Civil Engineering Community Research Articles

Temperature-based damage detection for the commissioning dataset of the MX3D Bridge

Environmental and operational variations (EOV) remain a major obstacle for the successful transfer of structural health monitoring (SHM) techniques from laboratory experiments, such as cracked beam experiments, to full-scale structures, such as long-span bridges. With evidence that timely interventions significantly increase the service-life and reduce the overall life-cycle cost of ageing infrastructure, carrying out SHM in the presence of EOV, such as temperature, is therefore of high priority within the civil engineering community. The temperature-based measurement-interpretation (TB-MI) approach was developed to monitor the thermal response of an instrumented structure and detect changes linked to damage by minimising the impact that temperature variations have on anomaly detection techniques. The iterative regression-based thermal response prediction (IRBTRP) methodology is utilised in the TB-MI approach, and is trained on the healthy condition of the bridge to predict its undamaged response to temperature fluctuations. Thermal response predictions are compared to the measured response and deviations between them are indicative of a variation in the thermal response, due to structural change such as damage. Small deviations can then be identified using anomaly detection techniques, which results in earlier damage detection than if thermal response predictions had not been used. The TB-MI approach and the IRBTRP methodology have been applied to detect damage on the MX3D Bridge, the world’s first structure produced through metal additive manufacturing (i.e. 3D printing). This study demonstrates that the use of the TB-MI approach enables earlier and more widespread damage detection amongst multiple sensor groups, compared to when no temperature effects are considered. The adoption of the TB-MI approach can therefore greatly increase the reliability of and our reliance on SHM techniques for critical infrastructure.

Cyber Game-Based Learning for DoD CEs

Cyber competition and conflict remain an enduring concern for the Department of Defense (DoD). Positive control of cyberspace is crucial across the vast diversity of military operations and supporting activities. People play an important role in cyber prevention, detection, and remediation, but they receive relatively little training outside of the annual Cyber Awareness Challenge. While this gamified training is a reasonable baseline, it primarily addresses cybersecurity from the office worker's perspective. Other career fields within the DoD may benefit from specialized training in cybersecurity, in particular the civil engineering (CE) community supporting critical infrastructure protection. This paper surveys a range of contemporary cyber serious games and assesses each for potential inclusion into CE training. Furthermore, it suggests game elements and characteristics that are likely to benefit the CE community.

Analytical and Experimental Behaviour of GFRP-Reinforced Concrete Columns under Fire Loading

Fire engineering endeavours to mitigate injury or the loss of life in the event of a fire. This is achieved primarily through fire prevention, containment, and extinguishment measures. Should prevention fail, the structural integrity of buildings, coupled with effective evacuation strategies, becomes paramount. While glass fibre-reinforced polymer (GFRP) materials have demonstrated efficacy in reinforcing concrete elements, their performance under fire conditions, notably in comparison to steel, necessitates a deeper understanding for structural applications. This study experimentally and numerically investigates the fire performance of GFRP-reinforced concrete (RC) columns subjected to only fire load without additional external loads. The research aims to ascertain the fire resistance based on the thickness of the concrete coating and the ultimate tensile strength of GFRP rebars after 90 min of fire exposure. Four GFRP-RC columns were subjected to a standardized fire curve on all sides in the experimental program. In the analytical program, a theoretical model was developed using the heat transfer module of the COMSOL software. The results of both analyses were very close, indicating the reliability of the procedure used. Based on the findings, recommendations regarding the fire resistance of GFRP-RC columns were formulated for structural applications. Results from this research provide the civil engineering community with data that will help them continue using FRP materials as internal reinforcement for concrete.

Numerical and experimental study of a suspension bridge with combined viscous-steel damping system under train and seismic loads

The longitudinal dynamic performance of long-span bridges with passive vibration control devices when subjected to vehicle and seismic loads has raised extensive attention of the civil engineering community. This study aims to provide numerical and experimental assessments of the dynamic performance of a railway suspension bridge with the Combined Viscous-Steel Damping System (CVSDS) under various excitations. The deck is simplified to a single-degree-of-freedom (SDOF) system according to the longitudinal vibration characteristics of the suspension bridge. The Dynamic Equation Method (DEM) and Fourier Expansion Method (FEM) are suggested for the equivalence of the spatiotemporal variable train loads to horizontal excitations. A simplified two-stage analytical model is proposed to simulate the restoring force characteristics and fuse-lock function of the CVSDS. Shake table tests are conducted to further illustrate the feasibility of the simplified model and evaluate the effectiveness of the CVSDS. The results indicate that the SDOF system is reasonable and satisfactory in simulating the deck displacement. The two-stage working mechanism of the CVSDS is verified by both the simulation and experiment, i.e. the viscous fluid damper works under train loads and the steel yielding damper operates under earthquakes. The vibration mitigation effectiveness of the CVSDS is remarkable.

Edukasi Bahaya Gempa Bumi di Sdn 51 Maluku Tengah, Dusun Wainuru, Desa Liang

Liang Village in Central Maluku district, Maluku province, was the village that was most affected by successive earthquakes in 2019. The location of the point of the earthquake which was near caused the Liang village to suffer a lot of damage to buildings. Damage to this building can cause the ceiling and walls of the building to collapse, so it is very dangerous for the community. The purpose of this service is that after carrying out this service, activity participants can understand the dangers of earthquakes, the causes of earthquakes, the disasters that follow earthquakes and rescue actions. This educational activity is one of a series of civil engineering community service activities at Pattimura University. This education is carried out by conducting live presentations and showing video material that will be delivered to teachers and students of SDN 51 Central Maluku. The results of this education can be seen from the enthusiasm of students who can answer the speaker's questions from the material that has been provided. After this educational activity, students and teachers at SDN 51 Central Maluku, Dusun Wainuru, are expected to be able to understand how to take preventive and rescue measures when an earthquake occurs in the future.

Earth-based building materials reinforced with flax fibers: an experimental investigation

Climate change has led to a notable shift towards sustainable design practices within the civil engineering community. In this context, earth-based building materials are particularly advantageous as they are locally sourced, easily recyclable and exhibit low levels of embodied and operational energy. Therefore, this work presents an experimental investigation of compressed earth materials reinforced with natural flax fibers. The primary objective is to investigate the influence of the embedded fibers on both the mechanical and thermal properties of the material with the aim of developing a novel type of masonry earth brick. Samples made of two types of earth (namely, a clayey silt Bouisset and a sandy silt Nagen), incorporating distinct percentages of fibers, were statically compacted at a target dry density of 1900 kg/m3 inside a metallic mould with dimensions of 40×40×160 mm3. The samples were then subjected to 3-point bending tests and compression tests, as well as thermal conductivity tests. Results indicate that the addition of fibers improves the samples’ compressive and bending strength, especially for the Nagen earth. Instead, the inclusion of fibers has a negligible effect on thermal conductivity and diffusivity. Only for the Bouisset earth, the thermal diffusivity improves with increasing fiber content, thus resulting in faster heat transfers.

Modified Frequency-Bessel Transform Method for Dispersion Imaging of Surface Wave from Six-Component Ambient Noise Recordings

Surface wave analysis methods based on ambient noise have attracted considerable attention within the geophysical and civil engineering communities, particularly in light of the limitations associated with traditional seismic surveys in densely populated urban areas. Conventionally, translational seismic sensors have been employed for the observation of ambient noise. Nevertheless, recent advancements in rotational sensor technology have facilitated the direct measurement of ground motion induced by seismic waves in a rotational manner. Through the integration of these rotational sensors with traditional inertial seismometers, a novel six-component seismic sensor has been developed. This innovative sensor enables the local observation of six degrees of freedom pertaining to ground motion, encompassing three orthogonal components of translational motion and three orthogonal components of rotational motion. In order to demonstrate the seismological significance of rotational ground-motion data, we applied the modified frequency-Bessel transform method (MFJ) to six-component ambient noise recordings for surface wave analysis. To underscore the practical utility of the MFJ method, a real-world case study is presented, illustrating its effectiveness in quantifying Rayleigh and Love wave dispersion from six-component ambient noise recordings.

Experimental investigation on corroded and non-corroded RC tunnels under different loading conditions

Underground reinforced concrete (RC) structures, such as tunnels and pipelines, are frequently employed in urban areas and are designed to withstand both static and seismic loads, including those that occur during earthquakes. However, the inspection of deteriorated underground structures has yielded valuable findings for the civil engineering community, highlighting the need for further experimental investigation of the various damage mechanisms affecting RC tunnels under different loading conditions. This research presents a comprehensive experimental study aimed at elucidating the damage mechanisms of underground RC structures exposed to various loading conditions. Specifically, the study includes experimental testing of the corrosion of tunnel reinforcement and an investigation into the overall performance of corroded tunnels. The experimental results indicate that existing vertical loads significantly impact the lateral carrying capacity and ductility of RC tunnels.

Dynamic Response Analysis of a Fiber-Reinforced Polymer Reinforced Viaduct under Full Scale Moving Maglev Train Load

Fiber-reinforced polymers (FRPs) are widely utilized in the construction of bridges all over the world and are thought to be a potential alternative to steel reinforcement, particularly in concrete structures exposed to harsh conditions or the effects of electromagnetic fields. Although some FRP bridges have already been put into service and others are still being built, there is ongoing discussion in the civil engineering community over the efficacy of FRPs in substituting steel in vibration-prone bridge parts. This study adopts finite element modeling based on numerical and analytical approaches to investigate the dynamic behavior of the viaduct during maglev train operation when the steel-reinforced girder concrete is replaced by FRP-reinforced girder concrete. In this way, a realistic coupled maglev train–viaduct system is developed and validated by comparative analysis with data from field experiments. Then, an investigation of the viaduct dynamic behavior when the girder is reinforced with polyacrylic nitrile carbon FRP or S-glass FRP reveals that system displacement is governed by viaduct stiffness, whereas acceleration is governed by structure weight. Nonetheless, the dynamic load frequency has a considerable impact on the efficacy of FRP as viaduct concrete reinforcement, which has been demonstrated to be effective at particular train speeds dependent on the structure’s natural frequency.

Behaviour of normal concrete with Sugarcane Bagasse Ash (ScBA) as partial cement replacement

Concrete has been known to the world to be one of the most crucial components of a developing country but there some downsides to the environment in making the concrete. Mixing concrete needs water, fine aggregates, coarse aggregates, and cements as the main component. Cement is the main cause of the disadvantages of normal concrete mixing because in cement production, it will emit a lot of carbon dioxide to the environment. The emission of carbon dioxide to the atmosphere is proven as one of the main problems that cause air pollution and greenhouse effect. Furthermore, in an agricultural dependent country like Malaysia, the agricultural waste had been concerning to the public whereby the Sugarcane Bagasse (ScB) is one of the agricultural wastes. Sugarcane Bagasse can be useful towards the civil engineering communities where the Sugarcane Bagasse can turn into ash by burning and grinding the Sugarcane Bagasse residual and turn into Sugarcane Bagasse Ash (ScBA). The Sugarcane Bagasse Ash (ScBA) need to grind to make the particles of the ash to be cement-like of the particle size. Therefore, the purpose of the Sugarcane Bagasse Ash (ScBA) in this research is to replace some percentage of the cement to minimize the production of cements. So, the objective of the research is to identify the optimum percentage of Sugarcane Bagasse Ash that can produce maximum value of compressive strength of concrete when it is being replace by Sugarcane Bagasse Ash (ScBA). The percentage of Sugarcane Bagasse Ash (ScBA) that will replace the percentage of cements is 0%, 4%, 8%, and 12%. Based on the results obtained the compressive strength of the concrete mix with 4% of Sugarcane Bagasse Ash (ScBA) is higher compared to the control sample which is 45.60MPa where the control sample only have 38.83MPa. In conclusion, by using the Sugarcane Bagasse Ash (ScBA) it is proven that with the agricultural waste, it can be useful to the not only civil engineering communities but also to the world with the invention of using the Sugarcane Bagasse Ash (ScBA) as a replacement for cements where it can reduce the carbon dioxide emissions and the concern towards agricultural waste.

High-dimensional data analytics in civil engineering: A review on matrix and tensor decomposition

Recent developments in sensing and monitoring techniques have led to the generation of high-dimensional data in the field of civil engineering. High-dimensional data analytics methods have thus been developed to interpret such complex data. Among the different high-dimensional data analytics techniques, matrix and tensor decomposition methods have acquired a notable interest in the civil engineering community over the past decade. Due to their unique ability to deal with highly redundant and correlated data, these methods are establishing themselves as promising and efficient tools to analyze high-dimensional data in the civil engineering arena. In this paper, high-dimensional data is referred to as a data set in which the number of features is comparable or larger than the number of observations. This review paper aims to summarize the applications of matrix and tensor decomposition methods in civil engineering over the last decade. The survey begins with a general overview of matrix and tensor decomposition followed by highlighting their significance in the field. Afterward, various applications of these high-dimensional data analytics methods in civil engineering are presented, while the advantages offered by these methods are discussed. Finally, challenges and potential research avenues for employing matrix and tensor decomposition and future emerging trends for their novel use are highlighted.

Assessing and Predicting Geogrid Reduction Factors after Damage Induced by Dropping Recycled Aggregates

To fulfill the modern concept of sustainable construction, the civil engineering community has shown increased interest in alternative options to replace natural backfills for engineering purposes. Since Recycled Construction and Demolition Waste (RCDW) has proven to be attractive in environmental, economic, and technical aspects, its behavior should be assessed considering its interaction with other construction materials, such as geosynthetics. Bearing in mind that the backfill affects the durability of geosynthetic materials, this study aims to assess the damage caused to geogrids by RCDW dropped by transportation (dump) trucks. Moreover, this study aimed to obtain an equation to predict the reduction factor caused by the backfill drop process. In an experimental facility, six RCDW materials (with different grain size distributions) were dropped (using a backhoe loader) from 1.0 m and 2.0 m heights over three distinct geogrids; the geogrid samples were exhumed and then tested under tensile loading. The results provided a database subjected to machine learning (Artificial Neural Network—ANN) to predict the reduction factor caused by the induced damage. The results demonstrate that the increase in drop height or potential energy cannot be directly associated with the damage. However, the damage increases as the maximum grain size of uniform gradation backfill increases, which is different from the results obtained from the fall of continuous gradation backfill. Moreover, since ANNs do not have any of the traditional constraints that multiple linear regression has, this method is an attractive solution to predict the geosynthetic reduction factors, providing relative errors lower than 8% compared to the experimental investigation reported in the study.

Earthquake data augmentation using wavelet transform for training deep learning based surrogate models of nonlinear structures

Machine learning methods have gained traction in the civil engineering community for analysis of civil infrastructures. A major field of application is in development of surrogate models for non-linear dynamic analysis for civil infrastructures. These data-driven models generally consist of a large number of parameters which need to be estimated from available data. However, due to limited availability of data in the field of earthquake engineering, often, it is difficult to develop stable models that can predict structural response by taking into account both material and earthquake uncertainty. To this end, the authors propose a discrete wavelet transform (DWT) enabled surrogate modeling framework for prediction of nonlinear structural response while accounting for material and earthquake uncertainty. DWT is used for earthquake data augmentation and feature extraction, which, along with constitutive material parameters, are used to train a deep neural network (DNN). It is shown that DWT can efficiently augment existing small earthquake datasets while the DNN can capture the non-linear structural response. The framework is validated by applying it to successfully predict structural response of 3DOF nonlinear spring–mass–damper system and non-linear three-story steel moment-resisting frame for unseen earthquakes with a median error less than 12%.

Retrofitting and rehabilitation of masonry structures using FRP composites

Fibre Reinforced Polymer (FRP) is used to reinforce a range of structural elements, including masonry walls, slabs, beams, and columns. By attaching FRP strips along the axis of bending at the soffit portion of beams and slabs, flexure can be reinforced. Wrapping around the cross-section of beams in a U-shape can strengthen beams under flexure and shear. The ultimate stress and strains of FRP composites are far higher than most of the alternatives available for structural strengthening. The density of FRP composites is low, thus adding less additional dead weight to the structure. Compression members like columns may be strengthened by externally wrapping them with FRP, or by casting them in FRP stay-in-place formwork. The externally bonded FRP imparts passive confinement to the column, improves the axial stiffness, reduces lateral expansion for given load levels, allows the column to reach higher stress and strain levels than the unwrapped columns. Recent years have seen a substantial increase in the adoption of seismic retrofit using FRP materials among the civil engineering community. The current state of using FRP materials as a retrofitting strategy for structures not built to withstand seismic activity is presented in this study in a representative overview. It provides an overview of the applications and range of FRP materials in seismic retrofitting plans for RC structures. The study also discusses the benefits, design principles, and restrictions of FRP applications for seismic retrofit. A case study revealed that using the FRP strengthening method improved the performance of the existing structure. Aesthetic appearance of the building maintained and also improved the strength aspects. After rehabilitation the structure requires less maintenance due to adherence of FRP laminates.

Uncertainty‐aware structural damage warning system using deep variational composite neural networks

AbstractStructural health monitoring (SHM) is, without a doubt, one of the most important assets for building resilient communities. The vast and rapidly advancing research in data science and machine learning has provided researchers in the civil engineering community with various tools that can facilitate the processing of significant amounts of gathered data. However, deep learning models are prone to mistakes, and with the catastrophic consequences that can happen due to damage misidentification, damage diagnosis models’ predictions should not be taken for granted. In this study, we present an uncertainty‐aware early‐warning system that can provide near real‐time SHM. The system utilizes a deep composite encoder‐decoder network that combines elements from convolutional neural networks, recurrent neural networks, and variational inference (VI) to provide damage index distributions. The framework can detect anomalies in the structural system during seismic events and provide a measure of uncertainty that can be used to question the model's predictions. To assess the system's validity and practicality, we apply our proposal to three real structures, two of which suffered damage during the 1994 Northridge earthquake. We found that the early warning system delivers an accurate, yet cautious, continuous monitoring that is capable of sending warning signals when damage occurs in the course of seismic events. Source code is available at: https://github.com/keltouny/VSCAN.

Characterizing Data Sharing in Civil Infrastructure Engineering: Current Practice, Future Vision, Barriers, and Promotion Strategies

Data sharing between different organizations is critical in supporting decision making in civil infrastructure engineering projects (e.g., transportation projects). Understanding the characteristics of data-sharing-related factors in civil infrastructure engineering is crucial for the civil engineering community to identify the priorities in promoting data sharing. The ASCE Data Sensing and Analysis (DSA) Committee initiated an investigation on data-sharing barriers in civil infrastructure engineering. This work produced (1) a classification of data-collection and data-use contexts in the domain of civil infrastructure engineering; (2) a comprehensive classification of data-sharing barriers and data-sharing promotion strategies in this domain; and (3) a synthesis of the opinions about the current practices, future vision, barriers, and data-sharing promotion strategies from civil infrastructure professionals and researchers using an online survey. The survey results revealed that (1) more data-sharing activities are occurring within the organizations, such as academia, government agencies, and for-profit corporations, compared with data exchanges among these communities; (2) “if there is a cost sharing in the data sharing,” is the condition that makes data providers more willing to share data with others; and (3) compared with technology improvements, the protocol of data sharing in the business domain has more potential in promoting data sharing. Meanwhile, this research identified the top five priorities among 20 data-sharing promotion strategies, which are protocol in industry and organization, data-standard regulation, data validity, data security protection, and large-scale data-sharing technology. These five priorities play critical roles in a roadmap showing how policy, business models, and technical solutions should cooperate to promote data sharing in civil infrastructure engineering.

Emerging steel frames with Fe-SMA U-shaped dampers for enhancing seismic resilience

Post-earthquake financial loss of structures induced by residual inter-story deformation (RID) has been recently noticed and various strategies have been proposed. A newly-emerged energy-dissipation material, namely, iron-based shape-memory-alloy (Fe-SMA), has gain favor in civil engineering community due to its extraordinary low-cycle fatigue resistance property. Besides, Fe-SMA is believed to help improve structure’s post-earthquake residual inter-story deformation control capacity due to its moderate strain hardening behavior and pseudo-elasticity. This study explores the performance of emerging steel frame systems equipped with energy-dissipation devices fabricated with Fe-SMA. In particular, a brace with built-in Fe-SMA-based U-shaped strips (USSs) is employed serving as the energy-dissipation devices in the proposed system. In this paper, the basic mechanical properties of Fe-SMA are discussed firstly, followed by a description of the working principle of the USSs. The hysteresis behavior of two types of USSs, fabricated with Fe-SMA and conventional mild steel (Q235), were investigated experimentally. Based on the test results, numerical models for the prototype braces equipped with USSs are established using ABAQUS and OpenSEES, and the necessary key material parameters are calibrated. Subsequently, system-level analysis is performed on 5-story prototype steel buildings. Specially, two types of steel frames, i.e., frames with high-strength-steel columns and frames with conventional structural steel-based columns, are established. Concurrently, braces with Fe-SMA-based USSs as well as mild steel-based USSs are considered. The results demonstrated that the Fe-SMA-based energy-dissipation devices along with the steel frames with high-strength-steel columns can provide the most satisfied RID control effectiveness compared with the other yielding structural systems investigated in this paper.

Biochar as bioretention systems for water quality improvement in Malaysia

Rapid urbanization and constant development of infrastructure in the civil engineering community has accelerated in the past decades. However, there has been a reduction of permeable surfaces for rainwater and surface runoff to escape, raising concerns regarding flooding and water quality especially in Malaysia where the tropical climate and heavy rainfall applies pressure on the bioretention systems. To lessen the issue, this paper will be looking into biochar’s benefits in bioretention systems focussing on the type of biochar which will be most suited in improving water quality. In particular, two types of biochar were compared such as rice husk biochar and palm biochar to be tested as bioretention system and different water samples were run through them. Various water quality parameter tests were conducted to evaluate biochar’s performance in reducing pollutants and contaminants from the water samples and thus enable to draw a conclusion on which is the most effective for bioretention use. With a deeper understanding of biochar’s capabilities and limitations, stormwater management strategies can be improved to make the construction industry more sustainable.

A review on damage detection techniques to enhance the sustainability of concrete infrastructures

Over the past twenty-four years, there has been a lot of interest in the condition assessment of civil engineering infrastructures made of concrete. For the purpose of identifying damage, various traditional non-destructive techniques, such as electromagnetic impedance, microwave imaging, impulse response and many others have been used extensively. However, a thorough review of current research on developments in damage detection methods for concrete-made infrastructures using techniques based on wave propagation, vibration, and combined wave and vibration is not yet provided. This paper uses an approach that incorporates systematic analyses of research work related to the damage detection of civil infrastructures to address the aforementioned limitations and add to the body of knowledge. In this study, the state-of-the-art of wave propagation, vibration, and combined wave and vibration, based techniques for damage identification in concrete, based civil infrastructure are described along with models' contributions, weaknesses, methodologies, and critiques. The study makes use of the ScienceDirect database. The systems include concrete based, bridges, dams, tunnels, multi-storey buildings, and other civil structures like treatment facilities and underground pipes. Finally, recommendations for future research directions are made to assist the civil engineering community in determining the critical areas that need to be investigated in the coming years.

Comparisons between non-interferometric and interferometric passive surface wave imaging methods—towards linear receiver array

SUMMARYPassive seismic methods in highly populated urban areas have gained much attention from the geophysics and civil engineering communities. Linear arrays are usually deployed for passive surface wave investigations because of their high convenience, and passive surface wave imaging methods commonly used for linear arrays can be grouped as non-interferometric methods (e.g. passive multichannel analysis of surface wave, refraction microtremor) and interferometric methods (e.g. multichannel analysis of passive surface waves and spatial autocorrelation). It is well known that the seismic interferometry method is able to retrieve Green’s function between inter-station pairs based on passive seismic data and that is how interferometric methods work. Although non-interferometric methods are also popular and effective in near-surface seismic imaging, particularly in the geotechnical industry, there is no theoretical proof to clarify the accuracy and/or the bias of these methods. In this study, we use numerical derivations and simulations to demonstrate the underlying physics for both non-interferometric and interferometric methods, under two common noise source environments including a homogeneous source distribution and a dominant in-line source distribution. We also prove the strength of interferometric methods for accurate dispersion imaging over the non-interferometric methods, and provide a way to estimate the biases in non-interferometric measurements. Finally, we present comprehensive comparisons between different passive surface wave methods with three typical field examples considering various observation systems.