Search Results (849)

Turbine systems equipped with doubly fed induction generation (DFIG) are becoming increasingly vital in wind power generation, with the reliability of the devices serving as a pillar in the industrial sector. Thermal stress and lifetime assessment are fundamental indicators in this regard. This paper primarily addresses the thermal stress and lifespan of power semiconductor devices utilized in a DFIG grid-side converter (GSC) and rotor-side converter (RSC). PLECS (Piecewise Linear Electrical Circuit Simulation) is employed to validate the electrical and thermal stress of the power devices. Additionally, Ansys Icepak, a finite element analysis (FEA) software, is utilized to confirm temperature fluctuations under various operations. The power consumption and junction temperature of the power devices in the GSC and RSC of a 2 MW DFIG are compared. It is evident that the most stressed power semiconductor is the IGBT for the GSC with a temperature swing of 3.4 °C, while the diode in the RSC is the most stressed with a temperature swing of 10.1 °C. This paper also presents a lifetime model to estimate the lifespan of the power device based on the annual wind profile. By considering the annual mission profile, we observe that the lifetime of the back-to-back power converter is limited by the diode of the RSC, whose B₁₀ lifetime is calculated at 15 years. Full article

Cloud computing is considered suitable for organizations thanks to its flexibility and the provision of digital services via the Internet. The cloud provides nearly limitless computing resources on demand without any upfront costs or long-term contracts, enabling organizations to meet their computing needs more economically. Furthermore, cloud computing provides higher security, scalability, and reliability levels than traditional computing solutions. The efficiency of the platform affects factors such as Quality of Service (QoS), congestion, lifetime, energy consumption, dependability, and scalability. Load balancing refers to managing traffic flow to spread it across several channels. Asymmetric network traffic results in increased traffic processing, more congestion on specific routes, and fewer packets delivered. The paper focuses on analyzing the use of the meta-optimization algorithm based on the principles of natural selection to solve the imbalance of loads in cloud systems. To sum up, it offers a detailed literature review on the essential meta-heuristic algorithms for load balancing in cloud computing. The study also assesses and analyses meta-heuristic algorithm performance in load balancing, as revealed by past studies, experiments, and case studies. Key performance indicators encompass response time, throughput, resource utilization, and scalability, and they are used to assess how these algorithms impact load balance efficiency. Full article

Despite extensive regulations, the systemic under-reporting of construction and demolition waste generation rates pervades the South African waste sector due to the extensive and active informal waste management practices that are typical of developing countries. This study merges the rapid development of high-technology 3D-printed concrete (3DPC) with the increasing pressure that the built environment is placing on both natural resource consumption and landfill space due to construction and demolition waste (CDW) by establishing an inventory of CDW that is suitable for use in 3DPC in South Africa. This is an essential step in ensuring the technical, economic, and logistical viability of using CDW as aggregate or supplementary cementitious materials in 3DPC. Of the methods considered, the lifetime material analysis and per capita multiplier methods are the most appropriate for the context and available seed data; this results in CDW estimates of 24.3 Mt and 12.2 Mt per annum in South Africa, respectively. This range is due to the different points of estimation for the two methods considered, and the per capita multiplier method provides an inevitable underestimation. In order to contextualise the estimated availability of CDW material for use in concrete in general, the demand for coarse and fine aggregate and supplementary cementitious material in South Africa is quantified as 77.9 Mt. This overall annual demand far exceeds the estimated CDW material (12.2–24.3 Mt) available as an alternative material source for concrete. Full article

Clustering strategy in wireless sensor networks (WSNs) affects the lifetime, adaptability, and energy productivity of the wireless network system. The low-energy adaptive clustering hierarchy (LEACH) protocol is a convention used to improve the lifetime of WSNs. In this paper, a novel energy-efficient clustering algorithm is proposed, with the aim of improving the energy efficiency of WSNs by reducing and balancing the energy consumptions. The clustering-based convention adjusts the energy utilization by allowing an equal opportunity for each node to turn them into a cluster head (CH). Two-level clustering (TLC) is introduced by adopting LEACH convention where CH selection process undergoes first and second level of clustering to overcome boundary problem in LEACH protocol. The TLC method structures nodes within the scope of the appointed CHs, in order to extend the lifetime of the system. The simulation results show that, in comparison with state-of-the-art methodologies, our proposed method significantly enhanced the system lifetime. Full article

The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending the network’s lifespan. In this paper, a hybrid of a fuzzy logic system and a quantum annealing algorithm-based clustering and routing protocol (FQA) is proposed to improve the stability of the network and minimize energy consumption. The protocol uses a fuzzy inference system (FIS) to select appropriate cluster heads (CHs). In the routing phase, we used the quantum annealing algorithm to select the optimal route from the CHs and the base station (BS). Furthermore, we defined an energy threshold to filter candidate CHs in order to save computation time. Unlike with periodic clustering, we adopted an on-demand re-clustering mechanism to perform global maintenance of the network, thereby effectively reducing the computation and overhead. The FQA was compared with FRNSEER, BOA-ACO, OAFS-IMFO, and FC-RBAT in different scenarios from the perspective of energy consumption, alive nodes, network lifetime, and throughput. According to the simulation results, the FQA outperformed all the other methods in all scenarios. Full article

In wireless sensor networks (WSNs), sensor nodes are randomly distributed to transmit sensed data packets to the base station periodically. These sensor nodes, because of constrained battery power and storage space, cannot utilize conventional security measures. The widely held challenging issues for the network layer of WSNs are the packet-dropping attacks, mainly sinkhole and wormhole attacks, which focus on the routing pattern of the protocol. This thesis presents an improved version of the second level of the guard to the system, intrusion detection systems (IDSs), to limit the hostile impact of these attacks in a Low Energy Adaptive Clustering Hierarchy (LEACH) environment. The proposed system named multipath intrusion detection system (MIDS) integrates an IDs with ad hoc on-demand Multipath Distance Vector (AOMDV) protocol. The IDS agent uses the number of packets transmitted and received to calculate intrusion ratio (IR), which helps to mitigate sinkhole attacks and from AOMDV protocol round trip time (RTT) is computed by taking the difference between route request and route reply time to mitigate wormhole attack. MATLAB simulation results show that this cooperative model is an effective technique due to the higher packet delivery ratio (PDR), throughput, and detection accuracy. The proposed MIDS algorithm is proven to be more efficient when compared with an existing LEACH-based IDS system and MS-LEACH in terms of overall energy consumption, lifetime, and throughput of the network. Full article

Our previous work demonstrated the presence of lead (Pb) and cadmium (Cd) contamination in cow milk (CM) and soy beverages (SBs) in Portugal. These metals share carcinogenic mechanisms, suggesting at least additive effects. Our goals were to assess carcinogenic risks from Pb and Cd intake detected in various CM and SB brands on the Portuguese market and to determine the relative contributions of Pb and Cd. Furthermore, we modeled different consumption scenarios for various age/body weight groups to estimate cumulative Excess Lifetime Carcinogenic Risk (ELCR). ELCR was computed by multiplying chronic daily intake by a cancer slope factor for each metal, with an ELCR > 1 × 10⁻⁴ indicating carcinogenic risk. Five CM and three SB brands posed cancer risks in children, with the highest values at 1.75 × 10⁻⁴ and 9.12 × 10⁻⁵, respectively; Pb had mean relative contributions of 87.8 ± 3.1% in CM and 54.9 ± 12.1% in SB. Carcinogenic risks were observed for children, adolescents, and adults in several CM or SB consumption scenarios, albeit at levels above typical Portuguese intakes. Strict monitoring of metal levels, such as Pb and Cd, is advised because CM is a component of many foods, including baby food. Full article

Energy management in the residential sector contributes to energy system dispatching and security with the optimal use of renewable energy systems (RES) and energy storage systems (ESSs) and by utilizing the main grid based on its state. This work focuses on optimal energy flow, ESS parameters, and energy consumption scheduling based on demand response (DR) programs. The primary goals of the work consist of minimizing electricity costs while simultaneously extending the lifetime of ESSs in conjunction with extracting maximum benefits throughout their operational lifespan and reducing CO₂ emissions. Effective ESS and photovoltaic (PV) energy usage prices are modeled and an efficient energy flow management algorithm is presented, which considers the life cycle of the ESSs including batteries, electrical vehicles (EVs) and the efficient use of the PV system while reducing the cost of energy consumption. In addition, an optimization technique is employed to obtain the optimal ESS parameters including the size and depth of discharge (DOD), considering the installation cost, levelized cost of storage (LCOS), winter and summer conditions, energy consumption profile, and energy prices. Finally, an optimization technique is applied to obtain the optimal energy consumption scheduling. The proposed system provides all of the possibilities of exchanging energy between EV, battery, PV system, grid, and home. The optimization problem is solved using the particle swarm optimization algorithm (PSO) in MATLAB with an interval time of one minute. The results show the effectiveness of the proposed system, presenting an actual cost reduction of 28.9% and 17.7% in summer and winter, respectively, compared to a base scenario. Similarly, the energy losses were reduced by 26.7% in winter and 22.3% in summer, and the EV battery lifetime was extended from 9.2 to 19.1 years in the winter scenario and from 10.4 to 17.7 years in the summer scenario. The integrated system provided a financial contribution during the operational lifetime of EUR 11,600 and 7900 in winter and summer scenarios, respectively. The CO₂ was reduced by 59.7% and 46.2% in summer and winter scenarios, respectively. Full article

With the pervasive consumption (currently >65% of total market shares and steadily increasing) of petroleum-derived synthetic textiles, the escalating concern of microfiber fragment (MF) pollution has emerged as a formidable menace to our ecological equilibrium. Over the lifetime (pre- and post-consumption) of these textiles, they shed tiny fibers recognized as MFs. These MFs are carriers of persistent organic pollutants and have been linked to cytotoxicity, oxidative stress, and genotoxicity, even at minimal exposures via air and water sources. Grounded in the state-of-the-art literature, this review discusses the primary and secondary sources of MF release, their fate, transport, environmental impacts, and novel technologies for MF pollutant remediation. Our results infer that MF pollution is a multifactorial issue with serious environmental and public health implications, as studies reported their presence in human blood, feces, and urine samples. We recommend a multifaceted approach to increase sanitation coverage, ensuring adequate wastewater treatment prior to environmental discharge for MF pollution mitigation. Additionally, transformation is warranted for consumers’ use, care, and purchase behavior of textile products. Government regulation of fast fashion (a major user of synthetic textiles), exemplified by recent French legislation, is essential to preventing microfiber pollution. We urge similar policy-making efforts globally to safeguard public health. Full article

A new decoding method for low-density parity-check (LDPC) codes is presented to lower the energy consumption of LDPC decoders for NAND flash-based storage systems. Since the channel condition of NAND flash memory is reliable for most of its lifetime, it is inefficient to apply the maximum-effort decoding with the full parity-check matrix (H-matrix) from the beginning of the lifespan. As the energy consumption and the decoding latency are proportional to the size of the H-matrix used in decoding, the proposed algorithm starts the decoding with a partial H-matrix selected by considering the channel condition. In addition, the proposed partial decoding provides various error-correcting capabilities by adjusting the partial H-matrix. Based on the proposed partial decoding algorithm, a prototype decoder is implemented in a 65 nm CMOS process to decode a 4 KB LDPC code. The proposed decoder reduces energy consumption by 93% compared to the conventional LDPC decoding architecture at maximum. Full article

Electric vehicles (EVs), which are environmentally friendly, have been used to minimize the global warming caused by fossil fuels used in vehicles and increasing fuel prices due to the decrease in fossil resources. Considering that the energy used in EVs is obtained from fossil resources, it is also important to store and use energy efficiently in EVs. In this context, recovery from a regenerative braking system plays an important role in EV energy efficiency. This paper presents a fuzzy logic-based hybrid storage technique consisting of a supercapacitor (SC) and battery for efficient and safe storage of a regenerative braking system. First, the constraints of the battery to be used in the EV for fuzzy logic control are identified. Then, the fuzzy logic system is created and tested in the ADVISOR and Siemens Simcenter Flomaster programs in the New European Driving Cycle (NEDC) driving cycle. A SC was selected for primary storage to prevent the battery from being continuously charged from regenerative braking, thus reducing its lifetime. In cases where the vehicle consumes more energy than the average energy consumption, energy consumption from the battery is reduced by using the energy stored in the SC, and the SC energy is discharged, making preparations for the energy that will come from the next regenerative braking. Thus, the high current values transferred to the battery during regenerative braking are effectively limited by the SC. In this study, the current values on the battery in the EV with a hybrid storage system decreased by 29.1% in the ADVISOR program and 28.7% in the Simcenter Flomaster program. In addition, the battery generated 46.84% less heat in the hybrid storage system. Thus, the heating and capacity losses caused by this current on the battery were minimized. The presented method provides more efficient energy management for EVs and plays an important role in maintaining battery health. Full article

Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and transmission of vital physiological data. However, the energy constraints of the battery-powered sensor nodes in WBANs pose a significant challenge to ensuring long-term operational efficiency. Two-hop routing protocols have been suggested to extend the stability period and maximize the network’s lifetime. These protocols select appropriate parent nodes or forwarders with a maximum of two hops to relay data from sensor nodes to the sink. While numerous energy-efficient routing solutions have been proposed for WBANs, reliability has often been overlooked. Our paper introduces an energy-efficient routing protocol called a Hybrid Clustering Approach for Extending WBAN Lifetime (HCEL) to address these limitations. HCEL leverages a utility function to select parent nodes based on residual energy (RE), proximity to the sink node, and the received signal strength indicator (RSSI). The parent node selection process also incorporates an energy threshold value and a constrained number of serving nodes. The main goal is to extend the overall lifetime of all nodes within the network. Through extensive simulations, the study shows that HCEL outperforms both Stable Increased Throughput Multihop Protocol for Link Efficiency (SIMPLE) and Energy-Efficient Reliable Routing Scheme (ERRS) protocols in several key performance metrics. The specific findings of our article highlight the superior performance of HCEL in terms of increased network stability, extended network lifetime, reduced energy consumption, improved data throughput, minimized delays, and improved link reliability. Full article

A multi-stack fuel cell system (MFCS) is a promising solution for high-power PEM fuel cell applications. This paper proposes an optimized stack allocation approach for power allocation, considering economy and dynamics to establish integrated subsystems with added functional components. The results show that an MFCS with target powers of 20 kW, 70 kW, and 120 kW satisfies lifetime and efficiency factors. The common rail buffer at the air supply subsystem inlet stabilizes pressure, buffers, and diverts. By adjusting the volume of the common rail buffer, it is possible to reduce the maximum instantaneous power and consumption of the air compressor. The integrated hydrogen supply subsystem improves hydrogen utilization and reduces parasitic power consumption. However, the integrated thermal subsystem does not have the advantages of integrated gas supply subsystems, and its thermal management performance is worse than that of a distributed thermal subsystem. This MFCS provides a solution for high-power non-average distribution PEM fuel cell systems. Full article

This paper illustrates a novel and cost-effective wireless monitoring system specifically developed for operational modal analysis of bridges. The system employs battery-powered wireless sensors based on MEMS accelerometers that dynamically balance power consumption with high processing features and a low-power, low-cost Wi-Fi module that ensures operation for at least five years. The paper focuses on the system’s characteristics, stressing the challenges of wireless communication, such as data preprocessing, synchronization, system lifetime, and simple configurability, achieved through the integration of a user-friendly, web-based graphical user interface. The system’s performance is validated by a lateral excitation test of a model structure, employing dynamic identification techniques, further verified through FEM modeling. Later, a system composed of 30 sensors was installed on a concrete arch bridge for continuous OMA to assess its behavior. Furthermore, emphasizing its versatility and effectiveness, displacement is estimated by employing conventional and an alternative strategy based on the Kalman filter. Full article

Infant cereals, one of the first solid foods introduced to infants, have been reported to pose risks to human health because they contain toxic elements and an excess of essential elements. The objective of this study was to assess the cancer and non-cancer risk of exposure to essential and toxic elements in infant cereal in Brazil. In our analyses, we included data from 18 samples of infant cereals made from different raw materials and estimated the incremental lifetime cancer risks and non-cancer hazard quotients (HQs) for their consumption. Rice cereal is particularly concerning because it is immensely popular and usually contains high levels of inorganic arsenic. In addition to arsenic, we assessed aluminum, boron, barium, cadmium, chromium, copper, lead, manganese, nickel, selenium, silver, strontium, and zinc. The cancer risk was highest for rice cereal, which was also found to have an HQ > 1 for most of the tested elements. Inorganic As was the element associated with the highest cancer risk in infant cereal. All of the infant cereals included in this research contained at least one element with an HQ > 1. The essential and non-essential elements that presented HQ > 1 more frequently were zinc and cadmium, respectively. The cancer and non-cancer risks could potentially be decreased by reducing the amount of toxic and essential elements (when in excess), and public policies could have a positive influence on risk management in this complex scenario. Full article