The stress–strain analysis of the entire construction process of underground diaphragm wall based on self-sensing FRP bar monitoring

Abstract

The diaphragm wall, as a key supporting structure in bridge anchorage projects, faces complex and variable stress conditions during construction. Therefore, ensuring structural safety and performance monitoring is crucial. Traditional rebar monitoring methods, due to poor corrosion resistance, insufficient real-time capabilities, and maintenance difficulties, cannot meet the high precision and reliability requirements of modern underground engineering. This study applies self-sensing technology to fiber-reinforced polymer (FRP) materials by embedding optical fiber sensors within the FRP, enhancing real-time monitoring of stress and strain during the construction of diaphragm walls. This technology has been successfully implemented in the Shiziyang Bridge project, enabling real-time monitoring of stress and strain in the anchor diaphragm wall. The study adopts a quasi-distributed optical fiber monitoring scheme, combined with wireless transmission and a cloud platform for remote data acquisition and analysis. The results indicate that the self-sensing FRP bar shows excellent stress and strain monitoring capabilities at various stages of diaphragm wall construction. In stages 1–3, the stress curve transitions from tensile stress to alternating tensile and compressive stress. The shallow and mid-layers exhibit tensile stress, while the deep layers experience compressive stress. The maximum tensile stress recorded is 35.8 MPa, and the maximum compressive stress is -20.3 MPa, mainly due to pressure imbalance caused by soil excavation and the decreasing groundwater level. In stage 4, the upper stress gradually decreases, while the lower stress transitions from tensile to compressive, with the maximum tensile stress at 13.9 MPa and the maximum compressive stress at − 37.7 MPa. These changes are attributed to the completion of the liner and bottom slab construction, backfilling of the soil, and the increased self-weight of the upper structure. In stage 5, as construction progresses, the stress curve forms an M-shape, with compressive stress gradually decreasing. The maximum tensile stress is 2.3 MPa, and the maximum compressive stress is − 11.8 MPa, mainly influenced by the increasing tensile force applied by the stay cables. As of November 14, 2024, the monitoring data show that the tensile strain in the shallow layers remains unchanged, while the compressive strain in the middle and deep layers is gradually decreasing.

Introduction

Underground diaphragm walls have been extensively employed as essential retaining and waterproofing structures in deep excavations, such as bridge anchorages, metro stations, and large underground commercial complexes, owing to their outstanding impermeability, structural integrity, and adaptability to complex construction conditions^1–3. However, during practical construction, the diaphragm walls frequently experience intricate stress variations induced by alternating processes such as excavation, bracing installation, and backfilling, resulting in complex stress–strain interactions between the wall structures and surrounding soil^4–6. These interactions exhibit pronounced nonlinear and time-dependent characteristics, posing significant challenges for structural safety evaluation and construction management⁷.

Currently, the monitoring techniques for diaphragm walls primarily include point-based sensing devices (e.g., inclinometers, strain gauges, accelerometers) and discretely distributed fiber-optic sensors^8–11. Nevertheless, these conventional methods commonly suffer from limitations such as poor real-time responsiveness, inadequate coverage in deep layers, restricted signal stability, and weak resistance to external interference^12–17. Particularly, these methods struggle to achieve continuous, full-scale, and all-weather monitoring of the dynamic evolution of stress–strain states in the deep portions of walls interacting with heterogeneous soil, significantly impeding effective structural diagnosis and proactive risk-warning mechanisms¹⁸.

In recent years, advances in intelligent sensing and self-sensing materials have provided innovative solutions for addressing these limitations. Among these, Fiber-Reinforced Polymer (FRP) composites, characterized by excellent corrosion resistance, high strength-to-weight ratios, and superior compatibility with concrete, have emerged as ideal substrates for embedded sensing systems^19–21. Embedded with miniature sensing units, self-sensing FRP bars enable real-time monitoring of multiple physical parameters, including stress, strain, and temperature, without compromising structural load-bearing performance^22–24. These FRP-based sensing systems offer distributed monitoring capabilities, automated data acquisition, and remote transmission features, providing a promising alternative for comprehensive diaphragm wall monitoring^25–30.

Compared to traditional surface-attached or shallowly embedded sensors, anchor-type FRP sensing bars provide continuous, in-depth monitoring across various depths within the diaphragm wall, effectively minimizing external disturbances and significantly improving monitoring accuracy and system reliability^25,31. Additionally, the dual functionality of FRP bars in load-bearing and sensing eliminates the need for extra structural modifications, simplifying the installation process and enhancing practical field adaptability^32–34.

For monitoring stress and strain along anchors or bolts, fiber Bragg grating (FBG) arrays or quasi-distributed FBG systems are preferable when sub-meter spatial resolution is required, whereas Brillouin scattering–based distributed fiber-optic sensing (DFOS) is more suitable for long-term monitoring where meter-level resolution suffices³⁵. Embedded FBGs, introduced during pultrusion or consolidation, can maintain the structural integrity of FRP anchors while providing stable and reliable stress measurements. Although surface-mounted or grooved FBGs are feasible, the groove geometry and adhesive selection must be carefully optimized to avoid strength degradation³⁶. In FRP anchors, the pull-out behavior is primarily governed by interfacial shear at the FRP–grout or grout–soil interface rather than by tensile rupture of the bar, and a critical bond length exists beyond which additional bonding offers negligible improvement in load capacity³⁷. The interpretation of strain profiles should account for local effects—particularly near anchor plates or exposed ends—since they may distort axial force readings under low loads. Experimental studies have emphasized the importance of grout quality, bar geometry, and interfacial shear properties in defining the minimum bond length, while current design guidelines remain limited and often rely on pull-out testing and field monitoring data to validate anchorage performance³⁸.

Considering the existing challenges in diaphragm wall monitoring, particularly the inadequate capture of deep structural responses, data acquisition delays, and ineffective early-warning mechanisms, there is an urgent need to develop intelligent monitoring systems featuring high spatial coverage, robust environmental adaptability, and precise sensing capabilities³⁹.

Addressing these needs, this study proposes and develops an integrated monitoring system based on self-sensing FRP bars for capturing the full-process stress–strain evolution of diaphragm walls during bridge anchorage construction. This system, combining embedded smart FRP bars with anchor-type distributed deployment strategies, aims to realize high-precision, distributed, and continuous monitoring across all construction phases. This comprehensive monitoring provides reliable foundational data for structural health assessment and safety early-warning systems.

Specifically, this research focuses on:

1. Adaptability and long-term stability of the self-sensing mechanism of FRP bars in underground diaphragm wall applications.

2. Monitoring and data-driven modeling of the full-process dynamic stress–strain response.

This research not only provides theoretical insights and practical experience for intelligent diaphragm wall monitoring but also significantly enhances structural safety management and risk assessment of critical infrastructure such as bridge anchorages, demonstrating substantial potential for wide engineering application and future advancement.

Embedded fiber optic self-sensing FRP bar

Working principle of self-sensing FRP bar

Self-sensing FRP Bar combines fiber optic sensing technology with fiber-reinforced composite materials. Its sensing capability is based on the fiber optic sensors embedded within the FRP material. When light waves traveling through the optical fiber meet the Bragg condition, they are reflected back. The change in the wavelength of the reflected light, due to variations in strain or stress within the material, provides information about the structural behavior and deformation of the reinforcement.

1

In the equation, λ_B represents the Bragg grating wavelength, n is the effective refractive index of the fiber core mode, and Λ is the grating period.

When the temperature, stress, strain, or other physical quantities in the environment of the optical fiber grating change, the grating period or the refractive index of the fiber core will also change. This results in a shift in the wavelength of the reflected light. By measuring the change in the reflected light wavelength before and after the physical quantity variation, the change in the measured physical quantity can be obtained, as shown in Fig. 1.The physical specimen is shown in Fig. 2.

Fig. 1.

Schematic diagram of the basic principle of self-sensing FRP bar.

Fig. 2.

Schematic diagram of the self-sensing FRP bar.

Based on the above basic principles, Eq. (1) can be expanded into the formulas related to the strain and temperature variations of the self-sensing FRP Bar, as shown in Eqs. (2) and (3).

2

3

In the equation, ε represents the total strain of the optical fiber; ε_L is the strain caused by applied force; ε_T is the strain caused by temperature changes; K_L is the sensitivity coefficient of the optical fiber grating to applied force; K_T is the sensitivity coefficient of the optical fiber grating to temperature; Δ_λL is the wavelength shift due to applied force; and Δ_λT is the wavelength shift due to temperature changes.

After conducting repeated experiments and neglecting the wavelength variation caused by temperature, the stress sensitivity coefficient of the self-sensing FRP bar is determined as KL = 1000/1.2 K_L = 1000/1.2 KL = 1000/1.2. Consequently, Eq. (3) can be simplified to Eq. (4):

4

Performance testing of self-sensing FRP bar

The self-sensing FRP bars used in this study were made of GFRP (Glass Fiber Reinforced Polymer), and the tensile properties of the Self-sensing FRP bars were tested. The tensile mechanical property tests were conducted using a 1000 kN universal testing machine. During the test, a displacement gauge was placed on the free segment of the Self-sensing FRP bars to measure the deformation of the specimen under loading. The loading rate was set at 6 mm/min. Axial displacement and strain measured by the extensometer were transmitted to a computer through a data acquisition system for recording. The test results indicated that the tensile strength of Self-sensing FRP bars was 798.7 MPa, the elastic modulus was 50.5 GPa, and the ultimate strain was 1.8%. The specific data are shown in Table 1.

Table 1.

Mechanical properties of self-sensing FRP bars.

Specimen number	Tensile strength (MPa)	Elastic modulus (GPa)	Elongation (%)	Diameter of the self-sensing FRP Bar (mm)	Diameter of the distributed fiber optic sensing fiber (mm)
1	798.7	50.5	1.8	50	3
2	796.8	50.4	1.8	50	3

To verify the stability of the fiber optic sensor combined with FRP materials, repeatability and linearity tests were conducted to confirm the range and accuracy of the sensitive element. The results indicate that the self-sensing FRP bar can simultaneously monitor both stress and performance, with the sensitive element and structure working in synergy to detect stress–strain fluctuations. Furthermore, the performance of the self-sensing FRP bar is stable, with a linear repeatability of 99% and a repeatability error of less than 0.6%. This demonstrates that the self-sensing FRP bar can maintain high-precision continuous monitoring, with measurement errors not exceeding 1% in multiple tests. The stability is confirmed to be 0.5% F.S. ± 2 μɛ. The results of the repeatability and linearity tests are shown in Figs. 3 and 4, with measurement accuracy details presented in Table 2.

Fig. 3.

Repeatability test curve of self-sensing FRP bar.

Fig. 4.

Linearity test curve of self-sensing FRP bar

Table 2.

Sensing performance requirements of self-sensing FRP bar.

Performance indicator	Parameter value
Measurement range	≥ 10000με
Wavelength range	1510 ~ 1590nm
Resolution	1με
Hysteresis	≤ 3%
Repeatability error	≤ 1%
Linearity error	≤ 1%
Total accuracy	≥ 0.5% F.S

Corrosion resistance and durability testing of self-sensing FRP bar

To accurately simulate the corrosion environment experienced by GFRP bars embedded in concrete, accelerated durability tests were performed following the recommendations of the ACI 440.3R-04 standard. This guideline specifies a standardized procedure for evaluating the long-term durability of FRP materials in concrete environments by immersing specimens in an alkaline solution maintained at 60°C, which effectively replicates the highly alkaline pore solution of concrete. According to the studies conducted by Dejke V and Porter M L et al., immersion tests at a temperature of (60 ± 1) °C with durations of 3.65, 18, 36.5, 92, and 183 days correspond approximately to natural exposure periods of 1, 5, 10, 25, and 50 years, respectively^40,41. This accelerated approach enables the evaluation of material degradation and performance retention within a shortened experimental timeframe, providing an effective means to assess the long-term corrosion resistance and durability of GFRP bars under simulated concrete environments.

An alkaline solution with a pH of 13.6 was prepared to simulate the pore solution generated during the hydration process of concrete, and its mixing composition is listed in Table 3.

Table 3.

Composition of Simulated Alkaline Solution (pH = 13.6).

Ca(OH)2	KOH	NaOH	NaCl	CaCl2	KCl	pH
118.5	4.2	0.9	27.96	1.18	0.36	12.6 ~ 13.6

Four experimental variables were considered in this study, namely the specimen diameter (10, 12, 16, and 25 mm), exposure environment, temperature (room temperature and 60 °C), and exposure duration (0, 4, 18, 37, 92, and 183 days). After 183 days of immersion in saline solution at an elevated temperature of 60 °C, the appearance changes of the GFRP bars were observed, as shown in Fig. 5.

Fig. 5.

Appearance changes of GFRP bars after immersion.

During the construction process, no prestress was applied to either the reinforcement or the Self-sensing FRP Bars embedded in the diaphragm wall; therefore, the initial stress level of the Self-sensing FRP Bars was considered to be 0%. According to the field monitoring data, the stress variation was relatively small. To evaluate the accuracy of the results under the most unfavorable conditions, a stress level of 40%, a temperature of 60 °C, and a diameter of 10 mm were selected for the Self-sensing FRP Bar specimens, and the data after 37 days of immersion were analyzed. The results indicated that the elastic modulus decreased from the initial 54.14 GPa to 52.86 GPa, and the tensile strength dropped from 848.997 MPa to 683.348 MPa. This represents a reduction of approximately 2.3% in elastic modulus and 19.5% in tensile strength, corresponding to an equivalent service period of about 10 years under adverse conditions of 60 °C and pH 13.6. The detailed tensile mechanical properties of GFRP bars after immersion in saline–alkaline solution are summarized in Tables 4 and 5.Therefore, it is concluded that the Self-sensing FRP Bar can maintain stable performance and reliable monitoring capability over a service period of up to 10 years.

Table 4.

Tensile elastic modulus of GFRP bars after immersion (Mean values/GPa).

(a)		0% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	55.10	52.61	50.06	50.70	50.89
	12 mm	52.99	55.53	52.97	55.53	53.07
	16 mm	55.64	55.39	56.37	55.10	58.55
	25 mm	54.10	50.66	56.88	54.9	55.93
60 °C	10 mm	53.12	54.27	52.61	53.25	53.82
	12 mm	50.44	52.21	51.32	54.69	56.90
	16 mm	55.54	55.54	55.88	57.11	55.61
	25 mm	55.79	54.54	54.03	55.15	55.61

(b)		40% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	49.36	50.13	52.87	51.40	50.00
	12 mm	54.65	54.25	53.54	52.08	54.47
	16 mm	54.66	54.81	54.66	53.92	58.80
	25 mm	54.29	48.61	49.84	53.82	54.08
60 °C	10 mm	54.14	54.77	52.86	50.83	50.02
	12 mm	52.92	53.54	53.54	53.01	53.21
	16 mm	50.07	55.64	54.43	56.37	55.01
	25 mm	53.11	53.77	51.68	51.58	51.35

(c)		80% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	52.74	49.75	52.10	49.3	51.08
	12 mm	54.96	54.38	54.56	53.1	55.30
	16 mm	56.74	55.39	56.4	53.68	55.20
	25 mm	54.03	54.91	54.82	56.07	54.51
60 °C	10 mm	53.03	50.96	50.32	53.50	50.10
	12 mm	55.62	55.04	53.10	52.83	52.01
	16 mm	55.64	56.86	56.13	58.83	55.06
	25 mm	53.67	53.17	55.86	55.56	54.14

Table 5.

Tensile strength of GFRP bars after immersion (Mean values / MPa).

(a)		0% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	805.961	841.867	742.045	819.712	775.658
	12 mm	833.177	808.154	808.066	822.92	735.296
	16 mm	834.818	857.299	859.238	846.158	792.791
	25 mm	751.436	743.797	723.384	737.624	709.857
60 °C	10 mm	813.473	759.361	600.97	465.497	451.746
	12 mm	797.102	805.148	596.213	489.932	429.011
	16 mm	864.361	805.225	743.006	601.009	518.696
	25 mm	719.778	692.5	668.034	629.327	542.706

(b)		40% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	814.365	781.897	744.718	795.011	785.462
	12 mm	860.941	878.624	748.913	860.233	809.569
	16 mm	914.893	836.36	849.938	845.213	796.472
	25 mm	746.343	726.073	705.905	724.362	694.334
60 °C	10 mm	848.997	721.8	683.348	462.95	407.437
	12 mm	800.285	836.89	702.316	482.594	415.572
	16 mm	870.777	809.602	703.465	597.926	522.228
	25 mm	730.575	684.576	638.902	542.38	452.255

(c)		80% Stress level
		4d	18d	37d	92d	183d
21 °C	10 mm	791.701	748.92	709.195	686.277	699.391
	12 mm	783.839	824.954	810.453	603.286	606.735
	16 mm	865.306	830.193	838.051	781.103	747.482
	25 mm	741.495	717.456	705.375	697.512	643.343
60 °C	10 mm	785.207	433.156	430.228	462.568	407.437
	12 mm	836.979	716.242	513.452	565.531	450.939
	16 mm	799.456	714.557	666.362	580.717	507.307
	25 mm	718.841	709.287	655.892	591.15	521.519

GFRP exhibits excellent corrosion resistance and durability because it is composed of chemically inert polymer resins and chemically resistant glass fibers. The two components form a dense interfacial structure that effectively prevents the ingress of water, ions, and other corrosive agents. In addition, GFRP contains no metallic constituents and is thus immune to electrochemical corrosion, enabling it to maintain stable mechanical performance over long periods even under harsh conditions such as acidic, alkaline, saline, or marine environments.

Production process of self-sensing FRP bar

The self-sensing FRP Bar is produced by embedding an optical fiber sensor into the FRP material during the pultrusion process of glass fiber reinforced polymer (GFRP). The GFRP material encapsulates and protects the optical fiber sensor, resulting in a self-sensing FRP Bar with an embedded optical fiber sensor. The production process is shown in Fig. 6. The fiber Bragg grating sensor is integrated and formed, as shown in Fig. 7.

Fig. 6.

Production process of self-sensing FRP bar.

Fig. 7.

Self-sensing FRP bar.

The self-sensing FRP Bar fundamentally addresses the drawbacks of traditional externally attached sensors, such as low monitoring accuracy, high cost, susceptibility to damage, and poor durability. In addition to providing reinforcement for linings, it enables long-term monitoring of the stress state of the linings. By achieving complete coupling between the optical fiber and the monitored object, the self-sensing FRP Bar fully inherits the excellent sensing properties of optical fiber sensors, significantly enhancing the accuracy and durability of sensor performance. Furthermore, the self-sensing FRP Bar can be installed directly into the reinforcement mesh along with steel bars during construction, eliminating the need for additional construction steps. Compared to traditional monitoring methods that require secondary manual intervention, it greatly reduces labor and time costs. The self-sensing FRP Bar measurement system consists of a power supply, a demodulator, optical fiber jumpers, cables, the self-sensing FRP Bar, and a data acquisition unit, as shown in Fig. 8.

Fig. 8.

Measurement system of self-sensing FRP bar with embedded optical fiber.

Design, installation, and application of the intelligent monitoring system for diaphragm walls

Design and installation of the intelligent monitoring system for diaphragm walls

A quasi-distributed optical fiber measurement scheme is adopted, in which multiple fiber Bragg grating (FBG) sensing points are distributed along a single transmission line according to design requirements, forming a multi-point self-sensing FRP Bar with embedded quasi-distributed FBG arrays. By inscribing seven FBGs at equal intervals on a single optical fiber, localized distributed monitoring can be achieved, as shown in Fig. 9. High-precision monitoring at different depths of the diaphragm wall enables an accurate assessment of the overall stress state of the structure.

Fig. 9.

Distribution of grating measurement points.

To prevent slippage caused by insufficient bonding strength between the self-sensing FRP Bar and the concrete, the reinforcement is secured to the inner side of the diaphragm wall’s reinforcement cage using clamping straps. After binding, the reinforcement cage is hoisted into position. Two 40-m-long self-sensing FRP Bars are installed in each panel of the diaphragm wall reinforcement cage, as illustrated in Fig. 10.

Fig. 10.

On-site installation of self-sensing FRP bar.

Temperature variations can affect the data from fiber Bragg grating (FBG) sensors, which may lead to inaccurate measurements during diaphragm wall monitoring. Therefore, it is necessary to eliminate the influence of temperature effects. Before performing effective measurements, the system must remain static for a period of time until the temperature of the diaphragm wall and the self-sensing FRP Bar stabilizes. The measurements taken at this stage represent the true values, free from temperature interference.

After determining the monitoring locations, the self-sensing FRP Bar, FBG demodulator, and cloud-based data acquisition system are sequentially installed to enable remote collection and analysis of monitoring data for the diaphragm wall. Considering that the diaphragm wall is a concealed underground structure, wireless transmission equipment is placed outside the anchorage for convenient data transmission. The layout of the monitoring system is shown in Fig. 11, and the detailed structure of the anchorage and diaphragm wall is illustrated in Fig. 12.

Fig. 11.

Schematic diagram of diaphragm wall monitoring.

Fig. 12.

Schematic diagram of anchorage and diaphragm wall.

The construction process of the intelligent monitoring system for diaphragm walls is illustrated in Fig. 13. After completing the reinforcement cage assembly, the self-sensing FRP Bar is tied to the reinforcement mesh and cast into the diaphragm wall together with the concrete. Upon completion of the diaphragm wall construction, the self-sensing FRP Bar is connected to the data acquisition equipment, enabling real-time monitoring and safety analysis of the diaphragm wall. Given that the self-sensing FRP Bar possesses sensing capabilities, special care must be taken to protect the sensing elements and connecting optical cables during the concrete pouring and vibrating processes to prevent potential damage caused by construction operations.

Fig. 13.

Installation flowchart of the intelligent monitoring system.

Application of intelligent monitoring

The Shiziyang Cross-River Passage is located in the core area of the Pearl River Estuary, connecting the eastern and western regions of Guangdong Province, with a total length of approximately 34.9 km. Its anchorage foundation adopts a circular diaphragm wall structure, featuring a wall thickness of 1.5 m, an outer diameter of 130 m, a foundation depth of 36 m, a top elevation of + 4.0 m, and a bottom elevation of − 32 m. The foundation embeds 8 m into the rock layer, with moderately weathered argillaceous sandstone serving as the bearing stratum. The anchorage dimensions are 110.6 m in length, 95.5 m in width, and 44.2 m in height. Given that the construction site is a coastal water-rich area and the anchorage is below the groundwater table, monitoring the deformation and stress changes of the diaphragm wall during anchorage excavation is critically important.

At the CX7 location of the diaphragm wall, one self-sensing FRP Bar was installed. Along its depth, the reinforcement was equipped with seven fiber Bragg grating (FBG) sensing points spaced 6–7 m apart, forming an FBG array spanning 40 m, as shown in Fig. 7. This setup allows for high-precision monitoring of the diaphragm wall in this region. After the self-sensing FRP Bar was installed, it was secured to the reinforcement cage using clamping straps to prevent detachment during concrete pouring. This also ensures better cooperative deformation among the self-sensing FRP Bar, concrete, and steel reinforcement, as illustrated in Fig. 12. To enable subsequent monitoring, the optical fiber jumper of the self-sensing FRP Bar should be led out before concrete pouring and protected using PVC tubing to avoid fiber damage during later construction, as shown in Fig. 14.

Fig. 14.

Optical fiber jumper protection device for self-sensing FRP bar.

The wireless transmission and data acquisition system for diaphragm wall monitoring is shown in Fig. 15. The self-sensing FRP Bar is connected to a fiber Bragg grating (FBG) demodulator via optical cables, which is then networked with a 4G router. Remote monitoring software is installed on a computer or mobile terminal, and an external antenna is connected to the router to mitigate signal attenuation caused by the enclosed environment of the control box. This system enables real-time storage and remote monitoring of the embedded fiber optic data within the smart reinforcement. It facilitates timely analysis of the stress state and installation conditions of the diaphragm wall, providing reliable data support for construction safety and quality control.

Fig. 15.

Wireless transmission and data acquisition system.

Intelligent monitoring information management

Based on the intelligent real-time monitoring of the Shiziyang Bridge diaphragm wall, a cloud service platform has been developed. This platform enables the automatic acquisition, storage, processing, and input/output of monitoring data collected by the safety monitoring automation system, as well as other safety-related information. It also provides comprehensive data interfaces for data analysis software, allowing operators to analyze and evaluate the project status using safety monitoring data and related safety information. Furthermore, the platform facilitates the compilation and analysis of safety monitoring records according to monitoring requirements, generating relevant reports and charts to support the safe operation and management of the project.

Currently, the cloud platform offers both web-based and mobile app access, enabling users to conveniently monitor project conditions anytime, anywhere. This paper introduces the mobile app version as an example. The mobile app includes the following key modules: project information, alarm management, enterprise information, monitoring conditions, curve analysis, raw records, and inspection records. Users can monitor and review project conditions in real time.

The alarm management module provides access to the latest alarm data, categorized by color: green indicates normal, yellow indicates a warning, red indicates an alarm, and purple indicates an over-alarm condition. The monitoring conditions module allows users to view the latest monitoring results, and the curve analysis module generates visual curves based on the data. Details are shown in Figs. 16 and 17.

Fig. 16.

Monitoring status interface.

Fig. 17.

Mobile app alarm management interface.

Stress evolution mechanism during diaphragm wall construction

Upon the completion of diaphragm wall construction, the self-sensing FRP Bar provides real-time data on the stress state of the diaphragm wall, enabling safety analysis. In the Shiziyang Bridge project, fiber Bragg gratings (FBGs) embedded in the self-sensing FRP Bar were placed at depths of 1 m, 8 m, 14 m, 20 m, 26 m, 33 m, and 40 m. The strain data from these locations reflect the stress state of the corresponding positions of the FRP Bar. As the self-sensing FRP Bar is securely fixed to the steel bars, both experience cooperative deformation, meaning the strain of the FRP Bar equals the strain of the steel bars. Therefore, the stress of the steel bars can be calculated based on the strain measurements.

The stress data collected during the excavation phase (from August 20, 2023, to November 14, 2024) and during the anchorage upper structure construction phase were plotted in Fig. 18. Blue curves represent stress data from the early stages of construction, while yellow curves correspond to later stages. The color of the stress curves transitions from blue to gray to yellow as construction progresses over time, clearly illustrating the changes in the diaphragm wall’s overall stress state.

Fig. 18.

Full stress variation process of the self-sensing FRP bar.

Based on the monitored stress conditions of the diaphragm wall, the stress mechanism of the FRP Bar was divided into five stages. The cumulative strain recorded on the final day of each stage was plotted in Fig. 19. These figures provide valuable insights into the stress mechanism and long-term stability of the diaphragm wall.

Fig. 19.

Full cumulative strain variation process of the self-sensing FRP bar.

Stress analysis of stages 1–5

Stage 1

The excavation of the diaphragm wall from the 1st to the 2nd layer is defined as the first construction stage. As the construction progresses, especially with the layered excavation of soil, the stress experienced by the diaphragm wall changes significantly. In Stage 1, the wall primarily experiences tensile stress. The reason for this is that, during the initial construction phase, the shallow soil on the inner side of the wall is extensively removed, while the outer side of the wall is subjected to substantial lateral pressure from the surrounding soil. Since less soil is excavated on the inner side, the pressure imbalance between the inner and outer sides of the wall is minimal, and the wall predominantly bears lateral pressure from the outer soil, leading to tensile stress in the self-sensing FRP Bar on the inner side. At this stage, due to the relatively shallow excavation, the wall deformation is small, and the tensile stress is not significant. As shown in Fig. 20, the stress curve during the excavation of the 2nd layer indicates that the stress range of the self-sensing FRP Bar in this stage is approximately 2.7–7.2 MPa.

Fig. 20.

Stress curve during excavation of the 2nd layer in stage 1.

Stage 2

The excavation of the diaphragm wall from the 3rd to the 9th layer is defined as the second construction stage. During this stage, the stress state of the wall is complex, with the outer side primarily experiencing compressive stress and the inner side potentially experiencing tensile stress. The stress curves of the FRP Bar exhibit an alternation of tensile and compressive stresses. This complexity is attributed to several factors: First, as deeper soil layers are excavated, the outer side of the wall continues to experience significant lateral pressure from the remaining soil, while the inner side undergoes a significant reduction in pressure due to soil removal, resulting in a pronounced imbalance between inner and outer pressures. Second, with the hardening of the lining concrete in the upper part of the wall, the diaphragm wall and the lining form an integrated structure, increasing the overall stiffness, self-weight, and resistance to deformation. Third, during the construction process, the groundwater level is maintained at least 1 m below the excavation layer, leading to an increase in the effective stress in the soil on the outer side of the wall, which exerts greater lateral pressure on the wall. Lastly, before the lining concrete reaches the designed strength, support structures are used to ensure the flatness of the concrete within the formwork, which imposes additional pressure on both the formwork and the diaphragm wall. As a result of these combined factors, the stress curves in Stage 2 exhibit a distinct alternation of tensile and compressive stresses. According to the monitoring data from the self-sensing FRP Bar, the maximum compressive stress during the excavation of the 9th layer was recorded as 15 MPa, while the maximum tensile stress during the excavation of the 8th layer reached 35.8 MPa. The specific stress curve is shown in Fig. 21. As the construction progressed, the stress variation of the Self-sensing FRP Bar gradually increased toward tensile stress, as illustrated in Fig. 22.

Fig. 21.

Stress curve during excavation of layers 6–9 in stage 2.

Fig. 22.

Trend of stress variationin in stage 2.

Stage 3

The excavation of the diaphragm wall from the 10th to the 12th layer is defined as the third construction stage. During this stage, the stress curve of the FRP Bar exhibits an M-shape, with the overall stress in the tensile state, as shown in the stress curves for the 10th and 12th layers in Fig. 23. The reasons for this behavior are as follows: First, as the excavation depth increases, the compressive stress on the outer side of the wall continues to rise. Second, as the lining of the diaphragm wall is nearly complete, the overall stiffness of the wall is significantly enhanced. Third, the compression and consolidation of the soil on the outer side of the wall are not yet fully completed, and the further lowering of the groundwater level increases the self-weight of the soil and the lateral pressure on the wall. As a result of these factors, the stress curve of the FRP Bar exhibits an M-shape, with the tensile stress in the middle and upper regions being particularly significant. During the excavation of the 10th layer, the maximum tensile stress reached 29.7 MPa, which is the highest tensile stress in this stage.As the construction progressed, the stress variation of the Self-sensing FRP Bar gradually decreased in the tensile direction, as illustrated in Fig. 24.

Fig. 23.

Stress curves during excavation of layers 10–12 in stage 3.

Fig. 24.

Trend of stress variationin in stage 3.

Stage 4

The construction period of the upper anchor structure of the underground diaphragm wall is defined as Stage 4, which includes the construction of the anchor blocks and anchor piers, with the monitoring period from March to June. During this stage, the stress curve of the self-sensing FRP Bar in the underground diaphragm wall transitioned from predominantly tensile stress on March 1st. The tensile stress in the upper section of the wall gradually decreased, while the tensile stress in the lower section progressively transformed into compressive stress, which increased over time.

The primary reasons for the stress changes in the self-sensing FRP Bar are as follows:

1. The internal lining and base slab of the underground diaphragm wall have been completely constructed. On this foundation, the backfilling of the internal soil was also completed, and the construction of the top slab was successfully finished. As a result, the pressure imbalance between the inner and outer sides of the wall, caused by the absence of soil on the inner side, drastically reduced.

2. The construction of the upper structure was gradually completed, and the self-weight of the upper structure increased significantly, exerting substantial pressure on the underground diaphragm wall.

After the pouring and curing of the upper anchor structure, the stress in the self-sensing FRP Bar reached a relatively stable state. As shown in Fig. 25, the curve on June 14th indicates that the maximum compressive stress measured during this stage was − 37.7 MPa, and the maximum tensile stress was 13.9 MPa. As the construction progressed, the stress variation of the Self-sensing FRP Bar gradually decreased in the tensile direction, with more pronounced changes observed at greater depths. For monitoring points located below 10 m, the tensile stress progressively transitioned to compressive stress during the middle and late stages of construction, and the compressive stress continued to increase thereafter. The detailed evolution of stress variation is illustrated in Fig. 26.

Fig. 25.

Stress curve in stage 4.

Fig. 26.

Trend of stress variationin in stage 4.

Stage 5

Stage 5 refers to the construction phase in which the bridge deck is laid after the connection between the pylon and the anchorage is completed, with the monitoring period spanning from July to November. During this phase, as construction progresses, the overall compressive stress in the diaphragm wall gradually decreases, and the stress curve exhibits an M-shaped distribution, as shown in Fig. 27. The gradual reduction in compressive stress is primarily due to the tensile force exerted on the anchorage by the stay cables on the pylon. Additionally, as the bridge deck construction advances, the tensile force applied by the stay cables increases, further affecting the stress state of the diaphragm wall.

Fig. 27.

Stress curve in stage 5.

At present, the observed variations in the stress curve align well with the construction process. According to the monitoring data from the self-sensing FRP Bar, as of November 14, the maximum compressive stress recorded in this phase is 11.8 MPa, while the maximum tensile stress is 2.3 MPa. These results indicate that the diaphragm wall undergoes significant stress adjustments during the bridge deck installation, and the monitoring system effectively captures these stress variations.As the construction progressed, the stress variation of the Self-sensing FRP Bar gradually shifted from compressive stress toward tensile stress, with the changes being more pronounced at greater depths. The detailed evolution of stress variation is shown in Fig. 28.

Fig. 28.

Trend of stress variationin in stage 5.

Stress increment analysis of stages 1–5

Stages 1–3

This construction phase corresponds to Stages 1, 2, and 3, with stress increments relative to the stress in the second excavation layer illustrated in Fig. 29. In the figure, hollow circles on either side of the box indicate the extreme values of stress increments at specific depths, solid circles represent the mean stress increments at those depths, and diamonds denote the stress increments during the 6th, 8th, 9th, 10th, and 12th excavations compared to the 2nd excavation.

Fig. 29.

Stress increment diagram for stages 1–3.

In the 0–8 m depth range, the stress increment is predominantly positive, indicating that the FRP Bar in the shallow layers is generally in a tensile stress state, with stress steadily increasing. This is primarily due to the removal of soil from the inner side of the wall and the increased effective self-weight stress in the soil behind the wall caused by the lowering of the groundwater level, which increases the lateral pressure on the wall. The calculated mean stress increments are 3.03 MPa at 1 m and 7.3 MPa at 8 m, both of which fall within the confidence interval, demonstrating high reliability.

In the 8–26 m depth range, the stress increment is symmetrically distributed around zero, but the mean value shows an increasing trend, indicating a complex stress environment at this depth. Although the stiffness of the wall is enhanced by the completed inner lining, the effects of external soil pressure and the increased effective self-weight stress due to the lowered groundwater level outweigh the impact of increased wall stiffness. The calculated mean stress increments are − 2.67 MPa at 14 m, 3.3 MPa at 20 m, and 6.76 MPa at 26 m, all of which are within the confidence interval, ensuring high reliability.

In the 26–40 m depth range, the stress increment is predominantly in the compressive stress zone. This is mainly attributed to the diaphragm wall’s bottom being embedded in deeper bedrock, providing significant tensile resistance. The calculated mean stress increments are − 0.33 MPa at 33 m and − 10.63 MPa at 40 m, both of which fall within the 95% confidence interval, indicating high reliability.

Stage 4

The stress increment in the 4th stage refers to the difference between the stress values of the self-sensing FRP tendons in the diaphragm wall from March to June and the stress values measured during the excavation of the 12th layer. As shown in Fig. 24, the overall stress increment at various depths is negative, and the average stress increment at different depths is also negative. This indicates that the tensile stress in the self-sensing FRP tendons gradually decreases, or the compressive stress gradually increases. The absolute value of the stress increment first increases and then decreases, with the maximum stress increment of − 24.53 MPa occurring at a depth of 20 m. The data shown in Fig. 30 generally falls within the 95% confidence interval, confirming that the data meets the error margin requirements and has a high level of reliability.

Fig. 30.

Stress increment curve in the 4th stage.

The changes in stress increment can be attributed to several factors:

1. The continued construction of the upper anchor structure (such as anchor blocks and anchor piers) gradually increases the self-weight stress.

2. The integration of the lining structure with the diaphragm wall forms a unified diaphragm wall structure, which increases the overall stiffness.

3. The completion of the backfilling of the diaphragm wall structure and the formation of a complete anchor diaphragm wall foundation result in a balance of internal and external pressures on the diaphragm wall.

Stage 5

The stress increment in Stage 5 is defined as the difference between the diaphragm wall stress values recorded from July to November and those recorded in June. As shown in Fig. 31, both the stress increment values and their mean values are positive, exhibiting an overall trend of initial decline followed by an increase. The minimum mean stress increment of 1.53 MPa occurs at a depth of 20 m, while the maximum mean stress increment of 12.83 MPa is observed at 40 m. Additionally, Fig. 31 indicates that all stress increment values fall within the 95% confidence interval, confirming that the data meets the required accuracy criteria. These results suggest that the compressive stress on the upper structure of the diaphragm wall is gradually increasing, while the compressive stress on the middle and lower sections is gradually decreasing.

Fig. 31.

Stress increment curve of the 5th stage.

The primary cause of the increasing tensile stress in the upper part of the diaphragm wall and the decreasing compressive stress in the middle and lower sections is the tensile force exerted on the anchorage by the stay cables of the pylon. As the bridge deck construction progresses, the tensile force applied by the stay cables continues to increase, further affecting the stress distribution within the diaphragm wall.

Comparison of stress results between self-sensing FRP bars and strain gauges of 1–4

Stages 1–3

To validate the monitoring effectiveness and accuracy of the GFRP smart reinforcement compared to traditional strain gauges, the monitoring data from strain gauges and self-sensing FRP Bar at the same positions were compared. It was found that the stress curves of the GFRP smart reinforcement and the strain gauges exhibit a similar trend. Taking the construction stages at the 6th and 12th layers as examples, as shown in Figs. 32 and 33, the stress curves of the self-sensing FRP Bar and strain gauges show good synchronization. Although the stress values at some depths of the self-sensing FRP Bar and strain gauges are not identical, the overall stress value ranges are relatively close.

Fig. 32.

Comparison of stress curves for the 6th layer excavation.

Fig. 33.

Comparison of stress curves for the 12th layer excavation.

The reasons for these differences can be attributed to two factors: First, there are inherent differences in the mechanical properties of the two materials (GFRP and steel), which may cause slight discrepancies in the stress values. For instance, strain gauges may be more sensitive to compressive or tensile stresses at certain depths, while the GFRP Bar may exhibit different responses. However, the overall stress trends of both methods remain similar. Second, the monitoring positions of the GFRP smart reinforcement and strain gauges are different. Although the data from both methods were collected on the same day, the different construction locations significantly affect the consistency of the monitoring data.

Overall, the similarity and consistency of the stress curves indicate that both monitoring methods yield accurate data. While material differences cause slight variations in local stress values, and differences in construction locations lead to some discrepancies in the monitoring data, the measurement results from both the GFRP Bar and strain gauges effectively reflect the stress variation trend in the diaphragm wall.

Stage 4

Figure 34 presents the comparison between the monitoring data of self-sensing FRP Bar and strain gauges. It can be observed that the stress variation curve of the self-sensing FRP Bar is continuous and stable. In particular, the stress values at depths ranging from 1 to 40 m on July 14, 2024, exhibit a similar fluctuation trend to that observed on March 1, indicating a consistent pattern in the stress variation of the underground structure. In contrast, strain gauges at certain measurement points (such as 6 m, 13 m, and 28 m) showed data gaps or instability, suggesting that the monitoring data from strain gauges may be influenced by environmental factors or the condition of the equipment. Although there are differences in monitoring precision and stability between the two methods, they maintain a reasonably consistent trend overall, reflecting the stress variation of the diaphragm wall and ensuring the reliability of the monitoring results.

Fig. 34.

Comparison of excavation stress curves in stage 4.

The self-sensing FRP Bar, combined with optical fiber sensing technology, offers higher precision and real-time data acquisition capability, and is less susceptible to environmental factors such as humidity and corrosion. This makes it capable of providing more stable and continuous stress data. On the other hand, strain gauges rely on electrical or mechanical sensing, and their data may be affected by factors such as sensor installation accuracy and measurement location, leading to data loss or fluctuations at certain depths. Nevertheless, the monitoring data from both the self-sensing FRP Bar and strain gauges show a close correlation in their overall trends.

Strain analysis of stages 1–5

Stages 1–3

The vertical cumulative strain of the diaphragm wall during Stages 1, 2, and 3 was plotted as strain curves, as shown in Fig. 35. In Stage 1, the diaphragm wall was entirely within the tensile strain range. As excavation progressed, the strain curve exhibited a linear decline and reached the maximum tensile strain or minimum compressive strain on December 1 during Stage 2. At this point, the maximum compressive strain and minimum tensile strain in the first three construction stages were observed at 1 m and 8 m depths, with values of − 4.16 με and 14.2 με, respectively.

Fig. 35.

Strain curves for stages 1–3.

As construction advanced, the cumulative strain showed a trend of increasing tensile strain or decreasing compressive strain, reaching its peak or inflection point on December 8. At this time, all depths except for 14 m exhibited tensile deformation, while the strain at 14 m indicated compressive deformation. Subsequently, tensile or compressive deformation at different depths further intensified. By the end of the construction stage, the cumulative strains at 1 m, 8 m, 14 m, 20 m, 26 m, 33 m, and 40 m depths were 37.5 με, 90 με, 80.8 με, 88.3 με, 126.7 με, 13.3 με, and − 83.3 με, respectively.

Upon excavating to the 12th layer, only the 40 m depth showed compressive deformation, while the remaining depths exhibited tensile deformation. The main reasons for this phenomenon are as follows: Throughout the entire diaphragm wall construction stage, the deepening excavation and continuous lowering of the groundwater level led to an increase in the effective self-weight stress of the backfill soil behind the wall, thereby increasing the lateral pressure on the outer side of the wall. However, with the inner side soil completely removed, the addition of the inner lining structure alone was insufficient to maintain the pressure balance between the inner and outer sides of the diaphragm wall, resulting in irreversible deformation of the wall.

Stage 4

The vertical cumulative strain of the diaphragm wall in the 4th stage is plotted as a strain curve, as shown in Fig. 36. It is observed that, with the progress of construction, the cumulative strain curve value gradually decreases, indicating that tensile deformation is gradually reduced while compressive deformation increases. The overall extreme values reached in June were 18.3, 25, − 70.8, − 59.2, − 37.5, − 137.5, and − 155 με, respectively.

Fig. 36.

Strain curves for stages 4.

The primary causes of this behavior are:

1. The continuous construction of the anchor block and anchor pier of the upper structure of the anchor body, leading to an increase in self-weight stress.

2. The formation of an integrated diaphragm wall structure due to the completion of the inner lining, resulting in increased stiffness.

3. The backfill soil within the diaphragm wall structure has been completed, forming a complete anchor body diaphragm wall foundation, thereby balancing the internal and external pressures of the diaphragm wall.

Stage 5

The vertical cumulative strain of the diaphragm wall during Stage 5 was plotted as a strain curve, as shown in Fig. 37. The analysis indicates that in the upper 8 m depth range, the cumulative strain remains relatively stable at approximately 10 με. By November, the cumulative strain at this depth was recorded as 11.7 με and 8.33 με, indicating that the tensile deformation of the wall in this region remained largely unchanged.

Fig. 37.

Strain curve of the 5th stage.

In the 8 m to 40 m depth range, as construction progressed, the cumulative strain curve exhibited a trend of gradual reduction in compressive strain, approaching 0 με. By November, the minimum cumulative strain values at this stage were − 42.5 με, − 35 με, 1.67 με, − 95 με, and − 59.2 με.

The gradual reduction in compressive strain in the diaphragm wall is primarily attributed to the tensile force exerted on the anchorage by the stay cables of the pylon. As bridge deck construction advances, the tensile force applied by the stay cables continues to increase, thereby further influencing the strain distribution within the diaphragm wall.

Discussion

When the construction of the anchor block reached the fifth phase, the deformation trend of the diaphragm wall became relatively stable. Therefore, a double exponential smoothing method was applied to train the data from this phase and predict the cumulative deformation trend of the diaphragm wall for the next month. The results indicate that, except for the measurement at 26 m, the cumulative deformation at the other six measurement points tends towards zero. This is primarily due to the combined effects of external tensile forces, the self-weight of the anchor block, soil pressure, and frictional forces. The prediction of future cumulative deformation trends also suggests that the anchor block diaphragm wall structure is gradually stabilizing, and the construction activities in the next month are expected to remain within a safe range. The predicted future cumulative deformation trend is shown in Fig. 38.

Fig. 38.

Predicted future deformation trend of cumulative displacement.

Conclusions

Conclusion

This study, based on the research of self-sensing FRP bars and the full-process monitoring of the underground diaphragm wall, draws the following conclusions:

• i.The Self-sensing FRP Bar exhibited excellent linearity (up to 99%) and repeatability (error < 0.6%), with an overall measurement accuracy better than 0.5% F.S. Under accelerated aging conditions (60 °C, pH = 13.6), the elastic modulus decreased by only 2.3% and the tensile strength by 19.5%, corresponding to an equivalent natural exposure period of approximately 10 years, demonstrating stable durability.
• ii.During Stages 1–3, the maximum tensile stress reached 35.8 MPa in shallow–middle layers, while the deepest layer exhibited a maximum compressive stress of − 20.3 MPa.
• iii.In Stage 4, after the completion of the inner lining and backfilling, compressive stress significantly increased, with a peak value of − 37.7 MPa, and the maximum tensile stress was 13.9 MPa. In Stage 5, due to the increasing tensile force from the stay cables, the maximum compressive stress decreased to − 11.8 MPa, while the maximum tensile stress was 2.3 MPa, forming a clear M-shaped distribution.
• iv.In Stages 1–3, cumulative tensile strain in shallow layers increased significantly (e.g., 90 με at 8 m), while cumulative compressive strain in the deep layer reached − 83.3 με.
• v.In Stage 4, cumulative compressive strain intensified, reaching − 137.5 to − 155 με at depths of 33–40 m. In Stage 5, shallow-layer tensile strain remained stable (around 10 με), and compressive strain in middle and deep layers gradually decreased to − 35 to − 95 με.
• vi.The stress curves of the Self-sensing FRP Bar and the steel stress gauges showed consistent trends, and the stress differences under the same conditions were mostly within ± 5 MPa, validating the monitoring reliability of the Self-sensing FRP Bar.
• vii.The maximum tensile stress of 35.8 MPa observed during the entire construction period was far below the ultimate tensile strength of the GFRP material, indicating that the structure remained within a safe stress range.

Limitations and prospects

In this study, although the self-sensing FRP bars demonstrated excellent stress–strain monitoring capabilities during the construction of underground diaphragm walls, several limitations remain. First, the installation and placement of self-sensing FRP bars require high precision in construction; improper installation could affect the accuracy of the monitoring data. Second, the impact of temperature fluctuations on the fiber optic sensors requires further investigation to mitigate potential interference with data collection. Furthermore, the current monitoring system relies on fiber optic transmission and wireless communication technologies, which may face limitations in extreme environmental conditions, potentially leading to signal interference or equipment failure.

With the continuous advancement of related technologies, the application of self-sensing FRP bars is expected to further enhance monitoring accuracy and reliability. Future research could focus on optimizing the manufacturing processes of self-sensing FRP bars to improve their adaptability in complex construction environments, as well as exploring methods to reduce the cost and complexity of monitoring systems. Additionally, integrating big data and artificial intelligence technologies could enable more intelligent and automated monitoring systems, which would not only provide more real-time and precise stress state monitoring but also contribute to enhancing engineering safety and optimizing the construction process.

Author contributions

J.L. (Jian Li) supervised the project, provided technical guidance and suggestions, and reviewed the manuscript. Q.S. (Qilong Shi) coordinated the research framework, managed project execution, and contributed to manuscript revision. S.X. (Shanchang Xu) developed the model, designed the methodology, and drafted the original manuscript. K.S. (Kangxin Sun) participated in project implementation and was responsible for data organization. Y.L. (Yue Liu) contributed to visualization, validation of results, and editing of the manuscript. All authors reviewed and approved the final version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (Grant No. 2023YFB3711600) and the National Natural Science Foundation of China (Grant No. 52178097).

Data availability

Data will be made available on request. Readers who wish to access the dataset used in this study may contact the corresponding author, Dr. Shanchang Xu, at xushanchangedu@163.com .

Declarations

Competing interests

The authors declare no competing interests.