A model for quickly predicting peak strength of building waste improved by MICP and a method for constructing and predicting the model

Abstract

This invention relates to a model for rapidly predicting the peak intensity of MICP-modified construction waste, as well as a method for constructing and predicting this model. The model constructed by this invention can significantly shorten the performance evaluation time for construction waste, enabling projects to enter the construction phase more quickly. This efficient evaluation method reduces the need for laboratory testing while minimizing manpower and material resources invested in the testing process, thereby reducing overall project costs and improving economic efficiency. The method of this invention is particularly suitable for situations with limited on-site conditions. This simplicity not only enhances the flexibility of the evaluation but also allows for timely adjustment of parameters during actual construction, ensuring the optimal effect of MICP modification.

Description

Technical Field

[0001] This invention belongs to the technical field of waste building material recycling, and relates to a model for rapidly predicting the peak intensity of MICP-modified building waste, as well as the model construction method and prediction method. Background Technology

[0002] With the rapid advancement of global urbanization, the construction industry is growing exponentially, generating a massive amount of construction waste. The indiscriminate dumping of this waste not only occupies vast amounts of land resources but also pollutes the environment. Therefore, how to efficiently treat and utilize this construction waste has become a crucial issue urgently needing to be addressed in the field of civil engineering. The reuse of construction waste can alleviate resource shortages and reduce environmental pressure, yielding significant social and economic benefits. Against this backdrop, how to improve the mechanical properties of construction waste through effective technological means to achieve its widespread application in engineering has become a hot research topic.

[0003] Microbial-induced calcium carbonate precipitation (MICP), as an emerging biotechnology, has shown great potential in the field of civil engineering material improvement. MICP utilizes the biochemical reactions of microorganisms to generate calcium carbonate deposits, thereby forming a stable bond between particles and improving the strength and durability of the material. Compared to traditional improvement methods, such as chemical curing agents or mechanical reinforcement, MICP technology has the advantages of being environmentally friendly, low-cost, and does not produce secondary pollution, thus being regarded as a material improvement technology with sustainable development prospects. In recent years, MICP technology has been applied to soil reinforcement and crack repair, demonstrating good results.

[0004] Construction waste has a complex composition and uneven physical properties, and its mechanical properties often fail to meet the requirements of direct engineering applications. Traditional construction waste remediation technologies often suffer from environmental hazards, high energy consumption, and high costs, while the introduction of Microbial Concrete Extraction (MICP) technology offers a new approach to solving these problems. Through MIP technology, calcium carbonate can be generated within construction waste using a microbial deposition reaction, resulting in tighter bonding between particles and significantly improving the strength and stability of the waste. However, due to the complexity of construction waste composition, the effectiveness of MIP remediation is influenced by various factors, including the type of microorganism, the composition of the nutrient solution, and reaction conditions. Therefore, a comprehensive evaluation of the effectiveness of MIP technology in remediating construction waste is essential before large-scale application.

[0005] Peak strength, as a crucial indicator of a material's mechanical properties, directly relates to the feasibility of engineering applications for modified construction waste. Traditional peak strength testing requires triaxial laboratory tests, which are typically time-consuming and costly, hindering rapid decision-making in engineering. Furthermore, the diverse and inhomogeneous composition of construction waste further increases the complexity and uncertainty of experimental measurements. Therefore, establishing a method for rapidly and accurately predicting the peak strength of MICP-modified construction waste is of great significance for promoting its application in practical engineering. Summary of the Invention

[0006] To address the above problems, this invention provides a model for rapidly predicting the peak intensity of MIP-modified construction waste, the model being:

[0007]

[0008] In the formula: k1, k2, a1, a2, a3, b1, b2, b3, c1, c2 are model parameters, σ3 is the confining pressure, and R g / s For the ratio of stone to sand, C Ca 2+ To improve the calcium ion concentration in MICP construction waste, D m The maintenance period is in days, and e is a mathematical constant.

[0009] The model parameters k1, k2, a1, a2, a3, b1, b2, b3, c1, and c2 mentioned above were obtained from static triaxial tests.

[0010] This application also provides a method for constructing the above model, the specific steps of which are as follows:

[0011] (1) Solid waste samples with different gradations were prepared using crushed construction waste particles and the samples were compacted to obtain the optimal moisture content and maximum dry density of the samples.

[0012] (2) Use equal volumes of MICP modification reaction solutions of different concentrations to add to different samples and mix thoroughly;

[0013] The reaction solution consists of bacterial solution and cementing solution, and the cementing solution consists of calcium chloride and urea.

[0014] (3) The fully mixed sample is made into a cylindrical sample and compacted, and then cured under different time conditions.

[0015] (4) Static triaxial test

[0016] Static triaxial tests were conducted on the cured specimens under different confining pressures σ3.

[0017] The peak strength of the specimen under different conditions can be calculated by analyzing the stress-strain curve;

[0018] (5) Based on the different conditions (R) obtained in step (4) g / s C Ca 2+ D m The peak intensity data under σ3 are horizontally shifted relative to σ3 to obtain the model formula:

[0019]

[0020] In the formula: k1, k2, a1, a2, a3, b1, b2, b3, c1, c2 are model parameters, σ3 is the confining pressure, and R g / s For the ratio of stone to sand, C Ca 2+ To improve the calcium ion concentration in MICP construction waste, D m The maintenance period is in days, and e is a mathematical constant.

[0021] Based on the above scheme, in step (1), the R of the sample g / s The values ​​are 1.0, 1.5, 2, 2.5 and 3 respectively.

[0022] Based on the above scheme, in step (2), C in the reaction solution Ca 2+ The concentrations were set to 0 mol / L, 0.5 mol / L, 1 mol / L, and 2 mol / L.

[0023] Based on the above scheme, in step (3), the maintenance time D m Set to 0, 1, 3, 6, or 10 days.

[0024] Based on the above scheme, in step (4), σ3 in the experiment is set to 50kPa, 100kPa, and 150kPa, and the shear rate is 0.5% / min.

[0025] Based on the above scheme, the bacteria in the bacterial solution of the reaction solution in step (2) are *Pasteurella multocida*, and the bacterial concentration is OD. 600 =3.0.

[0026] The beneficial effects of this invention are:

[0027] (1) Improved construction efficiency and reduced costs: The model constructed by the method of this application can significantly shorten the performance evaluation time of construction waste, enabling engineering projects to enter the construction phase more quickly. This efficient evaluation method reduces the need for laboratory testing while reducing the input of manpower and material resources in the testing process, thereby reducing the overall project cost and improving economic benefits.

[0028] (2) Ease of field application: Compared to traditional peak intensity testing, which typically requires specialized equipment and complex experimental procedures, the rapid prediction method proposed in this invention simplifies this process through a model. It only requires inputting the corresponding Rg / s value and C... Ca 2+ Concentration, Dm, and σ3 can be used to quickly predict the corresponding peak intensity; this is especially suitable for situations where site conditions are limited. This simplicity not only improves the flexibility of the assessment but also allows for timely adjustment of parameters during actual construction, ensuring the best results of MICP improvements.

[0029] (3) Optimization and Improvement Effects: The rapid prediction method proposed in this invention can also be used to guide the optimization of MICP technology, helping to determine key parameters such as calcium ion concentration and curing days, thereby achieving the best improvement effect under different construction waste conditions. This targeted parameter adjustment helps to improve the final mechanical properties of construction waste, ensuring its reliability and safety in engineering applications. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of the construction waste materials used in Embodiment 2 of this application;

[0032] Figure 2 This is a flowchart of the method for quantitative analysis of the particle shape of construction waste in Embodiment 2 of this application;

[0033] Figure 3 The shape classification results of different components of construction waste in Embodiment 2 of this application are as follows: (a) stones; (b) mortar blocks; (c) bricks;

[0034] Figure 4 For different R in Embodiment 2 of this application g / s The results of screening and compaction tests on construction waste under the specified conditions; wherein: (a) screening test results; (b) compaction test results;

[0035] Figure 5 This is a diagram of the triaxial testing apparatus in Embodiment 2 of this application;

[0036] Figure 6 For different R in Embodiment 2 of this application g / sThe effect on strength characteristics; where: (a) stress-strain curve; (b) peak strength;

[0037] Figure 7 For different C in Embodiment 2 of this application Ca 2+ The effect on strength characteristics; where: (a) stress-strain curve; (b) peak strength;

[0038] Figure 8 In embodiment 2 of this application, D m The effect on strength characteristics; where: (a) stress-strain curve; (b) peak strength;

[0039] Figure 9 The effect of different σ3 values ​​on strength characteristics in Example 2 of this application; wherein: (a) stress-strain curve; (b) peak strength;

[0040] Figure 10 This is a robustness verification diagram from Embodiment 2 of this application; Detailed Implementation

[0041] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0042] Example 1

[0043] This application provides a method for constructing a model to quickly predict the peak intensity of MIP-modified construction waste, the specific steps of which are as follows:

[0044] (1) Solid waste samples with different gradations were prepared using crushed construction waste particles, and compaction tests were conducted on the samples to obtain the optimum moisture content and maximum dry density of the samples; R of the solid waste samples g / s The values ​​can be set to 1.0, 1.5, 2, 2.5 and 3 respectively.

[0045] (2) Add equal volumes of different concentrations of MICP modification reaction solution to different samples and mix thoroughly; the reaction solution consists of bacterial solution and cementing solution, and the cementing solution consists of calcium chloride and urea.

[0046] C in the reaction solution Ca 2+ The concentrations were set to 0 mol / L, 0.5 mol / L, 1 mol / L, and 2 mol / L. The bacteria used in the bacterial suspensions could be *Pasteurella multocida*, with a bacterial concentration of OD0.05. 600 =3.0.

[0047] (3) The thoroughly mixed sample was made into a cylindrical sample and compacted, and then cured under different time conditions; curing time D m Set to 0, 1, 3, 6, or 10 days.

[0048] (4) Static triaxial test

[0049] The cured specimens were subjected to static triaxial tests under different confining pressures σ3; σ3 was set to 50 kPa, 100 kPa, and 150 kPa, and the shear rate was 0.5% / min.

[0050] The peak strength of the specimen under different conditions can be calculated by analyzing the stress-strain curve;

[0051] (5) Based on the different conditions (R) obtained in step (4) g / s C Ca 2+ D m The peak intensity data under σ3 are horizontally shifted relative to σ3 to obtain the model formula:

[0052]

[0053] In the formula: k1, k2, a1, a2, a3, b1, b2, b3, c1, c2 are model parameters, σ3 is the confining pressure, and R g / s For the ratio of stone to sand, C Ca 2+ To improve the calcium ion concentration in MICP construction waste, D m The maintenance period is in days, and e is a mathematical constant.

[0054] Example 2

[0055] Based on the method in Example 1, this application provides a specific method for constructing a model for rapidly predicting the peak intensity of MIP-modified construction waste.

[0056] Step a: Experimental materials and procedures

[0057] 2.1 Test Materials

[0058] The construction waste materials selected in this embodiment (after crushing and screening) originated from demolition waste from a construction site in Changsha City. Within a particle size range of 0-20mm, the specific mass percentages of each component are: stones 77.3%, mortar blocks 12.8%, bricks 7.5%, and other impurities (such as ceramic tiles, glass, etc.) 2.4%, as detailed below. Figure 1 As shown.

[0059] The geometric morphology of particles (such as sphericity, flatness, and slenderness ratio) has a significant impact on the skeletal structure and strength properties of fillers (such as peak strength, internal friction angle, and cohesion). Based on this, this embodiment performed three-dimensional blue light scanning and reconstruction on a total of 450 particles (150 stones, 150 mortar blocks, and 150 bricks) of stones, mortar blocks, and bricks. Figure 2 As shown), the aspect ratio (EI), flatness (FI), and sphericity (S) of each particle were calculated. P Shape indicators such as shape were used. Then, the particle shape was classified using the T. Zingg bivariate classification method, and the results are as follows: Figure 3 As shown. By Figure 3 It can be seen that most of the stone, mortar blocks, and brick particles are blocky or disc-shaped. Among them, the sphericity values ​​of stone and brick are mainly distributed between 0.5 and 1, while the sphericity values ​​of mortar blocks are concentrated between 0.67 and 1.

[0060] The basic physical performance indicators of construction waste are shown in Table 1. Meanwhile, considering the significant impact of gradation on the strength characteristics of construction waste, this embodiment introduces the stone-to-sand ratio (Ra) proposed based on particle packing theory. g / s ) indicator. R g / s The application must meet the following conditions: (1) The boundary particle size between coarse and fine particles must be around 5 mm; (2) The gradation curve can be well fitted by the Fuller function.

[0061] Among them, the R g / s The parameter can be determined by the maximum particle size D. max The shape parameter n of the gradation curve is calculated according to equation (1), and n can be calculated from the sieving results using the Fuller function (equation 2):

[0062]

[0063] In the formula, R g / s The ratio of stone to sand; p d For an aperture of d i The cumulative throughput corresponding to the sieve aperture; d i D is the sieve aperture diameter. max This refers to the maximum particle size. Furthermore, according to the USCS classification system (ASTM 2001), gravel is defined as particles that pass through a 75mm sieve and remain on a 5mm sieve, with a gravel content of 1-p5; sand(s) is defined as particles that pass through a 5mm sieve and remain on a 0.075mm sieve.

[0064] Table 1 Basic Physical Properties of Construction Waste

[0065]

[0066] Considering the "Specifications for Design of Highway Subgrade Structures" (JTGD30—2015) and the specimen size limitations for triaxial tests (the maximum particle size must not exceed 1 / 5 of the specimen diameter), this embodiment sieves the dried construction waste into different particle size groups, with the maximum particle size set at 20 mm. Furthermore, five different gradations of solid waste specimens were designed, with their R... g / s The values ​​are 1.0, 1.5, 2, 2.5, and 3, respectively, and the gradation curves are as follows: Figure 4 As shown in (a), the corresponding compaction test results are as follows: Figure 4 As shown in (b).

[0067] 2.2 Preparation of reaction solution

[0068] Based on the reaction mechanism of MICP, the reaction solution consists of bacterial solution and cementing solution, and its basic reaction equations are shown in formulas (3) to (5):

[0069]

[0070] Ca 2+ +Cell—→Cell-Ca 2+ (4)

[0071] Cell-Ca 2+ +CO3 2- —→Cell-CaCO3↓ (5)

[0072] In an alkaline environment, bacteria secrete urease through metabolic activities. This enzyme can continuously hydrolyze urea, producing NH4. + and CO3 2- Because bacteria carry a negative charge on their surface, they can attract calcium from the surrounding medium. 2+ And thus with CO3 2- The bacteria combine to form calcium carbonate crystals with a cementing effect. In this process, bacteria are not only responsible for the production of urease and the hydrolysis of urea, but also serve as the core attachment point for calcium carbonate precipitation. Therefore, cultivating a large quantity of highly active bacterial culture is a crucial step in implementing MIP (Microbial Concentration Program) technology.

[0073] Many strains can be used for MICP improvement. In this example, *Sporosarcina pasteurii* (CGMCC 1.3687), which is environmentally friendly and non-toxic, was selected as the strain. To activate and expand the culture, NH4-YE liquid medium was used, the specific components of which are shown in Table 2. After the medium was prepared, it was dispensed into sterile containers and autoclaved at 121°C for 20 minutes to ensure the sterility of the culture environment. After the medium cooled to room temperature, the activated strain was aseptically inoculated at a ratio of 1:100.

[0074] Table 2. Composition of NH4-YE liquid culture medium

[0075]

[0076] The inoculated bacterial culture was placed in a constant temperature shaking incubator and cultured continuously for 20 hours at 30℃ and 150 rpm. After the culture was completed, the optical density (OD) of the bacterial culture was measured using a TU-1950 UV-Vis spectrophotometer. 600 The bacterial growth concentration was assessed. Simultaneously, the urease activity of the bacterial culture was measured using a DDS-11A conductivity meter. Urease activity was calculated based on the empirical formula of Whiffin et al., converting the change in conductivity into the amount of urea hydrolyzed per unit time. In this embodiment, the concentration of the bacterial culture obtained was OD0.05. 600 =3.0, corresponding to a urease activity of 15.4 μmol of urea hydrolyzed per minute. Furthermore, this embodiment used a mixed cementing solution composed of calcium chloride (CaCl2) and urea. CaCl2 serves as the calcium source, providing the necessary calcium for the reaction. 2+ Urea not only provides a nitrogen source for bacterial metabolic activities, but also hydrolyzes to produce CO3 under the action of urease. 2- , with Ca 2+ They combine to form calcium carbonate precipitate.

[0077] 2.3 Test Plan

[0078] The test plan in this embodiment can be divided into the following four parts:

[0079] (a) MICP treats construction waste

[0080] Based on the results of compaction tests (such as...) Figure 4 (As shown) Determine different R g / s The optimal moisture content of the sample was determined, and the MICP reaction solution was prepared according to Section 2.2. The C content in the reaction solution... Ca 2+ The concentrations were set to 0 mol / L, 0.5 mol / L, 1 mol / L, and 2 mol / L. Equal volumes (same as the optimal water content volume) of the prepared reaction solution were added to different concentrations of R. g / s In the sample, thorough stirring and mixing are performed to ensure the presence of microorganisms and calcium. 2+ Uniform contact between particles.

[0081] (b) Sample preparation and curing

[0082] Cylindrical specimens with a diameter of 101 mm and a height of 200 mm were prepared using a standard split mold, and the results of compaction tests (such as...) were used to determine the appropriate specimens. Figure 4 (As shown) Determine different R g / sThe samples were compacted to 95% of their maximum dry density. Then, to ensure effective MIP treatment, the samples were immediately placed in a constant temperature and humidity curing chamber (curing temperature set at 25℃) after preparation. This was done to investigate different D... m The impact of D on the effectiveness of MICP treatment m The incrementing difference is set to 0, 1, 3, 6, and 10 days.

[0083] (c) Static triaxial test

[0084] ① Untreated with MICP (C Ca 2+ =0 mol / L, D m Construction waste samples with σ = 0 were tested at σ3 = 100 kPa and different R values. g / s The stress-strain curves and peak strengths under conditions (1.0, 1.5, 2, 2.5, 3) are as follows: Figure 6 As shown.

[0085] ②Different C Ca 2+ Solid waste samples (0 mol / L, 0.5 mol / L, 1 mol / L and 2 mol / L) were tested at R. g / s =2.5, σ3 = 100 kPa and D m =0,6(C Ca 2+ When = 0 mol / L, D m The stress-strain curve and peak intensity under the condition of 0) are as follows: Figure 7 As shown.

[0086] ③Different D m Solid waste samples with values ​​of (0, 1, 3, 6, 10) were analyzed at R. g / s =2.5, σ3 = 100 kPa and C Ca 2+ =0.1 mol / L (D m When C = 0, Ca 2+ The stress-strain curves and peak intensity under the condition of 0 mol / L are as follows: Figure 8 As shown.

[0087] ④R g / s For solid waste samples with a strength of 2.5, at different σ3 (50 kPa, 100 kPa, 150 kPa), C Ca 2+ =0 mol / L, D m The stress-strain curve and peak intensity under the condition of 0 are as follows: Figure 9 As shown.

[0088] Static triaxial tests were conducted using the Dynatriax100 / 14 fully automated triaxial testing system from Changsha University of Science and Technology (e.g., Figure 5 (As shown). To simulate the stress state of the subgrade filler under different depths and stress conditions as closely as possible, σ3 in the static triaxial (UU) test was set to 50 kPa, 100 kPa, and 150 kPa, with a shear rate of 0.5% / min. Based on this, the peak strength, internal friction angle, and cohesion of the specimen under different conditions can be calculated by analyzing the stress-strain curves. For strain-hardening curves, the axial stress corresponding to 15% axial strain is selected as the peak strength; for strain-softening curves, the axial stress corresponding to the peak value is selected as the peak strength. The corresponding internal friction angle and cohesion are obtained by combining the peak strength and the Mohr-Coulomb failure criterion.

[0089] The specific experimental plan is shown in Table 3.

[0090] Table 3 Triaxial Test Scheme

[0091]

[0092] Step b: Triaxial test results and analysis

[0093] 3.1 Effect of different aggregate-to-sand ratio on strength properties

[0094] Unprocessed by MICP (C Ca 2+ =0 mol / L, D m Construction waste samples with σ = 0 were tested at σ3 = 100 kPa and different R values. g / s The stress-strain curves and peak strengths under conditions (1.0, 1.5, 2, 2.5, 3) are as follows: Figure 6 As shown in the figure, the peak intensity increases with R. g / s The increase in R shows a trend of first increasing and then decreasing. g / s When R = 1, its peak intensity is 173.4 kPa. g / s When R = 2.5, its peak intensity reaches a maximum of 389.4 kPa, while when R... g / s When the value is 3, its peak intensity decreases to 356.3 kPa.

[0095] This is due to the lower R g / s (As shown in 1, 1.5) the internal structure of the sample is loose, and the friction between particles is weak, resulting in a lower peak strength. With R... g / s With the increase of [amount], the skeletal effect between stone particles becomes more significant, and the structural compactness and stability of the sample gradually improve, which is reflected macroscopically as R [value]. g / s =2.5 is the optimal R g / s However, when R g / sWhen the stress-strain coefficient is too high (e.g., 3), although the skeletal effect between stone particles is still strengthened, the interparticle adhesion is greatly weakened, thus reducing the overall load-bearing capacity of the sample. Furthermore, the strain softening effect increases with R... g / s The strength increases with the increase of R, and the stress decrease after the peak strength also increases accordingly, indicating that at high R... g / s Under these conditions, the specimen is more likely to experience a significant decrease in overall load-bearing capacity after local failure.

[0096] Choose R appropriately g / s The strength characteristics of roadbed filler material made from construction waste are of great significance. Therefore, in practical engineering, it is important to rationally select the optimal R. g / s It is absolutely necessary.

[0097] 3.2 Effect of different calcium ion concentrations on strength properties

[0098] Different C Ca 2+ Solid waste samples (0 mol / L, 0.5 mol / L, 1 mol / L and 2 mol / L) were tested at R. g / s =2.5, σ3 = 100 kPa and D m =0,6(C Ca 2+ When = 0 mol / L, D m The stress-strain curve and peak intensity under the condition of 0) are as follows: Figure 7 As shown. Overall, each C Ca 2+ The stress-strain curves under the given conditions all exhibited a similar trend: stress rose rapidly in the initial stage and then gradually decreased after reaching a peak. However, with C... Ca 2+ The specific shape of the curve and the change in peak intensity vary significantly depending on the individual curves.

[0099] First, in C Ca 2+ At 0 mol / L, the initial rate of stress rise in the soil sample was relatively slow, with a peak strength of 389.4 kPa. Subsequently, the stress showed a steady downward trend, indicating that the soil's internal structure was loose, the interparticle cohesion was weak, and its bearing capacity was limited. Then, as C... Ca 2+ =0.5mol / L, the initial stress rise rate of the soil sample increased, and the peak strength increased to 639.2kPa, indicating that an appropriate amount of Ca 2+ It can enhance the cementation force between soil particles, improving its bearing capacity, while exhibiting a relatively slow decrease in stress after the peak value, demonstrating a certain degree of toughness. Subsequently, when C... Ca 2+At a concentration of 1 mol / L, the initial ascent rate of the soil sample further increased, and the peak strength reached nearly 799.6 kPa, the maximum value under all test conditions. However, the stress dropped rapidly after reaching the peak strength, showing obvious brittle failure characteristics. This indicates that Ca... 2+ At this concentration, the soil's bearing capacity is greatly enhanced, but its toughness and post-failure bearing capacity are also reduced. Finally, C Ca 2+ At 2 mol / L, the peak intensity slightly decreased to 693.1 kPa, but remained higher than C. Ca 2+ =0.5 mol / L. This is because Ca 2+ It can react with mineral particles in the sample to form a stable cementing layer, significantly enhancing the bonding force between particles and thus improving the sample's strength. Especially in C Ca 2+ At concentrations of 0.5 and 1 mol / L, the peak strength of the samples increased significantly. Simultaneously, an appropriate amount of calcium ions can improve the arrangement and interlocking of soil particles, increasing interparticle friction and thus enhancing the strength properties of the soil. However, excessively high C... Ca 2+ (e.g., 2 mol / L) will lead to increased soil brittleness and a significant decrease in bearing capacity.

[0100] 3.3 Effect of different curing days on strength properties

[0101] Different D m Solid waste samples with values ​​of (0, 1, 3, 6, 10) were analyzed at R. g / s =2.5, σ3 = 100 kPa and C Ca 2+ =0.1 mol / L (D m When C = 0, Ca 2+ The stress-strain curves and peak intensity under the condition of 0 mol / L are as follows: Figure 8 As shown, the stress-strain curves under various curing conditions exhibit similar trends: in the initial stage, stress rises rapidly with strain, then levels off, and gradually decreases after reaching a peak. This indicates that the soil sample undergoes an elastic deformation stage in the initial loading phase, then enters a plastic deformation stage as stress increases, and finally decreases due to internal structural failure.

[0102] Specifically, under maintenance-free conditions (D m =0), the peak strength of the soil sample was 389.4 kPa, indicating weak interparticle cementation and a loose overall structure, resulting in low bearing capacity. With D m The increase in [value] significantly improved the peak intensity. mWhen = 1, the peak strength increases to 620.1 kPa, indicating that calcium carbonate precipitation begins to form preliminary cementation between particles, enhancing the soil's bearing capacity and internal structural stability. D m When the value is 3, the peak strength further increases to 697.1 kPa, indicating that the enhanced calcium carbonate deposition significantly improves the internal cementing force of the soil, makes the particles more tightly bonded, makes the soil structure more stable, and greatly improves the bearing capacity.

[0103] In D m At a strength of 6, the peak strength reached 799.6 kPa, the highest value under all curing conditions. This indicates that calcium carbonate precipitation within the soil was most complete at this point, with maximum interparticle bonding and friction, resulting in optimal bearing capacity and initial stiffness. However, as the peak strength increased, the curve decreased rapidly after reaching the peak, indicating increased brittleness and a rapid decline in bearing capacity after failure. This may be due to excessive cementation caused by excessive calcium carbonate precipitation, which prevents the soil from maintaining overall stability after local structural failure.

[0104] When D m When the strength reaches 10 kPa, the peak strength further increases to 817.7 kPa, but the downward trend of the curve is steeper, indicating a more pronounced strain softening effect. This suggests that although the increase in calcium carbonate precipitation improves soil strength, excessively long curing times may increase the heterogeneity of the soil's internal structure, thereby reducing the overall stability and toughness of the structure. Therefore, although the soil strength increases in the short term, its bearing capacity decreases rapidly after failure, exhibiting strong brittle characteristics.

[0105] The mechanism by which MICP curing days affect the strength properties of construction waste is mainly reflected in the following three aspects: First, with the increase of D m With the increase of calcium carbonate, microbially induced calcium carbonate precipitation gradually acts as a cementing material between particles, effectively enhancing the bonding force and friction between soil particles. During the 3 to 6 days of curing, calcium carbonate precipitation is relatively sufficient, the soil structure reaches its optimal state, and the bearing capacity is significantly improved. Secondly, when the curing period exceeds 6 days, excessive calcium carbonate deposition may lead to local heterogeneity within the soil, destroying the overall structural uniformity and stability, increasing the brittleness of the soil, and accelerating the rate of stress decline after peak strength. Finally, the brittle failure characteristics of the soil become more pronounced with the increase of curing days, especially at 6 and 10 days of curing, when the soil structure is prone to instability after reaching peak strength, and the bearing capacity declines rapidly.

[0106] In summary, different MIP curing days significantly impact the mechanical properties of soil. Appropriate curing time (e.g., 3 to 6 days) effectively improves the soil's bearing capacity and initial stiffness, resulting in better load-bearing capacity and structural stability. However, excessively long curing times (e.g., 10 days) may lead to excessive calcium carbonate deposition, increasing internal heterogeneity and brittleness, thereby reducing its overall strength and post-failure bearing capacity. Therefore, in practical engineering applications, the MIP curing time should be rationally controlled to achieve the optimal improvement in soil mechanical properties.

[0107] 3.4 Effect of different confining pressures on strength properties

[0108] R g / s For solid waste samples with a strength of 2.5, at different σ3 (50 kPa, 100 kPa, 150 kPa), C Ca 2+ =0 mol / L, D m The stress-strain curve and peak intensity under the condition of 0 are as follows: Figure 9 As shown. By Figure 9 It can be seen that with the increase of confining pressure, the stress-strain behavior of the soil gradually changes from strain softening to strain hardening. When σ3 = 50 kPa, the curve shows obvious strain softening characteristics, with a peak strength of 259.6 kPa. At this time, the contact between soil particles is relatively loose, the peak strength is low, and the stress gradually decreases after reaching the peak strength, indicating that the bearing capacity of the soil sample decreases during deformation, and it has good plastic deformation capacity. When σ3 = 100 kPa, the curve shape transitions from strain softening to strain hardening, and the peak strength increases to 389.4 kPa. At this time, the friction and cementation forces between soil particles are enhanced, and the structure is more compact. Although the stress decreases after the peak strength, the decrease is smaller, the strain softening effect of the soil is weakened, and the bearing capacity is maintained within a larger strain range, showing good plasticity and toughness. When σ3 = 150 kPa, the stress-strain curve of the soil shows obvious strain hardening characteristics, with a peak strength reaching 454.3 kPa. The interlocking and friction between soil particles are further enhanced, significantly improving structural stability and reaching maximum bearing capacity. The soil did not exhibit significant softening under high strain conditions, and its bearing capacity increased with increasing strain, demonstrating good plastic deformation capacity and toughness.

[0109] Step c: Model building and validation

[0110] Explanation of the principle of the principal curve translation method: that is, for (R) under different conditions g / s C Ca 2+ D mThe peak intensity data of σ3 are horizontally shifted relative to σ3 until these curves merge into a single S-shaped function, which takes into account R through a shift factor function. g / s C Ca 2+ D m Influenced by factors such as...

[0111] σ3 and S p There is a basic linear relationship, as shown in formula (C1):

[0112]

[0113] In the formula, S p The peak intensity is represented by k1 and k2, which are model parameters. The other parameters have the same meaning as above.

[0114] To facilitate calculation, formula (C1) is logarithmically transformed, as shown in formula (C2):

[0115] lnS p =k1+k2lnσ3 (C2)

[0116] By applying the principal curve translation method to gradually correct for different influencing factors, a comprehensive R value is obtained. g / s C Ca 2+ D m The peak intensity prediction model for σ3 is as follows:

[0117] ①R g / s Translation:

[0118] Formula C3 consists of formulas C3-1 and C3-2:

[0119] lnS p =k1+k2(lnσ3+a1R) g / s 2 +a2R g / s +a3) (C3)

[0120] in:

[0121] lnS p =k1+k2lnσ 3-① (C3-1)

[0122] lnσ 3-① =lnσ3+a1R g / s 2 +a2R g / s +a3 (C3-2)

[0123] ②C Ca 2+ -Rg / s Translation:

[0124] Formula C4 consists of Formula C4-1 and Formula C4-2:

[0125] lnS p =k1+k2(lnσ3+a1R) g / s 2 +a2R g / s +a3+b1C Ca2+ 2 +b2C Ca2+ +b3) (C4)

[0126] in:

[0127] lnS p =k1+k2lnσ 3-② (C4-1)

[0128] lnσ 3-② =lnσ 3-① +b1C Ca2+ 2 +b2C Ca2+ +b3 (C4-2)

[0129] ③D m -C Ca 2+ -R g / s Translation:

[0130] Formula C5 consists of Formula C5-1 and Formula C5-2:

[0131] lnS p =k1+k2(lnσ3+a1R) g / s 2 +a2R g / s +a3+b1C Ca2+ 2 +b2C Ca2+ +b3+c1ln(e+D m )+c2)(C5) where:

[0132] lnS p =k1+k2lnσ 3-③ (C5-1)

[0133] lnσ 3-③ =lnσ 3-② +c1ln(e+D m )+c2 (C5-2)

[0134] In summary, we can obtain formula C6.

[0135]

[0136] In the formula: a1, a2, a3, b1, b2, b3, c1, c2 are model parameters, and the others have the same meaning as above.

[0137] In addition, the parameters of each prediction model are shown in Table 4.

[0138] Table 4. Statistical Table of Predicted Model Parameters

[0139]

[0140] Model parameters are determined by Figures 6-9 The data was obtained using the nonlinear least squares fitting (NLSF) technique in the software SPSS.

[0141] To determine the applicability of the model constructed in this invention, the robustness of the above model formulas was verified. Specifically, S... p The measured values ​​are the x-coordinate and S. p A robustness verification scatter plot was drawn with the estimated value on the y-axis, and the results are as follows: Figure 10 As shown in the figure, it can be seen that most of the scattered points are concentrated around the line y = x, R 2 =0.98, RMSE=12.46, indicating a good fit. Therefore, the shear strength obtained from the model constructed in this embodiment is highly representative and meets engineering requirements.

[0142] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for constructing a model for rapidly predicting the peak intensity of MICP-modified construction waste, characterized in that, The specific steps are as follows: (1) Solid waste samples with different gradations were prepared using crushed construction waste particles, and compaction tests were conducted on the samples to obtain the optimum moisture content and maximum dry density of the samples; the R of the samples g / s The values ​​are 1.0, 1.5, 2, 2.5 and 3 respectively; (2) Use equal volumes of MICP modification reaction solutions of different concentrations to add to different samples and mix thoroughly; The reaction solution consists of bacterial solution and cementing solution, and the cementing solution consists of calcium chloride and urea. (3) The fully mixed sample is made into a cylindrical sample and compacted, and then cured under different time conditions; (4) Static triaxial test Static triaxial tests were conducted on the cured specimens under different confining pressures σ3. The peak strength of the specimen under different conditions can be calculated by analyzing the stress-strain curve; (5) Based on the peak intensity data obtained in step (4) under different conditions, the model formula is obtained by horizontally shifting the data relative to σ3. In the formula: k1, k2, a1, a2, a3, b1, b2, b3, c1, c2 are model parameters, σ3 is the confining pressure, and R g / s For the ratio of stone to sand, C Ca 2+ To improve the calcium ion concentration in MICP construction waste, D m The maintenance period is in days, and e is a mathematical constant.

2. The method according to claim 1, characterized in that, In step (2), C in the reaction solution Ca 2+ The concentrations were set to 0 mol / L, 0.5 mol / L, 1 mol / L, and 2 mol / L.

3. The method according to claim 1, characterized in that, In step (3), the curing time D m Set to 0, 1, 3, 6, or 10 days.

4. The method according to claim 1, characterized in that, In step (4), σ3 in the experiment is set to 50 kPa, 100 kPa, and 150 kPa, and the shear rate is 0.5% / min.

5. The method according to claim 1, characterized in that, The bacteria in the bacterial solution of the reaction solution in step (2) are *Bacillus pasteurellii*, and the bacterial concentration is OD0.

05. 600 =3.0.

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