Search Results (7,055)

As a pillar industry of the national economy for many countries, the construction sector has long faced challenges in workplace safety. Unsafe behaviors among construction workers are the core cause of safety incidents, and controlling these behaviors is key to enhancing safety management. Numerous studies confirm that unsafe behaviors are closely linked to cognitive biases and decision-making errors. However, existing research still has theoretical gaps in analyzing the multi-factor interaction mechanisms from a cognitive perspective. This study constructs a three-stage theoretical model to reveal the formation mechanism of unsafe behaviors, which is validated by structural equation modeling based on the data collected by a questionnaire from ongoing construction projects in Jiangxi Province, China. It is found that (1) Organizational environment (safety atmosphere, safety culture, and safety management) exerts a negative influence on unsafe behavior; (2) While safety atmosphere has no direct impact on safety motivation, the overall organizational environment positively affects individual cognition; (3) Individual cognitive factors exert a negative influence on unsafe behavior, with the following hierarchical order: safety motivation > safety competence > safety values. (4) While safety motivation does not mediate the relationship between safety atmosphere and unsafe behavior, individual cognitive factors overall mediate the relationship between organizational environment and unsafe behavior. This study theoretically enriches the knowledge system of safety behavior and provides a theoretical foundation for optimizing enterprise unsafe behavior management and formulating differentiated management policies. Full article

Artificial intelligence technology holds significant importance for building intelligent question-answering systems in the field of coal mine safety and enhancing safety management levels. Currently, there is a lack of specialized large language models and high-quality question-answering datasets in this field. To address this, this study proposes a two-stage fine-tuning method based on Low-Rank Adaptation (LoRA) and Group Sequence Policy Optimization (GSPO) for training a question-answering model tailored to the coal mine safety domain. The research begins by constructing a dedicated question-answering dataset based on domain-specific regulatory documents. Subsequently, using Qwen2.5-7B Instruct as the base model, the study fine-tunes the model through supervised learning with LoRA technology, followed by further optimization of the model’s performance using the GSPO reinforcement learning algorithm. Experiments show that the model trained with this method exhibits significant improvements in coal mine safety-related tasks, achieving superior results on multiple automated evaluation metrics compared to contrast models of similar scale. This study validates the effectiveness of the two-stage fine-tuning method in adapting large language models (LLMs) to specific domains, providing a new technical approach for the intelligentization of coal mine safety. It should be noted that due to the lack of external data, this study relies on a self-constructed dataset and has not yet undergone external independent validation, which constitutes the main limitation of the current work. Full article

With the expansion of photovoltaic (PV) systems, failures of bypass diodes (BPDs) embedded in PV modules can degrade the power-generation performance and pose safety risks. When a BPD fails, current circulates within the module, leading to overheating and eventual burnout of the failed BPD. The heating characteristics of a BPD depend on its fault resistance, and although many modules are connected in series in actual PV systems, the heating risk at the module-string level has not been sufficiently evaluated to date. In this study, a numerical simulation model is constructed to reproduce the operation of PV modules and module strings containing failed BPDs, and its validity is verified through experiments. The validated numerical simulation results quantitatively illustrate how series-connected PV modules modify the fault-resistance dependence of BPD heating under maximum power-point operation. The results show that, under maximum power-point operation, the fault resistance at which BPD heating becomes critical shifts depending on the number of series-connected modules examined, while the magnitude of the maximum heating decreases as the string length increases. The heat generated in a BPD at the maximum power point decreases as the number of series-connected modules increases for the representative string configurations analyzed. However, under open-circuit conditions due to power-conditioner abnormalities, the power dissipated in the failed BPD increases significantly, posing a very high risk of burnout. Considering that lightning strikes are one of the major causes of BPD failure, adopting diodes with higher voltage and current ratings and improving the thermal design of junction boxes are effective measures to reduce BPD failures. The simulation model constructed in this study, which was experimentally validated for short PV strings, can reproduce the electrical characteristics and heating behaviors of PV modules and strings with BPD failures with accuracy sufficient for comparative and parametric trend analysis, and serves as a practical tool for system-level safety assessment, design considerations, and maintenance planning within the representative configurations analyzed. Full article

By the year 2050, the United States aims to achieve net-zero carbon emissions. To achieve this target, the licensing of the Light Water Reactor (LWR) fleet has been extended for 20 more years. To stay economically competitive with other power sources such as renewable and fossil-fuel power plants, the U.S. Department of Energy has introduced a plan to modernize the existing LWR fleet and diversify the revenue stream. One of the plans is to dispatch thermal energy to endothermic industrial processes. SMART valves will play an important role in this initiative by efficiently balancing the load by regulating valves in a coordinated manner while monitoring the thermal-hydraulic systems to enhance safety and maintain the integrity of the power plant. This research aims to develop a facility to test the coordinated control algorithm and produce various test results for training the monitoring system. The constructed facility is capable of simulating various operational and accidental scenarios by coordinating all the valves (positions) and pump (flowrate). The facility is developed with an Internet of Things (IoT)-based custom system and a python-based valve position control and coordination mechanism. It has achieved stable sensor outputs, pump control, and coordinated valve regulation in all three valves with minimum obstruction in the system. Full article

Waste electrical and electronic equipment (WEEE) is one of the fastest-growing waste streams globally. Disposable e-cigarettes are among the products that have gained popularity in recent years. Their complex construction and embedded lithium-ion batteries (LIBs) present environmental, safety, and resource recovery challenges. Despite growing research interest, integrated analyses linking material composition with user disposal behavior remain limited. This study is the first to incorporate device-level mass balance, material contamination assessment, battery residual charge measurements, and user behavior to evaluate the waste management challenges of disposable e-cigarettes. A mass balance of twelve types of devices on the Polish market was performed. Plastics dominated in five devices, while non-ferrous metals prevailed in the others, depending on casing design. Materials contaminated with e-liquid residues accounted for 4.4–10.7% of device mass. Battery voltage measurements revealed that 25.6% of recovered LIBs retained a residual charge (greater than 2.5 V), posing a direct fire hazard during waste handling and treatment. Moreover, it was estimated that 7 to 12 tons of lithium are introduced annually into the Polish market via disposable e-cigarettes, highlighting substantial resource potential. Survey results showed that 46% of users disposed of devices in mixed municipal waste, revealing a knowledge–practice gap largely independent of gender or education. Integrating technical and social findings demonstrates that improper handling is a systemic issue. The findings support the relevance of eco-design requirements, such as modular casings for battery removal, alongside the enforcement of Extended Producer Responsibility (EPR) schemes. Current product fees (0.01–0.03 EUR/unit) remain insufficient to establish an effective collection infrastructure, highlighting a key systemic barrier. Full article

Personality traits are well-established predictors of safety behavior in construction, yet the cognitive mechanisms through which these traits influence such behavior remain poorly understood. In particular, hazard recognition and risk perception are underexamined cognitive mediators that elucidate how personality traits shape safety behavior. Moreover, the mediating effects of these cognitive processes are likely to vary across individuals, reflecting heterogeneity in background characteristics. Neglecting these mediating processes and their differentiated effects not only limits theoretical understanding of the pathways linking personality traits to safety behavior but also undermines the effectiveness of safety interventions. To address this gap, this study develops a framework incorporating cognitive mediators to examine how personality traits influence safety behavior (safety compliance and participation). The hypothesized cognitive-mediation pathways were tested using structural equation modeling based on offline questionnaire data collected from 213 site managers and workers. The findings reveal distinct cognitive pathways through which personality traits shape safety behavior. Extraversion and openness indirectly reduced safety compliance and safety participation by weakening hazard recognition and risk perception, either independently or sequentially. In contrast, agreeableness and conscientiousness enhanced safety behavior by strengthening these same cognitive processes. Higher education levels positively moderated certain mediating effects, whereas extensive work experience exerted mixed influences on specific pathways, facilitating some and inhibiting others depending on context. These findings deepen understanding of the internal mechanisms through which personality traits influence safety behavior via risk cognition. By identifying differentiated pathways across groups, this study further refines the theoretical framework explaining construction workers’ safety behavior. In addition, the theoretical insights generated by this study offer proactive and effective directions for safety practice, including improving person–job fit, designing targeted risk cognition training, and implementing stratified safety management strategies. Full article

Currently, research on the hydrodynamic characteristics of artificial reef deployment still faces challenges such as insufficient environmental coupling, but accurate simulation of the deployment process holds significant engineering importance for optimizing deployment efficiency and ensuring reef stability. This study employs the Smoothed Particle Hydrodynamics (SPH) method to establish a 3D numerical model, focusing on the influence of key parameters—inflow velocity and water entry angle—on the hydrodynamic characteristics of cubic artificial reef deployment. The results indicate that under flow velocities of 0.4–0.5 m/s, pressure fluctuations are relatively minor, with peak pressure gradients below 15 kPa/m, exhibiting a gradual trend, while particle concentration remains high, and drag gradually increases. At flow velocities of 0.6–0.8 m/s, the maximum pressure at the bottom reaches up to 35 kPa, with low-pressure areas at the tail dropping to −10 kPa; particle concentration decreases compared to conditions at 0.4–0.5 m/s; settling time extends from 8.4 s to 12 s, representing a 42% increase. Under different water entry angles, drag varies nonlinearly with the angle, reaching its maximum at 20° and its minimum at 25°, with a reduction of approximately 47% compared to the maximum. The anti-sliding safety factor and anti-overturning safety factor are used to assess the stability of the cubic reef placed on the seabed. Across different inflow velocities, the anti-sliding safety factor of the cubic artificial reef significantly exceeds 1.2, whereas the anti-overturning safety factor is below 1.2 at 0.4 m/s but exceeds 1.2 at velocities of 0.5 m/s and above, indicating that the reef maintains stability under the majority of these flow conditions. Our findings provide a scientific basis for the deployment process, site selection, and geometric design of cubic artificial reefs, offering valuable insights for the precise deployment and structural optimization of artificial reefs in marine ranching construction. Full article

With the explosive growth in the quantity of electrical equipment in distribution networks, traditional manual inspection struggles to achieve comprehensive coverage due to limited manpower and low efficiency. This has led to frequent equipment failures including partial discharge, insulation aging, and poor contact. These issues seriously compromise the safe and stable operation of distribution networks. Real-time monitoring and defect identification of their operation status are critical to ensuring the safety and stability of power systems. Currently, commonly used methods for defect identification in distribution network electrical equipment mainly rely on single-image or voiceprint data features. These methods lack consideration of the complementarity and interleaved nature between image and voiceprint features, resulting in reduced identification accuracy and reliability. To address the limitations of existing methods, this paper proposes distribution network electrical equipment defect identification based on multi-modal image voiceprint data fusion and channel interleaving. First, image and voiceprint feature models are constructed using two-dimensional principal component analysis (2DPCA) and the Mel scale, respectively. Multi-modal feature fusion is achieved using an improved transformer model that integrates intra-domain self-attention units and an inter-domain cross-attention mechanism. Second, an image and voiceprint multi-channel interleaving model is applied. It combines channel adaptability and confidence to dynamically adjust weights and generates defect identification results using a weighting approach based on output probability information content. Finally, simulation results show that, under the dataset size of 3300 samples, the proposed algorithm achieves a 8.96–33.27% improvement in defect recognition accuracy compared with baseline algorithms, and maintains an accuracy of over 86.5% even under 20% random noise interference by using improved transformer and multi-channel interleaving mechanism, verifying its advantages in accuracy and noise robustness. Full article

Future lunar south pole missions face dual challenges of highly variable illumination and rugged terrain that directly constrain rover mobility and energy sustainability. To address these issues, this study proposes a dynamic illumination-constrained spatio-temporal A* (DIC3D-A*) path-planning algorithm that jointly optimizes terrain safety and illumination continuity in polar environments. Using high-resolution digital elevation model data from the Lunar Reconnaissance Orbiter Laser Altimeter, a 1300 m × 1300 m terrain model with 5 m/pixel spatial resolution was constructed. Hourly solar visibility for November–December 2026 was computed based on planetary ephemerides to generate a dynamic illumination dataset. The algorithm integrates slope, distance, and illumination into a unified heuristic cost function, performing a time-dependent search in a 3D spatiotemporal state space. Simulation results show that, compared with conventional A* algorithms considering only terrain or distance, the DIC3D-A* algorithm improves CSDV by 106.1% and 115.1%, respectively. Moreover, relative to illumination-based A* algorithms, it reduces the average terrain roughness index by 17.2%, while achieving shorter path length and faster computation than both the Rapidly-exploring Random Tree Star and Deep Q-Network baselines. These results demonstrate that dynamic illumination is the dominant environmental factor affecting lunar polar rover traversal and that DIC3D-A* provides an efficient, energy-aware framework for illumination-adaptive navigation in upcoming missions such as Chang’E-7. Full article

Pile foundations are critical load-bearing components in bridge structures, particularly in soft, high-moisture soils susceptible to external disturbances. This study investigated the impact of large-scale soil excavation on the stability of adjacent pile foundations through comprehensive field monitoring of a newly constructed bridge during both the bridge construction and channel excavation phases. The close proximity of the excavation site to the pile caps facilitated a detailed assessment of soil–structure interaction. The results indicate that the pile axial force peaked at the pile head and decreased progressively with depth, consistent with the load transfer mechanism of friction piles. Notably, a distinct variation in axial force was observed at the bedrock interface, attributed to reduced relative displacement between the pile and the surrounding soil. Furthermore, channel water filling raised the local groundwater table, which increased the buoyancy and reduced negative skin friction, thereby decreasing the pile axial force. The study also highlighted the sensitivity of pile deformation in soft soil to unbalanced earth pressure. Asymmetric excavation and surface surcharge loading were identified as critical factors compromising pile stability and overall structural safety. These findings provide valuable insights for construction practices and offer effective strategies to mitigate adverse excavation effects, ensuring long-term structural stability. Full article

With socioeconomic development, cities face increasingly complex and diverse disaster risks, making the construction of resilient cities an inevitable choice. However, the driving forces and tactical approaches behind urban resilience development remain unclear for urban safety development, thus posing challenges to cities urgently needing to enhance their resilience. Therefore, this paper investigates this issue, covering the following aspects: (1) Eighteen influencing factors within the complex system of urban resilience were identified and summarized from five perspectives: Economic, Social, Environmental, Infrastructure, and Organizational & Institutional. The attributes of the influencing factors were analyzed using the Decision-Making Experimentation and Evaluation Laboratory (DEMATEL) method, and key factors were identified accordingly. (2) The Total Adversarial Interpretive Structure Model (TAISM) method was applied to construct a multi-perspective adversarial recursive structural model with integrated impact values. This model illustrates the interrelationships among the influencing factors and clarifies their hierarchical structure. (3) A Fuzzy Reachability Matrix (FR) was introduced to handle uncertain relationships between factors in the comprehensive influence matrix, enabling an explicit analysis of the hierarchical structure of the urban resilience complex coupling giant system, clearly showing the impact of factor hierarchical changes on the system structure. (4) Building upon the analysis of factors affecting urban resilience, the specific pathways and mechanisms were articulated, followed by recommended measures formulated from both internal (governmental) and external (community) perspectives. The results can provide theoretical support for resilient city construction and serve as a practical cornerstone. Full article

Blast-induced vibrations from newly constructed tunnels may adversely affect adjacent existing tunnel structures. To ensure the safety of the existing tunnel, it is essential to investigate its dynamic response under blast disturbances. Based on an expansion project for a highway double-arch tunnel, this study employed the dynamic finite element program LS-DYNA to analyze the vibration velocity and effective stress in the tunnel lining subjected to blast vibrations. The distribution characteristics of vibration velocity and effective stress at different locations of tunnel lining were obtained. A relationship model between the peak particle velocity (PPV) and effective stress was established. According to the maximum tensile stress theory, a safety criterion based on vibration velocity was determined. To facilitate field monitoring, a correlation between the vibration velocity at the arch waist and foot was established, leading to a proposed safety threshold for the arch foot vibration velocity. Furthermore, a statistical relationship was developed between the charge weight per hole in the upper bench cut and the vibration velocity at the arch foot to guide blasting design. Using the arch foot vibration velocity as the safety standard, the maximum permissible charge weight to ensure the structural safety of the existing tunnel was recommended. Full article

When a fire occurs in a tunnel during construction, the smoke cannot be discharged in time and continues to settle near the ground, which threatens the safety of personnel. It is essential to understand smoke layer distribution for safe evacuation. To fill the knowledge gap for the spatio-temporal distribution of the smoke layer, a series of fire experiments are carried out in 1/20 reduced-scale tunnel models. Multiple variables are considered, including longitudinal fire location, heat release rate, aspect ratio of the main tunnel, and the inclined shaft length. Two fire scenarios are defined according to the longitudinal fire location in the main tunnel: near the upstream closed end (scenario 1) and near the downstream closed end (scenario 2). The results show that the structural evolution of the smoke layer inside the main tunnel experiences roughly three stages: single-layer smoke flow stage, transition stage, and two-layer smoke flow stage. In different fire scenarios, the reasonable N value is 10, determined by comparing the smoke layer interface height (h_s) predicted by the N-percentage method with the observed results. Moreover, we find that the FDS simulation method has significant deviation in predicting poor stratification situations. Furthermore, the spatio-temporal distributions of h_s in the main tunnel are predicted based on N = 10. The coupled effects of heat release rate and the longitudinal fire location on the h_s values are analyzed. The t_ar value (time of smoke arrival at the respiratory height) is determined, and its spatial variations are predicted. By comparing the t_ar values at position 2^# (near the inclined shaft) in different fire scenarios, we can provide a reference for the evacuation of personnel. Full article

A well construction plan includes a drilling program, drilling fluids, casing-setting-depth selection, casing-grade-combination design, bit selection, cementing, and a wellhead design. Casing-setting-depth selection techniques are an integral part of the construction of oil and gas wells, where setting-depth selection methods rely on both safety and economics. In this study, a new casing-setting-depth selection method is developed. This new method is based on the estimation of the fracturing pressure using the Mohr–Coulomb failure criterion. To validate this new casing-setting-depth selection method, ten core samples, representing ten underground formations in the Saudi lithological column, were tested for uniaxial compressive and tensile strengths. The results were utilized to establish rock failure criteria and estimate casing setting depth using a newly proposed casing-setting-depth selection method based on the Mohr–Coulomb failure criterion and compared to other traditional casing-setting-depth estimation methods. The results demonstrated that the Hubbert & Willis method provided a very narrow safe mud window compared to the other methods, while the leak-off, Eaton, Mathews & Kelly, and other methods provided more economical results. On the other hand, the Mohr–Coulomb method provided the widest and most economical safe mud window compared to all other traditional methods. One of the main requirements of the Mohr–Coulomb casing-setting-depth selection method is that it either requires appreciable core samples from various depths to be tested in the laboratory for their mechanical properties and failure criteria, or that core-calibrated well logs be used. Additionally, relying on Mohr–Coulomb casing-setting-depth selection methods requires the use of filtration loss control materials to seal any microcracks that may form. Economical comparisons in terms of casing string number and length yielded that Eaton, leak-off, and Mathews and Kelly methods reduced casing cost by 31% compared to Hubbert and Willis methods. On the other hand, the new casing-setting-depth selection method based on the Mohr–Coulomb method reduced casing costs by 41% compared with the Hubbert and Willis methods and by 10% compared with the leak-off and Mathews and Kelly methods. Therefore, this study provides a new proof of concept for developing an efficient method for selecting the casing setting depth for oil and gas wells. Full article

Background: Teamwork and effective communication are widely recognized as essential pillars for the safety and quality of healthcare. However, in Portugal, no validated instrument had previously been available to assess healthcare professionals’ attitudes toward teamwork. This study aimed to translate, culturally adapt, and validate the TeamSTEPPS^® Teamwork Attitudes Questionnaire (T-TAQ) for the Portuguese context, resulting in the Portuguese version of the instrument. Methods: A methodological study with a quantitative approach was developed. The translation and cultural adaptation process followed internationally recognized guidelines. The sample consisted of 162 healthcare professionals (136 nurses and 26 physicians) from a hospital in Lisbon. Exploratory and confirmatory factor analysis techniques were used to assess construct validity. The internal consistency of the scale was analyzed using Cronbach’s alpha coefficient. Results: The Portuguese version comprises 30 items distributed across five dimensions: Effective Leadership Support, Team Functional Performance, Teamwork Coordination, Willingness to Engage in Teamwork, and Team Functioning Supervision. The scale demonstrated a total explained variance of 53.9% and an overall internal consistency coefficient (α) of 0.86, indicating good reliability. Confirmatory factor analysis supported the five-factor structure of the scale (χ²/df = 1.461; CFI = 0.900; GFI = 0.821; RMSEA = 0.054; MECVI = 4.731). Conclusions: The T-TAQ-PT proved to be a valid, reliable, and robust instrument for assessing healthcare professionals’ individual attitudes toward teamwork, contributing to the development of research and clinical practice in the Portuguese context. Full article