Search Results (66)

Structural Health Monitoring (SHM) techniques are crucial for evaluating the condition of structures, enabling early maintenance interventions, and monitoring factors that could compromise structural integrity. Modal analysis studies the dynamic response of structures when subjected to vibrations, evaluating natural frequencies and vibration modes. This study focuses on detecting and comparing the natural frequencies of a 3-DoF structure under various excitation scenarios, including ambient vibration (in healthy and damaged conditions), two types of transient excitation, and three harmonic excitation variations. Signal processing techniques, specifically Power Spectral Density (PSD) and Continuous Wavelet Transform (CWT), were employed. Each method provides valuable insights into frequency and time-frequency domain analysis. Under ambient vibration excitation, the damaged condition exhibits spectral differences in amplitude and frequency compared to the undamaged state. For the transient excitations, the scalogram images reveal localized energetic differences in frequency components over time, whereas PSD alone cannot observe these behaviors. For the harmonic excitations, PSD provides higher spectral resolution, while CWT adds insight into temporal energy evolution near resonance bands. This study discusses how these analyses provide sensitive features for damage detection applications, as well as the influence of different excitation types on the natural frequencies of the structure. Full article

Operational modal analysis (OMA) is widely used for its simplicity and reliance on ambient noise. While commercial OMA software exists, they often limit user control. Some researchers develop their own tools, but independent software tools remain scarce. The number of such independent software is limited, and the development of new ones with enhanced features, better performance, and varied user interfaces would be beneficial to spread the informed use of dynamic identification techniques, leading to more reliable and valuable results for structural engineering applications. This work introduces the new DYMOS software for OMA from ambient vibration test recordings. DYMOS includes various state-of-art algorithms and tools for vibration-based modal identification and for optimal sensor placement (OSP), allowing for customization of analysis parameters and procedures with the aim of reducing the gap between the needs of professional practice and research. Additionally, a new graphical tool is introduced for visualizing results in both buildings and bridges. By using CAD drawings as input, it streamlines model construction, making the process faster, more intuitive, and efficient. The article aims to describe DYMOS and to demonstrate its potential for OMA and OSP in civil engineering through the application on two real case studies dynamically tested. Full article

The growing complexity and uncertainty in modern power systems—driven by increased integration of renewable energy sources and variable loads—underscore the need for robust tools to assess dynamic stability. This paper presents an enhanced methodology for modal analysis that combines Adaptive Variational Mode Decomposition (A-VMD) with Prony’s method. A novel energy-based selection mechanism is introduced to determine the optimal number of intrinsic mode functions (IMFs), improving the decomposition’s adaptability and precision. The resulting modes are analyzed to estimate modal frequencies and damping ratios. Validation is conducted using both synthetic datasets and real synchrophasor measurements from Ecuador’s national power grid under ambient and disturbed operating conditions. The proposed approach is benchmarked against established techniques, including a matrix pencil, conventional VMD-Prony, and commercial tools such as WAProtector and DIgSILENT PowerFactory. The results demonstrate that A-VMD consistently delivers more accurate and robust performance, especially for low signal-to-noise ratios and low-energy ambient conditions. These findings highlight the method’s potential for real-time oscillation mode identification and small-signal stability monitoring in wide-area power systems. Full article

The behavior of structural elements, which is very important in structural engineering, can be determined non-destructively using ambient vibration tests. Composite elements used in structures can be formed by combining elements of different materials. It is much more difficult to predict the structural behavior of composite elements because they are made of different materials. Ambient vibration tests are one of the most important methods used to determine the dynamic characteristics of composite elements. In this study, composite cantilever beams were formed by combining wood and steel profiles in various combinations. The dynamic characteristics of these beams (natural frequency, mode shape, modal damping ratio) were determined by both the numerical method and operational modal analysis (OMA) method. Firstly, the initial analytical models of the beams were modeled using the finite element program. The natural frequencies and mode shapes of the models were determined using the modal analysis method. While creating the initial analytical model, the material properties of the beams were entered by taking into account the standard values in the literature. Then, the dynamic characteristics of the beams were determined using an experimental modal analysis method (operational modal analysis test). The dynamic characteristics obtained from tests and the analysis of the initial analytical models were compared. The analytical models were calibrated according to the test results. In this way, the modeled beams were provided with a more realistic dynamic behavior. Numerical models were modeled using the SAP2000 program. As a result of the analysis, the dynamic characteristics and structural properties of composite cantilever beams were compared. As the elasticity modules and cross-sections of the profiles used in the beams increase, the stiffness of the beams also increases. It was determined that the natural frequencies of the composite beams increase with the increase in their stiffness. When the frequencies of the first modes of the least rigid wood (W) beam and the most rigid steel–wood–steel (S-W-S) beam were compared, an increase of 47% was detected. Full article

This study proposes a simplified approach for the experimental dynamic characterization of the historic Messina Bell Tower (northeastern Sicily) using passive seismic single-station surveys. The Horizontal-to-Vertical Spectral Ratio (HVSR) analysis identified a site resonance frequency of approximately 1.06 Hz, while the Multichannel Analysis of Surface Waves (MASW) survey contributed to the characterization of the shear wave velocity profile, providing a coherent geophysical framework useful for structural dynamic analysis. Spectral ratios analysis revealed four distinct vibration modes, including a fundamental rocking mode (~1.4 Hz), a torsional mode (3.5 Hz), and two higher-frequencies flexural modes. The structure’s dynamic behavior, notably its sensitivity to torsion and rocking, is attributed to the deformable subsoil. Damping ratios estimated via the Random Decrement Method (RDM) were below 1%, consistent with the expected linear elastic response under ambient vibrations. The results show strong agreement with previous long-term monitoring, validating the effectiveness of passive seismic techniques for rapid, non-invasive assessment. This study demonstrates that streamlined, time-efficient methodologies are capable of delivering modal parameters consistent with those obtained from more extensive and resource-intensive monitoring campaigns, thereby providing a reliable and practical approach for the seismic vulnerability assessment of heritage structures. Full article

Strategically important objects, such as dams, tunnels, bridges, and others, require long-term structural health monitoring programs in order to preserve their structural integrity with minimal downtime, financial expenses, and increased safety for civilians. The current study focuses on developing a damage detection methodology that is applicable to the long-term monitoring of such structures. It is based on the identification of resonant frequencies from operational modal analysis, removing the effect of environmental factors on the resonant frequencies through support vector regression with optimized hyperparameters and, finally, classifying the global structural state as either healthy or damaged, utilizing the Mahalanobis distance. The novelty lies in two additional steps that supplement this procedure, namely, the nonlinear estimation of the relative effects of various environmental factors, such as temperature, humidity, and ambient loads on the resonant frequencies, and the selection of the most informative resonant frequency features using a non-parametric neighborhood component analysis algorithm. This methodology is validated on a wooden two-story truss structure with different artificial structural modifications that simulate damage in a non-destructive manner. It is found that, firstly, out of all environmental factors, temperature has a dominating decreasing effect on resonance frequencies, followed by humidity, wind speed, and precipitation. Secondly, the selection of only a handful of the most informative resonance frequency features not only reduces the feature space, but also increases the classification performance, albeit with a trade-off between false alarms and missed damage detection. The proposed approach effectively minimizes false alarms and ensures consistent damage detection under varying environmental conditions, offering tangible benefits for long-term SHM applications. Full article

In recent years, the integration of nano titanium dioxide (TiO₂) into building materials has become a popular research topic due to its superior mechanical, photocatalytic and self-cleaning properties. In this study, the dynamic behavior of a light steel container house model coated with nano-TiO₂ is investigated using Operational Modal Analysis (OMA). The effects of TiO₂ on the natural frequencies, damping ratios and mode shapes of the light steel container house model are investigated. The Stochastic Subspace Identification-Unweighted Principal Component (SSI-UPC) method is used to extract the modal parameters from the ambient vibration data. The results show that the TiO₂ coating significantly increases the stiffness and improves the damping properties by increasing the natural frequencies of the light steel container house model. The findings indicate that nano-TiO₂ coatings can increase the structural integrity and durability of light steel container houses. This study provides a foundation for future research on nano-reinforced coatings in light steel structural systems. Full article

Structural health monitoring is vital for the safety and longevity of infrastructure, particularly in seismic zones. This study focuses on identifying the dynamic properties of a reinforced concrete building in Chile’s Valparaíso region. Using an experimental approach, the study compares ambient vibration records, seismic events (moment magnitude > 4), and data collected during adjacent construction activities. Force-balanced accelerometers were used for vibration measurements. The analysis employs the Stochastic Subspace Identification with Covariances (SSI-COV) method within an operational modal analysis framework to extract the building’s modal parameters without requiring artificial excitations. This technique effectively identifies modal characteristics under different vibration sources, making it suitable for evaluating the structural condition under diverse loading conditions. The findings reveal the building’s modes and frequencies, offering critical insights for maintenance and management of infrastructure. Little to no variations were observed in the identified frequencies of the building when working with different types of input data. These data support the integration of real-time IoT systems for continuous monitoring, providing a foundation for future digital twin applications. These advancements facilitate early deterioration detection, enhancing resilience in seismic environments. Full article

The seismic assessment of historical masonry bell towers is of significant interest, particularly in Italy, due to their widespread presence and inherent vulnerability given by their slenderness. According to technical codes and standard practice, the seismic evaluation of masonry bell towers can be conducted using a range of methodologies that vary in their level of detail. This paper presents a case study of a historical masonry bell tower located in the Caserta Province (Italy). Extensive investigative efforts were undertaken to determine the tower’s key geometric and structural characteristics, as well as to document ongoing damage phenomena. The dynamic behavior of the tower was assessed through ambient vibration testing, which enabled the identification of the principal modal shapes and corresponding frequencies, also highlighting peculiar dynamical characteristics caused by the damage conditions. Subsequently, the seismic assessment was carried out using both Level 1 (simplified mechanical) and Level 2 (kinematic limit analysis) methodologies. This assessment helped identify the most probable collapse mechanisms and laid the foundation for employing more advanced methodologies to design necessary retrofitting interventions. The study emphasizes the importance of Level 2 analyses for structures where out-of-plane failure mechanisms are likely due to pre-existing cracking. Both approaches provide less-than-unity acceleration factors, ranging from 0.45 for Level 1 (assuming non-ductile behavior) to 0.59 for Level 2, in this case specifically using the information available about existing cracking pattern. Full article

The evaluation of bridge safety is closely related to structural stiffness, with dynamic characteristics and displacement being key indicators. Displacement is a significant factor as it is a physical phenomenon that bridge users can directly perceive. However, accurately measuring displacement generally necessitates the installation of displacement meters within the bridge substructure and conducting load tests that require traffic closure, which can be cumbersome. This paper proposes a novel method that uses wireless accelerometers to measure ambient vibration data from bridges, extracts mode shapes and natural frequencies through the time domain decomposition (TDD) technique, and estimates static displacement under specific loads using the flexibility matrix. A field test on a 442.0 m cable-stayed bridge was conducted to verify the proposed method. The estimated displacement was compared with the actual displacement measured by a laser displacement sensor, resulting in an error rate of 3.58%. Additionally, an analysis of the accuracy of displacement estimation based on the number of measurement points indicated that securing at least seven measurement points keeps the error rate within 5%. This study could be effective for evaluating the safety of bridges in environments where load testing is difficult or for bridges that require periodic dynamic characteristics and displacement analysis due to repetitive vibrations, and it is expected to be applicable to various types of bridge structures. Full article

Modal parameters are inherent characteristics of civil structures. Due to the effect of environmental factors and ambient loads, the physical and modal characteristics of a structure tend to change over time. Therefore, the effective identification of time-varying modal parameters has become an essential topic. In this study, an instantaneous modal identification method based on an adaptive chirp mode decomposition (ACMD) technique was proposed. The ACMD technique is highly adaptable and can accurately estimate the instantaneous frequencies of a structure. However, it is important to highlight that an initial frequency value must be selected beforehand in ACMD. If the initial frequency is set incorrectly, the resulting instantaneous frequencies may lack accuracy. To address the aforementioned problem, the Welch power spectrum was initially developed to extract a high-resolution time–frequency distribution from the measured signals. Subsequently, the time–frequency ridge was identified based on the maximum energy position in the time–frequency distribution plot, with the frequencies associated with the time–frequency ridge serving as the initial frequencies. Based on the initial frequencies, the measured signals with multiple degrees of freedom could be decomposed into individual time-varying components with a single degree of freedom. Following that, the instantaneous frequencies of each time-varying component could be calculated directly. Subsequently, a sliding window principal component analysis (PCA) method was introduced to derive instantaneous mode shapes. Finally, vibration data collected under various operational scenarios were used to validate the proposed method. The results demonstrated the effective identification of time-varying modal parameters in real-world civil structures, without missing modes. Full article

Output-only modal analysis using ambient vibration testing is ubiquitous for the monitoring of structural systems, especially for civil engineering structures such as buildings and bridges. Nonetheless, the instrumented nodes for large-scale structural systems need to cover a significant portion of the spatial volume of the test structure to obtain accurate global modal information. This requires considerable time and resources, which can be challenging in large-scale projects, such as the seismic vulnerability assessment over a large number of facilities. In many instances, a simple center-line (stairwell case) topology is generally used due to time, logistical, and economic constraints. The latter, though a fast technique, cannot provide complete modal information, especially for torsional modes. In this research, corner-line instrumented nodes layouts using only a reference and a roving sensor are proposed, which overcome this issue and can provide maximum modal information similar to that from 3D topologies for medium-rise buildings. Parametric studies are performed to identify the most appropriate locations for sensor placement at each floor of a medium-rise building. The results indicate that corner locations at each floor are optimal. The proposed procedure is validated through field experiments on two medium-rise buildings. Full article

With the growing demand for infrastructure and transportation facilities, the need for advanced structural health monitoring (SHM) systems is critical. This study introduces two innovative, cost-effective, standalone, and open-source data acquisition devices designed to enhance SHM through the latest sensing technologies. The first device, termed CEDAS_acc, integrates the ADXL355 MEMS accelerometer with a RaspberryPi mini-computer, ideal for measuring strong ground motions and assessing structural modal properties during forced vibration tests and structural monitoring of mid-rise buildings. The second device, CEDAS_geo, incorporates the SM24 geophone sensor with a Raspberry Pi, designed for weak ground motion measurements, making it suitable for seismograph networks, seismological research, and early warning systems. Both devices function as acceleration/velocity Data Acquisition Systems (DAS) and standalone data loggers, featuring hardware components such as a single-board mini-computer, sensors, Analog-to-Digital Converters (ADCs), and micro-SD cards housed in protective casings. The CEDAS_acc includes a triaxial MEMS accelerometer with three ADCs, while the CEDAS_geo uses horizontal and vertical geophone elements with an ADC board. To validate these devices, rigorous tests were conducted. Offset Test, conducted by placing the sensor on a leveled flat surface in six orientations, demonstrating the accelerometer’s ability to provide accurate measurements using gravity as a reference; Frequency Response Test, performed at the Gebze Technical University Earthquake and Structure Laboratory (GTU-ESL), comparing the devices’ responses to the GURALP-5TDE reference sensor, with CEDAS_acc evaluated on a shaking table and CEDAS_geo’s performance assessed using ambient vibration records; and Noise Test, executed in a low-noise rural area to determine the intrinsic noise of CEDAS_geo, showing its capability to capture vibrations lower than ambient noise levels. Further field tests were conducted on a 10-story reinforced concrete building in Gaziantep, Turkey, instrumented with 8 CEDAS_acc and 1 CEDAS_geo devices. The building’s response to a magnitude 3.2 earthquake and ambient vibrations was analyzed, comparing results to the GURALP-5TDE reference sensors and demonstrating the devices’ accuracy in capturing peak accelerations and modal frequencies with minimal deviations. The study also introduced the Record Analyzer (RECANA) web application for managing data analysis on CEDAS devices, supporting various data formats, and providing tools for filtering, calibrating, and exporting data. This comprehensive study presents valuable, practical solutions for SHM, enhancing accessibility, reliability, and efficiency in structural and seismic monitoring applications and offering robust alternatives to traditional, costlier systems. Full article

Ultramafic rocks are promising candidates for carbon sequestration by enhanced carbon dioxide (CO₂) mineralization strategies due to their highly CO₂-reactive mineral composition and their abundant availability. This study reports the mineralogy and microtextures of a representative ultramafic rock from the Ma-Hin Creek in northern Thailand and provides evidence of CO₂ mineralization occurring through the interaction between CO₂ and the rock in the presence of water under ambient conditions. After sample collection, rock description was determined by optical petrographic analysis. The rock petrography revealed a cumulated wehrlite comprising over 50% olivine and minor amounts of clinopyroxene, plagioclase, and chromian spinel. Approximately 25% of the wehrlite had altered to serpentine and chlorite. A series of CO₂ batch experiments were conducted on six different rock sizes at a temperature of 40 °C and pressure of 1 atm over five consecutive days. The post-experimental products were dried, weighed, and geochemically analyzed to detect changes in mineral species. Experimental results showed that product weight and the presence of calcite increased with reducing grain size. Additionally, the modal mineralogy of the wehrlite theoretically suggests potential CO₂ uptake of up to 53%, which is higher than the average uptake values of mafic rocks. These findings support the rock investigation approach used and the preliminary assessment of carbon mineralization potential, contributing to enhanced rock weathering techniques for CO₂ removal that could be adopted by mining and rock supplier industries. Full article

Due to their distinct features, including structural simplicity and exceptional load-carrying capacity, steel box girder bridges play a critical role in transportation networks. However, they are categorized as fracture-critical structures and face significant challenges. These challenges stem from the overloading and the relentless effects of corrosion and aging on critical structural components. As a result, these bridges require thorough inspections to ensure their safety and integrity. This paper introduces generalized approaches based on vibration-based structural health monitoring in response to this need. This approach assesses the condition of critical members in a steel girder bridge and evaluates their sensitivity to damage. A rigorous analytical evaluation demonstrated the effectiveness of the proposed approach in evaluating the Szapáry multi-span continuous highway bridge under various damage scenarios. This evaluation necessitates extensive vibration measurements, with piezoelectric sensors capturing ambient vibrations and developing detailed finite element models of the bridge to simulate the structural behavior accurately. The results obtained from this study showed that bridge frequencies are sufficiently sensitive for identifying significant fractures in long bridges. However, the mode shape results show a better resolution when compared to the frequency changes. The findings are usually sensitive enough to identify damage at the affected locations. Amplitude changes in the mode shape help determine the location of damage. The modal assurance criterion (MAC) served to identify damage as well. Finally, the results show a distinct pattern of frequency and mode shape variations for every damage scenario, which helps to identify the damage type, severity, and location along the bridge. The analysis results reported in this study serve as a reference benchmark for the Szapáry Bridge health monitoring. Full article