Bridge Health Monitoring Using Strain Data and High-Fidelity Finite Element Analysis

Ghahremani, Behzad; Enshaeian, Alireza; Rizzo, Piervincenzo

doi:10.3390/s22145172

Cited by 15 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As part of this study, this paper proposes a few simple strategies to identify structural anomalies of the structure as well as transient events. This paper expands the work of Ghahremani et al [ 38 ], where the finite element analysis of a prestressed concrete box beam bridge was discussed. It is disclosed here that the installation of the sensing system and the truck load test were performed a few years ago by two companies not involved in this study.…”

Section: Introductionsupporting

confidence: 62%

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges

Enshaeian,

Ghahremani,

Rizzo

2024

Sensors

Self Cite

View full text Add to dashboard Cite

Three Pennsylvanian bridges were studied using finite element and wireless sensor technology. A detailed finite element model of each bridge was created using a commercial software in order to calculate the strains generated by a load that simulates the presence of a standard truck. Pristine and damage scenarios were simulated, and the computed strains were compared to the experimental strains measured with proprietary wireless sensors during a truck test performed by companies not involved in the study presented in this article. The comparison demonstrated the accuracy of the model and the presence of a few non-critical anomalies in terms of load redistribution. In addition, the comparison proved the reliability of the wireless sensing system installed on the bridges, although some drift was observed. The structural monitoring program for the three bridges was also evaluated by processing more than two years of data streamed to a repository.

show abstract

Section: Introductionsupporting

confidence: 62%

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges

Enshaeian,

Ghahremani,

Rizzo

2024

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this application space, there have been both wired and wireless approaches for these SHM Digital Twinning systems. The wired approaches that have been reported in literature include the use of arrays of resistive strain gauges throughout a composite material 6 , 7 , carbon nanotube-based multi-axis strain sensing 8 , piezoelectric sensors that convert the mechanical deformation brought on by strain into a measurable voltage waveform 9 , 10 , and a Fiber–Bragg grating designed to monitor local strain and temperature 11 . While these sensing techniques provide reliable readings, these wired sensing systems leave much to be desired from an implementation stand-point.…”

Section: Introductionmentioning

confidence: 99%

5G-enabled, battery-less smart skins for self-monitoring megastructures and digital twin applications

Lynch,

Adeyeye,

Abbara

et al. 2024

Sci Rep

View full text Add to dashboard Cite

With the current development of the 5G infrastructure, there presents a unique opportunity for the deployment of battery-less mmWave reflect-array-based sensors. These fully-passive devices benefit from having a larger detectability than alternative battery-less solutions to create self-monitoring megastructures. The presented ‘smart’ skin sensor uses a Van-Atta array design enabling ubiquitous local strain monitoring for the structural health monitoring of composite materials featuring wide interrogation angles. Proof-of-concept prototypes of these ‘smart’ skin millimeter-wave identification tags, that can be mounted on or embedded within common materials used in wind turbine blades, present a highly-detectable radar cross-section of − 33.75 dBsm and − 35.00 dBsm for mounted and embedded sensors respectively. Both sensors display a minimum resolution of 202 $$\upmu $$ μ -strain even at 40$$^{\circ }$$ ∘ off-axis enabling interrogation of the fully-passive sensor at oblique angles of incidence. When interrogated from a proof-of-concept reader, the fully-passive, sticker-like mmID enables local strain monitoring of both carbon fiber and glass fiber composite materials. The sensors display a repeatable and recoverable response over 0–3000 $$\upmu $$ μ -strain and a sensitivity of 7.55 kHz/$$\upmu $$ μ -strain and 7.92 kHz/$$\upmu $$ μ -strain for mounted and embedded sensors, respectively. Thus, the presented 5G-enabled battery-less sensor presents massive potential for the development of ubiquitous Digital Twinning of composite materials in future smart cities architectures.

show abstract

“…The practicability of bridge health monitoring system promotes its rapid development in the future. [29][30][31][32] However, how to use the massive data from structural health monitoring systems has become the focus in this direction. [33][34][35] For example, Moon et al 36 introduced an artificial neural network for the accurate predictions of the vertical displacements from the axial strains with the SHM data.…”

Section: Introductionmentioning

confidence: 99%

“…The practicability of bridge health monitoring system promotes its rapid development in the future 29–32 . However, how to use the massive data from structural health monitoring systems has become the focus in this direction 33–35 .…”

Section: Introductionmentioning

confidence: 99%

Research on mapping relationship between environmental load and vibration response of bridge structure based on structural health monitoring data

Qiao,

Ding,

Zhou

et al. 2023

Engineering Reports

View full text Add to dashboard Cite

With the increasing lifespan of bridges, various forms of deterioration will inevitably occur. The bridge health monitoring system enables direct monitoring of the loads (such as wind, temperature, and vehicles) experienced by the bridge during operation, as well as the corresponding vibration response of the bridge structure (including main beam deformation, tower top displacement, cable acceleration, etc.). These data provide valuable insights into the safety and durability of the bridge during its operational lifetime. However, the challenge lies in extracting meaningful information from the vast amount of collected data. This article focuses on the Fuyu Bridge as a research case and analyzes the variations in environmental factors, such as temperature, humidity, wind load, and structural vibration responses (main beam and cable), obtained from the Fuyu Bridge's structural health monitoring system. It also conducts a structural safety assessment during the operational period of the bridge. Furthermore, the research explores the relationship between environmental factors, load effects, and structural response to establish a foundation for future structural safety assessments of the Fuyu Bridge during its operational period. For instance, changes in environmental factors or load effects can be used to predict structural responses. Additionally, this study provides access to the structural health monitoring data of the Fuyu Bridge, facilitating data‐driven research for other scholars in the field.

show abstract

Bridge Health Monitoring Using Strain Data and High-Fidelity Finite Element Analysis

Cited by 15 publications

References 39 publications

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges

5G-enabled, battery-less smart skins for self-monitoring megastructures and digital twin applications

Research on mapping relationship between environmental load and vibration response of bridge structure based on structural health monitoring data

Contact Info

Product

Resources

About