Search Results (108)

Water is essential to human civilization and development, yet its quality is increasingly threatened by climate change, pollution, and resource mismanagement. This work introduces an empirical, non-invasive framework for assessing water potability using electrical impedance spectroscopy (EIS) combined with a novel equivalent circuit model. A customized sensor holder was designed to reduce impedance magnitude and enhance phase sensitivity, improving detection accuracy. Various water samples, including seawater, groundwater, and commercially bottled water, were analyzed. The proposed method achieved a 100% classification accuracy in distinguishing among water types, as validated by extracted circuit parameters and verified by inductively coupled plasma (ICP) measurements. Sensitivity analysis demonstrated the ability to detect compositional changes as small as 10%, highlighting a strong potential for fine discrimination of ionic contents. The extracted parameters, such as resistance, capacitance, and inductance, showed clear correlations with ionic composition, enabling reliable potability classification in accordance with WHO guidelines. The approach is rapid, label-free, and suitable for field applications, offering a promising tool for real-time water quality monitoring and supporting sustainable water resource management. Full article

The development of technology has driven a rising need for high-accuracy and high-efficiency manufacturing of low-volume products. Incremental forming technology, characterized by die-free flexibility and low production costs, can effectively replace stamping processes for manufacturing customized small-batch products. However, high-performance aluminum alloys generally exhibit poor room-temperature plasticity but excellent high-temperature plasticity, necessitating the integration of thermal-assisted methods for manufacturing such products. However, the temperature of the forming region will excessively rise without temperature control, which will affect the forming performance of the material in hot incremental sheet forming of AA2024-T4 aluminum alloy. This study focuses on AA2024-T4 aluminum alloy and proposes a uniform temperature control method for the electric hot tube-assisted incremental sheet forming process, incorporating an adaptive fuzzy PID algorithm. The temperature difference of the forming region is lower than 6% under the various temperatures. On this basis, the forming limit angle and the microstructure state of the material are analyzed, and the grain feature of the material exhibits significantly refined grains and the uniform fine grain distribution under 180 °C with the temperature control of the adaptive fuzzy PID algorithm. Full article

Sales forecasting in make-to-order (MTO) production is particularly challenging for small- and medium-sized enterprises (SMEs) due to high product customization, volatile demand, and limited historical data. This study evaluates the practical feasibility and accuracy of statistical and machine learning (ML) forecasting methods in MTO settings across three manufacturing sectors: electrical equipment, steel, and office supplies. A cross-industry benchmark assesses models such as ARIMA, Holt–Winters, Random Forest, LSTM, and Facebook Prophet. The evaluation considers error metrics (MAE, RMSE, and sMAPE) as well as implementation aspects like computational demand and interpretability. Special attention is given to data sensitivity and technical limitations typical in SMEs. The findings show that ML models perform well under high volatility and when enriched with external indicators, but they require significant expertise and resources. In contrast, simpler statistical methods offer robust performance in more stable or seasonal demand contexts and are better suited in certain cases. The study emphasizes the importance of transparency, usability, and trust in forecasting tools and offers actionable recommendations for selecting a suitable forecasting configuration based on context. By aligning technical capabilities with operational needs, this research supports more effective decision-making in data-constrained MTO environments. Full article

Road freight transport is the key driver of the European economy and society; thus, distortion of its operation would have negative influence on growth and well-being. For that reason, implementation of European policies, including transport decarbonization, should be comprehensively evaluated from an environmental, social and economic perspective. In that case, introduction of electric trucks will create a mutual impact on the market and on haulage companies. The main research problem is to assess the future impact of decarbonization on the international road freight transport market structure on the supply side and the competitiveness of companies operating there. Today, a number of small and medium companies, to a great extent from Eastern Europe, render transportation services, creating a competitive structure with high flexibility, accessibility and low prices. Shifting towards electric trucks, with significantly higher upfront costs, will redefine the market structure, eliminating the small carriers and activating horizontal integration. The key objective of this research is to identify the main factors and challenges related to electric truck implementation and define crucial areas of its impact on future market structure. The research shows that the improvement of environmental performance requires low- or zero-emission trucks, where the battery technology is a leading solution. Thus, fleet renewal needs additional financial support from the public side. Different measures are available in European countries, so the level of support is not equal from a competitiveness perspective. Battery truck selling, as well as sustainable strategies, refer mostly to huge transport companies. On the other hand, the case of Polish truckers shows that the economic viability of SMEs is poor; thus, the introduction of BET would be beyond its reach. The research findings could be treated as recommendations for market regulators (EC), where the tempo of implementation, as well as availability of public support programs, should be rethinking. As a result, the costs of the transition will be covered by citizens, as customers, in the prices of products and transport service, or as taxpayers, in public support programs, mainly consumed by large market stakeholders. Full article

A pattern-reconfigurable, vertically polarized (VP), electrically small (ES), Huygens source antenna (HSA) is demonstrated. A custom-designed reconfigurable inverted-F structure is embedded in a hollowed-out cylindrical dielectric resonator (DR). It radiates VP electric dipole fields that excite the DR’s HEM_11δ mode, which in turn acts as an orthogonal magnetic dipole radiator. The HSA’s unidirectional properties are thus formed. It becomes low-profile and electrically small through a significant lowering of its operational frequency band by loading the DR’s top surface with a metallic disk. The entire 360° azimuth range is covered by each of the HSA’s four 90° reconfigurable states, emitting a unidirectional wide beam. A prototype was fabricated and tested. The measured results, which are in good agreement with their simulated values, demonstrate that the developed wideband Huygens source antenna, with its 0.085 λ_L low profile and its 0.20 λ_L × 0.20 λ_L compact transverse dimensions, hence, electrically small size with ka = 0.89, exhibits a wide 14.1% fractional impedance bandwidth and a 6.1 dBi peak realized gain in all four of its pattern-reconfigurable states. Full article

This paper provides an overview of the three-year effort to design and implement a prototypical sense-and-avoid (SAA) system based on a multisensory architecture leveraging data fusion between optical and radar sensors. The work was carried out within the context of the Italian research project named TERSA (electrical and radar technologies for remotely piloted aircraft systems) undertaken by the University of Pisa in collaboration with its industrial partners, aimed at the design and development of a series of innovative technologies for remotely piloted aircraft systems of small scale (MTOW < 25 Kgf). The system leverages advanced computer vision algorithms and an extended Kalman filter to enhance obstacle detection and tracking capabilities. The “Sense” module processes environmental data through a radar and an electro-optical sensor, while the “Avoid” module utilizes efficient geometric algorithms for collision prediction and evasive maneuver computation. A novel hardware-in-the-loop (HIL) simulation environment was developed and used for validation, enabling the evaluation of closed-loop real-time interaction between the “Sense” and “Avoid” subsystems. Extensive numerical simulations and a flight test campaign demonstrate the system’s effectiveness in real-time detection and the avoidance of non-cooperative obstacles, ensuring compliance with UAV aero mechanical and safety constraints in terms of minimum separation requirements. The novelty of this research lies in (1) the design of an innovative and efficient visual processing pipeline tailored for SWaP-constrained mini-UAVs, (2) the formulation an EKF-based data fusion strategy integrating optical data with a custom-built Doppler radar, and (3) the development of a unique HIL simulation environment with realistic scenery generation for comprehensive system evaluation. The findings underscore the potential for deploying such advanced SAA systems in tactical UAV operations, significantly contributing to the safety of flight in non-segregated airspaces Full article

This paper addresses the Capacitated Location Tree Problem with Interconnections, a new combinatorial optimization problem with applications in network design. In this problem, the required facilities picked from a set of potential facilities must be opened to serve customers using a tree-shaped network. Costs and capacities are associated with the opening of facilities and the establishment of network links. Customers have a given demand that must be satisfied while respecting the facilities and link capacities. The problem aims to minimize the total cost of designing a distribution network while considering facility opening costs, demand satisfaction, capacity constraints, and the creation of interconnections to enhance network resilience. A valid mixed-integer programming was proposed and an exact solution method based on the formulation was used to solve small- and medium-sized instances. To solve larger instances two metaheuristic approaches were used. A specific decoder procedure for the metaheuristic solution approaches was also proposed and used to help find solutions, especially for large instances. Computational experiments and results using the three solution approaches are also presented. Finally, a case study on the design of electrical transportation systems was presented and solved. Full article

Nanogrids are becoming an essential part of modern home power systems, offering sustainable solutions for residential areas. These medium-to-low voltage, small-scale grids, operating at medium-to-low voltage, enable the integration of distributed energy resources such as wind turbines, solar photovoltaics, and battery energy storage systems. However, ensuring power quality, stability, and effective energy management remains a challenge due to the variability of renewable energy sources and evolving customer demands, including the increasing charging load of electric vehicles. This paper reviews the current research on nanogrid architecture, functionality in low-voltage distribution systems, energy management, and control systems. It also explores power-sharing strategies among nanogrids within a microgrid framework, focusing on their potential for supplying off-grid areas. Additionally, the application of blockchain technology in providing secure and decentralized energy trading transactions is explored. Potential challenges in future developments of nanogrids are also discussed. Full article

To facilitate the participation of small- and medium-sized customer-side resources into the electricity market, with the aim of optimizing the allocation of electricity resources, this paper proposes the participation of small- and medium-sized adjustable resources in the electricity market in the form of generation load aggregators. Considering the coupling role of the electric energy market and the peaking auxiliary service market, a joint model of generation load aggregators that participate in the electric energy–peak shaving market is constructed. Comparing the model solution with those of the control group, the peak-to-valley difference of 10.5 MW is much lower than that of the control group, which is 16.54 MW. Compared with the control group, the profit was increased by USD 2.6 thousand, or 6.06%. It can be seen that the model proposed in this paper can reduce the peak and valley pressure as well as the control pressure of the power system from the load side. By participating in the peak shaving market, the transferable loads within the generation load aggregators can give full play to its adjustable characteristics, thereby reducing the cost of electricity consumption and increasing its profit, and providing a certain theoretical basis for the electricity market management to design the rules for adjustable users to enter the electricity market. Full article

In recent decades, the intensive development of renewable energy technology has been observed as a great alternative to conventional energy sources. Solutions aimed at individual customers, which can be used directly in places where electricity is required, are of particular interest. Small wind turbines pose a special challenge because their design must be adapted to environmental conditions, including low wind speed or variability in its direction. The research study presented in this paper considers the energy efficiency of a small wind turbine with a horizontal axis of rotation. Three key design parameters were analyzed: the shape and inclination of the turbine blades and additional confusor–diffuser shape casings. The tests were carried out for three conceptual variants: a confusor before the turbine, a diffuser after the turbine, and a confusor–diffuser combination. Studies have shown that changing the shape of the blade can increase the analyzed wind turbine power by up to 35%, while changing the blade inclination can cause an increase of up to 16% compared to the initial installation position and a 66% increase in power when comparing the extreme inclination of the blades of the tested turbine. The study has shown that to increase the wind speed, the best solution is to use a confusor–diffuser configuration, which, with increased length, can increase the air velocity by up to 21%. Full article

Optimal Reactive Power Dispatch (ORPD) is a power system optimization tool that modifies system control variables such as bus voltage and transformer tap settings, and it compensates devices’ Volt Ampere Reactive (VAR) output. It is used to decrease real power loss, enhance the voltage profile, and promote stability. Furthermore, several issues have been faced in electricity markets, such as price volatility, transmission line congestion, and an increase in the cost of electricity during peak hours. Programs such as demand response (DR) provide system operators with more control over how small customers participate in lowering peak-hour energy prices and demand. This paper presents an extensive study on ORPD methodologies and DR programs for lowering voltage deviation, limiting cost, and minimizing power losses to create effective and economical operations systems. The main objectives of this work are to minimize costs and losses in the system and reduce voltage variation. The Grasshopper Optimization Algorithm (GOA) and Dragonfly Algorithm (DA) have been implemented successfully to solve this problem. The proposed technique has been evaluated by using the IEEE-30 bus system. The results obtained by the implementation of demand response systems show a considerable reduction in costs and load demands that benefit consumers through DR considerations. The results obtained from the GOA and DA are compared with those generated by other researchers and published in the literature to ascertain the algorithm’s efficiency. Full article

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids is well established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge, which results in high costs. To enable a democratization of the technology by reducing the costs, this study provides a novel modular plug-and-play open-source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink (version 2024b) as well as experimental validation. The results show that transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network, as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems. Full article

Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in situ radiation measurements resulting in site-customized antenna design and positioning, and consequently in a higher reliability of such HF grid communications. Drone-borne measuring systems are already known as a flexible solution, but are mostly restricted to higher frequency ranges where full-wave, wide-band probes are feasible. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity; corrections on these two effects are the key methodological steps. We show that despite a realized gain figure in the order of −20 dBi, such a probe can provide stable results for near-field measurements, even at input power levels as low as 1 mW. Compared to other similar approaches, our configuration provides a wider frequency band of operation, higher stability in terms of pattern diagram, and a lower cost. Full article

Distributed grid-connected photovoltaic (PV) generation explores several methods that produce energy at or near the point of consumption, with the aim of reducing electricity losses among transmission networks. Consequently, home on-grid PV applications have garnered increased interest from both scientific researchers and industry professionals over the last decade. Nevertheless, the growing installation of intermittent nature residential PV systems (R-PV) in low-voltage distribution networks is leading to more cautious considerations of technology limitations and PV design challenges. This conservative perspective arises from the standpoint of grid quality and security, ultimately resulting in the revocation of PV connection authorization. Hence, the design of R-PV systems should consider not only the specifications of the PV panels and load profiles but also the characteristics and requirements of the connected power grid. This project therefore seeks to enhance the design considerations of grid-connected PV systems, in order to help the end-users meet the grid codes set out by the Saudi Electricity Regulatory Authority (SERA). Since the maximum amount of generated power is essential for PV system optimization, the ratio of grid strength to maximum transmitted power was employed to ascertain the suitable capacity of the PV system, while the assessment of PV power output was utilized to specify the system size. Furthermore, a battery energy storage system (BESS) with a small size (~10% of the PV capacity) is employed to enhance the PV power quality for a dependable grid interconnection. The BESS is equipped with a versatile power controller in order to achieve the designed objectives. The obtained results show an essential advancement in terms of power quality and reliability at the customer’s connection point. Moreover, with the design assessment process, the low-voltage ride-through (LVRT) and power factor requirements can be met, in addition to the total harmonic distortion (THD) and frequency transient limitations. The proposed solution assists end-users in efficiently designing their own R-PV systems while ensuring quality and sustainability for authorized grid interconnection. Full article

Semiconductors continue to shrink in die size because of benefits like cost savings, lower power consumption, and improved performance. However, this reduction leads to more defects due to increased inter-cell interference. Among the various defect types, customer-found defects are the most costly. Thus, finding the root cause of customer-found defects has become crucial to the quality of semiconductors. Traditional methods involve analyzing the pathways of many low-yield wafers. Yet, because of the extremely limited number of customer-found defects, obtaining significant results is difficult. After the products are provided to customers, they undergo rigorous testing and selection, leading to a very low defect rate. However, since the timing of defect occurrence varies depending on the environment in which the product is used, the quantity of defective samples is often quite small. Unfortunately, with such a low number of samples, typically 10 or fewer, it becomes impossible to investigate the root cause of wafer-level defects using conventional methods. This paper introduces a novel approach to finding the root cause of these rare defective chips for the first time in the semiconductor industry. Defective wafers are identified using rare customer-found chips and chip-level EDS (Electrical Die Sorting) data, and these newly identified defective wafers are termed vBADs (virtual bad wafers). The performance of root cause analysis is dramatically improved with vBADs. However, the chip-level analysis presented here demands substantial computing power. Therefore, MPP (Massive Parallel Processing) architecture is implemented and optimized to handle large volumes of chip-level data within a large architecture infrastructure that can manage big data. This allows for a chip-level defect analysis system that can recommend the relevant EDS test and identify the root cause in real time even with a single defective chip. The experimental results demonstrate that the proposed root cause search can reveal the hidden cause of a single defective chip by amplifying it with 90 vBADs, and system performance improves by a factor of 61. Full article