Sandro Doboviček, Elvis Krulčić, Duško Pavletić
et al.
This paper presents a concept for a Learning Factory (LF) designed for interdisciplinary engineering education. Learning factories are experiential learning environments that bridge the gap between theory and practice while supporting the demands of digital transformation. The proposed LF concept was developed using an integrated approach that assessed stakeholder needs and reviewed institutional infrastructure and capacity. These inputs were triangulated into a concept consisting of five core thematic components: Lean processes as an educational anchor, Enterprise Resource Planning (ERP) systems, Internet of Things (IoT)-based integration, simulation, and physical prototyping. Validation workshops with Small- and Medium-sized Enterprise (SME) managers, academic experts, and students confirmed the perceived relevance of this structure and its potential. The resulting concept focuses on practice-orientated, team-based learning methods that are in line with the principles of Education 4.0. The design sets goals in four key dimensions: educational integration, technological readiness, industrial relevance with SME orientation and flexibility and scalability. These design principles and practical insights can be utilized for future academic implementations of learning factories.
LiDAR is an essential tool for terrain data acquisition; however, its application in coastal environments is often limited by negative outliers caused by multipath reflections. The negative outliers can result in deviations of several meters, significantly complicating subsequent data processing and analysis. This article investigates the retroreflective characteristics of negative outliers in terms of spatial structure and intensity and presents a negative outlier removal algorithm based on these features. First, the LiDAR surveying equation is introduced to establish the intensity relationship between negative outliers and their corresponding preliminary reflection points. Second, by analyzing the spatial distribution of point clouds, a covariance matrix is generated, and eigenvalue decomposition is performed to extract structural descriptors for identifying outliers. Third, a terrain mesh model is constructed to approximate the retroreflective surface, enabling a feature-based comparison between negative outliers and their preliminary reflection points. Finally, points below the terrain mesh and their corresponding reflection points are extracted. By comparing their structural similarity and intensity relationships, negative outliers are accurately identified and removed. Experimental results validate the effectiveness of the proposed algorithm, achieving a precision of 88.97% and a recall of 91.94%, ensuring robust outlier removal while preserving terrain details.
Direct laser emission in the green–yellow spectral range remains a major challenge in semiconductor laser development due to material limitations. This study explores the formation dynamics and optical characteristics of CdSe quantum dots (QDs) induced by electron-beam irradiation as a strategy to bridge this spectral gap. Time-resolved diffraction analysis reveals that QD nucleation initiates rapidly within one minute of irradiation, with the formation rate strongly influenced by beam intensity. Spatially resolved photoluminescence (PL) and transmission electron microscopy measurements show distinct growth behaviors: enhanced Cd diffusion at the center of irradiated regions leads to smaller QDs and blueshifted emission, while Cd accumulation at the edges promotes larger QDs and redshifted emission. Under saturated irradiation conditions, the PL peak wavelength stabilizes within the 573–581 nm range, independent of initial CdSe thickness, indicating a self-regulating atomic rearrangement process. This convergence highlights the robustness of the electron-beam-induced QD formation mechanism, which enables wavelength-specific control over emission properties. The ability to engineer QDs with emission wavelengths spanning the green–yellow range demonstrates the potential of this approach for realizing compact, multi-wavelength optoelectronic devices. These findings establish electron-beam irradiation as a versatile tool for precise nanostructure engineering and spectral tuning in advanced photonic applications.
In this study, the active vibration control (AVC) of a cantilever beam with an end mass is considered first and studied experimentally and through simulation. The Laplace transform method, Newmark method, and ANSYS are used for simulations. An impulse force applied to the mass and the velocity actuation applied to the base are assumed to be disturbance and controlling input, respectively. The displacement of the mass is taken as the feedback signal in simulations. Four strain gauges are located near the bottom point, connected with a Wheatstone bridge, and the output voltage of a load-cell amplifier (LCA) is used as the feedback signal in experiments. Strain feedback is considered in experiments because it is easy to implement, cost-effective, and can be used in applications. Experimental displacement signals obtained from the top of the beam are compared with the output signals from LCA and it is observed that they are approximately linearly dependent. Velocity input is generated with a servo motor-driven linear actuator in experiments. The closed loop control is achieved by a personal computer with an Adlink-9222 PCI DAQ card and a C program in the experiments. The integration of the closed loop control action into the transient solution with Newmark method and ANSYS is implemented in simulations. The input reference value is taken as zero for vibration control. The instantaneous value of the feedback signal at a time step is subtracted from zero to find the error signal value and the error value is multiplied by the control gain to calculate the controlling signal. The simulation results obtained with the Newmark method and ANSYS are in good agreement with the analytical results obtained with Laplace transform method. Simulation results are also in acceptable agreement with the experimental results for explaining the behavior of the success of AVC depending on the control gain, K<sub>p</sub>. After verifying ANSYS solutions, the ANSYS procedure is applied to an aircraft wing as a real complex cantilever structure. The wing, with a length of 810.8 mm, 13 ribs with a length of 300 mm, and NACA 4412 airfoil, is considered in this study. It is observed that the AVC of real engineering structures can be simulated by integrating control action into transient solution in ANSYS.
This research focuses on the impact of smoke exhaust volume and smoke vent layout, which are two crucial factors affecting the smoke control efficiency in tunnels, on the smoke exhaust effect in tunnel fires. Numerical simulation methods are employed to investigate the impact of changing the smoke exhaust volume and the smoke vent number on the smoke exhaust performance in a curved tunnel with a ceiling centralized smoke exhaust system. This research primarily examines the length of the smoke distribution, the smoke temperature under the ceiling, the vertical visibility, and the exhausted smoke mass flow rate. The findings indicate that, in a tunnel with a single-side ceiling centralized smoke exhaust mode, an imbalance in smoke distribution occurs between the upstream and downstream of the fire source. The upstream area experiences a higher amount of smoke, while the downstream area has thinner smoke. Increasing the smoke exhaust volume yielded positive effects on smoke control, as evident in the reduced the smoke spread range, and improved the smoke exhaust efficiency. The influence of changing smoke vent number on the smoke exhaust effect was dependent on the smoke exhaust volume. When the smoke exhaust volume was excessive, altering the number of smoke vents had a minimal impact on smoke exhaust, while in cases with small smoke exhaust volumes, changes in smoke vent numbers obviously influenced the smoke control effect. Therefore, selecting an appropriate smoke exhaust volume and raising the smoke vent number can effectively optimize the performance of the ceiling centralized smoke exhaust system.
ABSTRACTCarbon fiber reinforced polymer (CFRP) can be applied for bridge cables due to its excellent properties. As the important load-bearing structural component, real-time force monitoring of the CFRP cable is required. This paper presents a new smart CFRP cable that combines the self-sensing rods with embedded sensors and the anchorage system using extrusion technology. By embedding optical fiber (OF) and coaxial cable Fabry-Perot interferometer (CCFPI) into CFRP rods respectively, two types of self-sensing rods (CFRP-OF rod and CFRP-CCFPI rod) were fabricated. A new anchorage unit using an extrusion process was proposed as a basic component of smart CFRP cables. Anchorage units holding a CFRP-OF rod and a CFRP-CCFPI rod were tested to obtain their sensing and mechanical properties. Three anchorage units were assembled to form a smart CFRP cable with self-sensing functionality. A verification test was carried out to confirm the capability of monitoring the cable force. The test results demonstrate that the smart CFRP cable composed of multiple anchorage units has good potential in bridge engineering.
Materials of engineering and construction. Mechanics of materials
Shallow bias tunnels are sensitive at the entrance section, where the existence of soil–rock interface (SRI) results in more complex deformation of surrounding rock and supporting structure. This study investigates the mechanical properties of surrounding rock and supporting structure of a shallow-buried bias tunnel crossing the soil–rock interface by a combination of model tests and numerical simulations. A shallow-buried biased tunnel with significant cracking at its entrance section is selected in southwest China. The plastic zone distribution, deformation, and pressure of surrounding rock, as well as the stress and deformation of supporting structure, are analyzed under different conditions with the tunnel vault, arch haunch, arch spring, and wall foot crossing the soil–rock interface. The test and numerical results show that the internal force of the lining structure is the largest at the left arch haunch and the right arch spring, with cracks occurring in the project. The surrounding rock and supporting structure are most prominently influenced by the arch haunch and arch spring crossing the soil–rock interface among different positions of the tunnel. The supporting structure is subjected to stress in three modes: there is mainly shearing when the tunnel vault passes through the soil–rock interface, extrusion and shearing co-exist when the tunnel arch haunch and arch spring pass through the soil–rock interface, and extrusion is dominant when the tunnel wall foot passes through the soil–rock interface. Inserting grouting steel pipes perpendicular to the soil–rock interface on the deep-buried side of the tunnel can effectively control the deformation of surrounding rock and the stress of supporting structure.
To ensure the safety and rational use of bridge traffic lines, the existing bridge structural damage detection models are not perfect for feature extraction and have difficulty meeting the practicability of detection equipment. Based on the YOLO (You Only Look Once) algorithm, this paper proposes a lightweight target detection algorithm with enhanced feature extraction of bridge structural damage. The BIFPN (Bidirectional Feature Pyramid Network) network structure is used for multi-scale feature fusion, which enhances the ability to extract damage features of bridge structures, and uses EFL (Equalized Focal Loss) to optimize the sample imbalance processing mechanism, which improves the accuracy of bridge structure damage target detection. The evaluation test of the model has been carried out in the constructed BDD (Bridge Damage Dataset) dataset. Compared with the YOLOv3-tiny, YOLOv5S, and B-YOLOv5S models, the mAP@.5 of the BE-YOLOv5S model increased by 45.1%, 2%, and 1.6% respectively. The analysis and comparison of the experimental results prove that the BE-YOLOv5S network model proposed in this paper has a better performance and a more reliable performance in the detection of bridge structural damage. It can meet the needs of bridge structure damage detection engineering with high requirements for real-time and flexibility.
Abstract A new self-centering concrete bridge column has been developed by the authors. The proposed bridge column uses unstressed partially unbonded seven-wire steel strands as elastic elements to reduce the residual displacement of the column after a strong earthquake. This research aimed to study the effect of concrete cover thickness ratio on the cyclic behavior of the proposed column. Four large-scale column specimens were tested using lateral cyclic loading. One column was the conventional concrete bridge column. The other three columns were the proposed self-centering bridge columns with varying concrete cover thickness ratios. Test results showed that partial unbonding effectively prevented the strands from yielding. The proposed columns showed post-yield stiffness ratios higher than the conventional column. The concrete cover thickness ratio did not significantly influence the hysteretic energy dissipation and the strain responses of longitudinal reinforcement. However, it had a significant impact on the post-yield stiffness ratio. The post-yield stiffness ratio of the proposed column tended to be inversely proportional to the concrete cover thickness ratio. A relationship was proposed between the concrete cover thickness ratio and the post-yield stiffness ratio for the preliminary design of the proposed column. Based on the relationship, the cover concrete thickness ratio should not exceed 5.1% to achieve a post-yield stiffness ratio of at least 5%, as recommended in the literature to control the residual displacement of a column.
Abstract A prominent challenge in performance-based earthquake engineering is to select a suitable set of ground motions records with which to perform probabilistic seismic assessment of structures. The most common approach for engineering purposes is to employ actual recordings of worldwide events, given that large earthquakes do not occur frequently hence regional recordings of such events are usually not widely available. To address this not that uncommon issue, regionally simulated ground motions using a stochastic finite-fault method have been proposed as an alternative to real records. This study aims to explore the use of simulated records through a stochastic finite-fault method in probabilistic seismic assessment frameworks for reinforced concrete bridges, when compared to using real records. Direct seismic losses for a case-study existing bridge and a bridge portfolio are estimated and compared, as the reference risk metric. Finally, the similarities between seismic demands, obtained using both real and simulated record sets, are quantified and discussed via statistical hypothesis testing, resulting fragility curves and expected annual losses. The results show how simulated records can be a promising alternative to real records, becoming particularly useful in the absence of available recorded ground motions with specific seismogenic features.
Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian
Automatic Speech Recognition (ASR) is widely used in many applications and tools. Smartphones, video games, and cars are a few examples where people use ASR routinely and often daily. A less commonly used, but potentially very important arena for using ASR, is the health domain. For some people, the impact on life could be enormous. The goal of this work is to develop an easy-to-use, non-invasive, inexpensive speech-based diagnostic test for dementia that can easily be applied in a clinician’s office or even at home. While considerable work has been published along these lines, increasing dramatically recently, it is primarily of theoretical value and not yet practical to apply. A large gap exists between current scientific understanding, and the creation of a diagnostic test for dementia. The aim of this paper is to bridge this gap between theory and practice by engineering a practical test. Experimental evidence suggests that strong discrimination between subjects with a diagnosis of probable Alzheimer’s vs. matched normal controls can be achieved with a combination of acoustic features from speech, linguistic features extracted from a transcription of the speech, and results of a mini mental state exam. A fully automatic speech recognition system tuned for the speech-to-text aspect of this application, including automatic punctuation, is also described.
Angel Santiago Fernandez-Bou, Angel Santiago Fernandez-Bou, Angel Santiago Fernandez-Bou
et al.
Frontline communities of California experience disproportionate social, economic, and environmental injustices, and climate change is exacerbating the root causes of inequity in those areas. Yet, climate adaptation and mitigation strategies often fail to meaningfully address the experience of frontline community stakeholders. Here, we present three challenges, three errors, and three solutions to better integrate frontline communities' needs in climate change research and to create more impactful policies. We base our perspective on our collective firsthand experiences and on scholarship to bridge local knowledge with hydroclimatic research and policymaking. Unawareness of local priorities (Challenge 1) is a consequence of Ignoring local knowledge (Error 1) that can be, in part, resolved with Information exchange and expansion of community-based participatory research (Solution 1). Unequal access to natural resources (Challenge 2) is often due to Top-down decision making (Error 2), but Buffer zones for environmental protection, green areas, air quality, and water security can help achieve environmental justice (Solution 2). Unequal access to public services (Challenge 3) is a historical issue that persists because of System abuse and tokenism (Error 3), and it may be partially resolved with Multi-benefit projects to create socioeconomic and environmental opportunities within frontline communities that include positive externalities for other stakeholders and public service improvements (Solution 3). The path forward in climate change policy decision-making must be grounded in collaboration with frontline community members and practitioners trained in working with vulnerable stakeholders. Addressing co-occurring inequities exacerbated by climate change requires transdisciplinary efforts to identify technical, policy, and engineering solutions.
Abstract Composite truss with hollow structural section (HSS) members is deemed as the structure applicable to large-span and heavily-loaded bridges. To promote the application of composite truss bridge with HSS members in China, this paper described its structural characteristics and technology in details. Besides, not only were 32 typical design cases of composite truss bridges with HSS members collected, but also the corresponding historical development was summed up. Comparisons on structural components, characteristics and engineering applications were made among composite truss bridges with HSS members in different structural forms. Then, the analysis on the characteristics of composite truss bridges with concrete-filled steel tubular (CFST) chords was conducted, and the challenges on the aspects of complicated joints and interfacial debonding were pointed out. To address these problems, the concrete-filled rectangular hollow section (CFRHS) stiffened with PBLs (Perfobond Ribs) was proposed to improve the reliability of confinement effect in CFST member and force transfer in joints. The advantages on the mechanical properties of CFRHS structure stiffened using PBLs were systematically expounded with respect to the behaviors of steel plate, interface, member and joint. Moreover, the structure design, construction technology, structural calculation and economic efficiency of the practical bridge with CFRHS chords stiffened using PBLs were comprehensively analyzed. The results demonstrated that composite truss bridge with PBL-stiffened CFRHS members was competitive in mechanical performance and construction.
AbstractThis paper proposes a novel fully prefabricated composite deck system to achieve green and accelerated construction in bridge engineering. Ultra-high-performance concrete (UHPC), which has ...
As a clean and highly valuable renewable energy, wind energy has gradually become an important branch of energy technology. By means of measurement methods, the wind characteristics, energy applications for distributed wind energy source (DWES) in six sites in Henduan Mountains and economic evaluation are investigated. According to the results, the wind characteristics including wind speed and wind direction in mountainous regions are affected significant by topography. Wind speed is season-dependent, while the mean wind direction is not. The maximum wind speed occurs in spring, the minimum wind speed occurs in summer. As for extreme value distribution, the wind data in mountainous areas are more in line with Frechet distribution type. By using Weibull distribution function, Weibull parameters are calculated and energy potential are estimated with five methods. Estimation methods suitable for coastal areas can also be used for energy assessment in mountain environments. The maximum wind power density is over 200 W∕m2, occurred in Zanli site, while the minimum value is less than 10 W∕m2in Yimen-A. Similar to mean wind characteristics, wind power density shows strong seasonality, with the maximum value in spring and the lowest value in summer. In addition, power generation facilities should be built in valleys or on the top of the mountain, and should not be built in the flat land surrounded by mountains. And the total cost of 1kWh wind-generated electricity is 0.305 CNY/kWh and 0.406 CNY/kWh with different type of wind turbine.
This paper compares design specifications and parameters for high-speed railway (HSR) earthworks in different countries (i.e., China, France, Germany, Japan, Russia, Spain and Sweden) for different track types (i.e., ballasted and ballastless), and for different design aspects (i.e., HSR embankment substructure, compaction criteria, width of the substructure surface, settlement control, transition section, and design service life). Explanations for differences in HSR implementation among different countries are provided and reference values of the design parameters are obtained. In an attempt to unify different types of HSR substructures around the world, a widely applicable definition of the stratified embankment substructure based on the practices adopted in different countries is proposed. The functions and requirements of each functional layer (i.e., the blanket layer, frost protection layer and filtering layer) are summarized.
Highway engineering. Roads and pavements, Bridge engineering
Structural health monitoring (SHM) of bridges has gained rapid development in the past few years. This paper describes application of SHM on long‐span bridges in China, with the aim to illustrate its practical value. A short review of its development and practice is firstly introduced. Three case studies are subsequently presented on utilization of SHM data in engineering practice. In the first case study, a ship collision incident is analyzed using SHM data. An alarm is sent and confirmed when the collision occurred, and mode parameters are identified with GPS measurements to evaluate the bridge condition. In the second case study, damage of expansion joints in a suspension bridge is assessed with girder end displacement measurements. Malfunction of viscous damper is found to correlate with cumulative displacement. The results show that cumulative displacement can be used for condition assessment of expansion joints. In the third case study, the performance of tuned mass dampers is evaluated with wind and vibration measurements before and after tuned mass damper installation. Through explanation of these case studies, the paper illustrates how to distill useful insights from SHM data, which could be instructive for further research in this field.
To test the nonlinearity and non-stationarity of measured dynamic signals from a bridge structure with high-level noise and dense modal characteristics, a method that combines the adaptive signal decomposition with the recurrence analysis is proposed to solve the difficulty of testing nonlinearity and non-stationarity of bridge structure signals. A novel white noise assistance and cluster analysis are introduced to the ensemble empirical mode decomposition to alleviate mode-mixing issues and generate single-mode intrinsic mode functions. Combining the hypothesis-testing scheme of nonstationary and nonlinear synchronization and surrogate techniques, a data-driven recurrence quantification analysis method is proposed and a novel recurrence quantification measure pairs are set up. To demonstrate the efficacy of the proposed methodology, complex signals, which are collected from a carefully instrumented model of a cable-stayed bridge, are utilized as the basis for comparing with traditional nonlinear and non-stationary test methods. Results show that the proposed multiscale recurrence method is feasible and effective for applications to a nonlinear and non-stationary test for real complex civil structures.