Method, medium, and apparatus for road subgrade design with material-enhanced reflective layer

Abstract

This invention belongs to the field of traffic engineering technology and discloses a roadbed design method, medium, and equipment containing a material-reinforced reflective layer. This invention establishes a multi-layer road medium model containing a material-reinforced reflective layer. By replacing the original structural layers with an embedded material-reinforced reflective layer, the reflection effect of B-Scan radar images is improved. By analyzing the influence of the thickness and position of the material-reinforced reflective layer on radar reflected waves, the optimal roadbed is output. Considering the antenna detection depth at different frequencies and the roadbed height of different roads, different positions and thicknesses of the material-reinforced reflective layer are recommended for projects with radar detection requirements. It also outputs the relationship between the dielectric constant of the roadbed and the changes in moisture content and compaction degree, which can accurately obtain the moisture content and compaction degree of the roadbed, overcoming the shortcomings of traditional roadbed defects and unclear moisture content test images, and providing signal enhancement solutions for projects with ground-penetrating radar detection requirements.

Description

Technical Field

[0001] This invention belongs to the field of traffic engineering technology, and in particular relates to a roadbed design method, medium and equipment containing a material-reinforced reflective layer. Background Technology

[0002] Ground penetrating radar (GPR), as a non-destructive, efficient, and convenient detection technology, has been widely adopted for detecting internal road surface defects. GPR transmits high-frequency electromagnetic waves and receives reflected signals from interfaces with different dielectric constants. The finite-difference time-domain (FDTD) method is the mainstream algorithm for GPR forward modeling, simulating electromagnetic wave propagation using discrete Maxwell's equations. A forward model is constructed, incorporating a material-enhanced reflective layer and internal road defects, outputting high-fidelity A-Scan signal waves and B-Scan images.

[0003] When inspecting road structures, the signals collected often contain significant non-target echoes and random interference due to the combined effects of complex geological conditions and surrounding environmental factors. These interference factors can cause signal aliasing and weakened target reflection characteristics in the detected images, leading to reduced reliability of the detection results and significantly hindering the accurate identification and interpretation of anomalies within the road. High dielectric constant materials significantly reduce their own wave impedance, creating a large wave impedance difference with the surrounding medium (such as air). According to the reflection coefficient formula in electromagnetic wave theory, this large impedance mismatch causes most of the incident wave energy to be reflected back, thus significantly enhancing the amplitude of the interface reflected wave. The high dielectric constant material property can significantly enhance the amplitude of interface reflected waves; embedding high dielectric constant materials to form a material-enhanced reflection layer improves the signal-to-noise ratio.

[0004] Traditional methods for detecting subgrade moisture content primarily rely on core drilling and drying, which requires damaging the pavement structure. Single-point testing can take over 24 hours and only reflects localized information, failing to characterize the spatial variation of subgrade moisture content over long distances. Compaction degree testing is similarly limited by core drilling, easily leading to pavement damage and shortening road life. Furthermore, when using ground-penetrating radar to detect moisture content and compaction degree, the images are blurry and difficult to interpret.

[0005] Therefore, it is of great significance to develop a new roadbed structure that can use ground-penetrating radar to achieve non-destructive testing and accurate detection of roadbed structure defects. Summary of the Invention

[0006] This invention discloses a roadbed design method containing a material-enhanced reflective layer. By embedding a high-dielectric-constant material structure layer in the roadbed, analyzing radar wave reflection intensity changes based on B-Scan radar images, and adjusting model parameters to control the position and thickness of the high-dielectric-constant material structure layer, an optimal roadbed with the material-enhanced reflective layer is designed. This overcomes the difficulties in accurate image recognition and interpretation in existing technologies caused by factors such as not considering the enhancement effect of the high-dielectric-constant material structure layer on radar signals, not considering the different detection depths of antennas at different frequencies, or the different roadbed heights of different roads. The technical solution is as follows:

[0007] A roadbed design method containing a material-reinforced reflective layer includes the following steps:

[0008] Step 1: Conduct preliminary design of the roadbed containing the material-reinforced reflective layer to obtain a multi-layer road media model. The multi-layer road media model includes a first structure and a second structure, wherein: the first structure includes, from top to bottom, a surface layer, a base layer, a material-reinforced reflective layer, a subgrade, and an embankment; the second structure includes, from top to bottom, a surface layer, a base layer, a subgrade, a material-reinforced reflective layer, and an embankment; set the electromagnetic parameters of the media.

[0009] Step 2: Determine an initial optimal thickness range for the material-enhanced reflective layer for both the first and second structures in Step 1.

[0010] Step 3: After adjusting the thickness of the material-enhanced reflective layer, obtain A-Scan signal waves and B-Scan radar images of the first and second structures;

[0011] Step 4: Analyze the A-Scan signal waves and B-Scan radar images of the first and second structures to output the optimal roadbed location and thickness of the material-enhanced reflective layer.

[0012] Preferably, it also includes the dielectric constant of the roadbed. With moisture content The changing relationship is as follows:

[0013] .

[0014] Preferably, it also includes the dielectric constant of the roadbed. With compaction degree The changing relationship is as follows:

[0015] .

[0016] Preferably, the relative permittivity of the material-enhanced reflective layer is 30 to 50.

[0017] Preferably, the material-enhanced reflective layer is a steel slag-containing structural layer and / or a titanium-containing blast furnace slag structural layer.

[0018] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described roadbed design method containing a material-enhanced reflective layer.

[0019] The present invention also discloses an electronic device, comprising:

[0020] processor;

[0021] and memory for storing the executable instructions of the processor;

[0022] The processor is configured to execute the roadbed design method with a material-reinforced reflective layer as described above by executing the executable instructions.

[0023] The effect of applying the technical solution of this invention is:

[0024] Compared with existing technologies, this invention establishes a multi-layer road medium model (FDTD model) containing a high dielectric constant material structural layer (i.e., a material-enhanced reflective layer). It utilizes FDTD principles to generate road A-Scan signal waves and B-Scan radar images with clearly defined parameters through forward modeling. By replacing the original structural layer with an embedded material-enhanced reflective layer, the reflection effect of the B-Scan radar image is improved. By analyzing the influence of the thickness and position of the material-enhanced reflective layer on the radar reflected wave, the optimal roadbed location and thickness for the material-enhanced reflective layer are output. Considering the antenna detection depth at different frequencies and the roadbed height of different roads, different material-enhanced reflective layer locations and thicknesses are recommended for various projects with radar detection requirements.

[0025] In addition, it also outputs the relationship between the dielectric constant of the road subgrade and the moisture content, and the relationship between the dielectric constant of the road subgrade and the compaction degree. It can accurately obtain the moisture content and compaction degree of the road subgrade, overcoming the shortcomings of traditional road subgrade defects and unclear moisture content test images. Attached Figure Description

[0026] 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.

[0027] Figure 1 This is a schematic diagram illustrating the principle of forward simulation in an embodiment of the present invention;

[0028] Figure 2(a) is a schematic diagram of the first structure of a multi-layer road medium model containing a material-reinforced reflective layer in an embodiment of the present invention;

[0029] Figure 2(b) is a schematic diagram of a second structure in an embodiment of the present invention where the defect is located between the base course and the subgrade;

[0030] Figure 2(c) is a schematic diagram of a second structure in an embodiment of the present invention, in which the defects are located between the base layer and the subgrade, and in which the defects are located between the surface layer and the base layer.

[0031] Figure 3 These are the dielectric constant fitting curve images under different moisture content conditions in the embodiments of the present invention;

[0032] Figure 4 This is a comparison image of B-Scan radar defects with the material-enhanced reflective layer placed on top of the defect in an embodiment of the present invention;

[0033] Figure 5(a) is a comparison of the B-Scan radar deflection defects with different thicknesses and positions of the reflective layers reinforced by different materials in the embodiments of the present invention, wherein: (a1) is a schematic diagram of deflection defects; (a2) is a schematic diagram of deflection defects with 11.4cm placed at the bottom of the base layer; (a3) ​​is a schematic diagram of deflection defects with 11.4cm placed at the bottom of the roadbed; (a4) is a schematic diagram of deflection defects with 21.5cm placed at the bottom of the base layer; (a5) is a schematic diagram of deflection defects with 31.6cm placed at the bottom of the base layer.

[0034] Figure 5(b) is a comparison diagram of the B-Scan radar cavity defects with different thicknesses and positions of the reflective layers reinforced by different materials in the embodiments of the present invention, wherein: (b1) is a schematic diagram of cavity defects; (b2) is a schematic diagram of cavity defects with 11.4cm placed at the bottom of the base layer; (b3) is a schematic diagram of cavity defects with 11.4cm placed at the bottom of the roadbed; (b4) is a schematic diagram of cavity defects with 21.5cm placed at the bottom of the base layer; (b5) is a schematic diagram of cavity defects with 31.6cm placed at the bottom of the base layer.

[0035] Figure 5(c) is a comparison of the B-Scan radar crack defects with different thicknesses and positions of the reflective layers reinforced by different materials in the embodiments of the present invention, wherein: (c1) is a schematic diagram of crack defects; (c2) is a schematic diagram of crack defects with 11.4cm placed at the bottom of the base layer; (c3) is a schematic diagram of crack defects with 11.4cm placed at the bottom of the roadbed; (c4) is a schematic diagram of crack defects with 21.5cm placed at the bottom of the base layer; (c5) is a schematic diagram of crack defects with 31.6cm placed at the bottom of the base layer.

[0036] Figure 5(d) is a comparison of the B-Scan radar loosening disease graphic features of different material-enhanced reflective layers with varying thicknesses and positions in the embodiments of the present invention. Specifically: (d1) is a schematic diagram of loosening disease; (d2) is a schematic diagram of loosening disease with a layer of 11.4cm placed at the bottom of the base layer; (d3) is a schematic diagram of loosening disease with a layer of 11.4cm placed at the bottom of the roadbed; (d4) is a schematic diagram of loosening disease with a layer of 21.5cm placed at the bottom of the base layer; and (d5) is a schematic diagram of loosening disease with a layer of 31.6cm placed at the bottom of the base layer.

[0037] Figure 6 These are comparison images of B-Scan radar images under different moisture contents after the material-enhanced reflective layer of this invention is enhanced, wherein: (a) is a dry flexible roadbed; (b) is a wet flexible roadbed; and (c) is a saturated flexible roadbed.

[0038] Figure 7 This is a comparison diagram of A-Scan signal characteristics under different moisture content conditions according to the present invention, wherein: (a) is a dry flexible roadbed; (b) is a wet flexible roadbed; and (c) is a saturated flexible roadbed.

[0039] Figure 8 These are comparison diagrams of B-Scan radar image features under different compaction conditions after the material of the present invention enhances the reflective layer, wherein: (a) is a schematic diagram of 65% compaction; (b) is a schematic diagram of 70% compaction; and (c) is a schematic diagram of 75% compaction.

[0040] Figure 9 These are comparison diagrams of A-Scan signal characteristics under different compaction conditions according to the present invention, wherein: (a) is a schematic diagram of 75% compaction; (b) is a schematic diagram of 70% compaction; and (c) is a schematic diagram of 65% compaction. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Example:

[0043] This embodiment provides a roadbed design method containing a material-reinforced reflective layer, including the following steps:

[0044] Step 1: Preliminary design of the roadbed containing the material-reinforced reflective layer to obtain a multi-layer road media model. The multi-layer road media model includes a first structure and a second structure. The first structure includes, from top to bottom, a surface layer, a base layer, a material-reinforced reflective layer, a subgrade, and an embankment, as shown in Figure 2(a). This illustrates that the defects are located in the base layer. The second structure includes, from top to bottom, a surface layer, a base layer, a subgrade, a material-reinforced reflective layer, and an embankment, as shown in Figures 2(b) and 2(c). Figure 2(b) illustrates that the defects are located in the subgrade, and Figure 2(c) illustrates that defects are present in both the base layer and the subgrade. Set the electromagnetic parameters of the media.

[0045] Step 2: Determine an initial optimal thickness range for the material-enhanced reflective layer for both the first and second structures in Step 1.

[0046] Step 3: After adjusting the thickness of the material-enhanced reflective layer, obtain A-Scan signal waves and B-Scan radar images of the first and second structures;

[0047] Step 4: Analyze the A-Scan signal waves and B-Scan radar images of the first and second structures to output the optimal roadbed location and thickness of the material-enhanced reflective layer.

[0048] In this preferred embodiment, the forward modeling parameters specifically include: the main space of the forward modeling model of the road structure is 4m×2m×0.002m, the spatial discretization dx-dy-dz size in the X, Y, and Z axes of the spatial coordinate system is 0.002m×0.002m×0.002m, and the time window size is 3×10 -8 The excitation source type is Ricker wavelet, the excitation source frequency is 1000MHz center frequency, and the antenna spatial step distance is 0.02m.

[0049] In this preferred embodiment, a material-enhanced reflective layer (i.e., a high dielectric constant material, such as a steel slag-containing structural layer or a titanium-containing blast furnace slag structural layer) is embedded to replace the original structural layer. Radar wave reflection intensity changes are analyzed based on B-Scan radar images. By adjusting model parameters to control the position (bottom of the roadbed or bottom of the base course) and thickness d (11.4cm, 21.5cm, and 31.6cm respectively), multiple sets of A-Scan signal waves and B-Scan radar images containing various defects (voids, voids, cracks, looseness, and water abundance) are generated using the FDTD principle.

[0050] This study analyzes B-scan radar images of various roadbed defects (voids, voids, cracks, loosening, and waterlogging) to determine the reinforcing effect of high-dielectric-content material layers. It also identifies optimal locations and thicknesses where the dielectric properties of the material-reinforced reflective layer can improve the ground-penetrating radar (GPR) reflection signal. The influence of the location and thickness of the material-reinforced reflective layer on GPR B-scan images of different roadbed defects is analyzed. Comparative analysis of GPR B-scan images of various defects reveals that the material-reinforced reflective layer can improve the detection accuracy of roadbed defects.

[0051] ① When focusing on road surface defects, placing the material-reinforced reflective layer at the bottom of the base layer with a thickness of 31.6cm will yield better results;

[0052] ② When focusing on subgrade defects, placing the material-reinforced reflective layer at the bottom of the subgrade with a thickness of 31.6cm will yield better results.

[0053] Considering that antennas of different frequencies have different detection depths and different roadbed heights on different roads, the recommended location and thickness of the material-enhanced reflective layer are as follows.

[0054] The differences in waveform characteristics of images with different moisture contents and compaction degrees are analyzed and compared as follows:

[0055] By enhancing the signals of ground-penetrating radar B-scan images with different roadbed moisture contents and compaction degrees using a material-reinforced reflective layer, the roadbed moisture content w (5%-25%) and compaction degree (65%-75%) were adjusted using the controlled variable method. Multiple sets of A-Scan signal waves and B-Scan radar images were generated using forward modeling based on the FDTD principle. The standard for roadbed moisture content is: dry flexible roadbed <8%, wet flexible roadbed >12%, and saturated flexible roadbed >16%.

[0056] Meanwhile, establishing a quantitative relationship between moisture content change and dielectric constant allows analysis to show that the dielectric constant of the subgrade increases linearly with increasing moisture content. The material-reinforced reflective layer can improve the accuracy of subgrade moisture content and compaction degree detection.

[0057] Specific application examples are as follows:

[0058] In this embodiment, the forward modeling of the ground-penetrating radar involves using a computer to simulate the environment surrounding the target object and the propagation of electromagnetic waves within that environment. This allows for effective analysis of the propagation patterns of electromagnetic waves, such as... Figure 1 As shown.

[0059] A multi-layer road media model is constructed by embedding a material-enhanced reflective layer (containing a steel slag structural layer (coarse steel slag aggregate, fine steel slag aggregate, steel slag powder / mineral powder, flake graphite, ordinary silicate cement, coupling agent, and water, with specific proportions referring to existing technologies) and a titanium blast furnace slag structural layer (coarse titanium blast furnace slag aggregate, fine titanium blast furnace slag aggregate, titanium blast furnace slag powder, ordinary silicate cement, graphene conductive slurry, high-efficiency water-reducing agent, and water, with specific proportions referring to existing technologies). (From top to bottom: Model ①: surface layer, base layer, material-enhanced reflective layer, roadbed, embankment; Model ②: surface layer, base layer, roadbed, material-enhanced reflective layer, embankment).

[0060] The electromagnetic parameters of the medium are set, and the steel slag structural layer and the titanium blast furnace slag structural layer are set as materials with high dielectric constants. The parameters of the layered model of the highway subgrade and pavement are shown in Table 1.

[0061] Table 1. Parameters of the Layered Model for Highway Subgrade and Pavement

[0062]

[0063] Here, the specific parameters for the forward modeling process include: the main space of the forward modeling model of the road structure is 4m×2m×0.002m; the spatial discretization dx-dy-dz size in the X, Y, and Z axes of the spatial coordinate system is 0.002m×0.002m×0.002m; and the time window size is 3×10. -8 The excitation source type is Ricker wavelet, the excitation source frequency is 1000MHz center frequency, the antenna spatial step distance is 0.02m, and the forward modeling parameters are shown in Table 2:

[0064] Table 2 Forward Simulation Parameters

[0065]

[0066] First, based on the principle of electromagnetic wave interference, an initial optimal thickness range that can theoretically generate the strongest reflection signal is determined for the material-enhanced reflective layer, avoiding blind and extensive trial calculations in an invalid parameter space.

[0067] When an electromagnetic wave is incident perpendicularly onto a dielectric layer, if the thickness of the dielectric layer satisfies a quarter wavelength requirement ( If the electromagnetic wave reflected from the top and bottom surfaces of the layer is an odd multiple of 4, and its wave impedance is between the upper and lower media, then the electromagnetic wave reflected from the top and bottom surfaces of the layer will be enhanced by constructive interference, thereby significantly improving the signal-to-noise ratio of the reflected signal.

[0068] According to electromagnetic wave theory, the wavelength of an electromagnetic wave propagating in a medium is... As shown in the following formula:

[0069] ;

[0070] Where: c is the speed of electromagnetic wave propagation in vacuum, and its value is 3 × 10⁻⁶. 8 m / s; The center frequency of the pulse signal. is the relative permittivity of the medium.

[0071] The theoretical value of the optimal thickness is:

[0072] ;

[0073] For structural layers such as subbases and functional layers in light traffic roads, the required thickness is typically 150mm-300mm; for main roads and highways, the required thickness is typically 300mm-500mm. When selecting values ​​for n in an arithmetic progression to meet the structural layer thickness requirements, the theoretical optimal thickness is:

[0074] ;

[0075] ;

[0076] ;

[0077] Adjusting the position and thickness d (11.4cm, 21.5cm, 31.6cm) of the material-enhanced reflective layer, B-Scan radar images were generated. Based on the parameters in Tables 1 and 2, a material with a high dielectric constant was used to replace the traditional roadbed and pavement materials. The position and thickness of the material-enhanced reflective layer were changed, and forward modeling was performed using the FDTD principle to generate B-Scan radar images and analyze the changes in radar wave reflection intensity.

[0078] The greater the dielectric difference between the defect-filling medium and the surrounding medium, the more obvious the defect characteristics and the stronger the diffraction signal at the boundary. Using the FDTD principle, multiple sets of A-Scan signal waves and B-Scan radar images containing various defects (voids, voids, cracks, looseness, and water abundance) are generated. Analysis of the B-Scan radar images of various defects (voids, voids, cracks, looseness, and water abundance) determines the reinforcing effect of high dielectric constant material layers and identifies optimal locations and thicknesses where the dielectric properties of the material-reinforced reflective layer can improve the ground-penetrating radar reflection signal and achieve better results.

[0079] The influence of the location and thickness of the material-enhanced reflective layer on the ground-penetrating radar B-scan images of different roadbed defects was analyzed. From Figures 5(a), 5(b), 5(c), and 5(d), we can see that:

[0080] Based on (a2)-(a3), (b2)-(b3), (c2)-(c3), and (d2)-(d3), it can be seen that controlling the thickness of the material-reinforced reflective layer (11.4cm) and changing its position (bottom of the subgrade vs. bottom of the base course) results in more distinct waveforms in (a2), (b2), (c2), and (d2), with clearer lines, sharper edges, and better continuity without breaks or blurring. In (a3), (b3), (c3), and (d3), the waveforms tend to blend with the background, resulting in jagged edges and reduced visibility in localized areas. This demonstrates that the dielectric properties of the high-dielectric-constant structural layer improve the reflected signal of ground-penetrating radar, and that placing it at the bottom of the base course (below and close to the disease) yields better results.

[0081] Based on (a3)-(a5), (b3)-(b5), (c3)-(c5), and (d3)-(d5), it can be seen that placing the material-reinforced reflective layer at the bottom of the substrate and changing its thickness (11.4cm, 21.5cm, 31.6cm) reveals the following: In (a3), (b3), (c3), and (d3), the waveform curves are thin, with a small lateral coverage and limited longitudinal amplitude. In (a4), (b4), (c4), and (d4), the waveform curves are thicker, with larger amplitudes, expanded lateral coverage, and are more visually striking, with improved surface smoothness and edge clarity compared to the thinner structural layer. In (a5), (b5), (c5), and (d5), the waveform curves are the thickest and have the greatest edge clarity, the widest lateral coverage, and are the most visually striking. Therefore, placing it at the bottom of the substrate (below and close to the disease) and increasing its thickness yields better results.

[0082] Comparative analysis of ground-penetrating radar B-scan images of various roadbed defects revealed that placing a material-enhanced reflective layer below the defect can improve the detection accuracy of roadbed defects. Figure 4 The effect is poor when placed above the disease (Figure 5 shows an enhanced effect when placed below the disease), and the thicker the structural layer and the closer it is to the disease, the clearer the image. Radar image analysis shows that the dielectric properties of the material-enhanced reflective layer improve the reflected signal of the ground-penetrating radar, which can enhance the feature representation of B-Scan radar images of different roadbed diseases.

[0083] ① When focusing on road surface defects, placing the material-reinforced reflective layer at the bottom of the base layer with a thickness of 31.6cm will yield better results;

[0084] ② When focusing on subgrade defects, placing the material-reinforced reflective layer at the bottom of the subgrade with a thickness of 31.6cm will yield better results.

[0085] Considering the different detection depths of antennas at different frequencies and the different roadbed heights of different roads, the recommended locations and thicknesses of the material-enhanced reflective layer are shown in Tables 3(a) and 3(b) below:

[0086] Table 3 (a) Recommended location and thickness of material-reinforced reflective layer

[0087]

[0088] Table 3(b) Recommended location and thickness of material-reinforced reflective layer

[0089]

[0090] Analysis and comparison of waveform characteristics of images with different moisture contents and compaction degrees

[0091] Adjust the subgrade moisture content (w) to 5%-25% and compaction degree to 65%-75%. Specifically, the standard for subgrade moisture content is: dry flexible subgrade <8%, wet flexible subgrade >12%, and saturated flexible subgrade >16%. (The last sentence refers to the wet subgrade moisture content.) It is the mass of water in the roadbed material. With the total mass of the roadbed The ratio:

[0092] ;

[0093] set up: , These represent the density and total volume of the roadbed, respectively. , These are the density and volume of water, respectively. , These represent the density and volume of the solid portion, respectively. , These represent the density and volume of air, respectively. Considering that the mass of air in the roadbed material is much smaller than the mass of solid particles and the mass of water, it can be ignored.

[0094] ;

[0095] Pick :

[0096] ;

[0097] Let the volume fraction of solid particles be... =1 The volume fraction of water is ,because , Therefore, the wet substrate moisture content of the roadbed It can be written as:

[0098] ;

[0099] Dry density of solid particles during construction It has been determined. Sem et al. gave the dielectric constant and minimum water volume fraction θ of saturated water sand (500 MHz) and saturated water glass microspheres (1.1 GHz) in 1981. w,min The relationship is:

[0100] ;

[0101] In the formula, ε, ε w ε s Let θ represent the dielectric constants of the subgrade medium, the aqueous medium, and the solid particles, respectively. The subgrade medium of highways is generally compacted, and air volume is not considered. The water volume fraction θ of the subgrade medium is... w Approaching its minimum water volume fraction θ w,min Therefore, we take θ. w ≈θ w,min Therefore, the water content of the roadbed ω(H2O) is:

[0102] ;

[0103] Since ε is known w =81, after the subgrade moisture content is determined and the aggregate materials are selected. and ε s Since the dielectric constant ε of the subgrade is known, the water content ω(H2O) of the subgrade can be determined by forward modeling (control parameters). The dielectric constants of subgrades with different water contents are shown in Table 4.

[0104] Table 4. Dielectric constants of roadbeds with different moisture contents

[0105]

[0106] From the data in Table 4, it can be analyzed that the dielectric constant of the roadbed increases linearly with increasing moisture content. The fitted graph is shown below. Figure 3 The fitting formula is:

[0107] ;

[0108] Furthermore, the dielectric constant is simultaneously regulated by both moisture content and compaction degree. These two factors work together by altering the ratio of the three phases (solid, liquid, and gas) in the soil. According to existing research, the dielectric constant increases with increasing compaction degree. The relationship between compaction degree (%) and dielectric constant is as follows:

[0109] ;

[0110] The compaction degrees were set to 65%, 70%, and 75%, and their dielectric constants were 14.2, 16.1, and 18.1, respectively. The dielectric constants of the roadbeds with different compaction degrees are shown in Table 5.

[0111] Table 5. Dielectric constants of subgrades with different compaction degrees

[0112]

[0113] A forward modeling simulation of a highway subgrade reinforced with a material-enhanced reflective layer was used to generate multiple sets of A-Scan signal waves and B-Scan radar images. The changes in B-Scan images and A-Scan signal amplitudes of subgrades with different moisture contents and compaction degrees were analyzed.

[0114] Based on the parameters in Tables 1, 2, and 4, the subgrade moisture content was controlled by adjusting the model dielectric constant. Forward modeling was performed using the FDTD principle to generate A-Scan signal waves and B-Scan radar images. The enhanced images were clearly visible. The A-Scan signal amplitude and B-Scan radar images of subgrades with different moisture contents were analyzed. Figure 6 It can be known that:

[0115] Figure 6 In the middle (a), the roadbed is dry and flexible. The reflected waves in the B-Scan image are strong and concentrated, and the surface reflection is obvious. Figure 6 In the middle (b), the roadbed is wet and flexible, and the intensity of the B-Scan reflected wave is reduced and the distribution is more uniform. Figure 6 In the middle (c), the roadbed is saturated and flexible. The reflected waves are enhanced again, but the distribution is more dispersed.

[0116] The changes in B-Scan images due to differences in water content are shown in Table 6.

[0117] Table 6. Changes in B-Scan images of roadbeds with different moisture contents

[0118]

[0119] Depend on Figure 7 It can be known that: Figure 7 In the middle (a), the roadbed is dry and flexible, with a high A-Scan amplitude, a significant first peak, and a slow decay. Figure 7 In the middle (b), the roadbed is wet and flexible, the amplitude is lower than that in the dry state, the peak value of the first wave is weakened, and the attenuation is accelerated. Figure 7 In the middle (c) segment, the saturated flexible subgrade exhibits a further decrease in amplitude, with the smallest initial peak value, and the waveform broadens and decays most rapidly. A-Scan amplitude can serve as an indirect indicator of subgrade moisture content; a sudden drop in amplitude may indicate saturation risk, requiring comprehensive judgment in conjunction with other detection methods. Table 7 shows the changes in A-Scan signals due to differences in moisture content.

[0120] Table 7. A-Scan signal variations in roadbeds with different moisture contents

[0121]

[0122] Based on the parameters in Tables 1, 2, and 5, a forward modeling simulation of the highway subgrade enhanced with a material-enhanced reflective layer was performed. The subgrade compaction degree was controlled by adjusting the model's dielectric constant. Forward simulation was conducted using the FDTD principle to generate B-Scan radar images. The enhanced images were clearly visible. Analysis of B-Scan radar images of subgrades with different compaction degrees was conducted. Figure 8 It can be known that: Figure 8 In the middle (a), the roadbed has a compaction degree of 65%. The reflected signals in the B-Scan image are scattered and messy, indicating that the material has many internal voids and a loose structure. Figure 8 In the middle (b), the roadbed has a compaction degree of 70%. The reflected signal intensity in the B-Scan image is moderate, and the difference between the deep and shallow layers is reduced, indicating that the material density tends to be uniform. Figure 8 In the middle (c) with a compaction degree of 75%, the deep reflection intensity is close to that of the shallow layer, indicating low energy attenuation and high overall material density with few voids. This proves that higher compaction degree leads to greater material density, faster wave propagation speed, clearer stratification, and reduced signal attenuation. The changes in B-Scan images due to differences in compaction degree are shown in Table 8.

[0123] Table 8. Changes in B-Scan images of subgrades with different compaction degrees.

[0124]

[0125] Depend on Figure 9 It can be known that: Figure 9 In the middle (a), the roadbed has a compaction degree of 75%. The A-Scan amplitude is relatively high, the first peak is obvious, and the decay is slow. Figure 9 In the middle (b) with 70% compaction, the amplitude decreases, the first wave peak weakens, and the decay accelerates. Figure 9 In the middle (c) region, the compaction degree is 65%, the amplitude is further reduced, the initial peak value is the smallest, the waveform is broadened, and the decay is the fastest. The A-Scan amplitude can be used as an indirect indicator of the compaction degree of the roadbed. A sudden drop in amplitude may indicate the risk of saturation and needs to be judged in conjunction with other detection methods.

[0126] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0127] 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 roadbed design method containing a material-reinforced reflective layer, characterized in that, Includes the following steps: Step 1: Conduct preliminary design of the roadbed containing the material-reinforced reflective layer to obtain a multi-layer road media model. The multi-layer road media model includes a first structure and a second structure, wherein: the first structure includes, from top to bottom, a surface layer, a base layer, a material-reinforced reflective layer, a subgrade, and an embankment; the second structure includes, from top to bottom, a surface layer, a base layer, a subgrade, a material-reinforced reflective layer, and an embankment; set the electromagnetic parameters of the media. Step 2: Determine an initial optimal thickness range for the material-enhanced reflective layer for both the first and second structures in Step 1. Step 3: After adjusting the thickness of the material-enhanced reflective layer, obtain A-Scan signal waves and B-Scan radar images of the first and second structures; Step 4: Analyze the A-Scan signal waves and B-Scan radar images of the first and second structures to output the optimal roadbed location and thickness of the material-enhanced reflective layer.

2. The roadbed design method containing a material-reinforced reflective layer according to claim 1, characterized in that, It also includes the dielectric constant of the roadbed. With moisture content The changing relationship is as follows: 。 3. The roadbed design method containing a material-reinforced reflective layer according to claim 1, characterized in that, It also includes the dielectric constant of the roadbed. With compaction degree The changing relationship is as follows: 。 4. A roadbed design method containing a material-reinforced reflective layer according to any one of claims 1-3, characterized in that, The relative permittivity of the material-enhanced reflective layer is 30~50.

5. A roadbed design method containing a material-reinforced reflective layer according to claim 4, characterized in that, The material-enhanced reflective layer is a steel slag-containing structural layer and / or a titanium-containing blast furnace slag structural layer.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the roadbed design method containing a material-reinforced reflective layer as described in any one of claims 1-5.

7. An electronic device, characterized in that, include: processor; and memory for storing the executable instructions of the processor; The processor is configured to execute the roadbed design method containing a material-reinforced reflective layer as described in any one of claims 1-5 by executing the executable instructions.

Images