Search Results (140)

This paper presents the application of a sliding mode observer for speed sensorless control of a six-phase induction machine. The use of nonlinear sliding mode techniques yields acceptable performance for both low- and high-speed motor operations over a wide speed range. The effectiveness and accuracy of the developed sensorless scheme are verified by experimental results, which demonstrate the system’s performance under various operating conditions. These results demonstrate the advantages of the proposal as a valid alternative to the conventional method, which uses a mechanical speed sensor for multiphase machines. Additionally, the sensorless approach can also serve as a redundant backup in the event of mechanical sensor failure, thereby increasing the reliability of the overall drive system. Full article

This study analyses the application of the Friction Stir Welding (FSW) process on polymeric materials manufactured by additive manufacturing (AM), specifically with polylactic acid (PLA). FSW is a solid-state welding process characterized by its low heat input and minimal distortion, which makes it ideal for the assembly of complex or large components made by additive manufacturing. To evaluate its effectiveness, a portable FSW device was developed for the purpose of joining PLA specimens made by AM using different filler densities (15% and 100%). Two tool geometries (a cylindrical and truncated cone) were utilized by varying the parameters of rotational speed, tilt angle, and feed rate. The results revealed two different process stages, transient and steady-state, and showed differences in weld quality depending on the material density, tool type, and material addition. The study confirms the viability of FSW for joining PLA parts made by AM and suggests potential applications in industries that require robust and precise joints in plastic parts, thereby helping hybrid manufacturing to progress. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

This research evaluates the performance of six metaheuristic algorithms in the active and reactive power management of wind turbines (WTs) integrated into an AC microgrid (MG). The population-based genetic algorithm (PGA) is proposed as the primary optimization strategy and is rigorously compared against five benchmark techniques: Monte Carlo (MC), particle swarm optimization (PSO), the JAYA algorithm, the generalized normal distribution optimizer (GNDO), and the multiverse optimizer (MVO). This study aims to minimize, through independent optimization scenarios, the operating costs, power losses, or CO₂ emissions of the microgrid during both grid-connected and islanded modes. To achieve this, a coordinated control strategy for distributed generators is proposed, offering flexible adaptation to economic, technical, or environmental priorities while accounting for the variability of power generation and demand. The proposed optimization model includes active and reactive power constraints for both conventional generators and WTs, along with technical and regulatory limits imposed on the MG, such as current thresholds and nodal voltage boundaries. To validate the proposed strategy, two scenarios are considered: one involving 33 nodes and another one featuring 69. These configurations allow evaluation of the aforementioned optimization strategies under different energy conditions while incorporating the power generation and demand variability corresponding to a specific region of Colombia. The analysis covers two-time horizons (a representative day of operation and a full week) in order to capture both short-term and weekly fluctuations. The variability is modeled via an artificial neural network to forecast renewable generation and demand. Each optimization method undergoes a statistical evaluation based on multiple independent executions, allowing for a comprehensive assessment of its effectiveness in terms of solution quality, average performance, repeatability, and computation time. The proposed methodology exhibits the best performance for the three objectives, with excellent repeatability and computational efficiency across varying microgrid sizes and energy behavior scenarios. Full article

Background/Objectives: Preclinical models of liver fibrosis only partially mimic human disease processes. Particularly, traditional transforming growth factor beta 1 (TGFβ1)-induced hepatic stellate cell (HSC) models lack relevant processes, including hypoxia-induced pathways. Here, the ability of a hypoxia-mimicking compound (IOX2) to more accurately reflect the human fibrotic phenotype on a functional level was investigated. Methods: Human primary HSCs were stimulated (TGFβ1 +/− IOX2), and the cell viability and fibrotic phenotype were determined. The latter was assessed as protein levels of fibrosis markers—collagen, TIMP-1, and Fibronectin. Next-generation sequencing (NGS), differential expression analyses (DESeq2), and Ingenuity Pathway Analysis (IPA) were performed for mechanistic evaluation and biological annotation. Results: Stimulation with TGFβ1 + IOX2 significantly increased fibrotic marker levels. Also, fibrosis-related pathways were activated, and hypoxia-related genes and collagen modifications, such as crosslinking, increased dose-dependently. Comparative analysis with human fibrotic DEGs showed improved disease representation in the HSC model in the presence of IOX2. Conclusions: In conclusion, the HSC model better recapitulated liver fibrosis by IOX2 administration. Therefore, hypoxia-mimicking compounds hold promise for enhancing the translational value of in vitro fibrosis models, providing valuable insights in liver fibrosis pathogenesis and potential therapeutic strategies. Full article

Depending on the type of fuels used by ships in maritime port operations, emissions may contribute more or less to the concentration of greenhouse gases in the atmosphere. The maneuvering of ships at maritime ports uses mainly auxiliary engines, resulting in a significant contribution to emissions. It is understandable that the energy transition in this sector brings benefits and is essential to sustainability, considering its economic and strategic importance. Among the measures established to ensure this transition is the onshore power supply and increased electrification in transportation operations. Maritime ports are not yet prepared for these adjustments, as their heterogeneity and contexts require further research, such as studying the impact of depth on energy consumption, terminal type, and others. The purpose of this paper is to quantify the reduction in greenhouse gas emissions achievable through the implementation of an onshore power supply at the Port of Sines, Portugal. Furthermore, it aims to identify the key factors influencing these adoptions to provide practical recommendations that can guide in advancing energy transition, reducing reliance on fuels, and fostering a sustainable future for the port industry. Full article

To tackle work-related stress in the evolving landscape of Industry 5.0, organizations need to prioritize employee well-being through a comprehensive strategy. While electrocardiograms (ECGs) and electrodermal activity (EDA) are widely adopted physiological measures for monitoring work-related stress, electrooculography (EOG) remains underexplored in this context. Although less extensively studied, EOG shows significant promise for comparable applications. Furthermore, the realm of human factors and ergonomics lacks sufficient research on the integration of wearable sensors, particularly in the evaluation of human work. This article aims to bridge these gaps by examining the potential of EOG signals, captured through smart eyewear, as indicators of stress. The study involved twelve subjects in a controlled environment, engaging in four stress-inducing tasks interspersed with two-minute relaxation intervals. Emotional responses were categorized both into two classes (relaxed and stressed) and three classes (relaxed, slightly stressed, and stressed). Employing supervised machine learning (ML) algorithms—Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbors (KNN)—the analysis revealed accuracy rates exceeding 80%, with RF leading at 85.8% and 82.4% for two classes and three classes, respectively. The proposed wearable system shows promise in monitoring workers’ well-being, especially during visual activities. Full article

The transportation of construction waste involves various complexities, including logistics, monitoring, and resource management. Nevertheless, conventional transportation methods struggle to meet the combined requirements of environmental sustainability and efficiency in modern urban development due to problems such as high idle rates and insufficient management. The swift advancement of Internet of Things (IoT) technology offers an innovative solution for the intelligent and effective management of construction waste transportation in response to these issues. This study explores how IoT technology can enhance construction waste transportation management by developing an evaluation framework using the Delphi method, analytic hierarchy process (AHP), and fuzzy comprehensive evaluation (FCE). This research focuses on the application of IoT to optimize the transportation and logistics process through real-time monitoring and data analysis. The capability of IoT technology to analyze real-time data facilitates the modification of routes to minimize empty mileage and transportation time, thus improving transport efficiency. Ultimately, the potential and challenges of IoT in construction waste transportation management have been discussed. Full article

E. coli O157:H7 contamination in food and the environment poses a serious threat to human health. Rapid and sensitive identification of foodborne pathogens remains challenging. Here, we prepared tungsten disulfide (WS₂)–Au nanocomposites coupled with the Raman signal molecule 5,5′-dithio-bis-(2-nitrobenzoic acid) (DTNB) and antibodies to replace the conventional colloidal gold nanoparticles and applied SERS-active nanotags in the SERS-ICA method for highly sensitive detection of E. coli O157:H7. The large surface area and numerous effective SERS hotspots of WS₂-Au nanotags provide superior SERS signals. Under optimized conditions, this ICA achieves the quantitative detection of E. coli O157:H7 in a broad linear range of 8 × 10²–8 × 10⁷ CFU/mL and at a low detection limit of 175 CFU/mL. In addition, the test strip indicates high specificity for E. coli O157:H7 identification, favorable reproducibility, and shows good accuracy in the detection of actual food samples, such as milk and pork. The proposed assay can be used for rapid qualitative and quantitative detection of E. coli O157:H7 and has great potential for field application. Full article

The cognitive ability of the elderly significantly influences evacuation performance in urgent situations. Despite its importance, many fire evacuation studies overlook the impact of cognitive ability on elderly evacuation performance. To address this gap, this study employs multicriteria decision-making to identify nudging factors that enhance the cognitive abilities of the elderly during fire evacuations in long-term care facilities. Based on a literature review, key nudging factors include guidance lights, guide lines, handrails, and guidance equipment, with sub-criteria such as location, color, size, and intervals. Experts from academic and practical fields analyzed the nudging factors, followed by a hybrid analytic hierarchy process (AHP–TOPSIS) analysis. The findings emphasize the necessity of providing auditory information through guidance equipment (e.g., voice evacuation system) in high-level scenarios (practice experts AHP: 0.31) and visual information through the continuous installation of guide lines in strategic locations (academic experts AHP: 0.35) to facilitate efficient evacuation. As a result, this study confirms both the differing and concordant opinions among expert groups while recognizing the absolute necessity of elderly evacuation research and considering the unique challenges that prevent actual evacuation experiments with elderly individuals. By synthesizing these perspectives, the study derives the weights and ranks of nudging factors based on urgent-level circumstances, thereby conducting a quantitative assessment of factors that enhance cognitive ability during elderly evacuation. The findings of this study can serve as a basis for future evacuation policy formulation for elderly-related facilities and, as a derivative effect, contribute to ensuring the life safety of elderly individuals within the local community. Full article

To improve safety through design, the state can take the initiative in building certification. In this study, we systematically review and review the Barrier-Free (BF) certification evaluation for barrier-free design by implementing information modeling. We developed and applied a BIM-based evaluation template to the evaluation items derived from IPA analysis. As a result of the application, we were able to construct an efficient evaluation sheet by utilizing BIM tools. The results of the study showed that there is a need to improve the BF certification criteria and develop evaluation-related items utilizing BIM functions. This study can be utilized in the future for the development of BIM-based certification criteria for the disabled and the development of evaluation sheets. Full article

Forestry and wood-processing by-products, such as pine bark, offer promising opportunities for sustainable resource utilization within a circular economy. This study aimed to assess the environmental impact of an aqueous extraction process for polyphenolic compounds from various pine residues, including bark, cones, and pruning, using life cycle assessment (LCA). The analysis revealed that ground and sieved pine bark powder had the lowest environmental impact, attributed to its simpler extraction process without chemical modifications and reduced energy consumption compared to other pine-derived products. Electricity and natural gas were identified as the primary drivers of environmental impacts across all categories. Sensitivity analyses demonstrated that increasing the tannin concentration in pine-derived products and integrating renewable energy sources could further improve environmental performance. These findings highlight the potential of utilizing underutilized pine residues as sustainable feedstock for producing valuable polyphenolic extracts with a relatively low environmental footprint. The insights gained from this LCA study provide a comprehensive foundation for advancing sustainable extraction technologies. They emphasize the critical role of energy efficiency, tannin concentration, and renewable energy integration in minimizing environmental impacts. Furthermore, these findings offer actionable guidance for optimizing resource recovery from forestry by-products, enhancing their viability as eco-friendly alternatives to conventional tannin sources. Full article

Parameter identification in dynamical systems is a well-known problem with many applications in control design, system monitoring, and fault detection. As these systems are increasingly integrated into complex and demanding environments, challenges such as rapid response, uncertainty handling, and disturbance rejection must be addressed. This paper presents a real-time estimation technique for parameters and load torque in brushless DC (BLDC) motors. These electrical machines are extensively used in engineering applications and often operate under hard conditions. The proposed method is based on algebraic identification, known for its robust performance in both linear and nonlinear systems. In utilizing the mathematical model of a BLDC motor, a set of equations is derived to enable parameter estimation, assuming the availability of input and output measurements in open loop. Moreover, unknown load torque is estimated by approximating the disturbance over a short time window using Taylor series expansion polynomials. The theoretical contribution is analytically validated and is also verified through numerical evaluations revealing the effectiveness of the proposed technique for real-time parameter and disturbance estimation in BLDC motors over other important techniques. Additionally, to address potential peaks in the estimation process, a modification involving an exponent is introduced to mitigate these issues. Full article

This study explores the development and characterization of biodegradable leather using alginate derivatives as sustainable tanning agents, aiming to reduce the environmental impact associated with traditional leather tanning processes. Alginate, a natural polysaccharide derived from brown algae, was modified through ultrasound treatment to reduce viscosity and improve its application in leather tanning. This study investigated the use of sodium alginates as bio-based retanning agents, comparing their performance against that of conventional chromium-tanned and vegetable-tanned leathers, as well as synthetic alternatives such as leatherette, Piñatex^®, and Desserto^®. The physical, chemical, and thermal properties of the resulting leathers were assessed. The results demonstrated that alginate-based tanning agents could produce leather with comparable or superior properties to conventional and synthetic leathers, meeting the quality standards required for high-end footwear and leather goods. This research highlights the potential of alginate derivatives to serve as eco-friendly alternatives in the leather industry. The findings underscore the feasibility of integrating bio-based materials into industrial applications, promoting environmental conservation and resource efficiency. Full article

The large-scale introduction of renewable energy, replacing fossil fuels, is presented as an essential part of the energy transition; this substitution is being observed in electrical systems, but its introduction will also be necessary in other sectors, such as transportation, either by incorporating renewable energy sources in the sector’s facilities, including automotive service centers, or through the electrification of transportation technology. The introduction of electromobility in a country is associated with a group of technologies that are required to make this introduction viable, such as electric vehicles themselves, charging stations and workshops for the repair and maintenance of this technology. Taking the above as a point of reference, this article addresses the basic elements of a proposal for an energy transition in the transport sector, identifying the limitations and barriers existing in the country for the introduction of electric mobility and, finally, arriving at a roadmap proposal to achieve the required synergy between energy transition and electromobility. Full article