Investigation of the Flow and Mechanical Performances of Foamed Concrete Used for Filling Cracks in the Base Layer of Asphalt Pavement

Abstract

Addressing the challenge that traditional flowability criteria cannot accurately characterize the grouting filling efficacy of foam concrete (FC) for cracks and voids in the base layer of asphalt pavement, this paper established a flowability evaluation method tailored for road grouting. Firstly, FC with varying flow performances were prepared by controlling the water–cement (W/C) ratio and water-reducing agent (WRA) dosage. Secondly, the flow cone method and micro-slump meter on a smooth flow degree pan method (MSM) characterized their flow performances. The porous Marshall specimens were constructed to simulate the crack–void structure of the base layer, and grouting plumpness was calculated using sectional image processing methods. Building upon this, gray relational analysis and regression analysis were employed to establish quantitative relationships between multiple factors and grouting plumpness. The results show that increasing W/C ratio and WRA dosage could improve the flow performance of FC, but reduce the compressive strength. Specifically, when the W/C ratio increased from 0.40 to 0.45, flow time decreased by 72.2% and flow diameter increased by 25%. Increasing WRA dosage from 0.3% to 0.5% could reduce flow time by 16% and increase flow diameter by 10%. Gray relational analysis revealed the strong correlations between flow indexes and grouting plumpness. The gray relational degree was 0.87 between grouting plumpness and flow diameter. In addition, the gray correlation between grouting plumpness and flow time was 0.65. Therefore, flow diameter should be first selected to measure the flow performance of FC. Furthermore, it was found that flow diameter should be higher than 230 mm to ensure that the average grouting plumpness of FC was above 80%. The results of this study provide a reliable basis for evaluating the flow performance of FC for filling cracks in the base layer of asphalt pavement.

1. Introduction

As the service life of asphalt pavement extends, the occurrences of cracks, voids, and other issues can greatly negatively impact the pavement’s performance [1,2]. Of these, cracks can lead to a reduction in the pavement’s bearing capacity, resulting in potholes or voids that threaten traffic safety and increase maintenance costs [3]. Milling and resurfacing technology is traditionally used to address the above issues [4,5]. However, this method presents challenges such as a long repair period and high cost. In contrast, road grouting technology is a potential solution for offering the benefits of rapid repair and in situ reinforcement [6].

The main types of road grouting materials include polymer grouting materials [7], biological grouting materials [8], and cement-based composite materials (e.g., geopolymer grouting materials [9], ultrafine cement slurry [10], bi-liquid cement-based composite material [11], and sulphoaluminate cement slurry [12]). At present, the commonly used geopolymer grouting materials have extremely high strength, generally withstanding over 40 MPa in 28 days [13]. According to the Chinese specification JTGT F20-2015 [14], the strength of the base layer in heavy-traffic expressways ranges from 5 to 8 MPa. Thus, there is a large amount of strength redundancy if geopolymer grouting material is used in road grouting, which will lead to a strength mismatch between the grouting material and the base layer. Under dynamic traffic loading, stress redistribution at the repair interface will cause the two mismatched materials to deform differently [15], easily inducing secondary damage and structural damage. Therefore, it is of great significance to develop a new type of grouting material that can adjust the strength of the grouting material according to the residual strength of the base layer, thereby improving the overall performance of the repaired road.

Foamed concrete (FC) is mostly used in building insulation and roadbed filling engineering in recent years due to its low density [16], controllable strength [17], and low energy consumption. FC can change its mechanical properties by adjusting the amount of foam [18]. Based on this characteristic of controllable strength, it can be used for grouting reinforcement of road bases. Although FC has many advantages, its engineering adaptability as a grouting material still faces many challenges. The flow performance of grouting materials can influence whether they can be smoothly injected into the target area under grouting pressure, and then fill voids and cracks. The existing test methods for road grouting materials include the flow cone method [19] and micro-slump meter on a smooth flow degree pan method (MSM) [20]. However, due to the differences in the characteristics of FC, the applicability of these two methods to FC has not been clarified. There remains a lack of an evaluation framework that quantitatively correlates conventional flowability test indices with the actual grouting plumpness in defected pavement structures. This gap has become a key limitation restricting the broader goals of flow performance in pavement grouting.

As a result, this study first reveals the influence mechanisms of the water–cement (W/C) ratio and the dosage of water-reducing agent (WRA) on the flow performance of FC. Secondly, the flow performances of FC are evaluated by the flow cone method and MSM, and the flexural and compressive strengths of FC are then tested. Finally, the applicability of the flow cone method and MSM for the determination of the flow performance of FC is evaluated by using digital image processing technology, gray relational analysis, and linear fitting methods.

2. Test Materials and Test Methods

2.1. Raw Materials

Ordinary Portland cement was used as the binder. Foam was prepared by compressing air along with a polymer composite blowing agent. Fly ash and silica fume were chosen as admixtures. Polycarboxylic acid water-reducing agents were selected to control the flow performance of FC. Specific raw material ratios [21,22] are presented in

Table 1. FC composition.

Group	W/C	WRA (wt.%)	Foam Dosage (vol.%)
P0.45-3-0.55	0.45	0.3%	55%
P0.45-3-0.35	0.45	0.3%	35%
P0.45-3-0.15	0.45	0.3%	15%
P0.45-5-0.55	0.45	0.5%	55%
P0.45-5-0.35	0.45	0.5%	35%
P0.45-5-0.15	0.45	0.5%	15%
P0.4-3-0.55	0.4	0.3%	55%
P0.4-3-0.35	0.4	0.3%	35%
P0.4-3-0.15	0.4	0.3%	15%
P0.4-5-0.55	0.4	0.5%	55%
P0.4-5-0.35	0.4	0.5%	35%
P0.4-5-0.15	0.4	0.5%	15%

. The wet density of fresh FC was determined to calculate porosity. The wet density of the fresh FC must differ by less than 1% from the actual design wet density, with each test series repeated three times. Foam reduction was controlled within ±2%.

In this study, the internal void structure and air void content of the porous Marshall specimens were deliberately controlled so that its internal morphology could adequately represent the typical cracking and void manifestations observed in base materials. In order to evaluate the grouting plumpness of FC, the asphalt mixture was prepared with an air void content of 20% [23,24]. This design approach enabled a more realistic simulation of the structural conditions encountered during non-excavation grouting reinforcement of the base layer. The gradation of the asphalt mixture is shown in Figure 1.

2.2. Test Methods

2.2.1. Flow Performance

The flow performance of FC was characterized using the flow cone method and MSM (see Figure 2). Flow time and flow diameter were used to evaluate the flow performance of FC, respectively. Furthermore, sensitivity analysis indicates that when the outlet diameter varies within a twofold range, the relationship between spread diameter and filling fullness, as well as the critical flow thresholds, changes by less than ±8%, demonstrating that this parameter has a limited influence on the main conclusions.

2.2.2. Mechanical Performance

The mechanical strength of FC is characterized by the flexural strength and compressive strength at 1 day, 7 days, and 28 days [25]. The cubic specimens (100 × 100 × 100 mm) were poured and placed in the standard curing room for curing. Then the specimens were taken out and put on the multifunctional pavement material strength tester, and tested at a loading speed of 1 mm/min until the specimens were damaged.

2.2.3. Grouting Plumpness

To simulate realistic grouting conditions, porous Marshall specimens were employed. The grouting plumpness η was used to quantify the degree of void filled by FC. This index was calculated based on the initial and final mass of the specimen, the known density of FC, and the effective porosity of the Marshall sample. The plumpness was computed using the following equation

$$\eta ={\displaystyle \frac{(m_2-m_1)}{\rho \times V\times VV}}\times 100\mathrm{\%}$$

(1)

where η is the grouting plumpness (%).${ m}_1$, $m_2$ are the mass of the porous Marshall specimen before and after grouting, respectively (g). $\rho$ is the density of FC (g/cm³). V is the volume of the porous Marshall specimen (cm³). VV is the connected air void content in the porous Marshall specimen (%).

2.2.4. Image Acquisition

To analyze the two-dimensional distribution characteristics of FC within the asphalt mixture, image acquisition was performed on specimens after curing for 28 days. Four disk-shaped slices were horizontally cut at 1 cm, 3 cm, and 5 cm from the top surface using a precision single-blade saw. The slices were naturally air-dried until no visible surface moisture remained (see Figure 3).

Photographs were taken under a controlled lighting environment, established using bilateral symmetrical illumination. A digital camera was positioned vertically above the samples to ensure high-resolution and high-contrast imaging. For each specimen, six-slice images at various depths were obtained. These images were subsequently used for gray correlation analysis to investigate the relationship between grouting plumpness and depth distribution. Currently, in the field of image processing, both domestically and internationally, there are MATLAB, DeepLab [26], and EfficientNet [27].This study employed MATLAB 2024a.

2.2.5. Gray Correlation Analysis

Gray correlation analysis is a multifactor statistical analysis method used to measure a system’s degree of association of factors. The method determines the degree of closeness between factors by comparing the similarity of the geometric shapes of the sequence curves. The specific calculation steps [28] (including determining the reference series, comparison series, dimensionless processing, correlation coefficient, correlation degree calculation, etc.) can be referred to in the method of Li et al. [29].

2.2.6. Test Verification of Grouting Plumpness

To verify the rationality of the proposed flow performance requirements, two FC mix designs were selected. Their flow characteristics were evaluated, and the measured and calculated grouting plumpness values were compared.

3. Results and Discussions

3.1. Performance Test Results of FC

3.1.1. Flow Performance

The flow performance of FC was evaluated using the flow cone method and MSM, respectively. The results are shown in Figure 4 and Figure 5. It can be found that the factors affecting the flow performance of FC include foam dosage, W/C ratio, and WRA dosage. With the decrease in foam dosage and the increase in W/C ratio and the WRA dosage, the flow performance of FC was improved.

Increasing the W/C ratio to 0.45 (P0.45-3-0.55) could reduce flow time by 72.2% and increase flow diameter by 25% as compared to P0.4-3-0.55. Reducing the foam dosage to 35% (P0.45-3-0.35) resulted in a 53.3% reduction in flow time and a 3.9% increase in flow diameter as compared to P0.4-3-0.35. Similarly, the specimen with 15% foam dosage (P0.45-3-0.15) showed a 40% reduction in flow time and a 1.8% increase in flow diameter compared to P0.4-3-0.15. It was shown that when the WRA dosage was the same, increasing the W/C ratio could improve the flow performance of FC. The mechanism is that the increase in water content can increase the distance between cement particles, causing better dispersion of cement particles [30], so that the effective collision between cement particles is reduced, and the generation of flocculation structure of cement particles is slowed down. In addition to this, as the foam dosage decreased, the flow performance was improved.

The flow performance was improved when the WRA dosage was increased from 0.3% to 0.5%. For example, compared with P0.45-3-0.55, P0.45-5-0.55 flow time decreased by 16% and flow diameter increased by 10%. Compared with the specimen with 35% foam dosage (P0.45-3-0.35), P0.45-5-0.35 flow time decreased by 9.5% and flow diameter increased by 3.8%. When the foam dosage was 15%, the flow performance of P0.45-5-0.35 decreased by 9.5% and flow diameter increased by 3.8%, compared with P0.45-3-0.15. The flow time of P0.45-5-0.15 decreased by 22.2% and its flow diameter increased by 1.1%. It is shown that when the W/C ratio is the same, increasing the dosage of WRA can improve the flow performance of FC. And after adding WRA, WRA can be adsorbed to the surface of the cement particles to change the electrical properties of the surface, which reduces the friction between the cement particles, and prevents the generation of flocculation structure of the cement particles and thus improves the flowability [31,32]. At low W/C ratios, the effect of WRA is significant, while at high W/C ratios, the distance between cement particles is larger, which leads to fewer flocculated structures. As a result, the effect of WRA to improve flow performance gradually decreases [33]. However, compared to increasing the W/C ratio, there was an overall reduction in the improvement of flow performance.

3.1.2. Mechanical Performance

The effects of W/C ratio, WRA dosage, and foam dosage on the mechanical performance of FC specimens were analyzed using 1d, 7d, and 28d flexural and compressive strengths. The test results are shown in Figure 6, Figure 7 and Figure 8. It can be seen that for P0.4-3-0.55 and P0.45-3-0.55, when the W/C ratio reduced from 0.45 to 0.40, the 7d flexural and compressive strengths increased by 31.9% and 67.2%, respectively. The 28d flexural and compressive strengths increased by 17.7% and 36.9%, respectively. This is because with the reduction in W/C ratio, the cement content per unit volume increases, leading to an increase in hydration products.

When the W/C ratio was 0.4, the addition of WRA had almost no effect on the strength of the specimen, but when the W/C ratio was 0.45, the increasing dosage of WRA could reduce the strength of the specimen. This is because when the W/C ratio is low, the increasing dosage of WRA will improve the flow performance, so that the distribution of particles in the slurry will be more uniform, and the hydration rate of the cement will be increased. However, when the W/C ratio is high, the WRA will cause the cement particles to be too dispersed. The effective collision between particles will be reduced, and the hydration rate will be reduced. Compared with P0.45-5-0.55, the 7d flexural strength and compressive strength of P0.45-3-0.55 increased by 71.7% and 17.5%, respectively, and the 28d flexural strength and compressive strength increased by 74.7% and 15.4%, respectively. The above results show that both W/C ratio and WRA dosage affected the strength of the specimens. So when designing FC, it is necessary to consider the flow and mechanical performance by adjusting the W/C ratio, WRA dosage, and foam dosage.

3.2. Tested Grouting Plumpness Results of FC

The results of the grouting plumpness tests are shown in Figure 9. It can be found that the grouting plumpness of FC increased with the increase in W/C and WRA dosage. Compared with P0.4-3-0.55, the grouting plumpness of P0.45-3-0.55 and P0.4-5-0.55 increased by 199% and 148%, respectively. Compared with P0.45-3-0.55, the grouting plumpness of P0.45-5-0.55 increased by 38.5%. In addition, compared with P0.4-3-0.55, the grouting plumpness of P0.4-5-0.55 increased by 47.7%. In the two groups of comparisons, although the W/C ratios of the two groups were different, the efficiency of improving the flow performance by increasing the dosage of WRA was basically the same.

3.3. Calculated Grouting Plumpness Results of FC

Six images of two-dimensional cross-sections were obtained for each specimen. MATLAB software was used to process the images, and the results are shown in Figure 10. Firstly, the contrast enhancement technique was used to strengthen the gray scale difference between different components, and then the median filtering algorithm was used to effectively suppress the dark noise points in the aggregate and asphalt mortar regions, to achieve the elimination of noise while retaining the edge characteristics of the image. Subsequently, taking the dark area as the benchmark, the optimal segmentation threshold was determined by optimizing the threshold segmentation strategy, and image binarization processing was performed based on this threshold. Finally, the gap areas in the image were accurately extracted.

3.3.1. Comparison of Grouting Plumpness

The calculated grouting plumpness η_c of the specimen was obtained based on the processing results of the 2D image, and the area of the initial void was represented by the sum of the area of the remaining void and FC, which was calculated using the Formula (2).

$${\eta }_c={\displaystyle \frac{A_C}{A_C+A_v}}\times 100\mathrm{\%}$$

(2)

where η_c is the calculated grouting plumpness, %. $A_C$ is the area of FC. $A_v$ is the area of the void.

The average of the calculated grouting plumpness η_c of the six pictures was taken as the calculated grouting plumpness of the specimen, and it was compared with the measured grouting plumpness $\eta$. As shown in

Table 2. Measured and calculated grouting plumpness.

Group	Measured Grouting Plumpness/%	Calculated Grouting Plumpness/%	Relative Difference/%
P0.45-3-0.55	58.63	61.60	−5.06
P0.45-3-0.35	73.89	69.83	5.49
P0.45-3-0.15	89.34	92.37	−3.39
P0.45-5-0.55	81.22	78.44	3.42
P0.45-5-0.35	85.99	80.36	6.55
P0.45-5-0.15	89.00	88.75	0.28
P0.4-3-0.55	19.56	22.16	−3.29
P0.4-3-0.35	51.04	49.57	2.88
P0.4-3-0.15	67.90	63.85	5.96
P0.4-5-0.55	48.44	49.76	−2.72
P0.4-5-0.35	66.08	62.18	5.90
P0.4-5-0.15	79.24	75.89	4.23

, the measured grouting plumpness was essentially the same as the calculated grouting plumpness, with relative differences of less than 7%. The calculated grouting plumpness was mostly smaller than the measured grouting plumpness. The reasons for this phenomenon were as follows. Firstly, the material was selected as FC, and the image recognition might have misjudged the pores as voids, which would lead to a lower grouting plumpness calculation. Secondly, when the image processing technology was used to extract the voids, a number of asphalt areas were incorrectly identified as voids due to the similar color of voids and asphalt, which led to an increase in the area of the voids. In summary, the calculated measured grouting plumpness had a good correlation and could be used to evaluate the degree of injectability of FC.

3.3.2. Distribution of FC

In order to investigate the distribution of FC with different flow performance in asphalt mixtures, three specimens with different injection effects, P0.45-3-0.55, P0.4-3-0.55 and P0.4-5-0.55, were compared, and the grouting plumpness of the specimens at different depths (1, 3 and 5 cm) was compared, as shown in Figure 11. It can be seen that the area around P0.45-3-0.55 was covered by FC, while for P0.4-3-0.55, only the upper part of the specimen was covered by FC. But FC could not be seen at the bottom, indicating that the flow performance of FC was poorer. However, the flow performance of P0.4-5-0.55 was the median value. FC can be seen at the bottom of P0.4-5-0.55, but it can be clearly seen that the area covered by FC in the middle and lower part of the specimen was not similar to the upper part.

From the calculated grouting plumpness at different depths of the specimen, it can be seen that the grouting plumpness from P0.45-3-0.55 to P0.4-5-0.15 decreased with the increase in the depth, which was negatively correlated (Figure 12). This is related to the fact that the asphalt mixture had different void sizes and distributions at different depths. At some depths, there were smaller voids, which prevented FC from being effectively injected, thereby decreasing the grouting plumpness as the depth increased. Combined with the flow performance of FC (Figure 4 and Figure 5), it can be found that with the improvement of the flow performance, the grouting plumpness decreased with the increase in the depth, but the reduction gradually decreased; this was because the improvement of the flow performance could make FC pass through more small voids. The measured grouting plumpness of the lowest layer of P0.45-3-0.55 was close to 60%, and the calculated grouting plumpness at different depths was basically the same as the average grouting plumpness. The average grouting plumpness of P0.45-3-0.55 was nearly 80%, and the calculated grouting plumpness at different depths was basically the same, which was more than 80%, indicating that the fluidity of FC in the P0.45-3-0.55 could ensure that the specimen was basically completely grouted. Therefore, if the average grouting plumpness of the specimen reaches 80% and the grouting plumpness at the bottom is more than 60%, it can be said that the flow performance of this FC can meet the grouting requirements.

3.4. Gray Correlation Analysis

Gray correlation analysis was employed to investigate the effects of W/C ratio, WRA dosage, and foam dosage on the grouting plumpness of FC, as well as the correlation between the two flow performance testing methods and grouting plumpness. The measured grouting plumpness was used as the reference sequence, while W/C, WRA dosage, foam dosage, flow time, and flow diameter function as the comparison sequence for calculating the gray correlation coefficients and gray correlations. According to gray system theory, ζ is typically set to 0.5 to balance discrimination ability and stability [34]. The results of these calculations are presented in

Table 3. Gray correlation analysis results for grouting plumpness.

Group	$\mathit{\gamma }\left({\mathit{x}}_0\right(\mathit{k}),{\mathit{x}}_1(\mathit{k}\left)\right)$	$\mathit{\gamma }\left({\mathit{x}}_0\right(\mathit{k}),{\mathit{x}}_2(\mathit{k}\left)\right)$	$\mathit{\gamma }\left({\mathit{x}}_0\right(\mathit{k}),{\mathit{x}}_3(\mathit{k}\left)\right)$	$\mathit{\gamma }\left({\mathit{x}}_0\right(\mathit{k}),{\mathit{x}}_4(\mathit{k}\left)\right)$	$\mathit{\gamma }\left({\mathit{x}}_0\right(\mathit{k}),{\mathit{x}}_5(\mathit{k}\left)\right)$
1	0.73	0.81	0.76	0.77	0.95
2	0.72	0.87	0.79	0.74	0.85
3	0.83	0.89	0.69	0.70	0.80
4	0.66	0.85	0.62	0.57	0.90
5	0.85	0.91	0.93	0.61	0.82
6	0.75	0.75	0.91	0.66	0.75
7	0.69	0.63	0.87	0.53	0.98
8	0.78	0.62	0.82	0.81	0.88
9	0.86	0.78	0.85	0.82	0.83
10	0.65	0.86	0.79	0.56	0.92
11	0.69	0.95	0.6	0.49	0.87
12	0.79	0.92	0.65	0.54	0.86
Gray correlation	0.75	0.82	0.78	0.65	0.87

Note: x₀(k), x₁(k), x₂(k), x₃(k), x₄(k) and x₅(k) correspond to the measured grouting plumpness (%), W/C, WRA dosage (%), foam dosage (%), flow time (s) and flow diameter (mm), respectively.

, which demonstrates that the influence of varying the W/C ratio, WRA dosage, and foam dosage on grouting plumpness was relatively similar. The gray correlations for the three dosages exceed 0.65, indicating that adjustments to these three dosages were feasible, thereby suggesting that the two flow performance test methods were correlated with grouting plumpness. The gray correlation values of all three dosages surpassed 0.65, which indicates that modifying the aforementioned dosages (W/C, WRA, and foam) could enhance the flow performance of FC, thereby improving its overall grouting plumpness.

Both test methods could be used to measure the flow performance of FC, but the flow diameters obtained using MSM had a higher correlation with the grouting plumpness compared to flow time tested by the flow cone method. The flow cone used a cone with a 13 mm diameter, which was a large difference to the diameter of the voids in the porous Marshall specimen. FC could only pass through smoothly in the larger voids. In addition, as FC contained a large amount of foam, some foam would float up when measuring the flow performance. When the main part of the slurry flowed through the cone, a small part of the foam did not pass through, which affected the measurement of flow time. However, using MSM had no impact, so the gray correlation coefficient of flow diameters was relatively high. Flow diameter measured by MSM characterized the flow performance of FC, which showed the penetration ability of the FC in the small-sized voids. In summary, MSM had a better correlation with the flow performance of FC and had a superior assessment capability in terms of measuring flow performance. According to flow time, flow diameter, and the distribution of grouting plumpness (Figure 13), the coefficients after fitting were more than 0.9. This indicates that the method of two flow performance tests could meet the flow performance requirements of FC.

The porous Marshall specimen usually showed a characteristic of decreasing air void content from top to bottom in the vertical direction, which affected the corresponding grouting plumpness. The flow time of polymer grouting materials should be controlled within 20 s. When the flow time of polymer grouting material was 20 s, the grouting plumpness was 80%. Therefore, when the slurry can fill 80% of the overall voids of the specimen, it is considered to meet the requirements. However, since the plumpness of the top layer was all above 90%, it was too one-sided to only measure the average grouting plumpness as being greater than 80%. Therefore, it was also necessary to ensure that the grouting plumpness of the bottom layer exceeded 60%, so as to ensure that the grouting plumpness of each layer was close to 80%. According to the fitting curve, it can be concluded that the flow time of FC was less than 30 s or the flow diameter was more than 230 mm, to make the bottom grouting plumpness of the porous Marshall specimen more than 60%, and the average grouting plumpness more than 80%.

3.5. Verification of the Grouting Feasibility Conclusion

In order to verify the reasonableness of the above flow performance requirements, the proportioning of FC was reformulated. Two FC batches were prepared, and the specific proportioning and flow performance indexes are shown in

Table 4. Mixing ratios and flow performances of P1 and P2.

Group	W/C	WRA Dosage	Foam Dosage	Flow Time/s	Flow Diameter/mm
P1	0.4	0.2%	55%	71	190
P2	0.4	0.4%	35%	25	260

. From Table 4, it can be seen that without changing the W/C ratio, increasing the dosage of WRA as well as reducing the foam dosage would improve the flow performance of FC. Two FC batches were injected into the asphalt mixture, and then their grouting plumpness was tested. The results are shown in

Table 5. Grouting plumpness at different depths.

Group	Grouting Plumpness/%
	1 cm	3 cm	5 cm	Average
P1	68.83	60.54	48.74	59.37
P2	90.73	85.47	64.97	80.39

. From Table 4 and Table 5 it can be seen that the flow time of P1 was higher than 30 s and the flow diameter was less than 230 mm. And the bottom grouting plumpness and the average grouting plumpness were lower than 60%. However, P2 flow time was less than 30 s, and flow diameter was greater than 230 mm. The bottom grouting plumpness was higher than 60%, and the average grouting plumpness was higher than 80%. The above results prove that the flow performance requirements in Section 3.1.1 are reasonable, and the above method can be used to the flow performance of FC.

4. Conclusions

(1)

Increasing W/C and WRA dosage could effectively improve the flow performance of FC. Compared with P0.4-3-0.55, increasing W/C by 0.05 (P0.45-3-0.55) reduced flow time by 72.22% and increased flow diameter by 25%. Increasing water reducing agent dosage by 0.2 (P0.4-3-0.35) reduced flow time by 65.56% and increased flow diameter by 40.63%.

(2)

Increasing W/C and the dosage of WRA reduced the mechanical performance of FC. For P0.4-3-0.55 and P0.45-3-0.55, when the W/C increased by 0.05, the 28d flexural and compressive strength reduced by 17.7% and 36.9%, respectively. Compared with P0.45-5-0.55, increasing the water-reducing agent dosage by 0.2 caused the 28d flexural strength and compressive strength to reduce by 74.7% and 15.4%, respectively.

(3)

Flow diameter should be higher than 230 mm to ensure that the average grouting plumpness of FC was above 80%. The result can be directly applied to the optimization and control of grouting mixture proportions in the field.

(4)

The flow performance indexes of FC obtained by the flow cone method and the MSM both had obvious correlations with the grouting plumpness. The correlation between flow diameter and the grouting plumpness was 0.85, and this method should be first selected to evaluate the flow performance of FC.

5. Future

Future research directions include extending this methodology to full-scale pavement structures for field validation, and integrating deep learning-based computer vision techniques to achieve higher-precision identification and quantitative characterization of grouting processes.