Search Results (207)

Accurate extraction of representative operating conditions is crucial for optimizing systems in renewable energy applications. This study proposes a novel framework that combines the Parzen window estimation method, ideal for nonparametric modeling of wind, solar, and load datasets, with a game theory-based time scale selection mechanism. The novelty of this work lies in integrating probabilistic density modeling with multi-indicator evaluation to derive realistic operational profiles. We first validate the superiority of the Parzen window approach over traditional Weibull and Beta distributions in estimating wind and solar probability density functions. In addition, we analyze the influence of key meteorological parameters such as wind direction, temperature, and solar irradiance on energy production. Using three evaluation metrics, the main result shows that a 3-day representative time scale offers optimal accuracy when determined through game theory methods. Validation with real-world data from Inner Mongolia confirms the robustness of the proposed method, yielding low errors in wind, solar, and load profiles. This study contributes a novel 3-day typical profile extraction method validated on real meteorological data, providing a data-driven foundation for optimizing energy storage systems under renewable uncertainty. This framework supports energy sustainability by ensuring realistic modeling under renewable intermittency. Full article

The muzzle velocity of electromagnetic rail launchers approaches 1550 m/s, exhibiting typical hypervelocity electrical contact characteristics. During the electromagnetic launching process, extreme conditions, such as high current density, high temperature rise, and strong strain can cause wear on the surfaces of the armature and rail. Electromagnetic launch tests are conducted to study the wear conditions of the rail surface and the relationship between the wear state and contact resistance. After the rail is abraded by hundreds of launching armatures, its surface 2D profile and morphological characteristics are measured and analyzed. Based on fractal theory, the static contact resistance model is developed. Concurrently, the contact resistance at various positions is measured to reveal the evolution of the static contact resistance between the armature and the rail under wear. The research results show that along the direction of the armature launch, the rail surface wear transitions from mechanical wear to electrical wear, the fluctuation range of the 2D profile becomes smoother, and the roughness of the rail surface shows a decreasing trend. When the roughness is greater, the contact resistance is more sensitive to changes in external load. Full article

The rapid development of electric transport necessitates efficient energy storage and redistribution in traction systems. A key challenge is the utilization of regenerative braking energy, which is often dissipated in resistors due to network saturation and limited consumption capacity. The paper addresses the problem of inefficient energy utilization in electric rail vehicles due to the absence of effective energy recovery mechanisms. A specific challenge arises when managing energy recuperated during regenerative braking, which is typically lost if not immediately reused. This study proposes the integration of on-board energy storage systems (ESS) based on supercapacitor technology to temporarily store excess braking energy. A mathematical model of a traction drive with a DC motor and supercapacitor-based ESS is developed, accounting for variable load profiles and typical urban driving cycles. Simulation results demonstrate potential energy savings of up to 30%, validating the feasibility of the proposed solution. The model also enables system-level analysis for optimal ESS sizing and placement in electric rail vehicles. Full article

This study presents the design, fabrication, and experimental validation of a two-finger robotic gripper featuring a 135° V-shaped fingertip profile tailored for lightweight waste collection in laboratory-scale environmental robotics. The gripper was developed with a strong emphasis on cost-effectiveness and manufacturability, utilizing a desktop 3D printer and off-the-shelf servomotors. A four-bar linkage mechanism enables parallel jaw motion and ensures stable surface contact during grasping, achieving a maximum opening range of 71.5 mm to accommodate common cylindrical objects. To validate structural integrity, finite element analysis (FEA) was conducted under a 0.6 kg load, yielding a safety factor of 3.5 and a peak von Mises stress of 12.75 MPa—well below the material yield limit of PLA. Experimental testing demonstrated grasp success rates of up to 80 percent for typical waste items, including bottles, disposable cups, and plastic bags. While the gripper performs reliably with rigid and semi-rigid objects, further improvements are needed for handling highly deformable materials such as thin films or soft bags. The proposed design offers significant advantages in terms of rapid prototyping (a print time of approximately 10 h), modularity, and low manufacturing cost (with an estimated in-house material cost of USD 20 to 40). It provides a practical and accessible solution for small-scale robotic waste-collection tasks and serves as a foundation for future developments in affordable, application-specific grippers. Full article

The growing integration of renewable energy and electric vehicle loads in parks has intensified the intermittency of photovoltaic (PV) output and demand-side uncertainty, complicating energy storage system design and operation. Meanwhile, under carbon neutrality goals, the energy system must balance economic efficiency with emission reductions, raising the bar for storage planning. To address these challenges, this study proposes a two-stage robust optimization method for shared energy storage configuration in a park-level integrated PV–storage–charging system (PV-SESS-CS). The method considers the uncertainties of PV and electric vehicle (EV) loads and incorporates carbon emission reduction benefits. First, a configuration model for shared energy storage that accounts for carbon emission reduction is established. Then, a two-stage robust optimization model is developed to characterize the uncertainties of PV output and EV charging demand. Typical PV output scenarios are generated using Latin Hypercube Sampling, and representative PV profiles are extracted via K-means clustering. For EV charging loads, uncertainty scenarios are generated using Monte Carlo Sampling. Finally, simulations are conducted based on real-world industrial park data. The results demonstrate that the proposed method can effectively mitigate the negative impact of source-load fluctuations, significantly reduce operating costs, and enhance carbon emission reductions. This study provides strong methodological support for optimal energy storage planning and low-carbon operation in park-level PV-SESS-CS. Full article

Background/Objectives: Previous studies have typically investigated injury risk factors either by body region or sport type in isolation, limiting their practical applicability to real-world settings where multiple factors interact. However, injury risk is inherently multifactorial—shaped by a complex interplay of demographic, physiological, and training-related characteristics that differ by anatomical site and sport context. This study addresses that gap by simultaneously analyzing predictors across multiple body regions and sport-specific environments. This integrated approach is critical for developing more precise, evidence-based injury prevention strategies tailored to the specific demands and risk profiles of amateur athletes. This study aimed to identify key predictors of injury risk across various body regions and sport-specific contexts among amateur athletes. Specifically, we sought to (1) develop predictive models that include demographic and body composition variables, and (2) compare the relative predictive strength of these variables across models, highlighting differences in their influence by injury location and sport type. Methods: A total of 454 amateur athletes (219 males and 235 females) participated. Data on anthropometry, body composition, training load were collected. Injury history was obtained via self-administered questionnaires, with participants reporting injuries that had occurred during the 12 months prior to the time of data collection. Logistic regression models were used to identify significant predictors, and Nagelkerke’s R² was calculated to assess model fit. Results: Overall, 49.78% of athletes experienced injuries, with a higher proportion in females (54.47%) than in males (44.75%). Age demonstrated divergent effects: it was protective against both upper and lower limb injuries in male individual-sport athletes (OR = 0.62 and OR = 0.69, respectively) and in female athletes across sport types (ORs = 0.75–0.64), but conversely increased the risk of upper limb injuries in male team-sport athletes (OR = 1.88). In female individual athletes, higher Skeletal Muscle Index (SMI) predicted upper limb injuries (OR = 1.18, p = 0.034). In female team athletes, higher Muscle-to-Fat Ratio (MFR) (OR = 2.46, p = 0.017) and BMI (OR = 1.67, p = 0.008) predicted upper limb injuries, while higher Fat Mass Index (FMI) predicted lower limb injuries (OR = 1.70, p = 0.009). Models showed moderate explanatory power (Nagelkerke’s R² ranging from 0.03 to 0.33). Conclusions: These findings suggest that injury risk profiles are highly context-dependent. Preventive strategies should be tailored by sex and sport type, for example, younger athletes in team sports may benefit from age-sensitive load monitoring, while in female team athletes, targeted interventions addressing both fat and muscle balance could be essential. Age, body composition, and sport-specific demands should be considered in individualized injury prevention planning. Full article

Integrating offshore renewable energy (ORE) into power systems is vital for sustainable energy transitions. This paper examines the challenges and opportunities in integrating ORE, focusing on offshore wind and floating solar, into grid systems. A simulation was conducted using a 5 MW offshore wind turbine and a 2 MW floating PV (FPV) system, complemented by a 10 MWh battery energy storage system (BESS). The simulation utilized the typical load profile of Belgium and actual 2023 electricity price data, along with realistic wind and solar generation patterns for a location at the sea border of Belgium and the Netherlands. The use of real operational and market data ensures the practical relevance of the results. This study highlights the importance of BESS, targeting a significant revenue by participating in system imbalance and providing ancillary services (aFRR and mFRR). Key findings emphasize the need for grid infrastructure transformation to support ORE’s growing investments and deployment. This research underscores the essential role of technological innovation and strategic planning in optimizing the potential of ORE sources. Full article

Due to the dynamic increase in the number of prosumer electrical installations in Poland, one may observe many negative effects of their development, including the deterioration of energy quality parameters and the reliability of the existing distribution network. The installation of solar panels in Polish homes was mainly motivated by economic reasons. One of the most important problems of the distribution network is the increase in voltage. The aim of this work was to develop a practical method for determining the maximum voltage changes caused by the connection of photovoltaic installations. To accomplish this, a representative low-voltage overhead line, typical of those found in Poland, was modeled using the NEPLAN software. More than 100 distinct simulations were conducted, exploring various locations and power capacities of photovoltaic installations and utilizing authentic annual profiles for both electrical loads and photovoltaic generation. From the analysis of the data obtained, relationships that enable the determination of voltage changes induced by photovoltaic connections at any node within the low-voltage circuit were established. The computational results derived from this simplified model demonstrate sufficient accuracy for practical applications, and the required input data is accessible to distribution system operators. Full article

The design of a removable module is proposed in order to enable the use of open wagons for container transportation. This module secures a container placed on an open wagon considering conditions for its strength under conditions of the operational load. The use of rectangular pipes was proposed as profiles for the removable module. The possibility of optimizing the cross-section parameters of the beams of the removable module frame was investigated. The optimization was carried out according to the criterion of a reduction in the material consumption of the removable module frame. It was established based on the preformed calculations that this optimization contributes to reducing the unit mass of the frame beam by 1.5% compared to using a typical rectangular profile. A spatial model of the removable module was built, and its strength was calculated considering the results of the optimization process. The results of the calculations show that the strength of the removable module is ensured under the considered load schemes. Moreover, within the framework of the research, an experimental study of the hatch cover strength of an open wagon when loaded by the removable module was carried out. At the same time, experimental tests were carried out in laboratory conditions using the method of the electrical strain gage. It was established that the strength of the hatch cover is maintained. The conducted research will contribute to the creation and development of the use of open wagons for container transportation and, accordingly, to increasing the efficiency of containerized cargo transportation, including in international traffic. Full article

This paper presents an experimental and numerical investigation of the axial compression behavior of perforated cold-formed steel upright profiles commonly used in pallet racking systems. The primary objective is to examine how slenderness influences the failure modes and load-bearing capacity of these structural elements. Three column lengths, representative of typical vertical spacing in industrial rack systems, were tested under pin-ended boundary conditions. All specimens were fabricated from 2 mm thick S355 steel sheets, incorporating web perforations and a central longitudinal stiffener. Experimental results highlighted three distinct failure mechanisms dependent on slenderness: local buckling for short columns (SS-340), combined distortional–flexural buckling for medium-length columns (MS-990), and global flexural buckling for slender columns (TS-1990). Finite Element Method (FEM) models developed using ANSYS Workbench 2021 R1 software accurately replicated the observed deformation patterns, stress concentrations, and load–displacement curves, with numerical results differing by less than 5% from experimental peak loads. Analytical evaluations performed using the Effective Width Method (EWM) and Direct Strength Method (DSM), following EN 1993-1-3 and AISI S100 specifications, indicated that EWM tends to underestimate the ultimate strength by up to 15%, whereas DSM provided results within 2–7% of experimental values, especially when the entire net cross-sectional area was considered fully effective. The originality of the study is the comprehensive evaluation of full-scale, perforated, stiffened cold-formed steel uprights, supported by robust experimental validation and detailed comparative analyses between FEM, EWM, and DSM methodologies. Findings demonstrate that DSM can be reliably applied to perforated sections with moderate slenderness and adequate web stiffening, without requiring further local reduction in the net cross-sectional area. Full article

Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions. Full article

A low Reynolds number (Re) environment leads to severe deterioration in compressor performance, and it is necessary and challenging to accurately predict performance at a low Re during the design phase of a compressor. This study first reveals the mechanism of typical flow characteristics in transonic compressor at a low Re via simulations. When comparing the cases with different Re, the equivalent blade profile variation due to the growth of the boundary-layer thickness is found to be the main reason for changing the flow field. On the basis of boundary-layer theory, a prediction model of the equivalent profile is developed for the viscous effect on the boundary layer, and a multiline strategy is applied to calculate the blade-load radial redistribution. The equivalent blade prediction error at different Re is up to 7.8% compared to the CFD results. Ultimately, this strategy improves the radial spatial resolution compared to the original method and is able to predict the compressor performance at a low Re with pressure ratio and efficiency errors of 0.23% and 1.8%, respectively. Full article

The internet data center (IDC) has experienced rapid growth recently. Computing power tasks have the characteristic of flexible adjustment and can participate in demand-side response; thus, they are suitable for balancing stochastic wind and solar power. Existing studies lack research on joint optimization between the IDC and power grid. This paper proposes a joint optimization scheduling approach for IDC and power systems, focusing on the response of computing tasks. Based on the adjustment characteristics of computing tasks, tasks are categorized, and operational constraints for each category are defined. The bi-level optimization model for the IDC and power grid is established, taking into account the task constraints, as well as the operational limits of power generation units and the IDC. A novel elasticity coefficient matrix for time-of-use (TOU) electricity pricing is proposed, considering the load characteristics of IDC tasks. The IDC’s demand response volume is determined using the elasticity coefficient matrix. The enhanced Benders decomposition method is then employed, incorporating the IDC’s demand response capacity and the constraints of the bi-level optimization model, to solve the optimal planning problem. To achieve scenario reduction, the K-means algorithm is utilized to derive the typical daily load profiles of the IDC. The simulation results validate the effectiveness and accuracy of the proposed method and show that the approach effectively reduces the operational costs of the IDC power system and enhances the sustainable integration of renewable energy. Full article

The Monit4Healthy system is an IoT-enabled health monitoring solution designed to address critical challenges in real-time biomedical signal processing, energy efficiency, and data transmission. The system’s modular design merges wireless communication components alongside a number of physiological sensors, including galvanic skin response, electromyography, photoplethysmography, and EKG, to allow for the remote gathering and evaluation of health information. In order to decrease network load and enable the quick identification of abnormalities, edge computing is used for real-time signal filtering and feature extraction. Flexible data transmission based on context and available bandwidth is provided through a hybrid communication approach that includes Bluetooth Low Energy and Wi-Fi. Under typical monitoring scenarios, laboratory testing shows reliable wireless connectivity and ongoing battery-powered operation. The Monit4Healthy system is appropriate for scalable deployment in connected health ecosystems and portable health monitoring due to its responsive power management approaches and structured data transmission, which improve the resiliency of the system. The system ensures the reliability of signals whilst lowering latency and data volume in comparison to conventional cloud-only systems. Limitations include the requirement for energy profiling, distinctive hardware miniaturizing, and sustained real-world validation. By integrating context-aware processing, flexible design, and effective communication, the Monit4Healthy system complements existing IoT health solutions and promotes better integration in clinical and smart city healthcare environments. Full article

In this work, we propose a method for the shape optimization of frame structures using a mixed analytical–numerical approach. The goal is to achieve a uniform-strength frame structure, ensuring optimal material utilization and weight minimization. The optimization is performed in two calculation steps. The first step uses an analytical model based on the Timoshenko beam theory, where appropriate mathematical steps give a uniform-strength shape of the entire structure. Depending on the type of cross-section analyzed, the exact uniform-strength profile of each element is derived by solving for three parameters related to the forces and moments acting on the element. These parameters are obtained by solving a nonlinear system of equations, which includes the external and internal kinematic constraints of the structure, as well as equilibrium equations for each element. However, the solution obtained using the one-dimensional theory is limited in areas affected by boundary effects, such as the interconnection regions between elements and those near the supports, for a decay distance at least equal to the characteristic diameter of the section. To address this limitation, the second optimization step involves incorporating solutions that account for a triaxial stress field. This is typically carried out by discretizing the structure using the finite element method. The frame geometry obtained from the previous analytical solution is constructed, and the regions affected by boundary effects are optimized using the Biological Growth Method (BGM). This is an iterative, bio-inspired method modeled on the growth of trees, which increases trunk diameter in proportion to the loads experienced. The method is applied simultaneously to all regions where three-dimensional effects are significant, with the aim of achieving uniform strength in areas influenced by boundary effects. An important aspect of applying the BGM is maintaining the topology of the initial mesh, which is ensured through the use of mesh morphing techniques. The results of the two-step optimization process are shown on simple geometries involving few elements, and on more complex geometries of mechanical interest. Full article