Hasil untuk "Bridge engineering"

Y. Lei, Bin Yang, Xinwei Jiang et al.

Abstract Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to machine fault diagnosis. This is a promising way to release the contribution from human labor and automatically recognize the health states of machines, thus it has attracted much attention in the last two or three decades. Although IFD has achieved a considerable number of successes, a review still leaves a blank space to systematically cover the development of IFD from the cradle to the bloom, and rarely provides potential guidelines for the future development. To bridge the gap, this article presents a review and roadmap to systematically cover the development of IFD following the progress of machine learning theories and offer a future perspective. In the past, traditional machine learning theories began to weak the contribution of human labor and brought the era of artificial intelligence to machine fault diagnosis. Over the recent years, the advent of deep learning theories has reformed IFD in further releasing the artificial assistance since the 2010s, which encourages to construct an end-to-end diagnosis procedure. It means to directly bridge the relationship between the increasingly-grown monitoring data and the health states of machines. In the future, transfer learning theories attempt to use the diagnosis knowledge from one or multiple diagnosis tasks to other related ones, which prospectively overcomes the obstacles in applications of IFD to engineering scenarios. Finally, the roadmap of IFD is pictured to show potential research trends when combined with the challenges in this field.

G. Baxter, I. Sommerville

D. Chattopadhyay, K. Raju

A. Blake, N. Champness, P. Hubberstey et al.

Hongnan Li, Dong-sheng Li, G. Song

J. Beck, Zhishen Wu

Dong Wang, Zuchao Liang, Guanghe Li et al.

Abstract Excavation is one of the key factors inducing slope instability in open-pit mines, particularly for intermediate bridge-supported slopes subjected to dual excavation disturbances. Improper handling of such conditions may lead to large-scale landslides. Therefore, it is essential to investigate the instability evolution mechanism of intermediate bridge-supported slopes under dual excavation conditions. In this study, the southern slope of the Zhahanaoer Open-Pit Coal Mine was selected as the research area, and a physical model of the intermediate bridge-supported slope capable of simulating eight excavation stages was constructed. Field monitoring was conducted using non-reflective cameras, earth pressure sensors, and a distributed optical fiber system to analyze the evolution characteristics of cracks, surface deformation, internal strain, and stress in the slope model during excavation. The reliability of the physical model tests was validated by comparing the results with field landslide cases using numerical simulation techniques. The results indicate that internal strain precedes surface displacement in predicting or inferring slope instability and can serve as an early warning indicator for landslides. The failure process of the intermediate bridge-supported slope model can be divided into five stages: crack initiation, crack propagation, deformation onset, crack penetration, and local and global instability on both sides of the intermediate bridge. Furthermore, excavation significantly increases the height of the arched failure surface on both sides compared to its span, and the increase in the height-to-span ratio is a critical characteristic of failure surface evolution. These findings provide a prerequisite for related slope stability analyses, intermediate bridge demolition engineering design, and slope remediation projects.

Zhenquan Zhou, Xiang Fan, Yuping Kou et al.

Modular construction is generally defined as a typical offsite construction approach that can improve environmental sustainability throughout the building project lifecycle. Based on this situation, identifying the strengths, weaknesses, opportunities, and threats (SWOT) while promoting this sustainable construction method effectively during the urbanisation process is essential. Generally, modular construction is a sustainable building approach that can improve project sustainability, considering the environmental, social, economic, and technological aspects. A comprehensive understanding of the basic situation of prefabricated construction is worthwhile to ensure the widespread adoption of this offsite building method. By employing the SWOT analytical framework, this study adopts a literature review approach to conduct the investigation. In terms of the project results, the core strengths of using modular construction include improving environmental sustainability, enhancing management effectiveness, and improving construction safety and quality. The major weaknesses, on the other hand, are a lack of expertise and research, excessively high initial costs, and difficulties in stakeholder coordination. On the other hand, the major opportunities include promoting the SDGs and other policies, the Industrial Revolution 4.0, and urbanisation and building demands. The main threats, however, include substitute construction technologies, imperfect building codes and standards, and a lack of social and market acceptance. Further research can increase the sample size and collect more accurate firsthand data to validate the results of the current investigation, which can increase the effectiveness of promoting modular construction in the targeted regions.

Daniel Attinger, C. Frankiewicz, A. Betz et al.

Owing to advances in micro- and nanofabrication methods over the last two decades, the degree of sophistication with which solid surfaces can be engineered today has caused a resurgence of interest in the topic of engineering surfaces for phase change heat transfer. This review aims at bridging the gap between the material sciences and heat transfer communities. It makes the argument that optimum surfaces need to address the specificities of phase change heat transfer in the way that a key matches its lock. This calls for the design and fabrication of adaptive surfaces with multiscale textures and non-uniform wettability. Among numerous challenges to meet the rising global energy demand in a sustainable manner, improving phase change heat transfer has been at the forefront of engineering research for decades. The high heat transfer rates associated with phase change heat transfer are essential to energy and industry applications; but phase change is also inherently associated with poor thermodynamic efficiency at low heat flux, and violent instabilities at high heat flux. Engineers have tried since the 1930s to fabricate solid surfaces that improve phase change heat transfer. The development of micro and nanotechnologies has made feasible the high-resolution control of surface texture and chemistry over length scales ranging from molecular levels to centimeters. This paper reviews the fabrication techniques available for metallic and silicon-based surfaces, considering sintered and polymeric coatings. The influence of such surfaces in multiphase processes of high practical interest, e.g., boiling, condensation, freezing, and the associated physical phenomena are reviewed. The case is made that while engineers are in principle able to manufacture surfaces with optimum nucleation or thermofluid transport characteristics, more theoretical and experimental efforts are needed to guide the design and cost-effective fabrication of surfaces that not only satisfy the existing technological needs, but also catalyze new discoveries.

Miao Su, Lei Liu, Yuxi Xie et al.

The mechanical properties of unidirectional carbon fiber reinforced polymer (UD-CFRP), such as its elastic modulus and ultimate strength, are crucial and fundamental indicators. Examining these properties from a microscopic perspective through numerical simulations can provide valuable insights for material modification and the design of new materials. This study employs a micromechanics-based representative volume element (RVE) method to predict the macroscopic mechanical properties of UD-CFRP. The results demonstrate that the established RVE models accurately predict the elastic and shear modulus, as well as the ultimate tensile and compressive strength of UD-CFRP. Additionally, simulations of 300 RVE models with varying input parameter combinations were performed, generating a dataset that encompasses both microstructure parameters and macroscopic mechanical properties of UD-CFRP. Using the dataset, random forest regression models were created and SHAP analysis was performed to identify the key microstructural parameters with significant feature importance. Subsequently, we systematically investigated their effects on the macroscopic mechanical properties of UD-CFRP. In the end, simplified analytical prediction formulas were proposed to evaluate the macroscopic mechanical properties of UD-CFRP, demonstrating superior predictive performance compared to existing formulas.

Jake M. Jackman, Naiara Guimarães Sales, Chiara Benvenuto et al.

ABSTRACT Environmental DNA (eDNA)‐based monitoring has become an established and efficient method for surveying biodiversity in aquatic systems. However, there is a need to compare and standardize sampling methods across different ecosystem types, particularly complex ecosystems such as estuaries, where unique challenges exist for monitoring fish populations due to fluctuating environmental factors. Here, we compare species richness obtained from eDNA metabarcoding data using four different eDNA filtration methods: three manual filtration methods with different pore sizes (0.45, 1.2, and 5 μm) and a newly established passive method, the metaprobe. The study was applied across a salinity gradient in a hyper‐tidal estuarine ecosystem. Overall, 44 fish species were detected across the four methods used. The 0.45 μm filter recovered the highest richness (39 species), then the metaprobe method (35), followed by the 1.2 μm (34) and 5 μm (33) filters. Filter performance between salinity gradients revealed that the 0.45 μm and the 1.2 μm methods recovered the highest species richness across all sampled zones. The 0.45 μm also had the most consistent detection probabilities using representative species from each zone. While the 0.45 μm method appeared to be the optimal method, each of the methods can be considered a viable and comparable option for biomonitoring in dynamic ecosystems such as estuaries and rivers. In particular, the passive metaprobe (used in a freshwater system for the first time here) performed well in comparison to the manual filtering methods despite a short deployment time. This study provides critical insights for optimizing fish diversity assessments using eDNA metabarcoding in estuarine ecosystems, providing a valuable framework for future monitoring efforts in similar systems worldwide.

Liang Tang, Xiao-Bei Liu, Yi-Jun Liu et al.

Abstract As the primary variable load of bridges, vehicle load is an important parameter for bridge health monitoring. However, traditional Weigh-in-Motion (WIM) systems and the commonly used method of placing sensors on the bridge are challenging to apply in load monitoring for many small and medium-sized bridges. Therefore, this paper proposes a bridge vehicle load identification method based on traffic surveillance video data. Leveraging the surveillance video data on the bridge, without introducing additional hardware devices, the displacement of target points is detected through sub-pixel level image detection algorithms, enabling non-contact measurement of bridge structural response through imaging. A spatiotemporal relationship model of structural displacement, vehicle load, and load distribution is established to solve for vehicle load. Finally, model bridge tests under various loading conditions and engineering practice experiments are conducted to validate the feasibility of the method. The results of the model bridge tests show that the structural displacement measured using traffic video measurement has a deviation of less than 10% compared to the measurements obtained using contact displacement sensors (LVDT), and it can accurately reflect the displacement characteristics of the structure. The results of the field tests demonstrate that the average estimation deviation for heavy vehicle loads ranging from 12 to 18 tons is approximately 18%, meeting the engineering requirements. The proposed method can provide load statistical information for the extensive health monitoring of small and medium-sized bridges and offer a new technical pathway for obtaining bridge load information.

B. Zou, Shu Jian Chen, A. H. Korayem et al.

G. Danezis, J. Domingo-Ferrer, M. Hansen et al.

Privacy and data protection constitute core values of individuals and of democratic societies. There have been decades of debate on how those values -and legal obligations- can be embedded into systems, preferably from the very beginning of the design process. One important element in this endeavour are technical mechanisms, known as privacy-enhancing technologies (PETs). Their effectiveness has been demonstrated by researchers and in pilot implementations. However, apart from a few exceptions, e.g., encryption became widely used, PETs have not become a standard and widely used component in system design. Furthermore, for unfolding their full benefit for privacy and data protection, PETs need to be rooted in a data governance strategy to be applied in practice. This report contributes to bridging the gap between the legal framework and the available technological implementation measures by providing an inventory of existing approaches, privacy design strategies, and technical building blocks of various degrees of maturity from research and development. Starting from the privacy principles of the legislation, important elements are presented as a first step towards a design process for privacy-friendly systems and services. The report sketches a method to map legal obligations to design strategies, which allow the system designer to select appropriate techniques for implementing the identified privacy requirements. Furthermore, the report reflects limitations of the approach. It concludes with recommendations on how to overcome and mitigate these limits.

Gholam Ali Shafabakhsh, Mostafa Sadeghnejad, Sajad Alizadeh

In recent years, several factors such as the increasing traffic loads and increasing number of vehicles have intensified the stress in pavement layers and thus reduced the service life of asphalt pavements. Today, with rising maintenance costs and traffic loads on asphalt pavements, researchers have paid more attention to diminishing defects such as cracks due to fatigue, temperature, moisture, and rutting as the most significant structural failures in asphalt pavements. The mentioned failures reduce road safety and service level during the operation period and impose huge costs on governments. In this study, we review recent research on nanotechnology applications to improve the performance of asphalt mixtures against these failures. Reviewing research suggests that different nanomaterials can improve the performance of bitumen and asphalt mixtures against cracking and rutting due to their structural properties.

Jiawei Wang, Hongshuai Gao, Kexin Zhang et al.

The bridge horizontal swivel system generally adopts a symmetrical structure and uses a spherical hinge structure that can adjust the rotation to complete rotation construction. Because of the complexity of railway lines under bridges, some asymmetrical horizontal swivel systems have been increasingly applied in practical engineering in recent years. This system is more suitable for areas with complex railway lines, reduces the bridge span, and provides better economic benefits. However, it is also extremely unstable. In addition, instability can easily occur under dynamic loads, such as earthquake action and pulsating wind effects. Therefore, it is necessary to study their mechanical behavior. Based on the horizontal swivel system of an 11,000-ton asymmetric continuous girder bridge, the dynamic response of the horizontal swivel system to seismic action was studied using the finite element simulation analysis method. Furthermore, using the Peer database, seismic waves that meet the calculation requirements are screened for time-history analysis and compared to the response spectrum method. The mechanical properties of the structural system during and after rotation were obtained through calculations. During rotation, the seismic response of the structure is greater. To reduce the calculation time cost, an optimization algorithm based on the mode shape superposition method is proposed. The calculation result is 87% that of the time-history analysis, indicating a relatively high calculation accuracy.

Audrius Vaitkus, Judita Gražulytė, Andrius Baltrušaitis et al.

Properly designed and maintained asphalt pavements operate for ten to twenty-five years and have to be rehabilitated after that period. Cold in-place recycling has priority over all other rehabilitation methods since it is done without preheating and transportation of reclaimed asphalt pavement. Multiple researches on the performance of cold recycled mixtures have been done; however, it is unclear how the entire pavement structure (cold recycled asphalt pavement overlaid with asphalt mixture) performs depending on binding agents. The main objective of this research was to evaluate the performance of cold in-place recycled asphalt pavements considering binding agents (foamed bitumen in combination with cement or only cement) and figure out which binder leads to the best pavement performance. Three road sections rehabilitated in 2000, 2003, and 2005 were analysed. The performance of the entire pavement structure was evaluated in terms of the International Roughness Index, rut depth, and pavement surface distress in 2013 and 2017.

Qian Dong, Xinping Li, Yongsheng Jia et al.

The initial stresses have a strong effect on the mechanical behavior of underground rock masses, and the initial stressed rock masses are usually under strong dynamic disturbances such as blasting and earthquakes. The influence mechanism of a blasting excavation on underground rock masses can be revealed by studying the propagation of stress waves in them. In this paper, the improved Mohr-Coulomb elasto-plastic constitutive model of the intact rock considering the initial damage was first established and numerically implemented in Universal Distinct Element Code (UDEC) based on the variation of the experimental stress wave velocity in the initial stressed intact rock, and the feasibility of combining the established rock constitutive model and the BB (Bandis-Barton) model which characterizes the nonlinear deformation of the joints to simulate stress waves across jointed rock masses under initial stress was validated by comparing the numerical and model test results subsequently. Finally, further parameter studies were carried out through the UDEC to investigate the effect of the initial stress, angle, and number of joints on the transmission of the blasting stress wave in the jointed rock mass. The results showed that the initial stress significantly changed the propagation of the stress waves in the jointed rock mass. When the initial stress was small, the transmission coefficients of the stress waves in the jointed rock were vulnerable to be influenced by the variation of the angle and the number of joints, while the effect of the angle and the number of joints on the stress wave propagation gradually weakened as the initial stress increased.

Jennifer Fouquier, Nancy Moreno Huizar, Jody Donnelly et al.

ABSTRACT Research relating gut microbiome composition to autism spectrum disorders (ASD) has produced inconsistent results, indicative of the disorder’s complexity and the need for more sophisticated experimental designs. We address this need by (i) comparing gut microbiome composition between individuals with ASD and neurotypical controls in Arizona and Colorado using standardized DNA extraction and sequencing methods at both locations and (ii) longitudinally evaluating the gut microbiome’s relationship to autism behavioral severity, diet, and gastrointestinal symptoms. Gut microbiome composition differed between individuals in Arizona and individuals in Colorado, and gastrointestinal symptoms were significantly higher in ASD individuals than in neurotypical individuals in Arizona but not in Colorado. Gut microbiome composition was significantly associated with ASD while controlling for study-site location but not when controlling for gastrointestinal symptoms. This suggests that non-ASD-related study site differences in gut microbiome composition and different degrees of gastrointestinal symptoms involvement with ASD between sites may contribute to inconsistent results in the literature regarding the association between gut microbiome composition and ASD. In the longitudinal analysis, we found that difference in levels of lethargy/social withdrawal measured in individuals at different time points correlated with the degree of change in gut microbiome composition and that a worsening of inappropriate speech between time points was associated with decreased gut microbiome diversity. This relationship between changes in the gut microbiome composition within individuals and ASD behavioral severity metrics indicates that longitudinal study designs may be useful for exploring microbial drivers of ASD severity when substantial variability exists in baseline microbiome compositions across individuals and geographical regions. IMPORTANCE Autism spectrum disorder (ASD) is a brain developmental disorder with varying behavioral symptom severity both across individuals and within individuals over time. There have been promising but also inconsistent literature results regarding how the gut microbiota (microbiome) may be involved. We found that the gut microbiome in individuals with ASD is affected by study-site location as well as gastrointestinal symptom severity. When we sampled some individuals with ASD at several different time points, we found that some behaviors, such as lethargy/social withdrawal and inappropriate speech, changed along with changes in the gut microbiota composition. This is the first study to relate severity of behavior symptoms to gut microbiome composition within individuals over time and suggests a dynamic relationship between ASD-associated symptoms and gut microbes. Longitudinal study designs as well as collaborative efforts across multiple centers are needed to fully characterize the relationship between ASD and gut microbes.

Christian Gallegos-Calderón, Javier Naranjo-Pérez, Iván M. Díaz et al.

Due to the high strength-to-weight ratio of fibre reinforced polymers (FRPs), human-induced vibration problematic remains as a subject to be fully comprehended in order to extend the use of composites in Bridge Engineering. Thus, this paper studies an ultra-lightweight FRP footbridge, which presents excessive vertical vibrations when the fourth harmonic of a walking pedestrian is synchronised with the structure’s fundamental frequency. Focusing on the vertical bending mode, at 7.66 Hz, the bridge dynamic behaviour was assessed under the action of a single pedestrian crossing the facility at a step frequency of 1.9 Hz. As an over prediction of the footbridge response was computed using a moving force (MF) model available in a design guideline, a mass-spring-damper-actuator (MSDA) system was adopted to depict a walker. Hence, Human-Structure Interaction (HSI) phenomenon was considered. Employing the experimental results, parameters of the MSDA system were identified, leading to a HSI model that considers the first fourth harmonics of a walking human. Additionally, a parametric analysis was carried out, determining that the damping ratio of the human body and the load factor associated to the fourth harmonic are the most relevant parameters on the estimation of the response. The identified HSI model may be used as a first approximation to accurately predict the dynamic response of ultra-lightweight composite structures and should be extended to account for crowd-induced loads.