A concrete self-adaptive carbonation control method based on pre-reaction feature recognition

Abstract

A concrete adaptive carbonation control method based on pre-reaction characteristic identification, comprising the following steps: S1, randomly sampling from a batch of concrete to be carbonated and placing it in a pre-reaction kettle; S2, setting pre-reaction parameters according to the moisture content and density of the sample, pre-reaction of the sample for a short time, and collecting reaction activity data; S3, calculating the key reaction parameters of the concrete raw material based on the collected data, including the carbonation rate constant and the maximum carbon absorption capacity; S4, calculating the carbonation control curve of the carbonation reaction according to the key reaction parameters, and determining the optimal reaction time; S5, placing the whole batch of concrete blocks in the main reaction kettle, and dynamically adjusting the carbonation reaction process according to the carbonation control curve; S6, monitoring the CO2 concentration and temperature and humidity changes during the reaction process, and automatically correcting the carbonation conditions according to the deviation, solving the problem of dynamic adjustment of reaction conditions in the concrete carbonation process, and ensuring the best carbonation effect of different batches of concrete.

Description

Technical Field

[0001] This invention relates to the field of concrete carbon sequestration technology, and more specifically to an adaptive carbonation control method for concrete based on pre-reaction feature recognition. Background Technology

[0002] Concrete, as a crucial material in modern construction, is widely used in various building structures. However, with the continuous increase in concrete usage, improving its performance, extending its service life, and reducing its negative environmental impact have become urgent issues to be addressed. In recent years, carbon dioxide mineral carbonation technology, as an effective carbon sequestration method, has gradually attracted widespread attention. By reacting alkaline minerals such as calcium hydroxide and calcium silicate in concrete with carbon dioxide to generate stable calcium carbonate, carbon dioxide can be fixed and permanently stored while simultaneously improving the strength of the concrete.

[0003] However, in existing technologies, the carbonation process typically employs fixed reaction conditions such as carbon dioxide concentration, temperature, and humidity. This "one-size-fits-all" approach cannot effectively adapt to the compositional differences between different batches of concrete. For example, within the same batch of concrete, variations in material properties such as moisture content and density can lead to significant differences in the rate and efficiency of the carbonation reaction, resulting in unstable reaction effects and even over- or under-carbonation. Furthermore, traditional carbonation equipment often fails to consider the need for dynamic adjustment of reaction conditions during the carbonation process and lacks real-time monitoring and feedback mechanisms, thus affecting the overall carbonation effect and the final performance of the concrete. Summary of the Invention

[0004] This invention provides an adaptive carbonation control method for concrete based on pre-reaction feature recognition, which solves the problem of dynamic adjustment of reaction conditions during the concrete carbonation process and ensures the best carbonation effect for different batches of concrete.

[0005] An adaptive carbonation control method for concrete based on pre-reaction feature recognition includes the following steps:

[0006] S1. Randomly sample from the batch of concrete to be carbonized and place it into the pre-reaction vessel;

[0007] S2. Set the pre-reaction parameters according to the moisture content and density of the sample, perform a short-term pre-reaction on the sample, and collect reaction activity data.

[0008] S3. Calculate the key reaction parameters of concrete raw materials based on the collected data, including carbonation rate constant and maximum carbon uptake capacity;

[0009] S4. Calculate the carbonization control curve of the carbonization reaction based on the key reaction parameters, and determine the optimal reaction time;

[0010] S5. Place the entire batch of concrete blocks into the main reactor and dynamically adjust the carbonation reaction process according to the carbonation control curve.

[0011] S6. Monitor CO2 concentration and temperature and humidity changes during the reaction process, and automatically correct carbonization conditions based on deviations.

[0012] Furthermore, the pre-reaction parameters in step S2 include CO2 concentration, gas pressure, temperature, relative humidity, and reaction time, wherein the CO2 concentration is 5%–10%, the gas pressure is 0.05–0.10 MPa, the temperature is 20–40 ℃, the relative humidity is 60%–80%, and the reaction time is 1–3 min.

[0013] Furthermore, the reaction activity data in step S2 includes the CO2 concentration change curve over time, the temperature rise curve, the humidity change curve, and the reaction initiation delay time.

[0014] Furthermore, the key reaction parameters calculated in step S3 include the carbonization rate constant, the maximum carbon absorption capacity, and the thermal-humidity coupling coefficient. The thermal-humidity coupling coefficient is calculated by the ratio of the highest humidity change value to the temperature rise, and is used to correct the subsequent carbonization control curve.

[0015] Furthermore, in step S4, the process of calculating the optimal reaction time includes the following steps:

[0016] The initial reaction time range is determined based on the carbonization rate constant and maximum carbon absorption capacity obtained during the pre-reaction process;

[0017] Based on the reaction time range, a preliminary carbonization control curve was set;

[0018] By simulating the reaction process and adjusting the matching relationship between CO2 concentration and reaction time, the optimal reaction time that conforms to the material properties is obtained.

[0019] Based on the simulation results, the matching between the carbonization rate and the gas supply rate was further optimized to determine the optimal reaction conditions.

[0020] Furthermore, the preliminary carbonization control curve was generated using an empirical fitting method based on reaction kinetics and heat and mass transfer balance. The carbonization control curve was calculated by inputting the carbonization rate constant, maximum carbon absorption capacity, and thermal-humidity coupling coefficient.

[0021] Furthermore, the carbonization control curve is divided into an initial activation stage, a middle stabilization stage, and a later equilibrium stage. In the initial activation stage, a higher CO2 concentration is used to accelerate the surface reaction. In the middle stage, constant pressure or constant rate carbonization is maintained. In the later stage, the gas pressure and ventilation rate are gradually reduced to achieve a smooth termination.

[0022] Furthermore, the carbonization reaction in step S5 specifically includes the following steps:

[0023] Adjust the CO2 concentration in real time according to the carbonization curve;

[0024] Adjust temperature and humidity parameters according to the reaction progress;

[0025] Monitor gas flow and pressure during the reaction process;

[0026] The reaction conditions are dynamically adjusted based on real-time data.

[0027] Furthermore, dynamically modified reaction conditions include:

[0028] Adjust the CO2 input rate or flow rate according to fluctuations in gas flow rate and pressure to ensure that the CO2 concentration remains within the optimal range during the reaction process;

[0029] Based on real-time data on temperature and humidity changes, adjust the operating status of heating or dehumidifying equipment to ensure that the temperature and humidity meet the requirements of the carbonization reaction.

[0030] When the carbonization reaction process is detected to deviate from the preset target threshold range, the reaction conditions are corrected by adjusting the gas input or temperature and humidity parameters to prevent over- or under-carbonization.

[0031] Furthermore, the automatic deviation correction logic is divided into first-level deviation, second-level deviation, and third-level deviation according to the deviation magnitude. When the deviation is at the first level, the recorded trend is not adjusted; when the deviation is at the second level, a slight correction is performed; and when the deviation is at the third level, the control parameters are recalculated and the reaction conditions are forcibly corrected.

[0032] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0033] This invention overcomes the limitations of the "one-size-fits-all" carbonation parameters in existing technologies by dynamically adjusting carbonation reaction conditions, achieving optimal carbonation results for different batches of concrete. This method primarily uses pre-reaction testing and real-time monitoring to precisely adjust key parameters such as carbon dioxide concentration, temperature, humidity, and reaction time during the carbonation process, thereby improving carbonation efficiency, enhancing concrete strength, and effectively achieving permanent carbon dioxide sequestration. Through real-time monitoring and dynamic adjustment, this invention addresses the differences in concrete composition between different batches by adjusting reaction conditions, avoiding the shortcomings of traditional fixed-parameter methods that cannot adapt to different concrete characteristics. Pre-reaction testing and data analysis accurately calculate the optimal carbonation conditions, significantly improving carbon dioxide sequestration efficiency and reducing resource waste. By optimizing the carbonation reaction, not only is the compressive strength of the concrete improved, but its durability is also increased, making the concrete more stable during long-term use.

[0034] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0035] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0036] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0037] Figure 1 This is a flowchart of an adaptive carbonation control method for concrete based on pre-reaction feature recognition, as disclosed in an embodiment of the present invention. Detailed Implementation

[0038] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0039] like Figure 1 As shown, this invention provides an adaptive carbonation control method for concrete based on pre-reaction feature recognition. This method addresses the problem of mismatched carbonation reaction conditions caused by variations in composition and density of different batches of concrete raw materials. By introducing small-sample pre-reaction testing and adaptive parameter control, it achieves precise regulation of the carbonation process. The steps include: randomly sampling concrete to be carbonized and performing a short-term, low-strength pre-reaction to collect activity data such as CO2 concentration, temperature, and humidity; calculating the carbonation rate constant and maximum carbon uptake capacity based on the collected data to generate a CO2 concentration versus time control curve for the main carbonation reaction (i.e., a carbonation control curve); dynamically adjusting gas input and reaction conditions according to this curve during the main reaction process, and monitoring CO2 and temperature / humidity changes in real time to automatically correct deviations. This method enables adaptive carbonation control for different batches of raw materials, thereby improving CO2 utilization and reaction efficiency, and preventing over-carbonation or under-carbonation. The specific steps are as follows:

[0040] S1, randomly select 1 to 3 representative samples from the batch of concrete to be carbonized.

[0041] It should be noted that the samples must be from newly made concrete products from the same batch of raw materials, and the moisture content and density of the samples must be representative of the overall characteristics of that batch of raw materials.

[0042] Before being placed into the pre-reaction vessel, the sample surface is cleaned of dust and weighed to ensure the accuracy of the test data.

[0043] S2. Based on the moisture content and density of the sample, set the pre-reaction parameters, perform a short-term pre-reaction on the sample, and collect reaction activity data. Specifically,

[0044] The samples were placed in a pre-reaction vessel for a short-term carbonation reaction to identify the carbonation reactivity of the current batch of concrete raw materials.

[0045] The pre-reaction vessel requires the installation of various sensors and monitoring modules, including:

[0046] A CO2 concentration sensor is used to monitor changes in CO2 concentration inside the reactor in real time.

[0047] Temperature sensor, used to detect the temperature rise curve caused by exothermic reaction;

[0048] A humidity sensor is used to monitor changes in the water vapor content generated by the carbonization reaction;

[0049] A pressure sensor is used to ensure a constant reaction gas pressure and to correct for concentration changes.

[0050] These sensors are distributed along the longitudinal and transverse sides of the vessel to form a multi-point monitoring network, ensuring that the data is spatially representative. The sensor signals are input into the control program through the acquisition module for real-time recording and calculation. The sampling frequency is preferably 1Hz to 10Hz to capture the rapid change stage in the early stage of the reaction.

[0051] Before the pre-reaction, pre-reaction parameters are set according to the moisture content and density of the sample. The parameter setting range is as follows:

[0052] CO2 concentration: 5%–10%;

[0053] Air pressure: 0.05~0.10 MPa;

[0054] Temperature: 20–40 ℃;

[0055] Relative humidity: 60%–80%;

[0056] Reaction time: 1–3 min.

[0057] The above parameters are set by the control program of the pre-reaction vessel.

[0058] S3. Based on the collected data, calculate the key reaction parameters of the concrete raw materials, including the carbonation rate constant and the maximum carbon uptake capacity. Specifically,

[0059] The activity data collected in step S2 are analyzed and calculated to obtain the key carbonation reaction parameters of this batch of concrete raw materials.

[0060] The main calculations include the following three aspects:

[0061] 1. Carbonization rate constant ( )

[0062] The value was obtained by fitting the CO2 concentration versus time curve C(t).

[0063] If C0 is the initial concentration Let be the concentration at time t, then the reaction rate can be expressed as:

[0064]

[0065] The reaction rate is classified as high, medium, or low based on the fitting results.

[0066] For example: k > 0.35 indicates a highly active sample; 0.15 < k ≤ 0.35 indicates a moderately active sample; and k ≤ 0.15 indicates a low-activity sample.

[0067] 2. Maximum carbon absorption capacity

[0068] Calculated by integrating the decrease in CO2 concentration.

[0069]

[0070] The actual result is converted to the carbon absorption per unit mass of concrete (g CO2 / kg).

[0071] Example: If sample A has a carbon adsorption capacity of 38 g / kg and sample B has a carbon adsorption capacity of 24 g / kg, the difference indicates that their components have significantly different activities.

[0072] 3. Thermal-humid coupling coefficient ( )

[0073] The temperature and humidity curves are correlated and calculated to correct the subsequent carbonization control curve.

[0074]

[0075] in To reflect the highest humidity change value, To correspond to the temperature rise,

[0076] like If the humidity is too high (>2.0), it indicates that the reaction generates too much water vapor and CO2 diffusion is hindered. The humidity setting should be appropriately reduced in the main reaction.

[0077] Among them, the thermal-humidity coupling coefficient It is used to reflect the combined effects of heat and humidity changes during the reaction process. The larger the value, the more intense the heat release and water vapor generation.

[0078] After the calculations are complete, a reaction characteristic report for this batch of samples is generated, as shown in the table below (example data):

[0079]

[0080] The calculation results were used to generate CO2 concentration versus time control curves for the subsequent main carbonization reaction.

[0081] S4. Calculate the CO2 concentration versus time control curve for the carbonation reaction based on key reaction parameters, and determine the optimal reaction time. Specifically, after obtaining the key reaction parameters of this batch of concrete raw materials in step S3 (including carbonation rate constant k, maximum carbon absorption capacity Cmax, and thermo-moisture coupling coefficient R...), h These parameters are used to dynamically model the main carbonation reaction process, generate the CO2 concentration and time control curves for this batch of concrete, and calculate the optimal reaction time and the conditions for determining the completion of carbonation.

[0082] Specifically, using the parameters identified in the pre-reaction step S2, the CO2 consumption rate, diffusion depth, and exothermic trend in the large-scale carbonization reaction are predicted, thereby achieving "material-specific" carbonization control. The carbonization control curve generation process includes the following:

[0083] Carbonization control curves are generated using computational logic based on reaction kinetics and heat and mass transfer balance. This computational logic can be obtained through empirical formulas or regression fitting, and the specific algorithm implementation is not limited.

[0084] Since the actual reaction is a nonlinear, multivariable process (affected by air pressure, humidity, temperature, and diffusion path), the following calculation steps are performed:

[0085] 1. Initialization phase:

[0086] k, Cmax and calculated in step S3 The input is combined with the pre-reaction pressure and temperature and humidity conditions as the initial boundary conditions.

[0087] 2. Establish a reaction prediction model

[0088] The control program uses data fitting to form a "CO2 concentration change over time prediction model".

[0089] That is, to simulate the decreasing trend of CO2 over time.

[0090] When k is large, the curve decreases rapidly and the reaction time is short.

[0091] when When the humidity is high, the system automatically introduces a humidity correction factor to slow down the initial gas input rate and prevent internal water vapor accumulation.

[0092] 3. Gas supply strategy generation

[0093] The predicted curve is converted into a control command curve, defining the CO2 injection rate, pressure value, and circulating fan power for each time period.

[0094] For example:

[0095] In the initial stage of the reaction (0-10 min), a higher CO2 concentration was set to activate the surface reaction;

[0096] During the intermediate stage (10-30 min), appropriately reduce the air pressure to maintain a constant carbonization rate;

[0097] In the later stage (after 30 minutes), the pressure was gradually reduced to allow the reaction to reach equilibrium.

[0098] 4. Temperature and humidity balance correction:

[0099] The control program simultaneously calls the temperature and humidity deviation correction logic to adjust the thermal-humidity coupling coefficient R. h Included in the calculation.

[0100] like If the value is too high, the control program will automatically reduce the CO2 input rate or increase the frequency of dehumidification circulation.

[0101] like If the temperature is too low, increase the temperature appropriately to maintain the reaction rate.

[0102] Furthermore, the optimal reaction time is determined by integrating the predicted curve to calculate the trend of CO2 absorption over time, identifying the inflection point where the reaction rate curve changes from rising to flat, and using this as the basis for determining the completion of the reaction.

[0103] This point in time is the optimal reaction time. .

[0104] The control program gradually integrates the CO2 absorption rate curve. When the absorption rate per unit time drops below 5% of the initial rate, and both temperature rise and humidity changes tend to stabilize, the current time is automatically determined. .

[0105] Based on the example data from step S3, the optimal reaction time for different samples was calculated, as shown in the table below:

[0106]

[0107] Based on this, the recommended reaction program for each batch is output, including: the curve of CO2 introduction rate changing over time; the pressure control curve; the frequency of humidity balance adjustment; and the automatic termination condition (automatic shutdown when the CO2 concentration decreases by <5%).

[0108] Furthermore, the generated carbonization control curve and The value is used as an input parameter for the main carbonization reaction and is used for subsequent actual reaction control.

[0109] Simultaneously, the calculation results and model parameters of this batch are saved to provide reference data for subsequent batches.

[0110] The main reaction carbonation control curve generated in this step allows for adjustment of reaction conditions to suit the carbonation characteristics of different concrete batches, achieving: synchronous matching of CO2 injection rate and reaction rate; dynamic controllability of the entire carbonation reaction process; shortened reaction time; and improved CO2 utilization rate.

[0111] S5. Place the entire batch of concrete blocks into the main reactor and dynamically adjust the carbonation reaction process according to the carbonation control curve. Specifically...

[0112] 1. Preparation for reactor operation

[0113] Air is pre-purged in the reactor and CO2 gas is introduced to bring the initial concentration to the starting value of the carbonization control curve (e.g., 10%–15%).

[0114] The vessel is equipped with the same type of sensing system as the pre-reaction vessel in the pre-reaction stage, including a CO2 concentration sensor, a temperature and humidity sensor, and a pressure sensor, which are distributed on the top, side walls, and bottom of the vessel to obtain data at different spatial levels.

[0115] It should be noted that, to prevent localized overheating or water vapor retention during the initial carbonization stage, the main reactor is equipped with a circulating flow guiding structure and a drying and filtration module. Simultaneously, based on the initial parameters generated by S4, the circulating fan is automatically activated, causing the gas to form a closed airflow loop within the reactor, flowing from top to bottom and then back to the bottom.

[0116] 2. Dynamic control logic

[0117] Gas introduction and environmental conditioning are performed according to the carbonization control curve described above. The entire carbonization reaction process is divided into three stages:

[0118] 2.1 Initial Activation Phase (t=0~t1)

[0119] It operates under conditions of high CO2 concentration and moderate temperature rise to rapidly activate the surface reaction.

[0120] The control logic is as follows: when the CO2 absorption rate is detected to be in the rising stage, the input rate is kept constant; when the rate reaches its peak, it automatically switches to constant pressure mode.

[0121] Example: The initial stage of the carbonization control curve for sample A is set with a CO2 concentration of 12%, a pressure of 0.1 MPa, a temperature of 35°C, and a duration of 10 minutes.

[0122] 2.2. Mid-term stable reaction stage (t1~t2)

[0123] This stage represents a period of relatively stable reaction rates. The control program maintains a match between the CO2 injection rate and the absorption rate, and maintains reaction equilibrium by fine-tuning the fan power and humidity adjustment frequency.

[0124] Control logic description: When the real-time monitoring shows that the rate of decrease in CO2 concentration is close to ±5% of the theoretical prediction rate, the current gas flow rate is maintained unchanged; if it exceeds the deviation range, it is corrected by adjusting the CO2 inlet rate or humidity.

[0125] Example: During the intermediate stage of sample B, the CO2 concentration was maintained at 8%, the gas pressure at 0.08 MPa, the humidity at 70%–75%, and the reaction was carried out at a constant rate for 20 minutes.

[0126] 2.3 Later equilibrium stage (t2~t3= )

[0127] When the CO2 absorption rate is detected to be continuously decreasing and the temperature and humidity changes tend to be stable, the gas pressure and ventilation rate are gradually reduced to allow the reaction to terminate smoothly.

[0128] The control logic is as follows: if the CO2 absorption rate decreases by less than 5% of the initial rate within three consecutive minutes, a depressurization procedure is executed, and gas input is stopped after stabilization.

[0129] Example: In the later stage, the pressure of sample C was reduced from 0.08 MPa to 0.04 MPa and maintained for 10 minutes before the reaction was terminated.

[0130] 3. Real-time correction mechanism

[0131] During the main reaction process, the control program compares the deviation between the real-time monitoring data and the predicted curve in step S4, and performs automatic corrections based on different deviation types, as follows:

[0132]

[0133] This correction mechanism ensures that the reaction process always remains within the optimal carbonization efficiency range.

[0134] For example, take sample A (highly active sample, k=0.38, For example, (35 minutes)

[0135] 0–10 min: CO2 concentration 12%, pressure 0.1 MPa, temperature 35 °C;

[0136] The control program maintains a constant flow rate, causing the CO2 absorption rate to rise rapidly.

[0137] 10–25 min: CO2 concentration stabilizes at 9%–10%, pressure 0.08 MPa;

[0138] Monitoring data shows that the temperature rise curve is stabilizing and the control program is maintaining constant pressure operation.

[0139] 25–35 min: The absorption rate gradually decreases, the control program initiates a depressurization program, the air pressure drops to 0.05 MPa, and the humidity is maintained at 70%;

[0140] When the CO2 concentration decreases by less than 5% of the initial rate, the control program automatically terminates the reaction.

[0141] The carbonization control curve enabled sample A to absorb 37.8 g / kg of CO2, which is about 1.25 times that of the traditional fixed parameter method, and the carbonized layer was of uniform thickness without embrittlement.

[0142] The data collected during the reaction process is used for real-time deviation correction and carbonization termination determination in step S6, and can also be used as a reference sample input for the next batch of raw materials.

[0143] Through dynamic carbonization control in this step, the following are achieved: the entire reaction process is adjustable and feedback-enabled, eliminating carbonization deviations caused by differences in raw materials from different batches; the carbonization rate is matched with the gas supply to improve CO2 utilization; over-carbonization and embrittlement are automatically prevented to ensure stable mechanical properties of the products; and continuous and controllable production is realized to meet the needs of industrial-scale applications.

[0144] S6. Monitor CO2 concentration and temperature / humidity changes during the reaction process, and automatically correct carbonization conditions based on deviations. Specifically,

[0145] The following key data are continuously collected through a multi-point sensor control program (described in S5) arranged in the main reactor, including:

[0146] CO2 concentration C(t) is used to monitor the change of gas concentration in the reactor over time, and is used to calculate the absorption rate and determine the degree of carbonization.

[0147] Temperature T(t) is used to monitor the heat release during the reaction and to determine the reaction rate and the location of the exothermic peak.

[0148] Humidity H(t) is used to monitor the amount of water vapor generated in the reaction and to determine diffusion hindrance and reaction saturation.

[0149] Pressure P(t) is used to monitor the stability of the pressure inside the vessel and to assist in correcting for changes in concentration and gas input.

[0150] Furthermore, its deviation determination mechanism performs multi-level judgments based on the type and magnitude of the deviation. Specifically, within each sampling period, the relative deviation between the real-time measured value and the target control curve is calculated:

[0151]

[0152] in,

[0153] These are measured parameters (CO2 concentration, temperature, or humidity).

[0154] This is the reference value for the corresponding moment in the carbonization control curve.

[0155] When any If the deviation exceeds a preset threshold (usually ±5%), the deviation correction procedure will be triggered.

[0156] Deviation determination is divided into three levels:

[0157] Level 1 deviation (±3~5%): The control program records the trend and does not adjust immediately;

[0158] Secondary deviation (±5~10%): The control program makes slight corrections, such as fine-tuning the gas input rate;

[0159] Level 3 deviation (>10%): Immediately recalculate and correct the reaction conditions according to the control logic.

[0160] Furthermore, depending on the type of deviation, the corresponding deviation correction logic is invoked, and the correction logic is as follows:

[0161]

[0162] The above strategies enable real-time correction of the reaction environment, keeping the carbonization reaction within the optimal thermal and moisture equilibrium range.

[0163] Furthermore, a "sliding window" data update mechanism is used in continuous sampling, that is, the trend deviation is recalculated every 5 to 10 minutes, and the subsequent carbonization control curve is corrected based on the average deviation. Specifically:

[0164] Over the past N sampling points (e.g., N=60, corresponding to 1 minute), the average deviation Greater than the set threshold At that time, the control program adjusts the target curve parameters for the next time period according to the direction of the deviation, so that the prediction model converges synchronously with the actual response.

[0165] For example:

[0166] like =-6%, indicating that the CO2 consumption rate is too fast, and the control program will automatically extend the remaining reaction time by about 5%;

[0167] like =+7% indicates a lag in response. The control program will increase the pressure by approximately 0.01 MPa or extend the constant pressure phase by 3 minutes.

[0168] Through this continuous update mechanism, the carbonization curve can self-calibrate based on real-time reaction characteristics, forming a dynamic evolution model.

[0169] Furthermore, the completion of carbonization is determined during the monitoring process based on the following three conditions to determine whether the carbonization reaction has reached a terminated state:

[0170] 1. The rate of decrease in CO2 concentration is less than 5% of the initial rate;

[0171] 2. Temperature changes tend to stabilize (ΔT < 1℃ / 5min);

[0172] 3. Humidity change rate is less than 2%. / 5min.

[0173] When the above conditions are maintained for 3 to 5 minutes, the control program will automatically determine that carbonization is complete and stop the CO2 input. When the above three conditions are met at the same time or any two conditions are met for more than 5 minutes, the carbonization reaction is determined to be complete.

[0174] Then, the depressurization and cooling processes are initiated to restore the pressure and temperature inside the reactor to normal.

[0175] Example:

[0176] Taking sample B as an example, when the reaction ran for 46 minutes, the CO2 concentration was detected to decrease from the initial 0.8% / min to 0.03% / min, the temperature change was stabilized within ±0.5℃, and the humidity fluctuation was less than 1.5%. At this point, a "reaction ended" signal was issued and the gas supply was stopped, and the carbonization process was automatically terminated.

[0177] After carbonization is completed, the real-time data, correction records, and final energy consumption parameters throughout the process are stored as the carbonization archive for that batch. This data is used for subsequent quality traceability.

[0178] Specifically, this invention first identifies the carbonation activity of materials through a short-term pre-reaction test on a small sample, calculates key parameters such as the carbonation rate constant and carbon absorption capacity, and then generates a CO2 concentration-time control curve for that batch of materials. During the main reaction, gas input, temperature, humidity, and pressure are dynamically adjusted to keep the carbonation reaction within the optimal range. Based on this, a control logic of "pre-reaction identification—parameter modeling—main reaction control—real-time correction" is established, achieving adaptive carbonation control for different batches of concrete materials. This method effectively overcomes the problems of uneven carbonation or over-carbonation caused by differences in raw materials in traditional fixed processes, achieving dynamic matching between carbonation rate and gas supply.

[0179] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0180] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0181] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0182] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0183] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0184] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A method for adaptive carbonation control of concrete based on pre-reaction feature recognition, characterized in that, Includes the following steps: S1. Randomly sample from the batch of concrete to be carbonized and place it into the pre-reaction vessel; S2. Set the pre-reaction parameters according to the moisture content and density of the sample, perform a short-term pre-reaction on the sample, and collect reaction activity data, including the CO2 concentration change curve over time, temperature rise curve, humidity change curve, and reaction initiation delay time. S3. Calculate the key reaction parameters of concrete raw materials based on the collected data, including carbonation rate constant, maximum carbon absorption capacity and heat-moisture coupling coefficient. The heat-moisture coupling coefficient is calculated by the ratio of the highest humidity change value to the temperature rise, and is used to correct the subsequent carbonation control curve. S4. Calculate the carbonization control curve of the carbonization reaction based on the key reaction parameters, and determine the optimal reaction time; S5. Place the entire batch of concrete blocks into the main reactor and dynamically adjust the carbonation reaction process according to the carbonation control curve. S6. Monitor CO2 concentration and temperature and humidity changes during the reaction process, and automatically correct carbonization conditions based on deviations.

2. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 1, characterized in that, The pre-reaction parameters in step S2 include CO2 concentration, gas pressure, temperature, relative humidity, and reaction time, wherein the CO2 concentration is 5%–10%, the gas pressure is 0.05–0.10 MPa, the temperature is 20–40 ℃, the relative humidity is 60%–80%, and the reaction time is 1–3 min.

3. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 1, characterized in that, In step S4, the process of calculating the optimal reaction time includes the following steps: The initial reaction time range is determined based on the carbonization rate constant and maximum carbon absorption capacity obtained during the pre-reaction process; Based on the reaction time range, a preliminary carbonization control curve was set; By simulating the reaction process and adjusting the matching relationship between CO2 concentration and reaction time, the optimal reaction time that conforms to the material properties is obtained. Based on the simulation results, the matching between the carbonization rate and the gas supply rate was further optimized to determine the optimal reaction conditions.

4. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 3, characterized in that, The initial carbonization control curve was generated using an empirical fitting method based on reaction kinetics and heat and mass transfer balance. The carbonization control curve was calculated by inputting the carbonization rate constant, maximum carbon absorption capacity, and thermal-humidity coupling coefficient.

5. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 4, characterized in that, The carbonization control curve is divided into an initial activation stage, a middle stabilization stage, and a later equilibrium stage. In the initial activation stage, a higher CO2 concentration is used to accelerate the surface reaction. In the middle stage, constant pressure or constant rate carbonization is maintained. In the later stage, the gas pressure and ventilation rate are gradually reduced to achieve a smooth termination.

6. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 1, characterized in that, The carbonization reaction in step S5 specifically includes the following steps: Adjust the CO2 concentration in real time according to the carbonization curve; Adjust temperature and humidity parameters according to the reaction progress; Monitor gas flow and pressure during the reaction process; The reaction conditions are dynamically adjusted based on real-time data.

7. The adaptive carbonation control method for concrete based on pre-reaction feature recognition as described in claim 6, characterized in that, Dynamically modified reaction conditions include: Adjust the CO2 input rate or flow rate according to fluctuations in gas flow rate and pressure to ensure that the CO2 concentration remains within the optimal range during the reaction process; Based on real-time data on temperature and humidity changes, adjust the operating status of heating or dehumidifying equipment to ensure that the temperature and humidity meet the requirements of the carbonization reaction. When the carbonization reaction process is detected to deviate from the preset target threshold range, the reaction conditions are corrected by adjusting the gas input or temperature and humidity parameters to prevent over- or under-carbonization.

8. The method for adaptive carbonation control of concrete based on pre-reaction feature recognition as described in claim 5, characterized in that, The automatic deviation correction logic is divided into three levels according to the deviation magnitude: Level 1 deviation, Level 2 deviation, and Level 3 deviation. When the deviation is Level 1, the recorded trend is not adjusted; when the deviation is Level 2, a slight correction is performed; and when the deviation is Level 3, the control parameters are recalculated and the reaction conditions are forcibly corrected.

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