A method for temperature control of large-volume concrete with dual time-delay predictive feedback

Abstract

This invention discloses a dual-time-delay predictive feedback method for temperature control of large-volume concrete, belonging to the field of temperature monitoring and regulation technology for large-volume concrete. Addressing the problems of response lag, regulation oscillation, and cold-blow cracking inherent in existing temperature control methods, this invention acquires concrete physical parameters and boundary convection heat transfer coefficients, and extracts historical temperature and cooling data using a FIFO queue. It constructs a dual-time-delay three-dimensional unsteady-state heat conduction model incorporating both heat conduction and cooling delays. Based on the comparison between predicted and measured temperatures from this model, a temperature slope limiter is used to calculate and control the cooling water temperature at the next moment. Furthermore, a flow rate coefficient based on a cosine function-based flow rate decay curve is used to calculate the cooling water flow rate coefficient at the next moment and control the operation of the cooling device. Simultaneously, updated concrete temperature data is written into the queue to form a closed loop. This invention accurately reflects time-delay inertia, achieving smooth adaptive regulation of water temperature and flow rate, effectively avoiding cold-blow cracking risks, and ensuring construction quality.

Description

Technical Field

[0001] This invention relates to the field of temperature monitoring and regulation technology for large-volume concrete, and in particular to a method for temperature control of large-volume concrete with dual time-delay predictive feedback. Background Technology

[0002] During the construction of pumped storage power stations, components such as the spiral casing, tailrace, and unit foundations are typically constructed using large-volume concrete pouring. These components will be subjected to long-term dynamic water pressure, mechanical vibration, and alternating loads after operation, thus requiring high-quality concrete pouring. Early-stage cracking in the concrete can easily lead to localized leakage, reduced structural rigidity, and in severe cases, affect the operational stability of the unit foundation.

[0003] After the large-volume concrete is poured, the cement continuously releases heat during hydration, causing the internal temperature to rise steadily. Meanwhile, the external surface dissipates heat more quickly upon contact with the air, easily creating a significant temperature difference between the interior and surface. During construction, it was found that when the temperature difference between the inside and outside of the concrete is too large, the resulting internal thermal stress can easily exceed the early tensile strength of the concrete, leading to surface cracks or through cracks. Temperature cracks are particularly prone to occur in areas with strong confinement, such as the outer perimeter of the casing.

[0004] In existing projects, cooling water pipes are typically installed to reduce the internal temperature of concrete, and the rate of temperature rise is controlled by adjusting the cooling water flow rate or inlet water temperature. Common on-site control methods rely primarily on manual adjustment based on experience, or use PID control to adjust cooling parameters based on temperature measurements. Manual adjustment is heavily influenced by the experience of construction workers, resulting in unstable temperature control accuracy. While traditional PID control can achieve automatic control, its effectiveness in controlling the temperature of large-volume concrete is not ideal.

[0005] This is because the internal temperature change of large-volume concrete is not a simple linear process. The rate of heat release from cement hydration varies over time, and there is a significant delay in heat conduction within the concrete. The cooling effect of cooling water on the surrounding concrete often cannot be immediately reflected at the temperature measurement point. After the control system issues an adjustment command, the actual temperature change usually takes several hours to become apparent.

[0006] In actual construction, traditional PID control cannot effectively handle this delay, easily leading to mismatch in regulation. For example, during the cooling phase, the controller continuously increases the cooling intensity, but the delayed cooling effect, when superimposed, may cause the local temperature to drop too quickly, resulting in cold shock and new temperature cracks. During the heating phase, the lag in regulation may prevent timely limitation of the maximum internal temperature. This can cause inconsistencies between the temperature prediction and actual changes, resulting in poor control performance.

[0007] Therefore, existing temperature control methods for large-volume concrete still have shortcomings in handling time delays. A temperature control method that can predict temperature changes in advance and compensate for control delays is needed to improve the stability of temperature control and reduce the risk of cracking. Summary of the Invention

[0008] The purpose of this invention is to provide a temperature control method for large-volume concrete with dual time-delay predictive feedback, so as to solve the problems existing in the prior art.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: A method for temperature control of large-volume concrete with dual time-delay predictive feedback includes the following steps: S1. Obtain the physical parameters and boundary convection heat transfer coefficient of the concrete structure, and determine the grid calculation step size and time calculation step size according to the spatial discretization requirements; S2. Obtain the measured heat conduction time delay and cooling effect time delay, determine the time delay buffer length in combination with the time calculation step size, and initialize the first-in-first-out (FIFO) queue; in each time step, extract the historical temperature data and historical cooling data corresponding to the time delay time from the FIFO queue, and calculate the temperature field prediction result at the current time according to the three-dimensional unsteady heat conduction model containing the double time delay effect. S3. Based on the temperature field prediction results, calculate the cooling water temperature for the next time step using a temperature slope limiter to ensure that the cooling water temperature change rate does not exceed a preset safety threshold. S4. Based on the current stage in the concrete hydration heat reaction cycle, calculate the cooling water flow coefficient for the next time step using the cosine function flow decay curve. S5. Control the operation of the cooling water circulation device according to the cooling water temperature and cooling water flow coefficient, and write the updated temperature field data into the FIFO queue for rolling updates to form a predictive feedback closed-loop control.

[0010] Preferably, the physical parameters and boundary convection heat transfer coefficients obtained in step S1 include one or more of the following: Concrete length, width, height, density, specific heat capacity, thermal conductivity, hydration heat characteristic time, initial pouring temperature, ambient temperature, top surface heat release coefficient, bottom surface heat release coefficient, side surface heat release coefficient, coordinates of the starting point of the cooling water pipe, coordinates of the ending point of the cooling water pipe, radius of the cooling water pipe, and heat transfer coefficient of the cooling water pipe wall.

[0011] Preferably, in step S2, the length of the heat conduction delay buffer is calculated based on the time calculation step size, the heat conduction delay time, and the cooling delay time. and the length of the cooling delay buffer The calculation formula is as follows: ; ; In the formula, The heat conduction delay time is mentioned above; The time delay of the cooling effect; Calculate the time step; [ ] indicates the rounding operation.

[0012] Preferably, in step S2, the three-dimensional unsteady-state heat conduction equation including the double time-delay effect is: ; In the formula, Density; Specific heat; For temperature; For time; Thermal conductivity; Indicates adoption Calculate the Laplace operator for the historical temperature field prior to the given time. The heat generation rate of hydration at the current moment; for The amount of heat dissipated by the cooling water before the specified time.

[0013] Preferably, in step S2, the heat generation rate of hydration at the current moment is... The result was obtained through a double-exponential hydration heat adiabatic temperature rise model. The heat dissipation delayed by the cooling effect The data is obtained by extracting historical cooling water temperature, historical cooling water flow rate, and current concrete temperature from the FIFO queue, and calculating them in conjunction with the convective heat transfer coefficient.

[0014] Preferably, in step S2, the FIFO queue is implemented using a four-dimensional array structure, where the first three dimensions represent spatial coordinate indices and the fourth dimension represents time history indices. ,in Corresponding to the oldest data of the team leader, The latest data corresponds to the end of the queue; The rolling update method of the FIFO queue is as follows: ; ; In the formula, The index in the time-delay buffer is Historical temperature field data; This is the node temperature calculated at the current moment.

[0015] Preferably, in step S3, the control law of the temperature slope limiter algorithm is as follows: ; ; ; In the formula, The next moment's cooling water temperature; To ideally follow the temperature; Temperature is limited by slope; This represents the highest concrete temperature at the current moment. To set a safe threshold for the temperature difference between inside and outside; The cooling water temperature of the previous time step; The maximum permissible rate of water temperature decrease; During the concrete heating period It employs an ideal temperature-following mechanism to provide cooling capacity; during the concrete cooling period, it uses a slope-limited temperature mechanism to avoid cold shock.

[0016] Preferably, the maximum allowable rate of temperature drop of the cooling water is no higher than 2.5°C / day.

[0017] Preferably, in step S4, the flow attenuation curve F(t) based on the cosine function is a piecewise function, as follows: when hour, when hour, when hour, ; In the formula, The maximum flow coefficient; The minimum flow coefficient; This is the decay start time; This is the time when decay ends.

[0018] Preferably, the attenuation start time The characteristic time for reaching 62% cumulative heat of hydration release is set. The attenuation end time The time is set to the moment when the hydration heat release rate decays to 20% of its peak value.

[0019] The present invention discloses a method for temperature control of large-volume concrete with dual time-delay prediction feedback, which has the following beneficial effects.

[0020] This invention introduces a dual-delay effect and combines it with FIFO queue management of historical data to accurately capture the inertial delay of heat conduction and cooling, thereby improving the proactive control and precise response of the concrete sump temperature field. Simultaneously, it utilizes a temperature slope limiter to achieve rapid following during the heating phase and strictly limit the rate of water temperature drop during the cooling phase, completely eliminating the potential for "cold shock" cracks caused by sudden water temperature drops. Furthermore, by employing a flow decay curve based on an infinite-order differentiable cosine function, it achieves a seamless and smooth transition of cooling power from full speed to maintenance, avoiding temperature oscillations caused by step flow rate adjustments. The entire predictive-feedback closed-loop architecture completely eliminates the reliance on manual experience and repeated trial-and-error with PID parameters. The algorithm can automatically calculate and adaptively adjust according to the actual physical parameters of different projects, reducing manual intervention while improving the robustness of the temperature control system and the reliability of the control results, providing high-precision intelligent assurance for the construction quality and safety of major engineering structures. Attached Figure Description

[0021] Figure 1 A flowchart of a method for temperature control of large-volume concrete with dual time-delay predictive feedback provided in an embodiment of the present invention; Figure 2 This is a measured temperature change diagram of a large volume concrete in the tailrace pipe of Unit 1 of a pumped storage power station under artificial control, provided as an embodiment of the present invention. Figure 3 A comparison curve of the predicted temperature field and the actual evolution after running the method of the present invention is provided for an embodiment of the present invention; Figure 4 This is a full-cycle temperature change curve of four characteristic points selected on the vertical line at the center of the concrete silo in an embodiment of the present invention. Figure 5 The graph showing the changes in cooling water temperature and flow rate after operation using the method of the present invention is provided for an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0023] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0024] As disclosed in the background section, there are still some problems with temperature monitoring and regulation of large-volume concrete: In existing projects, cooling water pipes are typically installed to reduce the internal temperature of concrete, and the rate of temperature rise is controlled by adjusting the cooling water flow rate or inlet water temperature. Common on-site control methods rely primarily on manual adjustment based on experience, or use PID control to adjust cooling parameters based on temperature measurements. Manual adjustment is heavily influenced by the experience of construction workers, resulting in unstable temperature control accuracy. While traditional PID control can achieve automatic control, its effectiveness in controlling the temperature of large-volume concrete is not ideal.

[0025] This is because the internal temperature change of large-volume concrete is not a simple linear process. The rate of heat release from cement hydration varies over time, and there is a significant delay in heat conduction within the concrete. The cooling effect of cooling water on the surrounding concrete often cannot be immediately reflected at the temperature measurement point. After the control system issues an adjustment command, the actual temperature change usually takes several hours to become apparent.

[0026] In actual construction, traditional PID control cannot effectively handle this delay, easily leading to mismatch in regulation. For example, during the cooling phase, the controller continuously increases the cooling intensity, but the delayed cooling effect, when superimposed, may cause the local temperature to drop too quickly, resulting in cold shock and new temperature cracks. During the heating phase, the lag in regulation may prevent timely limitation of the maximum internal temperature. This can cause inconsistencies between the temperature prediction and actual changes, resulting in poor control performance.

[0027] To improve the above problems, such as Figure 1 As shown, this invention proposes a method for temperature control of large-volume concrete with dual time-delay predictive feedback, comprising the following steps: S1. Obtain the physical parameters and boundary convection heat transfer coefficient of the concrete structure, and determine the grid calculation step size and time calculation step size according to the spatial discretization requirements; S2. Obtain the measured heat conduction time delay and cooling effect time delay, determine the time delay buffer length in combination with the time calculation step size, and initialize the first-in-first-out (FIFO) queue; in each time step, extract the historical temperature data and historical cooling data corresponding to the time delay time from the FIFO queue, and calculate the temperature field prediction result at the current time according to the three-dimensional unsteady heat conduction model containing the double time delay effect. S3. Based on the temperature field prediction results, calculate the cooling water temperature for the next time step using a temperature slope limiter to ensure that the cooling water temperature change rate does not exceed a preset safety threshold. S4. Based on the current stage in the concrete hydration heat reaction cycle, calculate the cooling water flow coefficient for the next time step using the cosine function flow decay curve. S5. Control the operation of the cooling water circulation device according to the cooling water temperature and cooling water flow coefficient, and write the updated temperature field data into the FIFO queue for rolling updates to form a predictive feedback closed-loop control.

[0028] The technical solution provided by this invention makes temperature control decisions based on physical mechanism derivation and mathematical modeling, avoiding the subjectivity and uncertainty caused by relying on manual experience or conservative parameter tuning. The rate constraint parameters of the slope limiter are determined by the national standard GB50496-2018 and have clear physical meaning; the time nodes of the cosine flow curve are quantitatively calculated based on the cumulative release of hydration heat, ensuring precise matching with the heat source decay law; the FIFO time delay buffer accurately captures the inertial delay characteristics of temperature evolution through a queue data structure. This "theory-driven + quantitative calculation" method provides a more reliable and scientific technical basis for the temperature control of large-volume concrete, helping to obtain more accurate and reproducible control results, and avoiding the arbitrariness of parameter selection and the uncertainty of results in traditional methods.

[0029] Through a unified control framework, automated and coordinated control of multiple aspects, including temperature field evolution, cooling water regulation, and flow optimization, is achieved. This significantly reduces the workload of manual monitoring, the time cost of parameter debugging, and potential operational errors. The slope limiter algorithm eliminates the need for repeated trial and error with PID parameters; the cosine flow curve automatically calculates the flow coefficient based on the current moment, eliminating the need for manual table lookups or segmented settings; and the predictive-feedback closed-loop architecture automatically executes control adjustments without real-time intervention from on-site personnel. This supports real-time or near-real-time temperature monitoring and control needs, providing a solid guarantee of computational efficiency for large-scale engineering applications.

[0030] This method relies directly on the actual physical parameters of the concrete structure and real-time temperature monitoring data, thus naturally adapting to the individual characteristics of different projects and responding to changes in the construction environment by updating the boundary convective heat transfer coefficient. For different climatic conditions, different concrete mix proportions, and different structural dimensions, the algorithm parameters do not require manual adjustment; only the corresponding physical parameters need to be input to automatically calculate the hydration heat source term and time-delay buffer. This highly adaptive characteristic provides an effective technical method for implementing personalized and dynamic temperature control and monitoring, enabling the same algorithm framework to be applied to various water conservancy and hydropower engineering construction scenarios.

[0031] The above plan will be explained in detail below.

[0032] A method for temperature control of large-volume concrete with dual time-delay predictive feedback includes the following steps: S1. Obtain the physical parameters and boundary convective heat transfer coefficient of the concrete structure. According to the temperature monitoring and control standard in GB50496-2018, the sampling point spacing should not be greater than 500mm. Therefore, the method is analogous to the spatial discretization requirement to determine the grid calculation step size. The calculation step size is selected as 0.1h according to the numerical calculation method of temperature field. Preferably, in this embodiment, the physical parameters and boundary convection heat transfer coefficients obtained in step S1 include one or more of the following: By using construction drawings and concrete material mix design, we can obtain the concrete's length, width, height, density, specific heat capacity, thermal conductivity, hydration heat characteristic time, initial pouring temperature, ambient temperature, top surface heat release coefficient, bottom surface heat release coefficient, side surface heat release coefficient, starting coordinates of cooling water pipes, ending coordinates of cooling water pipes, radius of cooling water pipes, and heat transfer coefficient of cooling water pipe walls. This provides basic parameters and data for establishing a three-dimensional temperature field for concrete.

[0033] Specifically, the formula for calculating the total number of spatial grids determined based on the spatial discretization requirements is as follows: , , ; In the formula: , , This represents the total number of grid cells in the x, y, and z directions of the concrete block. , , Let x, y, z be the dimensions of the concrete block in the x, y, z directions; , , This represents the grid step size in the corresponding direction.

[0034] S2. Obtain the measured heat conduction time delay and cooling effect time delay, determine the time delay buffer length by combining the time calculation step size, and initialize the first-in-first-out (FIFO) queue; in each time step, extract the historical temperature data and historical cooling data corresponding to the time delay time from the FIFO queue, and calculate the temperature field prediction result at the current time according to the three-dimensional unsteady heat conduction model containing the double time delay effect. Preferably, in this embodiment, in step S2, the length of the heat conduction delay buffer is calculated based on the time calculation step size, the heat conduction delay time, and the cooling delay time. and the length of the cooling delay buffer The calculation formula is as follows: ; ; In the formula, This refers to the heat conduction delay time. This refers to the time delay of the cooling effect; The time step is calculated; [ ] indicates the rounding operation.

[0035] in, and The time difference in temperature changes at the center of the concrete chamber, around the cooling water pipes, and on the surface of the concrete chamber was determined through on-site measurements. The length of the heat conduction time delay buffer zone was then obtained. Subsequently, since the contribution of the temperature field at different times to the current heat conduction process varies, a time-delay temperature field parameter is introduced to indicate the degree of influence of the historical temperature field on the current heat diffusion. To more accurately reflect the time delay effect, the following method is adopted: The calculation is based on the historical temperature field prior to the current moment, not the temperature field at the current moment.

[0036] Preferably, in this embodiment, the three-dimensional unsteady-state heat conduction equation including the double time-delay effect in step S2 is: ; In the formula, Density; Specific heat; For temperature; For time; Thermal conductivity; Indicates adoption Calculate the Laplace operator for the historical temperature field prior to the given time. The heat generation rate of hydration at the current moment; for The amount of heat dissipated by the cooling water before the specified time.

[0037] Preferably, in this embodiment, in step S2, the heat generation rate of hydration at the current moment is... The calculation was performed using a double-exponential hydration heat adiabatic temperature rise model. The specific steps are as follows: First, calculate the cumulative hydration heat up to τ after pouring. : ; In the formula: The unit is kJ / kg; θ0 is the final heat of hydration as τ→∞; τ0 is the characteristic time, in hours; m and n are constants determined by field measurements.

[0038] Considering the simplified relationship between adiabatic temperature rise and heat of hydration: ; In the formula: Q0 is the final heat of hydration per kg of cement, in kJ / kg; W is the amount of cement used per cubic meter, in kg / m³. 3 .

[0039] Differentiating both sides of the equations of the double-exponential hydration heat adiabatic temperature rise model with respect to time τ yields the hydration heat generation rate at the current moment. for: ; Heat dissipation delayed during cooling The data is calculated by extracting historical cooling water flow rate, cooling water temperature, and current concrete temperature from the FIFO queue. The specific formula is as follows: ; In the formula: for The constant cooling water flow coefficient is standardized using the cooling water pipe model parameters; To calculate the distance coefficient between the point and the cooling water pipe, the parameters of the concrete silo model are standardized per unit. for The temperature difference between the current temperature and the cooling water temperature, in °C; The attenuation coefficient is determined by on-site measurement data.

[0040] Preferably, in this embodiment, in step S2, the FIFO queue is implemented using a four-dimensional array structure, where the first three dimensions represent spatial coordinate indices and the fourth dimension represents time history indices. ,in Corresponding to the oldest data of the team leader, The latest data corresponds to the end of the queue; A queue is a linear data structure that follows the "first-in, first-out" principle: the element that entered the queue earliest is taken out first. This characteristic perfectly matches the requirements of time-delay systems, where the computations require retrieving historical data from tens of units of time ago.

[0041] Basic operation steps of queue data structure: Step 1: Enqueue: Add the new element to the end of the queue: Step 2: Dequeue: Remove the oldest element from the front of the queue. Step 3: For time-delay systems, the queue length should be: In the formula, tail represents the position of the rear of the queue; x new Indicates a new element; head indicates the head of the queue; x old L3 represents the old element; L3 represents the total length of the queue; τ3 is the total computation time. Calculate the time step.

[0042] The rolling update method for the FIFO queue is as follows: ; ; In the formula, The index in the time-delay buffer is Historical temperature field data; This is the node temperature calculated at the current moment.

[0043] This method initially assumes that the heating period is defined as the period before the heat released by the hydration reaction reaches 63.2% of the total heat, and the cooling period is defined as the period after reaching 63.2% of the total heat. This data is determined by a bi-exponential hydration heat adiabatic temperature rise model. After construction begins, the FIFO queue is updated continuously to determine the heating period, which is defined as the period before reaching the highest temperature point, and the cooling period as the period after reaching the highest temperature point.

[0044] S3. Based on the temperature field prediction results, calculate the cooling water temperature for the next time step using the temperature slope limiter to ensure that the cooling water temperature change rate does not exceed the preset safety threshold. Preferably, in this embodiment, the control law of the temperature slope limiter algorithm in step S3 is as follows: ; ; ; In the formula, The next moment's cooling water temperature; To ideally follow the temperature; Temperature is limited by slope; This represents the highest concrete temperature at the current moment. To set a safe threshold for the temperature difference between inside and outside; The cooling water temperature of the previous time step; The maximum permissible rate of water temperature decrease; During the concrete heating period It employs an ideal temperature-following mechanism to provide cooling capacity; during the concrete cooling period, it uses a slope-limited temperature mechanism to avoid cold shock.

[0045] It should be noted that when calculating the cooling water temperature control, in addition to considering the deviation between the current concrete temperature and the target temperature, the influence of the water temperature change rate on the thermal stress of the concrete surface must also be considered. Therefore, this invention uses the slope-limited temperature as a safety constraint, characterizing the upper limit of the water temperature drop rate. The smaller the maximum allowable drop rate, the more stringent the protection against cold shock risk, and the more conservative the resulting constraint boundary. Simultaneously, considering that when the concrete temperature rises rapidly, the cooling water temperature needs to rise synchronously to provide a certain cooling capacity and avoid excessive temperature differences between the inside and outside of the concrete chamber, the slope limit should not be an obstacle. Therefore, an ideal following temperature is introduced. When the ideal following temperature is greater than the slope-limited temperature, the ideal following temperature is used preferentially to improve the system's response speed during the heating period.

[0046] Preferably, in this embodiment, the maximum allowable rate of decrease in cooling water temperature is no higher than 2.5°C / day.

[0047] S4. Based on the current stage in the concrete hydration heat reaction cycle, calculate the cooling water flow coefficient for the next time step using the cosine function flow decay curve. Preferably, in this embodiment, in step S4, the flow attenuation curve F(t) based on the cosine function is a piecewise function, as follows: when hour, when hour, when hour, ; In the formula, The maximum flow coefficient; The minimum flow coefficient; This is the decay start time; This is the time when decay ends.

[0048] Preferably, in this embodiment, the attenuation start time The characteristic time for reaching 62% cumulative heat of hydration release is set. At the end of decay The time is set to the moment when the hydration heat release rate decays to 20% of its peak value.

[0049] It should be noted that, taking into account both the smoothness of flow regulation and the matching of the hydration heat decay law, this invention adopts a cosine flow decay curve. As a flow control strategy, the flow coefficient is calculated using a piecewise cosine function at the initial decay time. With the end of decay The transitions between these sections follow a cosine law, rather than a nonlinear or step-like approach. The cosine function is chosen based on its infinitely differentiable nature, ensuring absolute smoothness of flow rate changes, while the zero derivative at the boundary guarantees a seamless transition to the constant flow segment. Furthermore, the symmetrical "S-shaped" form of the cosine curve closely matches the natural transition of hydration heat from its peak to its decline, effectively preventing cooling power oscillations and temperature fluctuations caused by sudden changes in flow rate.

[0050] S5. Based on the cooling water temperature and cooling water flow coefficient, specific instructions are issued through a temperature acquisition and monitoring system integrated with peripheral hardware and software, typically via RS485 serial communication or wireless LAN communication. The cooling water temperature is adjusted in real time by the constant temperature water tank, and the cooling water flow rate is adjusted in real time by the water pump. The updated temperature field data is written to the FIFO queue for rolling updates to form a predictive feedback closed-loop control.

[0051] Application examples This paper takes the actual operating data of the large-volume concrete pouring process of the spiral casing and tailrace pipe foundation of a pumped storage power station as an example for analysis. Figure 2 The demonstration showed the temperature changes under artificial control during the large-volume concrete pouring process of the tailrace pipe of Unit 1 of the pumped storage power station. Figure 2 It can be seen that the cooling water temperature undergoes a significant abrupt change between sampling points 160 and 200°C. Subsequently, after 20 sampling points, both the internal average temperature and the surface average temperature show a rapid downward trend. More noteworthy is that the cooling water temperature exhibits a distinct "broken line" shape rather than a smooth curve throughout the process, with abrupt slope changes in multiple sections such as 40-80°C and 100-140°C, indicating a lack of continuity and predictability in manual adjustment. During the temperature decrease phase of hydration heat reaction decay, the internal temperature curve decreases significantly more than during the peak hydration heat reaction phase, suggesting that the manual operation mode lacks real-time calculation and feedback control mechanisms for indicators such as cold shock and temperature gradient, potentially leading to quality hazards such as microcracks in the concrete flow. This invention employs a predictive-feedback intelligent temperature control method for large-volume concrete in pumped storage units under the influence of dual time-delay effects, and performs numerical simulation of temperature control for large-volume concrete. The specific steps are as follows: S1. Take a 12m×12m×3m concrete block, with a spatial step size of 0.5m in the X and Y directions and 0.1m in the Z direction. Calculate the time step size Δ. t Take 0.1h; take concrete density as 2400 kg / m³ 3 With a specific heat capacity of 0.97 kJ / (kg·℃) and a thermal conductivity of 10.5 kJ / (m·h·℃), and with a water pipe spacing of 1.5 m and a cooling water pipe radius of 0.025 m, the basic physical parameters and mesh generation were determined.

[0052] S2. Based on the on-site measured data, perform inversion fitting to obtain the measured heat conduction time delay. The cooling time delay is 2 hours. The time step is 4 hours; the time step is calculated based on the time. h, calculate the length of the heat conduction time delay buffer. Equals 21, length of the cooling effect delay buffer zone. The value is 41. A first-in-first-out (FIFO) queue is initialized based on this length. At each time step, historical data corresponding to the time delay is extracted from the FIFO queue and substituted into a three-dimensional unsteady-state heat conduction model incorporating double time delay effects to calculate the predicted temperature field for the current moment. Simultaneously, the heat dissipated by the hydration heat reaction, the heat dissipation due to the cooling water effect, and the heat dissipation under the influence of boundary convection heat transfer are also calculated. S3. In accordance with the requirement in the national standard GB50496-2018 that the daily cooling rate should not exceed 2.5℃ / day, in this example, to allow for a safety margin, a maximum allowable water temperature drop rate is set. The temperature is 2.0℃ / day. The cooling water temperature for the next time step is calculated using a temperature slope limiter. The specific control law formula is as follows: ; ; ; In the formula, The next moment's cooling water temperature; To ideally follow the temperature; Temperature is limited by slope; This represents the highest concrete temperature at the current moment. To set a safe threshold for the internal and external temperature difference, 25℃ is used in this example; The cooling water temperature of the previous time step; The maximum permissible rate of water temperature decrease; The time step is calculated (0.1h in this example).

[0053] During the calculation, the ideal following temperature and the slope limit temperature are obtained in real time, and the maximum value of the two is taken as the cooling water temperature output at the next moment. This enables intelligent switching between preventing excessive temperature difference during the heating period and preventing cold shock during the cooling period.

[0054] S4. Construct a flow decay curve based on the cosine function. Set the maximum flow coefficient The value is 0.2; based on the hydration heat characteristics of this batch of concrete, the attenuation start time t1 is taken as 22.3 hours (i.e., the characteristic time corresponding to reaching 62% of the cumulative hydration heat release), and the attenuation end time t2 is taken as 96 hours (i.e., the time when the hydration heat release rate decreases to 20% of the peak value). Flow rate attenuation curve The formula for segmented calculation is as follows: when hour, when hour, when hour, ; In the formula, The maximum flow coefficient; The minimum flow coefficient; This is the decay start time; This is the time when decay ends.

[0055] Substituting the parameters determined in this example into the above formula, the system maintains a maximum flow rate of 1.0 for 0 to 22.3 hours; during 22.3 to 96 hours, the flow coefficient is smoothly reduced according to the above cosine function law; after 96 hours, the system maintains a minimum flow rate of 0.2 until the heat of hydration reaction ends.

[0056] S5. Based on the cooling water temperature and cooling water flow coefficient, generate control commands to control the operation of the cooling water circulation device. After each time step control action is completed, write the updated temperature field data to the tail of the FIFO queue for rolling updates and proceed to the next time step cycle.

[0057] After performing numerical simulations using the methods described in S1 to S5 above, the following results were obtained: like Figure 3 The figure shows the temperature evolution and intelligent control curves after the method of this invention has been implemented. The solid red line in the figure represents the center temperature, the black line with squares represents the highest temperature, and the purple dashed line represents the predicted temperature. It can be seen that the predicted temperature closely matches the actual temperature, and the highest temperature throughout the entire cycle is strictly controlled below the yellow dashed line (warning temperature) and the red dashed line (critical temperature), with no temperature exceeding the limit.

[0058] Furthermore, such as Figure 4 As shown, the temperature variation curves over the entire cycle are displayed for four characteristic points selected on the vertical line from the center of the concrete slab (center point H / 2 of P1, lower center point H / 4 of P2, upper center point 3H / 4 of P3, and center point H of the top surface of P4). Figure 4 It can be seen that the temperature at each feature point shows a regular trend of first rising and then falling, with a peak of about 53.9℃. The temperature difference at different depths is gradual, which verifies the accuracy of the three-dimensional temperature field model of this invention in simulating internal heat conduction.

[0059] Finally, as Figure 5 The diagram illustrates the core control output effect of this invention. Among other things, Figure 5The left figure shows a comparison of cooling water temperature control. The blue curve represents the water temperature after using the slope limiter of this invention, while the red curve represents the measured water temperature without the slope controller. The comparison shows that the blue curve exhibits a smooth transition during the cooling period, completely eliminating the drastic fluctuations and abrupt changes in the red curve, effectively avoiding the risk of "cold shock." Figure 5 The right figure shows the cooling water flow control curve. It can be clearly seen that the flow coefficient perfectly presents the "S-shaped" smooth decay law based on the cosine function between the decay start time (t1) and the decay end time (t2), avoiding the temperature fluctuation of concrete caused by the flow step change.

[0060] like Figures 3 to 5 As shown, after operating using the method of this invention, the cooling water temperature curve exhibits a smooth transition, completely eliminating... Figure 2 The temperature control system effectively eliminates the abrupt change in temperature; the highest internal temperature is safely controlled within a reasonable range, and throughout the entire cooling process, the actual cooling rate strictly follows the cosine decay law, with no cold shock occurring, significantly improving the quality of temperature control.

[0061] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for temperature control of large-volume concrete with dual time-delay predictive feedback, characterized in that, Includes the following steps: S1. Obtain the physical parameters and boundary convection heat transfer coefficient of the concrete structure, and determine the grid calculation step size and time calculation step size according to the spatial discretization requirements; S2. Obtain the measured heat conduction time delay and cooling effect time delay, determine the time delay buffer length in combination with the time calculation step size, and initialize the first-in-first-out (FIFO) queue; in each time step, extract the historical temperature data and historical cooling data corresponding to the time delay time from the FIFO queue, and calculate the temperature field prediction result at the current time according to the three-dimensional unsteady heat conduction model containing the double time delay effect. S3. Based on the temperature field prediction results, calculate the cooling water temperature for the next time step using a temperature slope limiter to ensure that the cooling water temperature change rate does not exceed a preset safety threshold. S4. Based on the current stage in the concrete hydration heat reaction cycle, calculate the cooling water flow coefficient for the next time step using the cosine function flow decay curve. S5. Control the operation of the cooling water circulation device according to the cooling water temperature and cooling water flow coefficient, and write the updated temperature field data into the FIFO queue for rolling updates to form a predictive feedback closed-loop control.

2. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 1, characterized in that, The physical parameters and boundary convection heat transfer coefficients obtained in step S1 include one or more of the following: Concrete length, width, height, density, specific heat capacity, thermal conductivity, hydration heat characteristic time, initial pouring temperature, ambient temperature, top surface heat release coefficient, bottom surface heat release coefficient, side surface heat release coefficient, coordinates of the starting point of the cooling water pipe, coordinates of the ending point of the cooling water pipe, radius of the cooling water pipe, and heat transfer coefficient of the cooling water pipe wall.

3. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 1, characterized in that, In step S2, the length of the heat conduction delay buffer is calculated based on the time calculation step size, the heat conduction delay time, and the cooling delay time. and the length of the cooling delay buffer The calculation formula is as follows: ； ； In the formula, The heat conduction delay time is mentioned above; The time delay of the cooling effect; Calculate the time step size; , This indicates the rounding operation.

4. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 3, characterized in that, In step S2, the three-dimensional unsteady-state heat conduction equation including the double time-delay effect is: ； In the formula, Density; Specific heat; For temperature; For time; Thermal conductivity; Indicates adoption Calculate the Laplace operator for the historical temperature field prior to the given time. The heat generation rate of hydration at the current moment; for The amount of heat dissipated by the cooling water before the specified time.

5. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 4, characterized in that, In step S2, the heat generation rate of hydration at the current moment The result was obtained through a double-exponential hydration heat adiabatic temperature rise model. The heat dissipation delayed by the cooling effect The data is obtained by extracting historical cooling water temperature, historical cooling water flow rate, and current concrete temperature from the FIFO queue.

6. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 3, characterized in that, In step S2, the FIFO queue is implemented using a four-dimensional array structure, where the first three dimensions represent spatial coordinate indices and the fourth dimension represents time history indices. ,in Corresponding to the oldest data of the team leader, The latest data corresponds to the end of the queue; The rolling update method of the FIFO queue is as follows: ； ； In the formula, The index in the time-delay buffer is Historical temperature field data; This is the node temperature calculated at the current moment.

7. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 1, characterized in that, In step S3, the control law of the temperature slope limiter algorithm is as follows: ； ； ； In the formula, The next moment's cooling water temperature; To ideally follow the temperature; Temperature is limited by slope; This represents the highest concrete temperature at the current moment. To set a safe threshold for the temperature difference between inside and outside; The cooling water temperature of the previous time step; The maximum permissible rate of water temperature decrease; During the concrete heating period It employs an ideal temperature-following mechanism to provide cooling capacity; during the concrete cooling period, it uses a slope-limited temperature mechanism to avoid cold shock.

8. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 7, characterized in that, The maximum allowable rate of temperature drop of the cooling water shall not exceed 2.5℃ / day.

9. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 1, characterized in that, In step S4, the flow attenuation curve F(t) based on the cosine function is a piecewise function, as detailed below: when hour, when hour, when hour, ; In the formula, The maximum flow coefficient; The minimum flow coefficient; This is the decay start time; This is the time when decay ends.

10. The method for temperature control of large-volume concrete with dual time-delay predictive feedback according to claim 9, characterized in that, The attenuation start time The characteristic time for reaching 62% cumulative heat of hydration release is set. The attenuation end time The time is set to the moment when the hydration heat release rate decays to 20% of its peak value.

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