracking, and the area amplifies the potential damage. Quantifying S can efficiently identify high-risk regions and avoid subjective judgment.

[0126] For example, in a large-volume concrete dam project, the temperature gradient of region A is G=25°C / m (high gradient), the area A=80m², and a=0.7, b=0.3 is set, then S=0.7×25 + 0.3×80 = 17.5 + 24 = 41.5. Based on the S value sorting, this region has high priority; specifically, cooling water pipe resources are prioritized. If S_th=40, since 41.5>40, immediate control measures such as increased ventilation cooling are started.

[0127] Next, referring to Figure 8 , the step of ranking the priority of regions based on S-value is described.

[0128] S801: Collect S-values of all regions, which involves obtaining priority scores of each monitoring region in the concrete structure, which represent cracking risk, calculated based on temperature stress or strain data.

[0129] S802: Calculate a ranking threshold T_sort based on S-value distribution, which involves determining an optimized threshold for subsequent ranking process by analyzing the score distribution.

[0130] S803: Rank by S-value from high to low, arrange regions in descending order of risk scores, and prioritize high-priority regions for prevention of cracking.

[0131] S804: If S_max - S_min > D, set T_sort as a dynamic value; where S_max represents the highest priority score (range typically 0-100, optimal value close to 100 represents the highest risk), S_min represents the lowest priority score (similar range, optimal value close to 0 represents the lowest risk), and D represents the score difference threshold (range 5-20, optimal value 10, depending on specific engineering requirements). The formula S_max - S_min > D means to judge the score dispersion: when the extreme difference exceeds D, it indicates that the score distribution is extensive, and T_sort needs to be dynamically adjusted to optimize the ranking efficiency and avoid excessive processing of low-risk regions when the score is concentrated. This formula setting aims to adapt to data fluctuations and ensure that resources are preferentially allocated to high-risk regions. In a specific embodiment, for example, when the extreme difference exceeds D, it indicates that there are more regions in the low-risk region, and at this time, the region for ranking is only the top 1 / 3 or other numerical value of all regions in terms of S-value, thereby avoiding excessive processing of low-risk regions.

[0132] For example, in a large-volume concrete cracking prevention embodiment, assume three regions: region A with S-value 85 (high cracking risk), region B with S-value 60 (medium risk), and region C with S-value 15 (low risk). After collecting S-values, calculate the initial value of T_sort; specifically, rank by S-value as A > B > C. If D is set to 50, then S_max - S_min = 70 > 50, triggering dynamic T_sort adjustment, such as recalculating the threshold based on distribution (e.g., only processing regions with S-value greater than 80), and prioritizing cooling measures for region A to prevent early cracking.

[0133] Next, referring to Figure 9 , the step of ranking the priority of regions based on S-value distribution to calculate the ranking threshold T_sort is described.

[0134] S901: analyze the average value S_avg and the variance V of S values;

[0135] S902: determine T_sort = S_avg + c x V, where c is an adjustment coefficient, based on the size of V;

[0136] S903: apply T_sort to filter high-priority areas;

[0137] S904: increase the value of c if V > V_th, where V represents the variance of priority scores, V_th represents the variance threshold, and c is used to amplify the threshold range.

[0138] Specifically, the first step analyzes S_avg and V, aiming to evaluate the overall level and volatility of priority scores to capture data distribution characteristics. In the second step of the formula T_sort = S_avg + c x V, S_avg is the average value of S values, reflecting the average priority level, and the range depends on the specific application data; V is the variance, indicating the degree of score dispersion, and the range is a non-negative real number; c is an adjustment coefficient that controls the sensitivity of the threshold, and the range is a positive real number, with an optimal value usually being 1-2, but it needs to be dynamically adjusted. The formula means that the threshold is set in combination with the average value and the standard deviation (V), and when V is large, the data fluctuates greatly, and increasing c can amplify the threshold range, ensuring that only truly high-priority areas are selected under high variance, avoiding false positives. The third step applies T_sort to filter areas with S values higher than the threshold, which are high-priority targets for subsequent processing. The fourth step increases the value of c when V > V_th to respond to cases where the variance is too large, where V_th is a pre-set safety threshold to prevent threshold failure due to fluctuations.

[0139] For example, in the method for preventing early cracking of mass concrete, the S value represents the area cracking risk score. In one embodiment, analyzing sensor data gives S_avg = 0.6 (average risk) and V = 0.12 (high volatility). Specifically, if V_th = 0.1, because V > V_th, increase c from 1.5 to 2.0; then calculate T_sort = 0.6 + 2.0 x √0.12 ≈ 0.6 + 2.0 x 0.346 = 0.6 + 0.692 = 1.292. Apply this threshold to filter areas with S values > 1.292 (such as high-stress areas), and prioritize implementing cooling measures to prevent cracking.

[0140] Next, referring to Figure 10 , the step of determining T_sort based on the size of V of the present application is described.

[0141] S1001: obtain V value and current c;

[0142] S1002: adjust c based on the ambient temperature T_env;

[0143] S1003: Calculate T_sort = S_avg + c x V;

[0144] S1004: If T_env > T_ref, set c as c_high.

[0145] Specifically, in this embodiment, the variance V of the S value and the initial adjustment coefficient c are obtained, and c is adjusted based on T_env, specifically, when T_env exceeds the reference temperature T_ref, c_high is used to enhance the response to high temperature of the environment. The calculation of T_sort = S_avg + c x V indicates that the sorting temperature threshold T_sort is determined, which is used to trigger cooling measures to prevent early cracking of concrete.

[0146] A method for preventing early cracking of mass concrete according to the present application, first, in the material preparation stage, high-performance cement is selected as the basic material, and the water-cement ratio is reasonably controlled within the range of 0.4-0.5 to ensure the compactness and strength of the concrete; at the same time, 10%-20% of high-activity mineral admixture (such as slag or silica fume) is mixed in to reduce the hydration heat generation rate and improve the microstructure; 0.5%-1% of high-strength fiber (such as steel fiber or synthetic fiber) is added to enhance the crack resistance of the concrete; and an appropriate amount of early strength agent (such as calcium-based or organic) is added to accelerate the early strength development, thereby reducing the initial shrinkage stress. These measures collectively optimize the composition of the concrete, inhibiting the accumulation of hydration heat from the source and laying the foundation for subsequent steps.

[0147] Secondly, in the construction process, the concrete is sprayed by adopting a reasonable pouring method to ensure uniform distribution and reduce cold joints; micro-prestressed steel bars (such as pre-tensioned steel strands) are set to provide internal restraint to offset thermal stress; at the same time, temperature sensors (such as thermocouples or optical fiber sensors) are buried in key positions of the concrete to monitor temperature changes in real time and obtain temperature gradient distribution data; and the construction environment (such as using sunshades or spray cooling systems) is controlled to avoid extreme temperatures (such as higher than 35°C or lower than 5°C) causing sudden changes. The core of this stage is to obtain the temperature gradient through real-time monitoring, identify the high-gradient areas (such as the core area or the surface) caused by the accumulation of hydration heat and changes in environmental temperature, and provide a basis for subsequent regulation.

[0148] Then, during the curing stage, constant temperature and humidity curing (temperature controlled at 20±2°C, humidity ≥90%) is adopted for no less than 14 days, and a moisture-retaining material (such as wet cloth or plastic film) is covered on the surface of the concrete to maintain water balance and slow down the drying shrinkage. More importantly, based on the temperature gradient distribution obtained by the aforementioned temperature sensor, the range and priority of the temperature regulation area are optimized: specifically, by using data analysis software (such as BIM model or AI algorithm), the area with the maximum temperature gradient (such as the core or edge of the concrete) is identified, and local cooling measures (such as circulating water system or air cooling) are preferentially implemented, while the intensity of environmental control is adjusted; this narrows down the internal and external temperature difference (usually controlled within 25°C), significantly reduces the thermal stress concentration, and thus prevents early cracking. The whole process forms a closed-loop control, solves the problem of excessive temperature gradient caused by the accumulation of hydration heat and the change of ambient temperature of mass concrete, and achieves efficient and active anti-cracking effect.

[0149] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present disclosure. It should be understood that the above description is only a specific embodiment of the present disclosure and is not intended to limit the protection scope of the present disclosure. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the embodiments of the present disclosure should be included in the protection scope of the embodiments of the present disclosure.

Claims

1. A method for preventing early cracking of mass concrete, characterized in that: The following steps are involved: Use high-performance cement, reasonably control the water-cement ratio, add 10%-20% of high-activity mineral admixtures, add 0.5%-1% of high-strength fiber, and an appropriate amount of early strength agent; Use reasonable pouring methods to pour concrete, install micro-prestressed steel bars, bury temperature sensors to monitor temperature changes in real time to obtain temperature gradients, and control the construction environment to avoid extreme temperatures; Use constant temperature and wet curing for no less than 14 days, and cover the concrete surface with moisturizing materials; The range and priority of the temperature control area are optimized based on the temperature gradient distribution.

2. The method for preventing early cracking of mass concrete according to claim 1, characterized in that: The step of optimizing the range and priority of the temperature control area based on the temperature gradient distribution further includes: Generate a temperature gradient distribution map based on real-time temperature sensor data; The key control areas are divided based on the size of the temperature gradient. The larger the gradient, the smaller the area. Set regional priority, the area with higher gradient has higher priority; If the maximum temperature gradient G_max is greater than the critical threshold G_th, the area is marked as the highest priority and is regulated first, where G_max represents the maximum temperature gradient value monitored and G_th represents the preset safety temperature gradient critical value.

3. The method for preventing early cracking of mass concrete according to claim 2, characterized in that: The step of dividing the key control areas based on the size of the temperature gradient further includes: Calculate the average temperature gradient G_avg of each area; Determine the region boundaries based on the relationship between G_avg and the overall distribution; The regions where G_avg is greater than the overall average are defined as key regulatory regions; If G_avg > G_overall × f, then narrow the region to focus on regulation, where G_avg represents the average regional temperature gradient, G_overall represents the average overall temperature gradient, f represents the adjustment factor, and f > 1.

4. The method for preventing early cracking of mass concrete according to claim 3, characterized in that: The step of determining the region boundary based on the relationship between G_avg and the overall distribution further includes: Analyze the standard deviation σ of the temperature gradient distribution; Adjust the region division accuracy based on the size of σ; Set the region boundaries to G_avg ± k × σ, where k is the range coefficient; If σ > σ_th, increase the k value to expand the boundary range, where σ represents the standard deviation of the temperature gradient distribution, σ_th represents the standard deviation threshold, and k represents the dynamically adjusted range coefficient.

5. The method for preventing early cracking of mass concrete according to claim 4, characterized in that: The step of adjusting the region division accuracy based on the size of σ further includes: Get the σ value and the current division precision P; Update P based on the rate of change R_σ of σ; Calculate the new precision P_new = P × (1 + m × R_σ), where m is the sensitivity coefficient; If R_σ > 0 and σ > σ_min, increase the value of m, where R_σ represents the standard deviation change rate, σ_min represents the minimum standard deviation reference value, and m is used to adjust the accuracy adjustment range.

6. The method for preventing early cracking of mass concrete according to claim 5, characterized in that: The step of updating P based on the rate of change R_σ of σ further includes: Monitor the change of σ over time; Calculate R_σ = (σ_current - σ_previous) / Δt based on historical σ data; Adjust the division accuracy P according to the positive or negative value of R_σ; If R_σ > R_max, increase the partitioning precision P to improve the response speed, where R_σ represents the standard deviation change rate, R_max represents the maximum allowable change rate, and Δt represents the time interval.

7. The method for preventing early cracking of mass concrete according to claim 2, characterized in that: The step of setting regional priorities, wherein regions with higher gradients have higher priorities, further includes: Assign a priority score S = a × G + b × A to each region, where G represents the regional temperature gradient value, A represents the regional area, and a and b are weight coefficients; Sort regional priorities based on S value; Prioritize the allocation of regulatory resources to areas with high S values; If S > S_th, then initiate immediate control measures, where S_th represents the priority score threshold.

8. The method for preventing early cracking of mass concrete according to claim 7, characterized in that: The step of sorting the regional priorities based on the S value further includes: Collect the S values ​​of all regions; Calculate the sorting threshold T_sort based on the S value distribution; Sort by S value from high to low; If S_max - S_min > D, then set T_sort to a dynamic value, where S_max represents the highest priority score, S_min represents the lowest priority score, and D represents the score difference threshold.

9. The method for preventing early cracking of mass concrete according to claim 8, characterized in that: The step of calculating the sorting threshold T_sort based on the S value distribution further includes: Analyze the mean S_avg and variance V of the S value; Based on the size of V, determine T_sort = S_avg + c × √V, where c is the adjustment coefficient; Apply T_sort to filter out areas where the S value is higher than T_sort; If V > V_th, increase the c value, where V represents the priority score variance, V_th represents the variance threshold, and c is used to enlarge the threshold range.

10. The method for preventing early cracking of mass concrete according to claim 9, characterized in that: The step of determining T_sort based on the size of V further includes: Get V value and current c; Adjust c based on the ambient temperature T_env; Calculate T_sort = S_avg + c × √V; If T_env > T_ref, set c to c_high, where T_env is the ambient temperature, T_ref is the reference temperature, and c_high is the adjustment coefficient for high temperature.

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