Search Results (133)

With the accelerated development of urban underground spaces, prefabricated tunnel linings have become a research focus due to their advantages in construction efficiency and cost effectiveness. However, issues such as stress concentration at joints and insufficient overall stability hinder their broader application. This study investigates a cut-and-cover prefabricated tunnel project in the Chongqing High-Tech Zone through scale model tests and numerical simulations to systematically compare the mechanical behaviors of cast-in situ linings and three-segment prefabricated linings under surrounding rock loads. The experimental results show that the ultimate bearing capacity of the prefabricated lining is 15.3% lower than that of the cast-in situ lining, with asymmetric failure modes and cracks concentrated near joint regions. Numerical simulations further reveal the influence of joint stiffness on structural performance: when the joint stiffness is 30 MN·m/rad, the bending moment of the segmented lining decreases by 37.7% compared to the cast-in situ lining, while displacement increments remain controllable. By optimising joint pre-tightening forces and stiffness parameters, prefabricated linings can achieve stability comparable to cast-in situ structures while retaining construction efficiency. This research provides theoretical and technical references for the design and construction of open-cut prefabricated tunnel linings. Full article

Molybdenum lithium compounds and materials are being researched and applied in cutting-edge industries; however, their bonding has not been explored in a systematic way. The present study investigates the MoLi molecule, to shed light on its bonding. Specifically, the electronic structure and bonding of the ground and 40 low-lying states of the MoLi molecule are explored, employing multireference methodologies, i.e., CASSCF and MRCISD(+Q) in conjunction with the aug-cc-pV5z(-PP) basis set. Bond distances, dissociation energies, dipole moments as well as common spectroscopic constants are given, while the potential energy curves are plotted. For the ground state, X${}^6\Sigma _{+}$, it is found that $R_{\mathrm{e}}$ = 2.708 Å, $D_{\mathrm{e}}$ = 24.1 kcal/mol, ${\omega }_{\mathrm{e}}$ = 316.8 ${\mathrm{cm}}^{-1}$, ${\omega }_{\mathrm{e}}{x}_{\mathrm{e}}$ = 2.11 ${\mathrm{cm}}^{-1}$, and μ = 3.63 D. Overall, the calculated states present a variety of bonds, from weak van der Waals up to the formation of 2.5 bonds. The dissociation energies of the calculated states range from 2.3 kcal/mol ($\mathrm{a}{}^8{\Sigma }^{+}$) to 34.7 ($\mathrm{c}{}^4\Pi$), while the bond distances range from 2.513 Å to 3.354 Å. Finally, dipole moment values up to 3.72 D are calculated. In most states, a 2s${2\mathrm{p}}_{\mathrm{z}}$ hybridization on Li and a ${4\mathrm{d}}_{{\mathrm{z}}^2}$5s${5\mathrm{p}}_{\mathrm{z}}$ or 5s${5\mathrm{p}}_{\mathrm{z}}$ hybridization on Mo are found. Moreover, it is observed that the excited Li(${}^2\mathrm{P}$) atom forms the shortest bonds because its empty ${2\mathrm{s}}^0$ orbital can easily accept electrons, resulting in a strong σ dative bond. Finally, the present work highlights the exceptional ability of lithium atoms to participate in a variety of bonding schemes, and it could provide the opening gate for further investigation of this species or associated material and complexes. Full article

The startup dynamics of wind turbines have a direct impact on their cut-in speed and thus their capacity factor, considering highly transient winds in urban environments. Due to the complex nature of the startup dynamics, the published research on it is severely lacking. Unless the startup dynamics and cut-in speed of a wind turbine are known, it is difficult to evaluate its capacity factor and levelized cost of energy (LCoE) for commercial viability. In this study, a Savonius vertical-axis wind turbine (VAWT) has been considered and its startup dynamics evaluated using numerical techniques. Moreover, the effects of turbine inertia, arising from bearing frictional losses, generator load, etc., on the startup dynamics have been studied. Advanced computational fluid dynamics (CFD)-based solvers have been utilized for this purpose. The flow-induced rotation of the turbine blades has been modeled using a six degree of freedom (6DoF) approach. Turbine inertia has been modeled using the mass moment of inertia of the turbine rotor and systematically increased to mimic the additional inertia and losses due to bearings and the generator. The results indicate that inertia has a significant impact on the startup dynamics of the VAWT. It was observed that as the turbine inertia increased, it took longer for the turbine to reach its steady or peak operational speed. Increasing the inertia by 10%, 20% and 30% increased the time taken by the turbine to reach its peak rotational speed by 13.3%, 16.7% and 23.2%, respectively. An interesting observation from the results obtained is that an increase in turbine inertia does not change the peak rotational speed. For the Savonius rotor considered, the peak rotational speed remained 122 rpm, and its tip speed ratio (TSR) remained 0.6 while increasing the turbine inertia. Full article

Background/Objectives: This study aimed to examine how uncertainties in inertial properties and minimal sets of inertial parameters (MSIP) affect inverse-dynamics simulations of high-acceleration sport movements and to demonstrate that applying MSIP identified through the free vibration measurement method improves simulation accuracy. Methods: Monte Carlo simulations were performed for running, side-cutting, vertical jumping, arm swings, and leg swings by introducing uncertainties in inertial properties and MSIP. Results: These uncertainties significantly affect the joint torques and ground reaction forces and moments (GRFs&Ms), especially during large angular acceleration. The mass and longitudinal position of the center of gravity had strong effects. Subsequently, MSIP identified by our methods with free vibration measurement were applied to the same tasks, improving the accuracy of the predicted ground reaction forces compared with the standard regression-based estimates. The root mean square error decreased by up to 148 N. Conclusions: These results highlight that uncertainties in inertial properties and MSIP affected the calculated joint torques and GRFs&Ms, and combining experimentally identified MSIP with dynamics simulations enhances precision. These findings demonstrate that utilizing the MSIP from free vibration measurement in inverse dynamics simulations improves the accuracy of dynamic models in sports biomechanics, thereby providing a robust framework for precise biomechanical analyses. Full article

The conversion of air currents through wind turbine technology stands as one of the most significant and effective means of generating green electricity. Wind turbines featuring a horizontal axis exhibit the greatest installed capacity. The study establishes a mathematical model for large wind turbines, categorized by megawatt output, utilizing measured data for key parameters, including wind speed, power output from the generator, and rotational speed. The analysis of the system’s behavior on startup—the cut-in wind speed, is conducted by transitioning the electric generator into motor mode. A mathematical model has been established for the dual-powered motor configuration, wherein both the stator and rotor are connected to a common frequency network, facilitating a shift to synchronous motor functionality. The equation that describes the kinetic moment highlights the importance of attaining optimal velocity, while simultaneously accounting for variations in the load angle. These fluctuations are observable in both the power output and the electrical currents. The simulations that have been processed are derived from experimental data, specifically inputs obtained from a 1.5 MW wind turbine located in the Oravita region of southwestern Romania. The paper thus outlines essential elements concerning the functionality of high-power wind turbines that utilize wound rotor induction generators, aiming to guarantee optimal performance from the moment the wind speed reaches the cut-in threshold. Full article

Understanding and knowing the extent of dynamic loads (forces and moments) acting on critical points of structures from the early stages of new product design allows companies to reduce product time-to-market and cut costs associated with physical validation tests. This is made possible through the use of commercial software that enables the simulation of the dynamic behavior of a wide range of mechanical systems, and beyond. However, the use of such software is not straightforward and often requires a specialist within the company to have in-depth knowledge of both simulations and the software itself. Consequently, many companies give up the use of these tools, compromising the whole product development process, falling into the design and testing iterative loop. The multibody mathematical model developed in this study, simulated using python programming language, allows easy retrieval of all the necessary information without requiring the user to be a specialist in multibody dynamics simulations. This model is intended as a tool specifically designed for the type of product (aerial work platform) that serves, during the conceptual and preliminary design phases, to predict dynamic loads through calculations. The balance between the simplicity of such a tool and the accuracy of the results is the key point for the success of this work. Full article

A clean environment enhances well-being and drives economic growth. BRICS nations aim to cut emissions while sustaining growth, aligning with global sustainability goals. Their strong economic progress underscores the need to explore the links between communication technology, financial efficiency, education, and renewable energy consumption (RENC). Therefore, to analyze these dynamics, this study examines data spanning from 1990 to 2020 using a rigorous methodological framework. Initially, model selection was guided by AIC and BIC criteria by ensuring optimal model fit. Furthermore, multicollinearity was assessed using the Variance Inflation Factor (VIF), while heteroscedasticity and autocorrelation issues were tested through the Breusch–Pagan Test and the Ljung–Box Test, respectively. Additionally, cross-sectional dependence (CSD) was checked, followed by stationarity analysis using the second-generation CIPS. The Westerlund Cointegration Test was employed to confirm long-run relationships. As a final preliminary test, the study uses the Hausman test for selection of the appropriate model specification. Subsequently, the PMG-ARDL approach was utilized to examine both short- and long-term dynamics. The findings reveal a significant negative relationship between RENC, Gross Domestic Product (GDP), and CO₂ emissions. Conversely, RENC exhibits a strong positive association with education (EDUC), information and communication technology (IACT), the financial markets efficiency index (FMEI), and the financial institutions efficiency index (FIEI). Finally, the robustness of the PMG-ARDL results was validated through advanced techniques, including Fully Modified OLS (FMOLS) and the Generalized Method of Moments (GMM), reinforcing the reliability of the findings. The study offers valuable policy recommendations to support sustainable development in BRICS nations. Full article

The growing penetration of renewable energy sources (RES) has exacerbated operational flexibility deficiencies in modern power systems under time-varying conditions. To address the limitations of existing flexibility management approaches, which often exhibit excessive conservatism or risk exposure in managing supply–demand uncertainties, this study introduces a data-driven distributionally robust optimization (DRO) framework for power system scheduling. The methodology comprises three key phases: First, a meteorologically aware uncertainty characterization model is developed using Copula theory, explicitly capturing spatiotemporal correlations in wind and PV power outputs. System flexibility requirements are quantified through integrated scenario-interval analysis, augmented by flexibility adjustment factors (FAFs) that mathematically describe heterogeneous resource participation in multi-scale flexibility provision. These innovations facilitate the formulation of physics-informed flexibility equilibrium constraints. Second, a two-stage DRO model is established, incorporating demand-side resources such as electric vehicle fleets as flexibility providers. The optimization objective aims to minimize total operational costs, encompassing resource activation expenses and flexibility deficit penalties. To strike a balance between robustness and reduced conservatism, polyhedral ambiguity sets bounded by generalized moment constraints are employed, leveraging Wasserstein metric-based probability density regularization to diminish the probabilities of extreme scenarios. Third, the bilevel optimization structure is transformed into a solvable mixed-integer programming problem using a zero-sum game equivalence. This problem is subsequently solved using an enhanced column-and-constraint generation (C&CG) algorithm with adaptive cut generation. Finally, simulation results demonstrate that the proposed model positively impacts the flexibility margin and economy of the power system, compared to traditional uncertainty models. Full article

This cross-sectional laboratory-based study investigates the stress characteristics of the anterior cruciate ligament (ACL) during side-cutting using a knee finite element (FE) model and identifies biomechanical factors influencing ACL stress. Kinematics and ground reaction forces (GRF) were collected from eight participants (age: 30.3 ± 5.3 years; BMI: 25.6 ± 2.4 kg/m²; time since surgery: 12.8 ± 1.2 months) one year post–ACL reconstruction during side-cutting tasks. A knee FE model incorporating time-varying knee angles, knee forces, and femoral translation was developed to simulate the knee biomechanics. The relationships between ACL stress and lower limb biomechanics were analyzed. The results indicated the highest stress concentrations at the femoral attachment during the early landing phase. Posterior femoral displacement relative to the tibia was significantly correlated with peak ACL equivalent stress (r = 0.89, p = 0.003) and peak ACL shear stress (r = 0.82, p = 0.023). Peak ACL equivalent stress also showed positive correlations with posterior GRF (r = 0.77, p = 0.025) and knee extension moments (r = 0.71, p = 0.049). In contrast, peak ACL shear stress exhibited a significant negative correlation with hip extension moment (r = −0.80, p = 0.032). This study identified key biomechanical factors affecting ACL stress, highlighting the roles of femoral displacement, knee extension moments, and ground reaction forces, while demonstrating a negative relationship with hip extension moments. Full article

Mechanical construction has gradually been applied in cross passages of metro lines, but more mechanical mechanisms should be revealed. The section between Jingrong Street Station and Kunjia Road Station in Suzhou Metro Line 11 adopts a mechanical construction method to construct a cross passage. A novel flat-face cutterhead, which is different from curved cutter head is first used to cut and break the main tunnel in construction of cross passage. Based on the background of practical engineering, the finite element method was applied to simulate the breaking process of the main tunnel to explore the dynamic variation in the mechanical response of the segments cut by the flat-face cutterhead. The results indicate that the maximum vertical displacement caused by cutting mainly concentrates on the top of the fully cut rings. The maximum horizontal displacement occurs at the waist on the side of the tunnel portal in the semi-cut rings. The axial force level inside both types of segment rings reaches its peak after the tunnel is formed. The maximum axial force exists at the bottom and top of the fully cut ring and semi-cut ring, respectively. The change in the displacement around the portal is not substantial before the third stage, and it begins to increase significantly from the moment the concrete at the portal is penetrated. The existence of the pre-support system effectively controls the displacement of the third and fourth fully cut rings. Emphasis should be placed on reinforcing the soil near the top and waist of the second to fifth rings. The findings demonstrate that the application of flat-face cutterhead in mechanical construction of cross passages is safe, reliable, and efficient, and can provide valuable suggestions for further cutting parameters and soil reinforcement as well. Full article

Duralumin 2024-T351 is an alloy characterized by a good mechanical strength, relatively high hardness and corrosion resistance frequently used in the aeronautical, automotive, defense etc. industries. In this paper, the variation of axial forces and torques when drilling aluminum alloy 2024-T351 was investigated, analyzing the measured values for different cutting regimes. Experimental data on the forces and moments generated during the drilling process were collected using specialized equipment, and these data were preprocessed and analyzed using MatLab R218a. The experimental plan included 27 combinations of the parameters of the cutting regime (cutting depth, cutting speed, and feed), for which energetic cutting parameters were measured, the axial force and the torsion moment, respectively Based on these data, a neural network was trained, using the Bayesian regularization algorithm, in order to predict the optimal values of the cutting energy parameters. The neural model proved to be efficient, providing predictions with a relative error below 10%, indicating a good agreement between measured and simulated values. In conclusion, neural networks offer an accurate alternative to classical analytical models, being more suitable for materials with complex behavior, such as aluminum alloys. Full article

Background: The ankle joint is among the most vulnerable areas for injuries during daily activities and sports. This study focuses on individuals with chronic ankle instability (CAI), comparing the biomechanical characteristics of the lower limb during side-step cutting under various conditions. The aim is to analyze the impact of kinesiology tape (KT) length on the biomechanical properties of the lower limb during side-step cutting, thereby providing theoretical support and practical guidance for protective measures against lower-limb sports injuries. Methods: Twelve subjects with CAI who met the experimental criteria were recruited. Each subject underwent testing without taping (NT), with short kinesiology tape (ST), and with long kinesiology tape (LT), while performing a 45° side-step cutting task. This study employed the VICON three-dimensional motion capture system alongside the Kistler force plate to synchronously gather kinematic and kinetic data during the side-step cutting. Visual 3D software (V6.0, C-Motion, Germantown, MD, USA) was utilized to compute the kinematic and kinetic data, while OpenSim 4.4 software (Stanford University, Stanford, CA, USA) calculated joint forces. A one-way Analysis of Variance (ANOVA) was conducted using SnPM, with the significance threshold established at p < 0.05. The Origin software 2021 was used for data graphic processing. Results: KT was found to significantly affect joint angles, angular velocities, and moments in the sagittal, frontal, and transverse planes. LT increased hip and knee flexion angles as well as angular velocity, while ST resulted in reduced ankle inversion and increased knee internal rotation. Both types of KT enhanced hip abduction moment and knee adduction/abduction moment. Additionally, LT reduced the ankle joint reaction force. Conclusions: These findings suggest that the application of KT over a short duration leads to improvements in the lower-limb performance during side-step cutting motions in individuals with CAI, thus potentially decreasing the risk of injury. Full article

This article presents a novel methodology for analyzing the resilience of an active distribution system (ADS) integrated with an urban gas network (UGN). It demonstrates that the secure adoption of gas turbines with optimal capacity and allocation can enhance the resilience of the ADS during high-impact, low-probability (HILP) events. A two-level tri-layer resilience problem is formulated to minimize load shedding as the resilience index during post-event outages. The challenge of unpredictability is addressed by an adaptive distributionally robust optimization strategy based on multi-cut Benders decomposition. The uncertainties of HILP events are modeled by different moment-based probability distributions. In this regard, considering the nature of each uncertain variable, a different probabilistic method is utilized. For instance, to account for the influence of power generated from renewable energy sources on the decision-making process, a diurnal version of the long-term short-term memory network is developed to forecast day-ahead weather. In comparison with standard LSTM, the proposed approach reduces the mean absolute error and root mean squared error by approximately 47% and 71% for wind speed, as well as 76% and 77% for solar irradiance network. Finally, the optimal operating framework for improving power grid resilience is validated using the IEEE 33-bus ADS and 7-node UGN. Full article

Background: Knee-related injuries often result from poor movement patterns that destabilize the joint and increase stress on knee structures. Understanding the influence of foot positioning on knee biomechanics is critical for identifying high-risk movement patterns and preventing injuries. Methods: Twenty healthy male participants performed side-cutting movements at three different foot progression angles. One participant’s data were used to develop and validate a knee finite element model with high-speed dual fluoroscopic imaging (DFIS). Combined with a musculoskeletal analysis, the model simulated internal knee loads under various foot-positioning conditions. Results: The analysis revealed that, as the external foot progression angle increased, the ankle plantarflexion decreased, while the ankle internal rotation and knee valgus moments increased. Higher stress concentrations were observed on the ACL, lateral meniscus, lateral tibial cartilage, and medial collateral ligament, particularly at the femoral–tibial ACL attachments. Conclusion: The findings suggest that a toe-out foot position elevates the risk of knee injuries by increasing stress on key structures, whereas a toe-in position may enhance joint stability, reduce the ACL injury risk, and promote favorable muscle activation patterns. Full article

Effective weed detection is essential in modern agriculture to improve crop yield and quality. Farmers can optimize their weed control strategies by applying herbicides tailored to the identified weed species and the areas they affect. Real-time object detection has been transformed by recent advances in image detection technology, especially the You Only Look Once (YOLO) algorithm; of these, YOLOv7 has been shown to be more accurate than its predecessors in weed detection. Because of its novel E-ELAN layer, the YOLOv7 model achieves 97% accuracy, compared to the estimated 78% accuracy of the YOLOv5 model. This study suggests using Internet of Things (IoT) sensors in conjunction with YOLOv7 to improve weed detection using an integrated strategy. It was advantageous to include a variety of sensors in the proposed method to detect and manage weeds. Greater accuracy and comprehensiveness were achieved by combining a variety of sensors to improve the data obtained. An enhanced weed detection system has been developed by utilizing each sensor type’s distinct information. A comprehensive set of environmental data, including soil moisture, temperature, humidity, light intensity, pH, and ultrasonic distance sensors, were used to determine correlation with weed growth patterns. This information was sent to a central Internet of Things gateway for in-the-moment analysis and merged with video footage of agricultural fields. Farmers will be able to anticipate weed infestations and optimize their management tactics using predictive analytics, which will be made possible by integrating sensor data with YOLOv7’s weed-detecting capabilities. This methodology seeks to revolutionize weed control procedures by utilizing cutting-edge technology and IoT connectivity, making them more effective and efficient. Full article