Search Results (280)

Double-Side-Cooled (DSC) power modules, widely utilized in various industrial and transportation applications, are favored for their remarkable high cooling efficiency and minimal packaging parasitics. To extend the life cycle, the design and optimization of metal or alloy spacers have garnered significant research attention due to their role in mitigating thermal-expansion-mismatch-induced stresses. Among the optimization approaches, topology optimization (TO) methods have the merit of generating innovative spacer shapes, thereby maximizing the buffering effects. However, without certain design considerations and constraints predetermined, the overall processes can become computationally costly. This paper proposes an efficient strategy for finding the optimized spacer topology for a double-sided 1700 V/400 A DSC SiC MOSFET power module. First, comparative thermal-stress investigations are carried out to predetermine the spacer height prior to TOs. Subsequently, to identify the appropriate optimization target, different objectives are employed in the TOs of a 2D simplified model. Following this, TO with the selected target function is performed on 3D simplified models featuring diverse spacer combination architectures, with the preferable one chosen based on the outcomes. Eventually, leveraging the predetermined spacer height, objective function, and preliminary structure, a 3D TO spacer design utilizing a full-domain model is conducted to validate the effectiveness of the proposed methodologies. The final spacer design reduces the maximum von-Mises stress in the attachment by 19.42% (from 111.78 MPa with brick spacers of the same height to 90.07 MPa). The proposed multi-step TO method can therefore be used to improve the thermo-mechanical lifetime of DSC power modules. Full article

The integration of the Internet of Things (IoT) into mobile agent technology has fundamentally transformed the landscape of e-commerce by enabling intelligent, adaptive, and energy-efficient solutions. In this paper, we present a new system for integrating the information-sharing capability of IoT-enabled devices with the advanced abilities of mobile agents for the optimal utilization of energy when conducting e-commerce activity. The mobile agents are used as a mediating agent in the transaction and will capture operation data to share with stakeholders (not in the transaction) who might be able to provide services in association with that transaction. The operational data is collected, stored, and analyzed in real-time via IoT devices, facilitating adaptive decision-making while providing continuous monitoring of the system and servicing to improve energy management, efficiency, and operational performance. The combined IoT and energy capacity will enhance data sharing and provide more energy-efficient activities. The evaluation of the system was completed through simulations, as well as through real-world scenarios, achieving a decrease of approximately 27.8% in total energy consumption and savings of over 30% on operational costs. Moreover, the proposed architecture achieved a reduction of up to 38.9% for response times for resource management, under load, while also demonstrating a 50% reduction in response time for real-time event handling. Therefore, the effects of the proposed approach have been proven to be effective through simulations and real-world case studies, showing improvements in energy consumption and costs, as well as flexibility and adaptability. The findings of this study show that this framework not only minimizes energy consumption but also maximizes scalability, responsiveness to user demands, and robustness against variability in an e-commerce workload. This effort illustrates the potential for extending the lifetimes of e-commerce infrastructures and developing sustainable e-commerce models, demonstrating how IoT-based architectures can facilitate better resource allocation while achieving sustainability goals. Full article

This paper introduces a new cluster head selection algorithm for wireless sensor networks (WSNs) to maximize the time until the last sensor node depletes its energy. The algorithm is based on a formal analysis in which network lifetime is modeled as a function of node energy consumption. In contrast to existing energy-balancing strategies, this analytical foundation leads to a distinctive selection rule that prioritizes the node with the highest transmission probability and the lowest initial energy as the initial cluster head. The algorithm employs distributed per-cluster computation, enabling scalability without increasing complexity relative to network size. Unlike traditional approaches that rotate cluster heads based on time or equal energy use, our method adapts to heterogeneous energy consumption patterns and enforces a cluster head rotation order that maximizes the lifetime of the final active node. To validate the effectiveness of the proposed approach, we implement it on a real-world LoRaWAN-based sensor network prototype. Experimental results demonstrate that our method significantly extends the lifetime of the last active node compared to representative state-of-the-art algorithms. This research provides a practical and robust solution for energy-efficient WSN operation in real deployment scenarios by considering realistic and application-driven communication behavior along with hardware-level energy consumption. Full article

Food spoilage caused by microbial contamination remains a global challenge, driving demand for sustainable antibacterial packaging. Conventional photocatalytic materials suffer from limited spectral response, rapid charge recombination, and insufficient reactive oxygen species (ROS) generation under visible light. Here, a Z-scheme heterojunction was constructed by coupling zeolitic imidazolate framework-8 (ZIF-8) with Ag₃PO₄, achieving dual-spectral absorption and spatial charge separation. The directional electron transfer from Ag₃PO₄’s conduction band to ZIF-8 effectively suppresses electron-hole recombination, prolonging carrier lifetimes and amplifying ROS production (·O₂⁻/·OH). Synergy with Ag⁺ release further enhances bactericidal efficacy. Incorporated into a cellulose acetate matrix (CAM), the ZIF-8/Ag₃PO₄/CAM film demonstrates 99.06% antibacterial efficiency against meat surface microbiota under simulated sunlight, alongside high transparency. This study proposes a Z-scheme heterojunction strategy to maximize ROS generation efficiency and demonstrates a scalable fabrication approach for active food packaging materials, effectively targeting microbial contamination control and shelf-life prolongation. Full article

Wind energy is paramount to the European Union’s decarbonization and electrification goals. As wind farms expand with larger turbines and more powerful generators, conventional ‘greedy’ control strategies become insufficient. Coordinated control approaches are increasingly needed to optimize not only power output but also structural loads, supporting longer asset lifetimes and enhanced profitability. Despite recent progress, the effective implementation of multi-objective wind farm control strategies—especially those involving yaw-based wake steering—remains limited and fragmented. This study addresses this gap through a structured review of recent developments that consider both power maximization and fatigue load mitigation. Key concepts are introduced to support interdisciplinary understanding. A comparative analysis of recent studies is conducted, highlighting optimization strategies, modelling approaches, and fidelity levels. The review identifies a shift towards surrogate-based optimization frameworks that balance computational cost and physical realism. The reported benefits include power gains of up to 12.5% and blade root fatigue load reductions exceeding 30% under specific scenarios. However, challenges in model validation, generalizability, and real-world deployment remain. AI emerges as a key enabler in strategy optimization and fatigue damage prediction. The findings underscore the need for integrated approaches that combine physics-based models, AI techniques, and instrumentation to fully leverage the potential of wind farm control. Full article

The sizing of photovoltaic (PV) systems has been a concern since the 1990s, particularly with the trend of inverter undersizing as PV module prices decrease. While many studies have assessed the behavior of AC energy and economic parameters with varying Inverter Load Ratios (ILRs), they often neglect the impact of degradation on system lifetime or fail to analyze how it influences ILR selection in depth. This study examines the relationship between DC loss curves and ILRs, their evolution over time, and their effects on efficiency and Final Yield. Simulating solar resources in 27 Brazilian cities, it evaluates clipping losses and optimal ILR values ranging from 0.8 to 2.0 for 28 recent inverters. The research aims to identify the ILR that minimizes the Levelized Cost of Energy (LCOE) while maximizing Final Yield, revealing variations in optimal ILR ranges across different inverter–city combinations. The optimal ILR was between 1.1 and 1.3 for modern medium- and high-power inverters, while low-power inverters had a range of up to 1.8. The findings highlight that practical ILR considerations can overlook real-world challenges, leaving the system’s full potential untapped. Full article

With recent guidelines expanding transcatheter aortic valve replacement (TAVR) to younger patients, indications for redo-TAVR will also likely increase. When compared with TAVR, redo-TAVR is a rare and novel procedure. Current clinical data derived from registries suggest excellent safety, with low rates of 30-day and 1-year mortality following redo-TAVR. Proper understanding of data from bench studies regarding optimal valve configurations, of patient anatomy and of the technical properties of transcatheter heart valves (THV) is essential for patient selection and procedural success. Lifetime management of redo-TAVR should start before the index procedure, as the choice of the index THV has a major impact on the feasibility of redo-TAVR. Procedural optimization by adequate valve sizing, commissural alignment and adequate implant depth of both index and redo-THV are critical determinants of optimal hemodynamics for maximized valve longevity, as well as lifelong coronary access. Full article

Animals often regulate their nutrient intake according to their physiological needs. There is evidence that different traits require specific nutrient blends, and that animals cannot always maximize all traits with a single diet (“nutritional trade-offs”). However, we still do not have a clear understanding of which traits might be involved in nutritional trade-offs. I compiled data from the Geometric Framework of Nutrition literature on the ratio of proteins and carbohydrates that maximize (best PC ratios) or minimize (worst PC ratios) several larval and adult traits in Drosophila melanogaster. Best and worst PC ratios clustered into three regions in the protein-carbohydrate nutrient space: (1) Low PC ratios (1:8 or higher) are best for lifespan but worst for growth or reproductive traits; (2) High PC ratios (1:1 or lower) are best for adult body mass, male reproduction, and larval developmental time but worst for lifespan; and (3) Intermediate PC ratios (<1:1 and >1:8) are best for female lifetime egg production, female reproductive rate, and larval survival. These findings support lifespan–reproduction nutritional trade-offs, highlight the potential for metamorphosis to solve nutritional trade-offs across life stages, and underscore the potential for intralocus sexual conflict to emerge over the expression of metabolic genes. Full article

In the control of agricultural and forestry pests, excessive reliance on chemical pesticides has led to increasingly severe issues, such as toxic residues and heightened pest resistance. The effective use of biological control has become a major focus in pest management. Parasitoid wasps, as a critical natural enemy of pests, are widely distributed, diverse in species, and play an essential role in natural pest control. Copidosomopsis nacoleiae, a recently discovered polyembryonic endoparasitoid wasp, parasitizes Diaphania angustalis; yet, its biological characteristics remain insufficiently studied. The artificial rearing and population propagation of this wasp have not yet been achieved, and its reproductive behavior and rhythm are not fully understood. To better utilize natural enemy resources and maximize their pest control benefits, we conducted laboratory rearing, behavioral observation, and population surveys to investigate the morphological characteristics, life history, and behavioral patterns of C. nacoleiae. Under laboratory conditions, C. nacoleiae has a generational cycle of 48.71 ± 0.48 days, with an egg–larval period of 32.17 ± 0.20 days and a pupal period of 14.36 ± 0.27 days. Adult wasps require nutritional supplementation and have a maximum lifespan of 2.18 ± 0.09 days when fed 10% honey water. The pre-mating period for adults is 4.72 ± 0.24 h, with an average mating frequency of 5.17 ± 1.65 times per lifetime. Females have a pre-oviposition period of 2.80 ± 0.31 h and an oviposition period of 4.52 ± 0.12 h, laying between 2 and 95 eggs, with an average of 12.75 ± 9.99 eggs, totaling 107.55 ± 28.38 eggs over their lifespan. Offspring production increases with the body length of the host’s mature larvae. Through the successful establishment of a laboratory population of D. angustalis, the biological characteristics, reproductive behavior, and rhythms of C. nacoleiae were systematically examined in this study, and its occurrence dynamics in the field were investigated. These results provide a theoretical foundation for the large-scale propagation and application of C. nacoleiae to control D. angustalis populations effectively. Full article

This work investigates a new erase scheme in NAND flash memory to improve the lifetime and performance of modern solid-state drives (SSDs). In NAND flash memory, an erase operation applies a high voltage (e.g., >20 V) to flash cells for a long time (e.g., >3.5 ms), which degrades cell endurance and potentially delays user I/O requests. While a large body of prior work has proposed various techniques to mitigate the negative impact of erase operations, no work has yet investigated how erase latency and voltage should be set to fully exploit the potential of NAND flash memory; most existing techniques use a fixed latency and voltage for every erase operation, which is set to cover the worst-case operating conditions. To address this, we propose Revisiting Erase Operation, (REO) a new erase scheme that dynamically adjusts erase latency and voltage depending on the cells’ current erase characteristics. We design REO by two key apporaches. First, REO accurately predicts such near-optimal erase latency based on the number of fail bits during an erase operation. To maximize its benefits, REO aggressively yet safely reduces erase latency by leveraging a large reliability margin present in modern SSDs. Second, REO applies near-optimal erase voltage to each WL based on its unique erase characteristics. We demonstrate the feasibility and reliability of REO using 160 real 3D NAND flash chips, showing that it enhances SSD lifetime over the conventional erase scheme by 43% without change to existing NAND flash chips. Our system-level evaluation using eleven real-world workloads shows that an REO-enabled SSD reduces average I/O performance and read tail latency by 12% and 38%, respectivley, on average over a state-of-the-art technique. Full article

Energy plays a major role in wireless sensor networks (WSNs), and measurements demonstrate that transmission consumes more energy than processing. Hence, organizing the transmission process and managing energy usage throughout the network are the main goals for maximizing the network’s lifetime. This paper proposes an algorithm called RLDCSSA-CDG, which is processed through the 3F phases: foundation, formation, and forwarding phases. Firstly, the network architecture is founded, and the cluster heads (CHs) are determined in the foundation phase. Secondly, sensor nodes are dynamically gathered into clusters for better communication in the formation phase. Finally, the transmitting process will be adequately organized based on an adaptive wake-up/sleep scheduling algorithm to transmit the data at the “right time” in the forwarding phase. The MATLAB platform was utilized to conduct simulation studies to validate the proposed RLDCSSA-CDG’s effectiveness. Compared to a very recent work called RLSSA and RLDCA for CDG, the proposed RLDCSSA-CDG reduces total data transmissions by 22.7% and 63.3% and energy consumption by 8.93% and 38.8%, respectively. It also achieves the lowest latency compared to the two contrastive algorithms. Furthermore, the proposed algorithm increases the whole network lifetime by 77.3% and promotes data recovery accuracy by 91.1% relative to the compared algorithms. Full article

With the continuous growth of Industry 4.0 (I4.0), the industrial sector has transformed into smart factories, enhancing business competitiveness while aiming for the sustainable development of organizations. Machinery is a critical component and key to the success of production in a smart industrial factory. Minimizing unplanned downtime (UPDT) poses a significant challenge in designing an effective maintenance system. In the era of Industry 4.0, the most widely adopted maintenance frameworks are intelligent maintenance systems (IMSs), which integrate predictive maintenance with computerized systems. IMSs are intelligent tools designed to efficiently plan maintenance cycles for each machine component in a smart factory. This research presents the application of a search algorithm named state space search (SSS) in conjunction with a newly designed IMS, aimed at optimizing maintenance routines by identifying the optimal timing for maintenance cycles. The design began with the development of a new IMS concept that incorporates three key elements: the automation pyramid standard, Industrial Internet of Things (IIoT) sensors, and a computerized maintenance management system (CMMS). The CMMS collects machine data from the maintenance database, while real-time parameters are gathered via IIoT sensors from the supervisory control and data acquisition (SCADA) system. The new IMS concept provides a summary of the total maintenance cost and the remaining lifetime of the equipment. By integrating with SSS algorithms, the IMS presents optimized maintenance cycle solutions to the maintenance manager, focusing on minimizing costs while maximizing the remaining lifetime of the equipment. Moreover, the SSS algorithms take into account the risks associated with maintenance routines, following factory standards such as failure mode and effects analysis (FMEA). This approach is well suited to smart factories and helps to reduce UPDT. Full article

Wireless body area networks (WBANs), which continually gather and transmit patient health data in real time, are essential for improving healthcare administration. Patient outcomes can be improved by sending these data to medical professionals for prompt review and treatment. For the effective deployment of WBANs, communication solutions are necessary to maximize critical performance parameters, such as low power consumption, minimal delay, and acceptable data rates, while guaranteeing dependable transmission. Two prominent technologies in this field are LoRaWAN, which is renowned for its long-range capabilities and energy efficiency, and IEEE 802.15.6, which was created especially for short-range medical applications with high data throughput. This study provides a comparative evaluation of these two technologies to determine their suitability for diverse WBAN healthcare scenarios. By using the NS3, a simulation was performed to calculate six key performance metrics: throughput, arrival rate, delay, energy consumption, packet delivery ratio (PDR), and network lifetime. The study analyzed each technology’s performance under varying node counts. At a density of 50 nodes, IEEE 802.15.6 demonstrated superior throughput, with 45 kbps, compared to LoRaWAN, and a higher PDR of 30%. Additionally, IEEE 802.15.6 showed a higher arrival rate, of 0.33%, than LoRaWAN. On the other hand, LoRaWAN showed notable strengths in energy consumption, with only 42 J, compared to IEEE 802.15.6, and significantly lower delay, with a delay of 7 s. Additionally, LoRaWAN offered an extended network lifetime, of 18 h, compared to IEEE 802.15.6. Full article

The emerging wireless energy transfer technology enables sensor nodes to maintain perpetual operation. However, maximizing the network performance while preserving short charging delay is a great challenge. In this work, a Wireless Mobile Charger (MC) and a directional charger (DC) were deployed to transmit wireless energy to the sensor node to improve the network’s throughput. To the best of our knowledge, this is the first work to optimize the data sensing rate and charging delay by the joint scheduling of an MC and a DC. We proved we could transmit maximum energy to each sensor node to obtain our optimization objective. In our proposed work, a DC selected a total horizon of 360° and then selected the horizon of each specific ${90}^{\circ }$ area based on its antenna orientation. The DC’s orientation was scheduled for each time slot. Furthermore, multiple MCs were used to transmit energy for sensor nodes that could not be covered by the DC. We divided the rechargeable wireless sensor network into several zones via a Voronoi diagram. We deployed a static DC and one MC charging location in each zone to provide wireless charging service jointly. We obtained the optimal charging locations of the MCs in each zone by solving Mix Integral Programming for energy transmission. The optimization objective of our proposed research was to sense maximum data from each sensor node with the help of maximum energy. The lifetime of each sensor network could increase, and the end delay could be maximized, with joint energy transmission. Extensive simulation results demonstrated that our RWSNs were designed to significantly improve network lifetime over the baseline method. Full article

As electronic devices continue to shrink in size and increase in complexity, the current densities in interconnects drastically increase, intensifying the effects of electromigration (EM). This renders the understanding of EM crucial, due to its significant implications for device reliability and longevity. This paper presents a comprehensive simulation framework for the investigation of EM in nano-interconnects, with a primary focus on unravelling the influential role of microstructure, by considering the impact of diffusion heterogeneity through the metal texture and interfaces. As such, the resulting atomic flux and stress distribution within nano-interconnects could be investigated. To this end, a novel approach to generate microstructures of the conductor metal is presented, whereby a predefined statistical distribution of grain sizes obtained from experimental texture analyses can be incorporated into the presented model, making the model predictive under various scales and working conditions with no need for continuous calibration. Additionally, the study advances beyond the state-of-the-art by comprehensively simulating all stages of electromigration including stress evolution, void nucleation, and void dynamics. The model was employed to study the impact of trench dimensions on the dual damascene copper texture and its impact on electromigration aging, where the model findings were corroborated by comparing them to the available experimental findings. A nearly linear increase in normalized time to nucleation was detected as the interconnect became wider with a fixed height for aspect ratios beyond 1. However, a saturation was detected with a further increase in width for lines of aspect ratios below 1, with no effective enhancement in time to nucleation. An aspect ratio of 1 seems to maximize the EM lifetime for a fixed cross-sectional area by fostering a bamboo-like structure, where about a 2-fold of increase was estimated when going from aspect ratio 2 to 1. Full article