Search Results (216)

For the past few decades, during each disastrous earthquake, severe damage and poor seismic performance of masonry infilled RC frames, including many newly designed ones, have been reported extensively. Inherent problems related to analysis and design methods for tight-fit infilled frame structures have not yet been solved and are recognized as being far from satisfactory in terms of completeness and reliability. The primary objective of this research was to propose and test an innovative method that can effectively mitigate undesirable interaction damage to masonry infilled RC frame structures. This proposed technical solution consists of connection of the infill panel to the bounding columns with steel reinforcement connections deployed in mortar layers and anchored to the columns. This is practical, cheap and easy to implement without any specific technology, which is especially important for developing countries. A three story, two bay RC building model with the proposed connection implemented on the infill walls was designed and tested on the shake table at IZIIS in Skopje, N. Macedonia. The test results and design guidelines/recommendations from the proposed research are also expected to benefit the infrastructural development in other countries threatened by earthquakes, preferably in the Balkan and the Mediterranean region. Full article

The performance of reinforced concrete (RC) frame structures will gradually decrease over time, posing a threat to the safety of buildings. Although the performance of some buildings may still meet the safety requirements, they cannot meet new usage requirements. Therefore, this paper proposes a new-type joint to promote the development of research on the reinforcement and renovation of RC frame structures in response to this situation. The RC beams and columns of the joints are connected by embedded horizontal steel plate (a single plate with dimension of 150 mm × 200 mm × 5 mm), and the beams and columns are individually wrapped in steel. Through conducting low cyclic loading tests, this paper analyzes the influence of carrying out wrapped steel treatment and the thickness of wrapped steel of the beam and connector on mechanical performance indicators such as hysteresis curve, skeleton curve, stiffness, ductility, and energy dissipation. The experimental results indicate that the reinforcement using steel plate can significantly improve the dynamic performance of the joint. The effect of changing the thickness of the connector on the dynamic performance of the specimen is not significant, while increasing the thickness of wrapped steel of beam can effectively improve the overall strength of joint. The research results of this paper will help promote the application of reinforcement and renovation technology for existing buildings, and improve the quality of human living. Full article

In order to verify the rationality and feasibility of a demountable and replaceable fabricated RC beam with bolted connection under mid-span compression, one cast-in-place RC beam and four fabricated RC beams were designed and fabricated. Through the mid-span static loading test and analysis of five full-scale RC beams, the effects of high-strength bolt specifications and stiffeners were compared, and the behavior of the fabricated RC beams with bolted connections was analyzed. The test process was observed and the test results were analyzed. The failure mode, cracking load, yield load, ultimate load, stiffness change, deflection measured value, ductility, and other indicators of the specimens were compared and analyzed. It was shown that the failure mode of the fabricated RC beam was reinforcement failure, which met the three stress stages of the normal section bending of the reinforcement beam. The failure position occurred at 10~15 cm of the concrete outside the bolt connection, and the beam support and the core area of the bolt connection were not damaged. The fabricated RC beam has good mechanical performance and high bearing capacity. In addition, comparing the test value with the simulation value, it is found that they are in good agreement, indicating that ABAQUS software of 2024 can be well used for the simulation analysis of the behavior of fabricated RC beam structure. Full article

This paper introduces a data-driven methodology for accurately estimating the residual capacity (RC) of lithium iron phosphate (LFP) batteries through a tailored artificial neural network (ANN) architecture. The proposed model integrates a long short-term memory (LSTM) layer with a fully connected layer, leveraging their combined strengths to achieve precise RC predictions. A distinguishing feature of this study is its ability to deliver highly accurate estimates using a limited dataset that was derived from a single cylindrical LFP battery with a 40 Ah capacity and collected during a controlled experimental campaign. Despite the constraints imposed by the dataset size, the ANN demonstrates remarkable performance, underscoring the model’s capability to operate effectively with minimal data. The dataset is partitioned into the training and testing subsets to ensure a rigorous evaluation. Additionally, the robustness of the approach is validated by testing the trained ANN on data from a second battery cell subjected to a distinct aging process, which was entirely unseen during training. This critical aspect underscores the method’s applicability in estimating RC for batteries with varying aging profiles, a key requirement for real-world deployment. The proposed LSTM-based architecture was also benchmarked against a GRU-based model, yielding significantly lower prediction errors. Furthermore, beyond LFP chemistry, the method was tested on a broader NMC dataset comprising seven cells aged under different C-rates and temperatures, where it maintained high accuracy, confirming its scalability and robustness across chemistries and usage conditions. These results advance battery management systems by offering a robust, efficient modeling framework that optimizes battery utilization across diverse applications, even under data-constrained conditions. Full article

Flat slab structures are extensively utilized in modern construction owing to their efficient load transfer mechanisms and optimized space utilization. Nevertheless, the persistent issue of brittle punching shear failure at connection zones continues to pose significant engineering challenges. This study proposes an innovative cross-shaped steel-reinforced concrete (SRC) column–slab connection. Through combining test and numerical analyses, the failure mechanisms and performance control principles are systematically analyzed. A refined finite element model incorporating material nonlinearity, geometric characteristics, and interface effects is developed, demonstrating less than 3% error upon test validation. Using the validated model, the influence of key parameters—including concrete strength (C30–C60), reinforcement ratio (ρ = 0.65–1.77%), shear span–depth ratio (λ = 3–6), and limb height-to-thickness ratio (c₁/c₂ = 2–4)—on the punching shear behavior is thoroughly investigated. The results demonstrate that increasing concrete strength synergistically improves both punching shear capacity (by up to 49%) and ductility (by 33%). A critical reinforcement ratio threshold (0.8–1.2%) is identified. When exceeding this range, the punching shear capacity increases by 12%, but reduces ductility by 34%. Additionally, adjusting the shear span–depth ratio enables controlled failure mode transitions and a 24% reduction in punching shear capacity, as well as a 133% increase in displacement capacity. These results offer theoretical support for the design and promotion of this novel structural system. Full article

This paper is devoted to determining the influence of some risk elements on the asphalted surfaces of bridge ramps, in order to detect possible damages or potential collapses of the embankment. The main factors will be characterized by (a) movements of floating reinforced concrete (r.c.) slab over the embankment connected to the border of the bridge; (b) longitudinal cracks on the asphalt produced by small sliding deformations; (c) emerging vegetation from the slope of the ramps. The authors propose a set of possible techniques to determine level of risk indicators, illustrating a set of case studies related to several asphalt roads approaching r.c. bridges. Full article

The electrical grid is undergoing increasing integration of decentralized power sources connected to the low-voltage network. In this context, the concept of a microgrid has emerged as a system comprising small-scale energy sources, loads, and storage devices, coordinated to operate as a single controllable entity capable of functioning in either grid-connected or islanded mode. The microgrid may be organized in a centralized configuration, such as a master-slave scheme, wherein the centralized converter, i.e., the grid-forming converter (GFC), plays a pivotal role in ensuring system stability and control. This paper introduces a plug-in repetitive controller (RC) strategy tuned to even harmonic orders for application in a three-phase GFC, diverging from the conventional approach that focuses on odd harmonics. The proposed control is designed within a synchronous reference frame and is targeted at centralized AC microgrids, particularly during islanded operation. Simulation results are presented to assess the microgrid’s power flow and power quality, thereby evaluating the performance of the GFC. Additionally, the proposed control was implemented on a Texas Instruments TMS320F28335 digital signal processor and validated through hardware-in-the-loop (HIL) simulation using the Typhoon HIL 600 platform, considering multiple scenarios with both linear and nonlinear loads. The main results highlight that the RC improves voltage regulation, mitigates harmonic distortion, and increases power delivery capability, thus validating its effectiveness for GFC operation. Full article

Sparse borehole sampling at contaminated sites results in sparse and unevenly distributed data on soil pollutants. Traditional interpolation methods may obscure local variations in soil contamination when applied to such sparse data, thus reducing the interpolation accuracy. We propose an adaptive graph convolutional network with spatial autocorrelation (ASI-GCN) model to overcome this challenge. The ASI-GCN model effectively constrains pollutant concentration transfer while capturing subtle spatial variations, improving soil pollution characterization accuracy. We tested our model at a coking plant using 215 soil samples from 15 boreholes, evaluating its robustness with three pollutants of varying volatility: arsenic (As, non-volatile), benzo(a)pyrene (BaP, semi-volatile), and benzene (Ben, volatile). Leave-one-out cross-validation demonstrates that the ASI-GCN_RC_G model (ASI-GCN with residual connections) achieves the highest prediction accuracy. Specifically, the R for As, BaP, and Ben are 0.728, 0.825, and 0.781, respectively, outperforming traditional models by 58.8% (vs. IDW), 45.82% (vs. OK), and 53.78% (vs. IDW). Meanwhile, their RMSE drop by 36.56% (vs. Bayesian_K), 38.02% (vs. Bayesian_K), and 35.96% (vs. IDW), further confirming the model’s superior precision. Beyond accuracy, Monte Carlo uncertainty analysis reveals that most predicted areas exhibit low uncertainty, with only a few high-pollution hotspots exhibiting relatively high uncertainty. Further analysis revealed the significant influence of pollutant volatility on vertical migration patterns. Non-volatile As was primarily distributed in the fill and silty sand layers, and semi-volatile BaP concentrated in the silty sand layer. At the same time, volatile Ben was predominantly found in the clay and fine sand layers. By integrating spatial autocorrelation with deep graph representation, ASI-GCN redefines sparse data 3D mapping, offering a transformative tool for precise environmental governance and human health assessment. Full article

Direct interface circuits (DICs) connect resistive, capacitive, and inductive sensors directly to microcontrollers or FPGAs, eliminating analog conditioning stages and offering compact, low-cost, and low-power instrumentation. This systematic review qualitatively synthesizes research up to March 2025 on DIC operation principles, performance metrics, and application domains. Following PRISMA guidelines, 90 studies from IEEE Xplore, ScienceDirect, MDPI, SpringerLink, Scopus, and Google Scholar were selected based on predefined inclusion criteria. Most studies focused on RC-based circuits (53%), followed by RL-based (5%) and charge transfer capacitive interfaces (5%). RC-DICs demonstrated accuracies below 0.01% using adaptive calibration; RL-DICs achieved resolutions of 10–12 bits with higher cycle requirements, while charge transfer interfaces presented systematic errors up to ±5% due to parasitic capacitances. Environmental monitoring, biomedical sensing, liquid-level control, and vehicular detection were frequent application fields. Due to methodological heterogeneity, findings were synthesized qualitatively without quantitative meta-analysis or formal bias assessments. Future research directions include enhanced noise immunity, simplified calibration, and robust parasitic effect compensation. Full article

The work presents and examines a fiber anchoring system of NSM CFRP strips proposed for strengthening RC beams. The study included 11 beams: 3 unstrengthened beams, 3 beams strengthened with NSM CFRP strip without anchorage, and 5 beams strengthened with NSM CFRP strips with additional anchorage in two variants (the fiber anchor wrapped around the CFRP strip end and fan-folded on the beam surface; the fiber anchor connected with a 20 cm overlap to the strip). All beams were loaded until failure with two concentrated forces (four-point loading test). The measurements were carried out using digital image correlation (DIC). The obtained ultimate load values reached an average of 43.5 kN for unstrengthened beams, while for strengthened beams, they ranged between 56.6 kN and 60.2 kN. The strengthening efficiency was comparable for all beams regardless of the anchorage used and ranged from 29% to 37%. All strengthened beams failed due to strip debonding. The obtained results did not allow confirmation of the effectiveness of the proposed anchoring system. Detailed analysis showed that the lack of anchoring effectiveness was related to the debonding initiating factor, i.e., vertical crack opening displacement, which has not been described in proper detail by the researchers. Full article

Specific emitter identification (SEI) methods based on deep learning (DL) have effectively addressed complex, multi-dimensional signal recognition tasks by leveraging deep neural networks. However, this advancement introduces challenges such as model parameter redundancy and high feature dimensionality, which pose limitations for resource-constrained (RC) edge devices, especially in Internet of Things (IoT) applications. To tackle these problems, we propose an RC-SEI method based on efficient design and model compression. Specifically, for efficient design, we have developed a lightweight convolution network (LCNet) that aims to balance performance and complexity. Regarding model compression, we introduce sparse regularization techniques in the fully connected (FC) layer, achieving over 99% feature dimensionality reduction. Furthermore, we have comprehensively evaluated the proposed method on public automatic-dependent surveillance-broadcast (ADS-B) and Wi-Fi datasets. Simulation results demonstrate that our proposed method exhibits superior performance in terms of both recognition accuracy and model complexity. Specifically, LCNet achieved accuracies of 99.40% and 99.90% on the ADS-B and Wi-Fi datasets, respectively, with only 33,510 and 33,544 parameters. These results highlight the feasibility and potential of our proposed RC-SEI method for RC scenarios. Full article

This paper presents the design of a four omni-wheeled mobile robot consisting of four omni wheels, with each wheel connecting to a separate DC motor. Additionally, the presence of a telescopic leg with a linear RC servo actuator enables the robot to adapt to various landscape changes, including obstacle overcoming. We have designed and manufactured the physical prototype of the robot based on the simulation results. The proposed robot can traverse in both vertical and horizontal directions without altering its orientation, thereby enhancing its stability during operation. The experimental results confirm the robot’s effectiveness in autonomously adapting its position in response to sudden changes in the landscape, enabling it to navigate and climb steps successfully. Full article

Composite and mixed steel-concrete buildings, apart from high structural efficiency, have great potential in terms of reuse of structural elements at the end of the life of the buildings. The use of most demountable connectors can assure the reuse of steel elements; however, the reuse of reinforced concrete (RC) elements and embedded connectors remains relatively uncertain due to potential damage of connectors during disassembly. One of the possible solutions to assure the reuse of all components could be to use demountable connectors assembled from a demountable bolt and an embedded mechanical coupler with a rebar anchor. The key challenge for practical implementation of this type of demountable connector is adequate analysis under tension loads, due to a lack of design recommendations. This paper presents experimental investigations of the connection with demountable connectors with mechanical couplers and rebar anchors, located close to the concrete edge, under pure tension load. Nine pull-out tests on single connectors embedded in the RC element and six in-air tests on bare connectors were conducted in order to define the global behavior of the connection and the local behavior of the connector, respectively. The influence of concrete strength (concrete class C20/25 and C30/37), connector diameter (with M16 and M20 bolts), and bolt grade (grades 5.8 and 8.8) on the connection behavior was discussed in terms of resistance, stiffness, deformation capacity, and failure modes. Ultimate resistance varied from 77 kN to 135 kN, with failure modes shifting from taper thread stripping to bolt fracture based on bolt grade. Based on the obtained test results, analytical equations for the calculation of tension resistance and overall deformation capacity of the connection were proposed. Full article

This study experimentally examines the flexural performance, crack formation patterns, and failure mechanisms of glass fiber-reinforced polymer (GFRP) bar-reinforced concrete beams with varying concrete compressive strengths (low, moderate, and high), addressing a gap in the current literature. Furthermore, it employs an innovative machine learning approach to enhance analysis. Nine RC beams reinforced with GFRP bars, having concrete compressive strengths of low (CC20), moderate (CC30), and high (CC40), each measuring 150 × 200 × 1100 mm, were fabricated and tested under three-point bending conditions. Through the integration of three-point bending tests and machine learning-based prediction models, this study connects experimental findings with advanced analytical approaches. One of the key innovations in this study is the use of eighteen ML regression models implemented with Python’s PyCaret library, achieving an impressive average prediction accuracy of 91.5% for RC beam deflection values. In particular, the Ada Boost Regressor and Gradient Boosting Regressor models performed exceptionally well on GFRP bar-reinforced concrete beams, providing the highest number of consistent and highly accurate predictions, making them very useful tools for GFRP bar-reinforced beam ultimate load-carrying capacity/deflection predictions. The outcomes identified clear failure mechanisms: RC beams with CC20, CC30, and CC40 concrete compressive strengths typically developed a single, large flexural crack at the midpoint. Although the ultimate load-carrying capacity of GFRP bar RC beams improved with higher concrete compressive strength, CC20 and CC30 beams displayed more ductile failure behavior than CC40 beams. The ultimate load-carrying capacity of CC40 RC beams was determined to be approximately 74% higher than that of CC20 RC beams. Regardless of the concrete compressive strength class, the absence of shear cracks and the prevention of sudden failure under bending in GFRP bar-reinforced concrete beams are considered major advantages of using GFRP bar reinforcement. Full article

This study examines the differential impact of proactive and reactive work connectivity behaviors on job well-being, drawing from the perspective of boundary theory. The increasing popularity of work connectivity behavior after-hours (WCBA) has attracted widespread attention from scholars on the relationship between WCBA and employee well-being. One view suggests that the impact of WCBA is negative, while another view suggests it is positive. Obviously, the impact of (WCBA) on well-being at work is still contradictory. To clarify the complexity of the impact of WCBA on well-being at work, based on boundary theory, we divided WCBA into proactive WCBA (PC) and reactive WCBA (RC), and examined the double-edged sword effect of WCBA on well-being at work, as well as the mediating mechanisms of job control and work-to-home conflict, and the moderated effects of boundary segmentation preferences. This study uses an empirical sampling method to collect data from 125 employees for a period of five days for quantitative research. The results show that, first, PC has an inverted U-shaped effect on job control, and job control is negatively related to well-being at work. Thus, the mediating effect of job control is significant. Second, RC has a negative impact on job control, and there is also a negative relationship between job control and well-being at work. Therefore, the mediating effect of job control is significant. Third, PC and RC are positively correlated with work-to-home conflict, and work-to-home conflict has a significant positive impact on well-being at work. Therefore, the mediating effect of work-family conflict is significant. Fourth, the study also found that integration preference moderates the relationship between work-to-home conflict and PC on well-being at work; that is, the mediating effect of work-to-home conflict is stronger for employees with a low integration preference. This study enriches our understanding of WCBA, PC, and RC from the perspective of proactive and passive employee behaviors. The study also provides a new interpretation of the impact of WCBA on well-being at work and offers valuable insights into sustainable development in digital social transformation and the application of boundary theory and the theory of empowerment–subjugation in achieving the United Nations’ Sustainable Development Goals. In addition, the study deepens our understanding of the heterogeneous regulatory role played by work–family integration preferences in influencing well-being at work under different types of WCBA. Full article