Search Results (7,595)

Concrete sleepers are essential components of railroad infrastructure, yet their service life has been reduced by one-third due to deterioration caused by internal swelling reactions (ISR), leading a major Brazilian railroad to replace millions of sleepers within a decade. This study investigates the reliability of various non-destructive testing (NDT) techniques to estimate damage levels in concrete sleepers. The methods evaluated include surface hardness testing, stress wave propagation, electromagnetic wave propagation using ground-penetrating radar (GPR), electrical resistivity, and resonant frequency. These techniques were applied to assess sleepers diagnosed as affected by alkali-silica reaction (ASR) and delayed ettringite formation (DEF) at different deterioration degrees. Although findings indicate that most NDT methods are limited and unreliable for quantifying ISR-induced damage, resonant frequency testing combined with energy dissipation analysis provided the highest accuracy across all damage stages and was able to capture microstructural changes before significant expansion occurred. These results support the use of vibration-based screening tools to enhance early detection and guide condition assessment of railroad infrastructure, helping to reduce the premature replacement of ISR-affected concrete sleepers. Full article

Polypropylene fiber, as a micro-scale reinforcement material, has been widely recognized for its ability to effectively inhibit crack propagation during the service life of concrete, thereby enhancing both its crack resistance and durability. This study presents an experimental investigation of the mechanical properties of polypropylene fiber-reinforced concrete specimens. The primary objective of this study was to assess the influence of varying fiber lengths and volumetric fiber contents on the load-bearing behavior of concrete. Seven sets of concrete specimens with different polypropylene fiber parameters (dosage and length) were prepared and subjected to a series of tests, including compressive strength, splitting tensile strength, flexural strength, and axial compressive stress–strain behavior. Specifically, coarse polypropylene fibers with two lengths (30 mm and 50 mm) and three dosages (0.5%, 1%, and 1.5%) were investigated. Experimental results facilitated the identification of the optimal fiber dosage and length at which the mechanical properties of the concrete specimens were maximized. Subsequently, a constitutive model for polypropylene fiber-reinforced concrete was established. The analysis elucidated the relationships between the parameters within the constitutive model, axial compressive strength of the concrete, and characteristic fiber parameters. The derived formulations provide a theoretical foundation for subsequent finite element analyses of polypropylene-fiber-reinforced concrete. Full article

Electric Level 4 connected automated vehicles (CAVs) are now allowed to demonstrate their automation capability in shared mobility robotaxi and microtransit services in geofenced areas in several cities around the world. Private and public sector stake-holders need predictions of their adoption without regulatory constraints for personal mobility and use in shared mobility services. In anticipation of the future presence of CAVs in transportation vehicle fleets, governments are planning necessary regulatory and infrastructure changes. Accompanying this need for forecasts is the acknowledgement that CAV adoption decisions must be made under uncertain states of technology and infrastructure readiness. This paper presents a Bayesian predictive modelling framework for electric Level 4 CAV adoption in the 2030–2035 application context. The inputs to the Bayesian model are obtained from effectiveness estimates of CAV applications that are processed with the Monte Carlo method to account for uncertainties in these estimates. Scenarios of CAV adoption in the 2030–2035 period are analyzed using the Bayesian model, including the quantification of the value of new information obtainable from demonstration studies intended to reduce uncertainties in technology and infrastructure readiness. The results show that in the 2030–2035 application context, the CAVs are likely to be adopted, provided that the trajectory of progress in technology and infrastructure readiness continues, and potential adopters are offered opportunities to learn about Level 4 CAV technological capabilities in a real life service environment. The threshold level of the probability of adoption enhances significantly with high-reliability demonstration results that can reduce uncertainties in adoption decisions. The findings of this research can be used by private and public sector interest groups. Full article

Strain monitoring during the service life of a nuclear containment structure is an effective means to evaluate whether the structure is operating safely. Due to the failure of embedded strain sensors, surface-mounted strain sensors should be installed on the outer wall of the structure. However, whether the data from these substitute sensors can reasonably reflect the internal deformation behavior requires further investigation. To ensure the feasibility of the added strain sensors, a refined 3D model of a Chinese Pressurized Reactor (CPR1000) nuclear containment structure was developed in ANSYS 19.1 to study the internal and external deformation laws during a containment test (CTT). Solid reinforcement and cooling methods were employed to simulate prestressed cables and pre-tension application. The influence of ordinary steel bars in concrete was modeled using the smeared model, while interactions between the steel liner and concrete were simulated through coupled nodes. The model’s validity was verified against embedded strain sensor data recorded during a CTT. Furthermore, concrete and prestressed material parameters were refined through a sensitivity analysis. Finally, the variation law between the internal and external deformation of the containment structure was investigated under typical CTT loading conditions. Strain values in the wall thickness direction exhibited an essentially linear relationship. Near the equipment hatch, however, the strain distribution pattern was significantly influenced by the spatial arrangement of prestressed cables. Refined FEM and sensor systems are vital containment monitoring tools. Critically, surface-mounted strain sensors offer a feasible approach for inferring internal stress states and deformation behavior. This study provides theoretical support and a technical foundation for the safe assessment and maintenance of nuclear containment structures during operational service. Full article

The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive exploration of sensor technologies, detailing their integral role within IoT frameworks and examining their impact on optimizing efficiency and service delivery in modern wireless communications systems. Also, it presents a thorough review of sensor technologies, current research trends, and the associated challenges in this evolving field, providing a detailed explanation of recent advancements and IoT-integrated sensor systems, with a particular emphasis on the fundamental architecture of sensors and their pivotal role in modern technological applications. It explores the core benefits of sensor technologies and delivers an in-depth classification of their fundamental types. Beyond reviewing existing developments, this study identifies key open research challenges and outlines prospective directions for future exploration, offering valuable insights for both academic researchers and industry professionals. Ultimately, this paper serves as an essential reference for understanding sensor technologies and their potential contributions to IoT-driven solutions. This study offers meaningful contributions to academic and industrial sectors, facilitating advancements in sensor innovation. Full article

Ultra-long pool structures used in mine water treatment projects are typical large-volume concrete structures that are highly susceptible to cracking due to the combined effects of cement hydration heat, seasonal temperature variations, and internal water pressure. Such cracking can compromise the durability and long-term service performance of the structure. In this study, distributed fiber optic sensing and finite element analysis were conducted to observe the response of ultra-long pool structures under thermal–load effects. System comparison shows that the average error between the monitored peak thermal strain values and the corresponding simulated values is within 9%. Parametric analysis using the validated simulation model indicates that the hydration protocol with temperatures of 15 °C (casting), 55 °C (peak), and 15 °C (stable), a temperature drop of −20 °C, and loading conditions in sub-pools 3+6 and sub-pools 1+3+5 are the most unfavorable scenarios for inducing tensile stress. When a temperature drop of −20 °C is combined with loading conditions in sub-pools 3+6 or sub-pools 1+3+5, the tensile stress in the pool structure increases by 30% compared to the stress induced by loading alone. This indicates that during the service life of the pool structure, extreme temperature variations combined with mechanical loading may result in localized cracking. This study provides a comprehensive understanding of ultra-long pool behavior during construction and service phases, supporting effective maintenance and long-term durability. Full article

Bridge cranes generally have a significant disparity between their actual service life and design life. If they are scrapped according to the design life, it is likely to result in resource wastage or pose potential safety hazards due to extended service. Existing studies have not thoroughly examined the coupling relationship among actual working conditions, structural damage, and load-matching strategies. It is difficult to achieve real-time and accurate adaptation between loads and the carrying capacity of equipment, and thus cannot effectively narrow this life gap. To this end, this paper defines a digital twin system framework for crane load adaptive matching, constructs a load adaptive matching optimization model, proposes a method for developing a digital twin system for bridge crane load adaptive matching, and builds a digital twin system platform centered on virtual-real mapping, IoT connectivity, and data interaction. Detailed experimental verification was conducted using the DQ40 kg-1.8 m-1.3 m light-duty bridge crane. The results demonstrate that this method and system can effectively achieve dynamic matching between the load and real-time carrying capacity. While ensuring the service life exceeds the design life, the difference between the two is controlled at around 3467 cycles, accounting for approximately 0.000462% of the design life. This significantly improves the equipment’s operational safety and resource utilization efficiency, breaks through the limitations of load reduction schemes formulated based on human experience under the traditional regular inspection mode, and provides a scientific load-matching decision-making basis and technical support for special equipment inspection institutions and users. Full article

With the ongoing advancement of urbanization in China, a disparity has arisen between population demands and the allocation of community resources, resulting in a persistent increase in residential vacancy rates. The integration of service facilities into vacant residential spaces has enabled functional housing transformations. This study analyzes three typical types of communities in Xi’an to examine these transformations, identifying distinct types and patterns across five scenarios, which include social, health, leisure, cultural, and educational contexts. Through structured questionnaires and in-depth interviews, we collected data on residents’ life satisfaction and NIMBY (not in my backyard) perceptions. Applying a NIMBY index algorithm, we quantified characteristics and identified root causes. The results demonstrated that leisure scenarios most significantly affected satisfaction, while social scenarios showed the highest NIMBY index. Using an ordered logistic regression model, we determined key NIMBY factors influencing satisfaction across scenarios, revealing their differential impact mechanisms. Drawing on the findings, we investigated coordination mechanisms between the transformations of residential spaces and the needs of residents. Based on this analysis, the research objective was to explore how vacant housing can integrate service facilities while mitigating NIMBY effects and meeting resident needs. Proposed strategies include hierarchical facility allocation, NIMBY mitigation measures, and spatial planning optimization, ultimately adapting to diverse lifestyles and housing demands. Full article

Purpose: Grounded in Social Cognitive Theory and Self-Determination Theory, this study analyzed gender differences in the relationships between teachers’ sense of efficacy, basic psychological need satisfaction and frustration (competence), and life satisfaction among Physical Education (PE) pre-service teachers. Method: A sample of 368 PE pre-service teachers (Mage = 23.41 ± 2.37; 48.1% women) participated. A multi-group structural equation modeling approach was used. Results: Male participants reported significantly higher levels of competence satisfaction compared to their female counterparts. Teaching efficacy positively predicted life satisfaction, both directly and indirectly via competence satisfaction. Notably, the indirect effects were stronger among women, while direct effects were observed only in the female group. Conclusions: The findings emphasize the key role of competence satisfaction in explaining how teaching efficacy influences life satisfaction in pre-service teachers. Gender differences suggest that while both men and women benefit from feeling competent, the pathways differ, highlighting the importance of gender sensitive strategies in teacher education programs. Full article

The long-term durability of steel structures in contact with soil remains a critical challenge due to the complex and aggressive nature of many soil environments. This study presents a thorough evaluation of the corrosion resistance and microstructural evolution of Magnelis^® ZM430-coated steel exposed to highly aggressive, heterogeneous soils. Gravimetric analysis revealed that the Magnelis^® ZM430 coating exhibits low corrosion rates and enhanced initial barrier properties, even under severe soil conditions. Although the literature frequently reports that Zn–Al–Mg coatings outperform conventional hot-dip galvanized coatings, our results highlight that this superiority is not universal and may be limited under highly aggressive, heterogeneous soils. Microstructural characterization by optical microscopy, SEM/EDS, and XRD demonstrated that the as-received coating consists of a homogeneous layer with well-distributed Zn-, MgZn₂-, and Al-rich phases. Upon soil exposure, corrosion preferentially initiates in the Mg- and Al-rich interdendritic and eutectic regions, leading to selective phase depletion and localized breakdown of the protective layer. Despite these localized vulnerabilities, the overall performance of Magnelis^® ZM430 remains superior, especially during the early stages of exposure. While no direct comparisons were performed in this work, our findings align with previous literature reporting superior performance of Zn–Al–Mg coatings compared to conventional hot-dip galvanized coatings in similar environments. Importantly, the integration of precise corrosion rate data with detailed soil characterization enables accurate prediction of coating service life, allowing for optimized coating thickness selection and proactive maintenance planning. These findings underscore the value of combining advanced Zn–Al–Mg coatings with site-specific environmental assessment to ensure the long-term integrity of buried steel infrastructure. Full article

This study focuses on buildings in the Chinese–Baroque Historic Shopping District in Harbin. In view of global climate change and high carbon emissions from the construction industry, this study aims to quantify carbon emissions during the decoration process and explore low-carbon decoration strategies that suit the local characteristics. This research adopts a four-stage framework of “data collection–quantitative analysis–strategy design–verification and optimization” and integrates Life Cycle Assessment (LCA) and multi-objective optimization theory. Data are collected through questionnaires and field investigations, and simulations and analyses are carried out using Grasshopper and Honeybee. The results show that there are differences in carbon emissions between different decoration schemes. The chosen scheme of raw concrete and paint results in relatively low carbon emissions over the 10.12-year usage cycle. Based on this, design strategies such as extending the service life of decorations, rationally renovating windows, and preferentially selecting local low-carbon materials are proposed and applied to practical projects. This study not only fills a gap in the research on the low-carbon renovation of historical commercial blocks from the perspective of LCA but also provides practical solutions for the sustainable development of historical shopping blocks in Harbin and similar regions, promoting the low-carbon transformation of cities. Full article

The presence of a minimum quantity lubrication (MQL) under the conditions of a burnishing process can contribute to an improvement in the process performance by reducing the heights of the resulting surface asperities, by decreasing the temperature values, and by diminishing the size of the burnishing force components. On the other hand, there are situations in which it is possible to increase the service life of the parts made of EN AW-2007 aluminum alloy by applying a burnishing process. To verify how the results of applying a burnishing process applied to cylindrical specimens in the aluminum alloy when using and not using a minimum quantity lubrication, an experimental research based on a planned variation between certain limits of the values of the peripheral speed and the feed rate has been conceived and materialized. The experimental results were processed mathematically. It has been found that by using the minimum quantity of mineral oil type Valona MS7023 HC, it was possible to reduce the value of the Sa roughness parameter by up to 18%, a decrease in temperature by about 20 °C, and the size of the burnishing force by up to 45%. Full article

Capsule-based self-healing technologies offer a promising solution to extend pavement service life without requiring external activation. The effect of the capsule content on the mechanical behaviour of self-healing asphalt mixtures still needs to be understood. This study presents a numerical evaluation of the isolated effect of incorporating capsules containing encapsulated rejuvenators, at different volume contents, on the stiffness and strength of asphalt mixtures through a three-dimensional discrete-based programme (VirtualPM3DLab), which has been shown to predict well the experimental behaviour of asphalt mixtures. Uniaxial tension–compression cyclic and monotonic tensile tests on notched specimens are carried out for three capsule contents commonly adopted in experimental investigations (0.30, 0.75, and 1.25 wt.%). The results show that the effect on the stiffness modulus progressively increases as the capsule content grows in the asphalt mixture, with a reduction ranging from 4.3% to 12.3%. At the same time, the phase angle is marginally affected. The capsule continuum equivalent Young’s modulus has minimum influence on the overall rheological response, suggesting that the most critical parameter affecting asphalt mixture stiffness is the capsule content. Finally, while the peak tensile strength shows a maximum reduction of 12.4% at the highest capsule content, the stress–strain behaviour and damage evolution of the specimens remain largely unaffected. Most damaged contacts, which mainly include aggregate–mastic and mastic–mastic contacts, are highly localised around the notch tips. Contacts involving capsules remained intact during early and intermediate loading stages and only fractured during the final damage stage, suggesting a delayed activation consistent with the design of healing systems. The findings suggest that capsules within the studied contents may have a moderate impact on the mechanical properties of asphalt mixtures, especially for high-volume contents. For this reason, contents higher than 0.75 wt.% should be applied with caution. Full article

Semi-rigid base asphalt pavements, a common highway structure in China, often suffer from debonding defects which reduce road stability and shorten service life. In this study, a new method of road debonding detection based on the acoustic vibration method is proposed to address the needs of hidden debonding defects which are difficult to detect. The approach combines the Transformer model and the Transformer-based Parallel Cross-Gated Convolutional Neural Network (T-PCG-CNN) to classify and recognize semi-rigid base asphalt pavement acoustic data. Firstly, over a span of several years, an excitation device was designed and employed to collect acoustic data from different road types, creating a dedicated multi-sample dataset specifically for semi-rigid base asphalt pavements. Secondly, the improved Mel frequency cepstral coefficient (MFCC) feature and its first-order differential features (ΔMFCC) and second-order differential features (Δ₂MFCC) are adopted as the input data of the network for different sample acoustic signal characteristics. Then, the proposed T-PCG-CNN model fuses the multi-frequency feature extraction advantage of a parallel cross-gate convolutional network and the long-time dependency capture ability of the Transformer model to improve the classification performance of different road acoustic features. Comprehensive experiments were conducted to analyze parameter sensitivity, feature combination strategies, and comparisons with existing classification algorithms. The results demonstrate that the proposed model achieves high accuracy and weighted F1 score. The confusion matrix indicates high per-class recall (including debonding), and the one-vs-rest ROC curves (AUC ≥ 0.95 for all classes) confirm strong class separability with low false-alarm trade-offs across operating thresholds. Moreover, the use of blockwise self-attention with global tokens and shared weight matrices significantly reduces model complexity and size. In the multi-type road data classification test, the classification accuracy reaches 0.9208 and the weighted F1 value reaches 0.9315, which is significantly better than the existing methods, demonstrating its generalizability in the identification of multiple road defect types. Full article

Background and Objectives: As maternal mortality has become increasingly rare in developed countries, it is no longer a reliable metric for evaluating obstetric care quality. To address this limitation, the World Health Organization (WHO) introduced the concept of maternal near miss (MNM)—a term adapted from aviation—to standardize the identification and analysis of severe maternal complications. In addition to MNM, various indices are used to assess both access to and the quality of healthcare services. Materials and Methods: This retrospective study evaluated all pregnant women who presented at Başakşehir Çam and Sakura City Hospital, including postpartum referrals, between May 2020 and May 2023. Given the ongoing COVID-19 pandemic during the study period, data from COVID-19-positive patients were reported separately. All definitions and classifications were based on the standardized WHO MNM criteria. Results: A total of 45,458 births occurred at our institution during the study period. Among the COVID-19-excluded cohort, we identified 223 life-threatening conditions (LTCs), 206 MNM cases, and 17 maternal deaths. The resulting mortality index was 7.62%. The most frequent primary diagnoses included placental invasion anomalies, severe preeclampsia, and uterine atony. The most common interventions among LTC cases were ICU admission, prolonged hospitalization, hysterectomy, and massive transfusion. Conclusions: Although the rates of LTCs, MNM, and maternal mortality (MM) are gradually declining, they remain essential metrics for assessing healthcare quality. This study reveals that, while tertiary centers may report higher-than-global-average indices, there remains a significant gap between current outcomes and ideal targets. Enhancing diagnostic training, optimizing intervention strategies, and implementing robust clinical algorithms are critical steps toward reducing severe maternal morbidity and mortality. Full article