MICP intelligent preparation and targeted reinforcement method suitable for pervious concrete

Abstract

The invention relates to a pervious concrete MICP intelligent preparation and targeted reinforcement method, which comprises a big data intelligent decision-making platform, a mixing module is controlled to prepare concrete according to a mix proportion suggestion given by a digital twin system, concrete performance data is obtained through nondestructive testing, and the data is fed back to the big data intelligent decision-making platform in real time. The data is pushed to a digital twin system to establish a performance database of the microbial pervious concrete, the LMM mixed model assists the digital twin system to give an optimized microbial pervious concrete ratio, and the pervious concrete based on the MICP technology is prepared according to the optimized microbial pervious concrete ratio. When the mechanical property is obviously degraded, targeted reinforcement is carried out by utilizing microbial factors, and a reinforcement process capable of recovering the mechanical property of the pervious concrete under different environmental conditions is obtained. The MICP technology is used for fixing the microbial material to reinforce the pervious concrete, and the performance of the pervious concrete can be reinforced in a targeted mode through microorganisms in the later period.

Description

Technical Field

[0001] This invention relates to the field of intelligent configuration technology for permeable concrete, specifically to a method for intelligent preparation and targeted reinforcement of permeable concrete MIP. Background Technology

[0002] In my country, urban roads are generally covered with non-permeable cement concrete or asphalt concrete, making it difficult for rainwater to infiltrate the ground. This leads to problems such as overloading drainage systems, urban flooding, and the urban heat island effect. Therefore, the concept of sponge cities is attracting increasing attention. Permeable concrete, due to its excellent water permeability, air permeability, sound absorption and noise reduction, and water filtration properties, has become an important direction for the construction of sponge cities.

[0003] Permeable concrete is a new type of eco-friendly concrete. It features high porosity, no segregation, moderate strength, and low thermal conductivity, allowing water to drain freely, making it ideal for parks, scenic areas, roadsides, and pavements. It not only allows rainwater to infiltrate the earth, replenishing groundwater reserves and meeting the water needs of vegetation, but also facilitates pedestrian travel during rainy days, reducing urban flooding and the urban heat island effect. In recent years, the research and development of permeable concrete has become a hot topic in China. Permeable concrete is an important technology in "sponge cities." It is a type of concrete that allows water to pass through easily, typically composed of cement, coarse aggregate, a small amount or no fine aggregate, admixtures, and water. Its slump is close to zero, its porosity is between 15% and 35%, and the diameter of interconnected pores is between 2 and 8 mm. With the construction of sponge cities in my country, the application of permeable concrete in urban pavements has attracted widespread interest. Permeable concrete pavements offer advantages such as reducing rainwater runoff, alleviating urban flooding, improving effluent quality, increasing groundwater levels, mitigating the urban heat island effect, reducing traffic noise, and enhancing skid resistance. However, they often suffer from disadvantages such as low strength, susceptibility to clogging, and low durability. Therefore, they are currently mainly used in parking lots, sidewalks, bicycle lanes, and other areas with low pedestrian traffic. Developing high-performance permeable concrete is one of the future directions for its development.

[0004] In recent years, microbial induced calcium carbonate precipitation (MICP) technology has received widespread attention in geotechnical engineering as a novel and environmentally friendly soil reinforcement technique. MICP technology mainly utilizes urease produced by the metabolism of microorganisms widely found in nature. The carbonate ions generated after the decomposition of urea combine with free metal cations in nature to form gel crystals, altering the physical mechanics and engineering shape of the soil, thereby achieving the goals of environmental purification, soil remediation, and geological reinforcement.

[0005] The existing production process of permeable concrete has the following problems: 1. Because permeable concrete needs to ensure a certain level of permeability, i.e., a rich permeable pore structure, the use of a small amount of cementitious material results in insufficient physical and mechanical properties, which limits its application to high-load scenarios and restricts its application to low-load areas, making it difficult to meet diverse application scenarios; 2. Permeable concrete has poor durability. In actual use, with temperature changes and long-term loads, its mechanical properties decline, especially in harsh environments such as cold and highly corrosive areas; 3. Existing permeable concrete technology has poor adaptability to changes in different environmental factors, and a post-production control measure is needed to solve the above problems. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the technical problem this invention aims to solve is to provide a method for the intelligent preparation and targeted reinforcement of permeable concrete using MIP technology. This method utilizes MIP technology to fix microbial materials to strengthen permeable concrete and enables targeted reinforcement of permeable concrete performance through microorganisms in the later stages.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for intelligent preparation and targeted reinforcement of permeable concrete using MIP (Micro-Injection Polymerization), the method comprising: Big data intelligent decision-making platform, including digital twin system and LMM hybrid model; The digital twin system is equipped with a machine learning model that can build a training database based on background information (location, load, meteorological data) of the completed project. After inputting the requirements for permeable concrete, it can automatically generate the corresponding optimal mix proportion of ordinary permeable concrete. LMM Hybrid Model: The mix proportion of conventional permeable concrete derived from machine learning is used to predict the performance of microbial permeable concrete after adding biological factors based on MICP technology. The big data intelligent decision-making platform controls the mixing module to prepare concrete based on the mix proportion suggestions given by the digital twin system. The concrete is then cured under environmental factors simulated by the curing module or the environmental simulation module. The concrete performance data is obtained by the non-destructive testing module and fed back to the big data intelligent decision-making platform in real time. The big data intelligent decision-making platform pushes the data to the digital twin system to establish a performance database of microbial permeable concrete. The LMM mixing model assists the digital twin system in providing an optimized mix proportion for microbial permeable concrete. Permeable concrete based on MICP technology is then prepared using the optimized mix proportion. The performance database of microbial permeable concrete includes the relationship between permeable concrete performance and mix proportion, and the performance degradation curve of permeable concrete. Integrated PLC control system: The big data intelligent decision-making platform provides instructions to control the bacterial particle preparation module, mixing module, curing module, environmental simulation module, and microbial targeted reinforcement module to prepare permeable concrete. The performance is tested by the non-destructive testing module. The test data is collected and pushed to the big data decision-making platform, which makes decisions to optimize the mix ratio and train the LMM hybrid model. The bacterial-carrying particle preparation module is used to encapsulate microbial agents and porous media using negative pressure adsorption to form bacterial-carrying particles. The mixing module initially sets the microbial agent, porous media type, and addition ratio for the preparation of bacterial particles. The bacterial particle preparation system prepares the bacterial particles. Based on the optimal traditional permeable concrete mix ratio determined by the big data decision platform, the bacterial particles are mixed with the raw materials of traditional permeable concrete to obtain a slurry. The curing module intelligently cures the slurry obtained from the mixing module. The non-destructive testing module performs non-destructive testing on the mechanical and permeability properties of permeable concrete and feeds the data back to the big data intelligent decision-making platform. The environmental simulation module is used to simulate environmental factors in the corresponding region, apply corresponding environmental factors to the test blocks after intelligent curing, accelerate the degradation process of the mechanical properties of the test blocks, and obtain the curves of the corresponding degradation properties through the non-destructive testing module; The microbial targeted reinforcement module is used to reinforce permeable concrete by supplementing microbial inoculum, calcium source, and nitrogen source when its mechanical properties deteriorate significantly. When the mechanical properties are restored to the set value, the reinforcement process ends, thus obtaining a reinforcement process that can restore the mechanical properties of permeable concrete under different environmental conditions.

[0008] Furthermore, during the curing process, the performance of the specimen is obtained through a non-destructive testing module. If the performance of the specimen does not meet the mechanical and permeability requirements, the data is fed back to the big data intelligent decision-making platform to change the type of microorganism, the type of carrier, or the thickness of the coating. After the microorganisms are filled, their mechanical properties and permeability are tested in real time through the non-destructive testing module. If the permeability can be improved without compromising the mechanical properties, the optimal mix proportion of microbial permeable concrete is determined.

[0009] Furthermore, the non-destructive testing module includes a strength development non-destructive testing unit, a water permeability testing unit, and a porosity testing unit. The strength development non-destructive testing unit includes an ultrasonic tester and a digital rebound hammer, which are combined to achieve both strength and non-destructive testing. The water permeability testing unit uses a water permeability coefficient measuring instrument to test water permeability, and the porosity testing unit uses a BET surface area analyzer to test porosity. Through water permeability testing, it is possible to observe whether microorganisms are active, and by combining the mechanical properties, the degree of microbial activity can be determined.

[0010] Furthermore, the porous medium is fly ash ceramsite; the fiber is basalt fiber.

[0011] Furthermore, in the microbial targeted reinforcement module, the mechanical properties are tested in real time using a non-destructive testing module. When the mechanical properties degrade to a preset performance threshold (compressive strength decreases by 25%), microbial liquid is sprayed at a rate of 5L per square meter, with the spraying speed set to 10-20mL / min. After the set immersion time is reached, calcium and nitrogen sources are added in batches. After each batch reaches the preset reaction time, the next batch is added. After the set batch is reached, the next cycle of microbial liquid, calcium source, and nitrogen source are added until the mechanical properties are restored to 75% of the original value, at which point the targeted reinforcement process ends.

[0012] Furthermore, the digital twin system also includes a multi-source data fusion module, a database, a cost-constraint extension module, and a dynamic visualization monitoring module. These modules are used to dynamically adjust the material mix ratios based on different environmental factors by traversing the material database. They also combine the material cost quotation table from the cost-constraint extension module with three objectives—mechanical performance, permeability, and cost—to optimize the mix ratio of traditional permeable concrete suitable for the corresponding application environment and provide a recommendation table of nearby material manufacturers. The environmental factors include climate temperature, humidity, rainfall, rainfall intensity, ultraviolet radiation intensity, and load requirements. The load requirements include the load demands of vehicles and pedestrians. The cost constraint extension module stores material cost quotations from material suppliers in different regions. The database is used to store the minimum strength requirements of traditional permeable concrete under different environmental data, as well as the permeability, mechanical properties, porosity range, durability and environmental protection requirements of different traditional permeable concrete mix proportions under different environmental data. The multi-source data fusion module analyzes information including climate, load requirements, and cost for regions corresponding to the mix proportions of existing permeable concrete projects. The machine learning model is trained using the data processed by the multi-source data fusion module, and the optimal mix proportion of traditional permeable concrete is obtained from the trained machine learning model. The dynamic visualization monitoring module provides intuitive data display and decision support.

[0013] Furthermore, after curing, the concrete is placed under different working conditions to obtain corresponding performance degradation curves. When the performance of the permeable concrete degrades to a threshold, a reinforcement mechanism is triggered, restoring the performance of the permeable concrete to 75% of its original state. The different working conditions refer to simulated extreme temperatures (freeze-thaw), rainstorm runoff, solar radiation, chemical media, and standard environment. The simulated extreme temperatures refer to freeze-thaw conditions, solar radiation refers to different ultraviolet radiation intensities, and chemical media refers to different liquid environments of salt, alkali, or acid solutions.

[0014] This invention also protects a permeable concrete based on MICP technology that can be microbially targeted and reinforced, wherein the raw material composition and mass ratio of the permeable concrete are as follows: The mass ratio of aggregate, cement matrix, basalt fiber, BLP, silica fume, water, water-reducing agent, urea, and calcium lactate is: 1:0.2~0.3:0.002~0.003:0.05~0.06:0.02~0.03:0.08~0.09:0.009~0.01:0.011~0.0012:0.005~0.006; The aggregate is limestone crushed stone with a particle size of 4.75~9.5mm, the basalt fiber is 12mm short-cut basalt fiber, and the bacteria-carrying particles are porous ceramsite coated with metakaolin and loaded with Bacillus pasteurella. The optimal mix ratio for preparing microbially targeted reinforced permeable concrete based on MICP technology was determined using the method described above at the aforementioned mass ratio.

[0015] Compared with the prior art, the present invention has the following beneficial effects: This invention applies MIP (Micro-Induced Polymerization) technology to permeable concrete. Urease produced by urease-producing bacteria catalyzes the hydrolysis of urea to generate carbonate ions, which in turn catalyze the hydrolysis of urea to produce NH3 and CO2. Then, NH3 and CO2 dissolve in water to form NH4. + OH - HCO3 - and CO3 2- Plasma causes an increase in the pH level of the environment; finally, CO3... 2- In an alkaline environment, it reacts with Ca. 2+ By combining the deposition of CaCO3 crystals to fill the internal pores of permeable concrete, the generation of ineffective pores is reduced, thereby enhancing its mechanical properties. In this process, urea indirectly provides the substrate for the mineralization reaction, while calcium lactate provides free calcium ions. As the actual service life of permeable concrete increases, its mechanical properties significantly decrease. Simultaneously, by utilizing a microbial targeted reinforcement module, a corresponding reinforcement process for permeable concrete after incorporating MIP technology can be obtained, facilitating the reinforcement application of permeable concrete after its service in actual working environments.

[0016] In the later stages of use, the permeable concrete of this invention can restore the performance of permeable concrete by supplementing calcium sources, nitrogen sources and microbial agents to allow urease bacteria to continue to exert mineralization.

[0017] This invention employs MIP technology and fiber-reinforced materials, particularly by using Bacillus pasteurellium to microbially modify aggregates, thereby enhancing the bonding ability between aggregates and cementitious materials and significantly improving the mechanical properties of permeable concrete. This modification ensures that permeable concrete can meet higher performance requirements in high-load application scenarios and maintain good environmental tolerance during use, avoiding cracks or damage to traditional permeable concrete after working stress loads.

[0018] This invention utilizes the property of urease-producing bacteria in MIP technology to generate calcium carbonate precipitate, which has the property of repairing microcracks in rock mass, thereby improving the self-healing ability of permeable concrete, extending the service life of concrete, and enhancing its environmental tolerance.

[0019] In this invention, the traditional permeable concrete mix proportion is dynamically adjusted based on environmental factors of concrete application (temperature and humidity (the actual climate conditions of the application scenario are determined based on the latitude and longitude of the application environment), rainfall, rainfall intensity, and load intensity) through a big data intelligent decision-making platform. This achieves the best performance of permeable concrete in different application scenarios and ensures its optimal environmental tolerance.

[0020] This invention's platform features big data input capabilities, allowing users to input concrete application locations (place name, latitude and longitude, load requirements such as vehicles and pedestrians) and integrate multi-source data from weather stations, satellites, and models. It creates a climate database including rainfall, ultraviolet radiation intensity, temperature, and humidity, as well as a target minimum strength. Real-time statistical analysis of various indicators reveals the required performance characteristics of the target concrete (permeability, mechanical properties, porosity range, durability, and environmental requirements) and its economic viability (through cost prediction analysis). The required performance requirements are input into a machine learning model, which uses a hybrid model (LMM) to predict the performance of permeable concrete after the addition of microorganisms (MICP technology). A big data intelligent decision-making platform then determines the usage of various materials and provides recommendations from nearby material manufacturers to optimize costs.

[0021] The process for determining the mix proportion on the platform of this invention is as follows: parsing location information, parsing performance requirements, searching for similar engineering cases, analyzing local material supply, generating a recommended mix proportion, predicting performance, cost analysis, generating optimization suggestions, and constructing the recommended results.

[0022] The highly alkaline environment of concrete inhibits microbial activity, and directly adding microorganisms does not achieve the desired strengthening effect. This invention, based on MICP technology, enables dynamic reinforcement of permeable concrete, obtaining corresponding reinforcement processes, improving the performance of permeable concrete, and extending its service life. The microbial carrier has two main functions: firstly, it protects bacteria from the harmful effects of the highly alkaline environment in concrete; secondly, it provides space for microbial growth and metabolism, acting like a "house." The carrier serves as a space to store and maintain bacterial activity, allowing it to continue to function within the concrete. In the examples, the compressive strength of permeable concrete specimens prepared according to the optimal mix ratio can reach 35 MPa, far exceeding the requirements of the "Technical Specification for Permeable Cement Concrete Pavement" (CJJ / T135-2009). The strength of the permeable concrete is controlled in the later stages of its construction to ensure that its mechanical properties and permeability meet the specifications for a long period. Attached Figure Description

[0023] Figure 1 This is a logic framework diagram of one embodiment of the present invention applicable to the intelligent preparation and targeted reinforcement method of permeable concrete (MICP).

[0024] Figure 2 This is a mix proportion diagram of permeable concrete after introducing MICP technology, as output by an embodiment of the present invention.

[0025] Figure 3 This is a schematic diagram of the interaction logic between the various parts of the present invention applicable to the intelligent preparation and targeted reinforcement method of permeable concrete (MICP). Detailed Implementation

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. However, it should be understood that the embodiments described herein are merely exemplary and not all embodiments.

[0027] In this embodiment, the preparation of bacterial-loaded particles and the specific operation of fixing bacteria with ceramic particles are described. The Bacillus pasteurellium suspension is mixed with ceramic particles in a certain proportion and then subjected to negative pressure adsorption to prepare bacterial-loaded particles and coating.

[0028] This invention establishes a big data intelligent decision-making platform to assist in the mixing of various materials. The big data intelligent decision-making platform consists of a digital twin system (composed of a multi-source data fusion module and a machine learning model). It automatically adjusts the material ratio based on three environmental factors: temperature changes, precipitation, and load requirements, to ensure that traditional permeable concrete has the optimal comprehensive performance (mechanical properties and permeability).

[0029] The big data intelligent decision-making platform collects real-time temperature and precipitation data using real-world instruments (temperature and rainfall sensors), analyzes historical meteorological data, and calculates suitable mix proportions for conventional permeable concrete through machine learning and multi-source data fusion analysis. It can also input the requirements for microbially reinforced permeable concrete into the platform, using an LMM (Large Mixture Model) to assist the digital twin system in providing optimized microbial permeable concrete mix proportions.

[0030] Example 1 A big data intelligent decision-making platform is established to assist in the mixing of aggregates and microbial-carrying particles. This platform uses machine learning models to automatically adjust the material ratio of traditional permeable concrete (which does not contain microbial-carrying particles, urea, or calcium lactate) based on the future application area, load, temperature changes, and rainfall. This ensures optimal overall performance of the permeable concrete. The platform collects real-time temperature and rainfall data for each region using temperature and rainfall sensors. Real-time data from each region is collected and compared with actual instruments through a big data digital twin system. Machine learning models analyze the environmental data and calculate the appropriate material ratio for traditional permeable concrete. The platform then determines the required quantities of various materials.

[0031] This embodiment of the preparation of high-performance microbial permeable concrete based on MICP technology uses a big data intelligent decision-making platform to determine the following formula: aggregate, cement matrix, basalt fiber (BF), BLP (bacteria-laden particles), silica fume (SF), water, water-reducing agent, urea, calcium lactate, and cementitious materials are mixed together in the following mass ratio: 1: 0.2~0.3: 0.002~0.003: 0.05~0.06: 0.02~0.03: 0.08~0.09: 0.009~0.01: 0.011~0.0012: 0.005~0.006.

[0032] The data input requirement for this mix design is: permeable concrete pavement for a park in Beichen District, Tianjin, with load requirements for pedestrians, bicycles, and light passenger vehicles. The digital twin system analyzes the requirements to generate a corresponding conventional permeable concrete mix design, and then incorporates a mix design for microbially enhanced permeable concrete. The big data intelligent decision-making platform uses this mix design to prepare the corresponding permeable concrete, tests its performance, and confirms that the performance meets the input requirements.

[0033] The aggregate is limestone crushed stone with a particle size of 4.75~9.5mm, the basalt fiber is 12mm short-cut basalt fiber, and the bacterial-carrying particles are porous rock particles coated with metakaolin and loaded with Bacillus pasteurella. The preparation process of the bacterial-carrying particles is as follows: fly ash ceramsite with a particle size of 2.36~4.75mm is screened, and washed and dried to ensure that each particle is clean inside and out. The washed and dried ceramsite is then soaked in OD... 600 The particles are subjected to negative pressure adsorption in a bacterial solution with a microbial activity of 1, allowing the particles to absorb the bacterial solution. After three hours of negative pressure adsorption, the particles are drained and dried at low temperature. The particles are then coated with a dilute solution of metakaolin and water glass, and dried at 40°C after coating.

[0034] First, the aggregate and bacteria-carrying particles are poured into a high-efficiency mixer and 35% water is added. The mixture is stirred for 60 seconds to fully wet the aggregate. Then, the cementitious material (cement, silica fume, calcium lactate powder, urea, and powder water-reducing agent are mixed evenly using a common admixture method) is added and stirred for 120 seconds to coat the aggregate surface with a layer of cement paste. Next, the remaining raw materials (fiber and the remaining 65% water) are added and stirred for 60 seconds. The mixture is then discharged and molded to obtain a slurry. This slurry is then formed using a standard mold with dimensions of 100mm × 100mm × 100mm. A combination of tamping and vibration molding is used for compaction. The tamping method strictly follows the People's Republic of China Building Materials Industry Standard "Permeable Concrete" (JC / T2558-2020). The mass of 1L of permeable concrete is weighed according to the mix proportion. Two layers were placed into the mold, each layer tamped 16 times: once at each of the four corners, twice on each side, and four times in the plane. The tamping frequency on the sides and in the plane was to be evenly distributed. A vibrating table was then used for shaping, with a vibration frequency of 20-30Hz and a vibration time of 30-60 seconds. The surface of the shaped concrete was then smoothed with a trowel to ensure a flat surface. The shaped concrete was placed in a standard curing room for curing, with the curing temperature controlled between 20℃ and 30℃ and the humidity controlled above 90%. The curing time was 7-14 days. During this period, the hardening progress and strength gain of the permeable concrete were monitored using a temperature and humidity control module (ultrasonic humidifier, industrial precision air conditioner, PTC ceramic heater) to automatically adjust the temperature and humidity, accelerate the hydration reaction of the concrete, and improve its strength. During curing, temperature and humidity sensors were used to monitor the internal temperature and humidity of the concrete in real time, and the curing conditions were adjusted accordingly.

[0035] After curing, the specimens were tested using the permeability test method to determine the permeability coefficient of the permeable concrete, ensuring that the permeability met national standards. After the permeability test, the specimens were allowed to dry naturally to constant weight before undergoing compressive strength testing, frost resistance testing, and acid resistance testing.

[0036] The compressive strength test shall be conducted in accordance with the national standard. The compressive strength of the test sample shall be greater than 25 MPa. During the test, a hydraulic universal testing machine shall be used to apply pressure to the standard specimen until it fails, and the maximum load force of the specimen shall be recorded.

[0037] According to national standards, the frost resistance test is conducted. The test samples are required to have a strength loss of no more than 20% and a mass loss rate of no more than 5% after 25 freeze-thaw cycles. The standard specimens are subjected to freeze-thaw cycle tests using a freeze-thaw test chamber to test their mechanical properties and mass loss. At the same time, crack width and crack propagation are monitored to ensure the long-term stability of permeable concrete in cold regions.

[0038] Example 2 This embodiment describes a microbially controlled permeable concrete based on MICP technology, comprising aggregates, microbial-loaded particles, basalt fibers, a cement matrix, a water-reducing agent, powdered calcium lactate, silica fume, powdered urea, and water. The aggregates are crushed limestone of the same particle size range obtained through crushing and screening; in this embodiment, the crushed limestone has a particle size of 4.75-9.5 mm. The microbial-loaded particles are ceramsite treated with negative pressure adsorption and labeled BLP. The cement matrix is ​​silicate cement, and the water-reducing agent is a powdered polycarboxylate water-reducing agent. The water is tap water. The silica fume is micro-silica fume. The basalt fibers are 12 mm chopped basalt fibers. The cement matrix is ​​PO42.5 ordinary silicate cement.

[0039] In this example, the input project background requirement is a permeable concrete pavement in a park in Beichen District, Tianjin, with load requirements for pedestrians, bicycles, and light passenger vehicles. The optimized microbial permeable concrete mix proportion provided by the LMM hybrid model-assisted digital twin system is as follows:

[0040] This mix proportion calculation assumes the total mass is set to 1. For details, please refer to [link / reference needed]. Figure 2 .

[0041] The preparation process of BLP is as follows: Before adding the expanded clay aggregate to the concrete, it is first coated with metakaolin clay as the coating material. The coating material is prepared by mixing the metakaolin clay with water glass in a ratio of 1.0:2.2:1.1 to form a spraying material slurry. The spraying material is mixed and stirred for 5 minutes. After adjusting the air compressor pressure to 0.5 MPa, the mixed spraying material is added to the spray gun barrel and sprayed on one side of the particle surface. After spraying, the carrier particles are turned over and the other side of the bacteria-containing particles is sprayed. This process is repeated twice. After standing for 12 hours, the material is sprayed twice more. This operation forms a thin film on the surface of the expanded clay aggregate, forming bacteria-carrying particles. In this embodiment, the porous medium is expanded clay aggregate (fly ash expanded clay aggregate). The coated expanded clay aggregate is not only compatible with the cement matrix, but also effectively prevents the activity of microorganisms from decreasing due to the high alkalinity of the concrete during soil mixing and molding. This ensures that microorganisms can effectively play a strength-regulating role in the concrete for a long time, improving the concrete strength and extending the service life of the concrete.

[0042] Mix the slurry according to the above proportions, and place the mixed slurry in a standard molding mold with dimensions of 100mm × 100mm × 100mm. Then place it in the curing chamber for curing. To ensure that microorganisms maintain stable and long-term activity during concrete curing, the temperature and humidity in the curing chamber are controlled by zones. Different temperature and humidity sensors and regulating devices are set up according to the different placement locations of the concrete specimens. For example, in the area near the entrance of the curing chamber, where heat and moisture loss is relatively faster, a temperature compensation device is installed to make the temperature 1-2℃ higher and the humidity 5%-10% higher than the central area of ​​the curing chamber, ensuring that the concrete in different locations throughout the curing chamber is cured under suitable temperature and humidity conditions. At the same time, during the curing process, the air in the curing chamber is regularly ventilated, once every 4-6 hours, with each ventilation changing 10%-15% of the total volume of the curing chamber, to remove potentially accumulated harmful gases such as carbon dioxide, providing a good environment for the hydration reaction of the concrete. The curing temperature is 20-30℃, the humidity is above 90%, and the curing time is 7-28 days.

[0043] After the maintenance is completed, relevant performance tests will be conducted, namely permeability coefficient test and mechanical performance test, to ensure that the permeability and mechanical performance meet the standards.

[0044] Example 3 In this embodiment, the preparation of bacterial-carrying particles includes the following steps: SP1. Microbial Culture Procedure: Prepare LB liquid medium by adding 10g tryptone, 5g yeast extract, and 10g sodium chloride per liter of LB liquid medium solvent. Adjust the pH to 10.0 and sterilize at 121℃. After high-temperature sterilization, add sterile urea solution at a volume ratio of 1:9 (LB liquid medium is always 2% by mass urea solution). In a sterile operating table, inoculate with Bacillus pasteurellii culture at a 5% inoculation ratio according to the standard aerobic microbial inoculation procedure, and incubate in a constant temperature shaker (set to 30℃) for 36 hours.

[0045] SP2, Microbial Adsorption Steps for Ceramsite: Sift 2.36~4.75mm fly ash ceramsite and thoroughly wash it to remove surface dust. During washing, use high-pressure water flow combined with steel sieve filtration to ensure each ceramsite surface is clean. Place the washed ceramsite in an oven at 105℃ to dry the moisture. After drying, cool to room temperature and place in a vacuum saturation device. Turn on the vacuum pump until the internal negative pressure of the saturation device is stable at 0.8MPa for 5 minutes. Turn off the vacuum pump, open the feed valve, and stably draw in the cultured bacterial solution through negative pressure. After the ceramsite has adsorbed the bacterial solution for 2 hours, filter out the excess unadsorbed bacterial solution from the ceramsite and dry it in an oven at 40℃.

[0046] SP3, Bacterial-Carrying Particle Coating Process: After drying, the bacterial-carrying particles are placed flat on a clean tray, and the outer coating is performed by spraying. The spraying process is as follows: the microbial-carrying ceramic particles are spread flat on the tray; a spraying material slurry is prepared according to a certain ratio (industrial water glass: metakaolin: water = 1.0: 2.2: 1.1), and the spraying material is mixed and stirred for 5 minutes. After adjusting the air compressor pressure to 0.5 MPa, the mixed spraying material is added to the spray gun barrel, and one side of the particle surface is sprayed. After spraying, the carrier particles are turned over, and the other side of the bacterial-carrying particles is sprayed. This process is repeated, and the particles are sprayed twice. After standing for 12 hours, the particles are sprayed twice more to obtain bacterial-carrying particles.

[0047] Concrete mixing process: First, pour the aggregate and bacteria-carrying particles into a high-efficiency mixer and add 35% water and mix for 60 seconds to fully wet the aggregate. Then, add the cementitious material (cement, silica fume, calcium lactate powder, urea, and powder water-reducing agent are mixed evenly to obtain the cementitious material) and mix for 120 seconds to coat the surface of the aggregate with a layer of cement paste. Then, pour in the remaining raw materials (fiber and the remaining 65% water) and mix for 60 seconds before discharging and molding.

[0048] This invention adds BLP to permeable concrete, which allows microorganisms to stably produce calcite, filling ineffective voids. Furthermore, when microcracks appear in the concrete, the expanded clay aggregate breaks, releasing a large amount of microorganisms. These microorganisms react with urea and calcium lactate in the cement matrix to produce calcite, which fills and repairs the cracks, thus extending the service life of the concrete.

[0049] The concrete is formed using standard molds measuring 100mm×100mm×1000mm. A vibratory tamping table is used for compaction at a frequency of 20-30Hz for 30 seconds to 1 minute to ensure a smooth surface and compact interior. The formed concrete is then placed in a temperature- and humidity-controlled curing room. The curing temperature should be maintained between 20℃ and 30℃, and the humidity above 90%. The curing time is 7 to 28 days. During this period, the hardening progress and strength gain of the concrete are monitored. A temperature-controlled curing system is used to automatically adjust the temperature and humidity, accelerating the hydration reaction and increasing the concrete's strength. Temperature and humidity sensors (platinum resistance temperature sensor array and capacitive humidity sensor array) are used to monitor the internal and external temperature and humidity of the concrete, adjusting curing conditions in real time. SP4. The permeability coefficient test method is used to test the permeability of permeable concrete. During the test, the concrete sample is placed in a water leakage device, and the time it takes for water to pass through the concrete is measured to calculate the permeability coefficient. This ensures that the permeability meets the national standard. Then, the compressive strength test is carried out according to the national standard. The compressive strength of the test sample should be greater than 25MPa. During the test, a hydraulic testing machine is used to apply pressure to the standard specimen until it breaks. The maximum bearing capacity is recorded. The sample is then placed in a freeze-thaw test chamber and subjected to 25 freeze-thaw cycles. The mass loss rate and changes in freeze resistance of the sample are observed. At the same time, the crack width and crack propagation are monitored to ensure the long-term stability of permeable concrete in cold regions.

[0050] Example 4 The entire concrete preparation process mainly includes the following steps: Raw material preparation stage: Aggregate Screening and Pretreatment: Crushed stone purchased from the quarry is screened using aggregate screening equipment to separate aggregate particles with a diameter of 4.75~9.5mm. Then, these aggregates are placed in a large washing tank, and a high-pressure water jet washing device is activated, with the water pressure set at 3-5MPa. Simultaneously, a mechanical scrubbing device is used to ensure that the mud and dust on the surface of each aggregate are thoroughly removed. After washing, the aggregates are air-dried in a naturally ventilated environment for 24~48 hours to remove excess surface moisture.

[0051] Preparation of BLP: The purchased bacterial cells were inoculated and cultured using liquid culture medium according to the conventional inoculation and culture methods for aerobic microorganisms to obtain a bacterial suspension, which was then diluted to OD. 600The value is 1. 2.36~4.75mm ceramsite is sieved, and the diluted bacterial solution is mixed with the ceramsite using a vacuum impregnation method. After the ceramsite absorbs the bacterial solution for 2 hours, excess unabsorbed bacterial solution is filtered out, and the ceramsite is dried in an oven at 40℃. The outer coating is applied using a spray coating method. The spraying process using a bottom vibrating table and a mechanical wall spray gun is as follows: Microbial-laden ceramic particles are spread evenly in the vibrating table tray; a spraying material slurry is prepared according to a certain ratio (meta-kaolin: industrial water glass: water = 2.31:1.0:1.1); the spraying material is mixed and stirred for 5 minutes; after adjusting the air compressor pressure to 0.5 MPa, the robotic arm spray gun automatically picks up the mixed spraying material cylinder and sprays one side of the particle surface; the side electric drying system is activated, blowing out a 40°C hot airflow to dry the coating material; after spraying, the vibrating table is turned over to flip the carrier particles, and the other side of the bacteria-containing particles is sprayed; the electric drying system is then activated again and maintained for 5 minutes; this process is repeated twice; the above operation is repeated twice.

[0052] Other material preparation: Use silicate cement with a grade of 42.5 as the cement matrix, and the water reduction rate of polycarboxylate water-reducing agent is 25%-35%. Ordinary tap water is used.

[0053] Building a Big Data Intelligent Decision-Making Platform: Module 1: Multimodal Sensing and Monitoring System Temperature sensor (accuracy ±0.5°C): Platinum resistance temperature sensing array Outdoor temperature monitoring points: High protection level (IP67) and strong weather resistance models should be selected and installed in louvered boxes next to the permeable concrete area where it will be put into service, avoiding direct sunlight and rain.

[0054] Temperature monitoring points in the indoor raw material storage area: The focus is on monitoring the temperature and humidity of different raw material (cement, aggregate) areas, as changes in humidity may affect the physical properties of the raw materials (flowability, moisture content).

[0055] Rainfall sensor: Deployed outdoors, its main function is to detect recent rainfall. After heavy rain, air humidity and aggregate surface moisture content change drastically, making it a key input for mix proportioning adjustments.

[0056] Ultraviolet sensor (measurement range 280-600nm, accuracy ±5%): Multi-band ultraviolet sensing and recording module Outdoor UV monitoring point: Monitors UV intensity, which, along with temperature, affects certain additives (such as pasteurized spores). Indoor UV monitoring points: Usually no installation is required unless there is a translucent ceiling and the material is sensitive to UV radiation.

[0057] Industrial-grade data acquisition unit: Its functions are (1) to power the sensors. (2) to read the analog / digital signals from each sensor. (3) to perform preliminary data processing. (4) to package and upload the data to the central processing server via the industrial Ethernet protocol.

[0058] Data acquisition frequency: Environmental data changes relatively slowly, so a timed acquisition mode (once every 5 minutes) combined with change triggering (when the temperature changes by more than 1°C) is adopted.

[0059] Module Two: Data Analysis and Processing Module Data preprocessing and feature engineering Data cleaning: Handling outliers and missing values ​​from sensors (e.g., using mean imputation, preceding / following value imputation, or predictive imputation). Data fusion: Aligning sensor data from different sources and frequencies and integrating them into a series of timestamp-synchronized "environmental status" records.

[0060] Feature construction: In addition to the raw data, construct more meaningful features, such as moving average (average temperature over the past hour, reducing fluctuation noise), cumulative rainfall (total rainfall over the past 12 / 24 hours), and temperature difference (the difference between the current indoor temperature and the standard temperature (20°C)).

[0061] Machine learning models (such as decision tree algorithm models): Input: Preprocessed environmental feature vectors (temperature, humidity, UV intensity, cumulative rainfall).

[0062] Output: Predicted performance indicators of permeable concrete (compressive strength, porosity, permeability coefficient, slump).

[0063] Objective: To find the optimal material ratio that meets all performance requirements (strength > 25 MPa, porosity > 15%) under the current environmental conditions.

[0064] Decision variables: dosage of each raw material (water-cement ratio, aggregate particle size and proportion, fiber, BLP and admixture (water-reducing agent, permeable concrete reinforcing agent, etc.)). Constraints: Lowest cost, maximum performance, and meeting the target formulation range.

[0065] Module 3: Hardware Control and Data Acquisition Module Integrated PLC control system: Industrial PLCs receive optimal mixing ratio instructions from data analysis and processing modules. Based on the mixing ratio, the PLC precisely controls the start, stop, and speed of raw material conveying equipment (belt scales, screw conveyors, liquid pumps) by controlling frequency converters, weighing sensors, and pneumatic / electric valves. Raw material conveying equipment includes precision feeders under each silo, weighing hoppers, and water pumps. The control precision of these components directly determines the accuracy of the final mixing ratio. The mixer control system controls the mixing time and speed to ensure uniform mixing.

[0066] Mixing and stirring: First, pour the aggregate and bacteria-carrying particles into a high-efficiency mixer and add 35% water and stir for 60 seconds to fully wet the aggregate. Then, add the cementitious material (cement, silica fume, calcium lactate powder, urea, and powder water-reducing agent are mixed evenly to obtain the cementitious material) and stir for 120 seconds to coat the surface of the aggregate with a layer of cement paste. Then, pour in the remaining raw materials (fiber and the remaining 65% water) and stir for 60 seconds before discharging and molding. The inner wall of the mixer drum is equipped with a special wear-resistant coating to reduce wear and material residue during the mixing process. The mixing blades adopt a double-layer spiral structure, with the upper blades rotating left and the lower blades rotating right. During mixing, the material can form a composite motion of vertical convection and horizontal shearing.

[0067] Concrete forming and curing: Molding: Pour the mixed material into a standard steel mold with dimensions of 100mm×100mm×100mm. The inner surface of the mold is pre-coated with a release agent with a coating thickness of 0.05-0.1mm. Place the mold on a vibration table with a vibration frequency of 25Hz and a vibration time of 45 seconds to compact the concrete material within the mold.

[0068] Curing: The molded concrete specimens are immediately transferred to specially designed curing racks in the curing chamber. The temperature control system of the curing chamber employs an intelligent thermostat, using multiple temperature sensors distributed throughout the chamber to monitor the temperature in real time. When the temperature drops below 20°C, the heating device (electric heating wire power of 10-15kW) is activated; when the temperature exceeds 30°C, the air conditioning (cooling capacity of 3-5 horsepower) is turned on, maintaining the curing temperature between 20-30°C. The humidity control system uses an ultrasonic humidifier and an exhaust fan working in tandem. When the humidity drops below 90%, the humidifier automatically starts to increase indoor humidity; when the humidity exceeds 95%, the exhaust fan turns on to expel some moisture, ensuring the humidity remains stable between 90% and 95%. During curing, temperature and humidity sensors (temperature accuracy ±0.3°C, humidity accuracy ±3%) monitor the internal temperature and humidity of the concrete in real time. The data is transmitted to the central control system in the curing chamber, which automatically adjusts the curing conditions according to the set curing curve. During this period, the hardening progress and strength growth of the concrete were monitored regularly (every 2 days), and non-destructive testing methods (rebound hammer testing) were used to preliminarily assess the development of concrete strength.

[0069] Performance testing and evaluation: Permeability coefficient test: After curing, take the concrete sample out of the curing room and put it into a standard permeability coefficient test device (leakage device). The water level in the test device is kept at 100mm. Measure the time it takes for water to pass through the concrete sample and calculate the permeability coefficient according to the formula to ensure that the permeability meets the national standard. The permeability coefficient is required to be greater than 0.5mm / s.

[0070] Compressive strength test: Concrete compressive strength test specimens (100mm×100mm×100mm in size) are prepared according to national standards. Pressure is applied to the specimens using a hydraulic testing machine, with the loading rate controlled at 0.5-1MPa / s, until the specimen fails. The maximum bearing capacity is recorded. The compressive strength of the test sample should be greater than 25MPa.

[0071] The freeze-thaw cycle test involves placing concrete samples in a freeze-thaw test chamber, setting the number of freeze-thaw cycles to 25, the freezing temperature to -20℃, and the thawing temperature to 20℃, with each freezing and thawing cycle lasting 4 hours. During the freeze-thaw cycle, the mass loss rate and changes in frost resistance of the samples are observed periodically (every 5 cycles). Simultaneously, a high-precision microscope is used to monitor crack width and crack propagation to ensure the long-term stability of permeable concrete in frigid regions. The mass loss rate is required to be no more than 5%, and the compressive strength loss after freeze-thaw cycles is required to be no more than 20%.

[0072] Example 5 1. Raw materials and proportions: Short-cut basalt fibers are used to improve the mechanical properties of concrete. The destruction of the cement matrix can maintain the integrity of the concrete and provide nucleation sites for urease bacteria to produce calcite, further enhancing mechanical properties. Silicate cement, polycarboxylate water-reducing agents, silica fume and other additives improve the workability, strength and adhesion of concrete.

[0073] Reinforcing material: Utilizing the mineralization ability of Bacillus pasteurellii, calcite is produced during the concrete forming and curing stage to seal ineffective pores in the concrete and enhance its mechanical properties; 2. Technological Innovation Big Data Intelligent Decision-Making Platform: By monitoring environmental factors in real time, it automatically adjusts the material ratio to ensure the optimal performance of concrete under different climatic conditions.

[0074] Internal reinforcement technology: By using urease-producing bacteria in BLP to generate deposited calcite inside the permeable concrete to fill ineffective pores, the mechanical properties of the concrete are enhanced, thus ensuring its permeability.

[0075] Certain repairability: In actual service, permeable concrete will generate a certain number of microcracks inside, which will reduce its mechanical properties. However, MICP technology can be used to repair and heal these microcracks, thus extending the service life of permeable concrete.

[0076] 3. Performance Testing The permeability test meets the permeable concrete standard, the compressive strength is >25MPa, the freeze-thaw performance meets the standard for extremely cold regions, microbial reinforcement materials are added, and multiple materials improve the overall performance of permeable concrete. The big data intelligent decision-making platform improves the adaptability and stability of materials, and MICP technology improves the durability and environmental friendliness of concrete.

[0077] Example 6 Permeable concrete regulation and reinforcement module Preparation of microbial reinforcing agent: The prepared cementing solution and the cultured microbial standard solution were placed separately in an air pump sprayer. The cementing solution was a mixed solution of 0.6 mol / L calcium lactate and 0.75 mol / L urea. The microbial standard solution was obtained by centrifuging the cultured bacterial solution in a centrifuge (4500 r / min) for 15 min, and then diluting it into a bacterial suspension (OD200). 600 The value is 0.40.

[0078] Automatic triggering mechanism for microbial targeted reinforcement module For permeable concrete that has reached the reinforcement threshold, a cyclic spraying of binder and bacterial solution is performed. The specific reinforcement treatment method is as follows: use a sprayer at a rate of 5L / m per round. 2 Equal amounts of bacterial solution and binder were sprayed onto the sample, with the sprayer positioned approximately 20 cm from the sample surface and a spraying speed of 10-20 mL / min. To ensure sufficient bacterial penetration and fixation inside and outside the permeable concrete, the bacterial solution was sprayed first, allowed to stand for 3 hours, and then the binder was sprayed. This curing process was repeated three times to complete one cycle. A non-destructive testing module was used to monitor the performance changes of the permeable concrete during the MICP reinforcement process in real time, and the results were fed back to the big data intelligent decision-making platform. The reinforcement process was automatically shut down once the permeable concrete performance was detected to have recovered below a threshold (a 25% loss of the original permeable concrete performance).

[0079] Example 7 Applicable to the intelligent preparation and targeted reinforcement method of permeable concrete MIP. Phase 1 (Materials Design and Decision-Making): Input environmental parameters, climate conditions, and load requirements into the big data intelligent decision-making platform. The platform outputs a material mix design scheme (digital twin system), which specifically includes aggregate gradation, cement grade, admixture type, and bacterial particle specifications, thus entering Phase 2.

[0080] The second stage (material preparation and pretreatment): According to the material ratio design scheme output from the first stage, raw materials are selected and bacterial particles are prepared according to the design scheme. The preparation of bacterial particles is carried out in four steps in sequence: the first step is microbial culture, the second step is carrier negative pressure adsorption, the third step is carrier coating treatment, and the fourth step is 40℃ fan drying. After the pretreatment is completed, the third stage begins.

[0081] The third stage (concrete mixing and molding): precise material feeding into the mixing module and monitoring and adjusting relevant indicators (temperature, water-cement ratio, workability), followed by casting, tamping, and vibration compaction. Then proceed to the fourth stage.

[0082] Phase 4 (Maintenance and Monitoring): A multimodal sensing and monitoring system (temperature 20~30℃) monitors changes in the maintenance environment in real time and intelligently controls temperature and humidity to achieve optimal maintenance conditions. Phase 5 begins after maintenance is complete.

[0083] Phase 5 (Performance Testing and Standards): Testing of core concrete performance, including permeability coefficient, porosity, and mechanical properties (compressive / flexural strength). Phase 6 follows performance testing. Phase 6 (Data Analysis and Optimization): Evaluate the performance of permeable concrete and compare it with the initial output model of the big data intelligent decision-making platform to determine whether it meets the design requirements. If it does not meet the requirements, the data is fed back to the design phase of the big data intelligent decision-making platform, and a database is built based on the feedback data to provide data support for outputting a prediction model again. If the requirements are met, the mix proportion and preparation process parameters of permeable concrete are output and the process enters Phase 7.

[0084] Stage 7 (Microbial Targeted Reinforcement): The output concrete is placed under different working conditions, including simulated extreme temperatures (freeze-thaw), rainstorm runoff, solar radiation (ultraviolet light), chemical media (salt and alkali), and standard environments, to obtain corresponding performance degradation curves. When the permeable concrete performance degrades to a threshold, the reinforcement mechanism is triggered. The specific process of the reinforcement mechanism is as described in Example 6. After the regulation is completed, the corresponding microbial targeted reinforcement process is obtained.

[0085] Example 7 The digital twin system consists of three main modules: a multi-source data fusion module, a machine learning module, and a dynamic visualization and monitoring module. The multi-source data fusion module is responsible for integrating and analyzing multi-dimensional data such as climate, geology, materials, and engineering. The machine learning model uses AI algorithms to optimize mix design and establish the correlation between materials, performance, and processes.

[0086] The dynamic visualization monitoring module provides intuitive data display and decision support.

[0087] The big data intelligent decision-making platform controls the mixing module to prepare concrete based on the mix proportion suggestions provided by the digital twin system. The concrete is then cured under environmental factors simulated by the curing module or the environmental simulation module. Concrete performance data is obtained through the non-destructive testing module and fed back to the big data intelligent decision-making platform in real time. The platform then pushes the data to the digital twin system to establish a performance database for microbial permeable concrete. The LMM mixing model assists the digital twin system in providing an optimized mix proportion for microbial permeable concrete. The platform then instructs the big data intelligent decision-making platform to complete the concrete preparation, using the optimized mix proportion to prepare permeable concrete based on MICP technology; and the above instruction logic is repeated.

[0088] The microbial targeted reinforcement module is activated upon feedback from the big data intelligent decision-making platform that the concrete performance degradation has reached a threshold, and then regulates and reinforces the degraded permeable concrete. The relevant properties of the concrete are monitored in real time during the reinforcement process and fed back to the big data intelligent decision-making platform.

[0089] Ultimately, the optimal mix proportion and corresponding microbial targeted reinforcement process that meet the service requirements of permeable concrete are obtained by each module and the big data intelligent decision-making platform.

[0090] Any aspects not covered in this invention are applicable to existing technologies.

Claims

1. A method for intelligent preparation and targeted reinforcement of permeable concrete using MIP (Micro-Injection Polymerization), characterized in that, The method includes: Big data intelligent decision-making platform, including digital twin system and LMM hybrid model; The digital twin system is equipped with a machine learning model that can build a training database based on background information (location, load, meteorological data) of the completed project. After inputting the requirements for permeable concrete, it can automatically generate the corresponding optimal mix proportion of ordinary permeable concrete. LMM Hybrid Model: The mix proportion of conventional permeable concrete derived from machine learning is used to predict the performance of microbial permeable concrete after adding biological factors based on MICP technology. The big data intelligent decision-making platform controls the mixing module to prepare concrete based on the mix proportion suggestions given by the digital twin system. The concrete is then cured under environmental factors simulated by the curing module or the environmental simulation module. The concrete performance data is obtained by the non-destructive testing module and fed back to the big data intelligent decision-making platform in real time. The big data intelligent decision-making platform pushes the data to the digital twin system to establish a performance database of microbial permeable concrete. The LMM mixing model assists the digital twin system in providing an optimized mix proportion for microbial permeable concrete. Permeable concrete based on MICP technology is then prepared using the optimized mix proportion. The performance database of microbial permeable concrete includes the relationship between permeable concrete performance and mix proportion, and the performance degradation curve of permeable concrete. Integrated PLC control system: The big data intelligent decision-making platform provides instructions to control the bacterial particle preparation module, mixing module, curing module, environmental simulation module, and microbial targeted reinforcement module to prepare permeable concrete. The performance is tested by the non-destructive testing module. The test data is collected and pushed to the big data decision-making platform, which makes decisions to optimize the mix ratio and train the LMM hybrid model. The bacterial-carrying particle preparation module is used to encapsulate microbial agents and porous media using negative pressure adsorption to form bacterial-carrying particles. The mixing module initially sets the microbial agent, porous media type, and addition ratio for the preparation of bacterial particles. The bacterial particle preparation system prepares the bacterial particles. Based on the optimal traditional permeable concrete mix ratio determined by the big data decision platform, the bacterial particles are mixed with the raw materials of traditional permeable concrete to obtain a slurry. The curing module intelligently cures the slurry obtained from the mixing module. The non-destructive testing module performs non-destructive testing on the mechanical and permeability properties of permeable concrete and feeds the data back to the big data intelligent decision-making platform. The environmental simulation module is used to simulate environmental factors in the corresponding region, apply corresponding environmental factors to the test blocks after intelligent curing, accelerate the degradation process of the mechanical properties of the test blocks, and obtain the curves of the corresponding degradation properties through the non-destructive testing module; The microbial targeted reinforcement module is used to reinforce permeable concrete by supplementing microbial inoculum, calcium source, and nitrogen source when its mechanical properties deteriorate significantly. When the mechanical properties are restored to the set value, the reinforcement process ends, thus obtaining a reinforcement process that can restore the mechanical properties of permeable concrete under different environmental conditions.

2. The method according to claim 1, characterized in that, During the curing process, the performance of the specimen is obtained through a non-destructive testing module. If the performance of the specimen does not meet the mechanical and permeability requirements, the data is fed back to the big data intelligent decision-making platform to change the type of microorganism, the type of carrier, or the thickness of the coating. After the microorganisms are filled, their mechanical properties and permeability are tested in real time through the non-destructive testing module. If the permeability can be improved without compromising the mechanical properties, the optimal mix proportion of microbial permeable concrete is determined.

3. The method according to claim 1, characterized in that, The non-destructive testing module includes a strength development non-destructive testing unit, a water permeability testing unit, and a porosity testing unit. The strength development non-destructive testing unit includes an ultrasonic tester and a digital rebound hammer, which are combined to achieve both strength and non-destructive testing. The water permeability testing unit uses a water permeability coefficient measuring instrument to test water permeability, and the porosity testing unit uses a BET surface area analyzer to test porosity. By testing water permeability, it is possible to observe whether microorganisms are active, and by combining this with mechanical properties, the extent of microbial activity can be determined.

4. The method according to claim 1, characterized in that, The porous medium is fly ash ceramsite; the fiber is basalt fiber.

5. The method according to claim 1, characterized in that, In the microbial targeted reinforcement module, the mechanical properties are tested in real time using a non-destructive testing module. When the mechanical properties degrade to the preset performance threshold (compressive strength decreases by 25%), microbial liquid is sprayed at a rate of 5L per square meter at a spraying speed of 10-20mL / min. After the set immersion time is reached, calcium and nitrogen sources are added in batches. After each batch reaches the preset reaction time, the next batch is added. After the set batch is reached, the next cycle of microbial liquid, calcium source, and nitrogen source are added until the mechanical properties are restored to 75% of the original value, at which point the targeted reinforcement process ends.

6. The method according to claim 1, characterized in that, The digital twin system also includes a multi-source data fusion module, a database, a cost-constraint expansion module, and a dynamic visualization monitoring module. These modules dynamically adjust the material mix ratios based on different environmental factors by traversing the material database. Combining the material cost quotation table from the cost-constraint expansion module with three objectives—mechanical performance, permeability, and cost—the system optimizes the mix ratio of traditional permeable concrete to suit the specific application environment and provides a recommendation table of nearby material manufacturers. The environmental factors include climate temperature, humidity, rainfall, rainfall intensity, ultraviolet radiation intensity, and load requirements. The load requirements include the load demands of vehicles and pedestrians. The cost constraint extension module stores material cost quotations from material suppliers in different regions. The database is used to store the minimum strength requirements of traditional permeable concrete under different environmental data, as well as the permeability, mechanical properties, porosity range, durability and environmental protection requirements of different traditional permeable concrete mix proportions under different environmental data. The multi-source data fusion module analyzes information including climate, load requirements, and cost for regions corresponding to the mix proportions of existing permeable concrete projects. The machine learning model is trained using the data processed by the multi-source data fusion module, and the optimal mix proportion of traditional permeable concrete is obtained from the trained machine learning model. The dynamic visualization monitoring module provides intuitive data display and decision support.

7. The method according to claim 1, characterized in that, After curing, the concrete is placed under different working conditions to obtain corresponding performance degradation curves. When the performance of the permeable concrete degrades to a threshold, a reinforcement mechanism is triggered, which restores the performance of the permeable concrete to 75% of its original state. The different working conditions refer to simulated extreme temperature (freeze-thaw), rainstorm runoff, solar radiation, chemical media, and standard environment. The simulated extreme temperature refers to freeze-thaw conditions, solar radiation refers to different ultraviolet radiation intensities, and chemical media refers to different liquid environments of salt, alkali, or acid solutions.

8. A permeable concrete with microbial targeted reinforcement based on MICP technology, characterized in that, The raw material composition and mass ratio of the permeable concrete are as follows: The mass ratio of aggregate, cement matrix, basalt fiber, BLP, silica fume, water, water-reducing agent, urea, and calcium lactate is: 1:0.2~0.3:0.002~0.003:0.05~0.06:0.02~0.03:0.08~0.09:0.009~0.01:0.011~0.0012:0.005~0.006; The aggregate is limestone crushed stone with a particle size of 4.75~9.5mm, the basalt fiber is 12mm short-cut basalt fiber, and the bacteria-carrying particles are porous ceramsite coated with metakaolin and loaded with Bacillus pasteurella. Under the above-mentioned mass ratio, the optimal mix ratio is determined using the method described in claim 1 to prepare permeable concrete based on MICP technology that can be microbially targeted and reinforced.

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