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نتیجه جستجو - Energy harvesting

تعداد مقالات یافته شده: 20
ردیف عنوان نوع
1 Advances in Electrical Engineering, Electronics and Energy: Global Developments in New Energy Technologies and Development of Energy Technology from the Micro to the Macro-Scale
پیشرفت‌ها در مهندسی برق، الکترونیک و انرژی: تحولات جهانی در فناوری‌های انرژی جدید و توسعه فناوری انرژی از مقیاس خرد تا مقیاس کلان-2021
Global warming and increasingly severe weather events have given a new and increasingly urgent focus to energy technology. Currently there is major growth in novel technologies such as energy harvesting, self-powering wearable devices, and options enabling a move to a post carbon future using a range of advanced materials (for example, carbon-based nanomaterials), especially for low power devices. By contrast, large thermal energy development is focused on either using renewable energy or developing thermal boilers with high electrical efficiency and low emissions. Electrical energy efficiency of 50% or more is increasingly being held out as feasible in the next several decades. However, most of these advancements concerning large boilers depend heavily on materials development, which can be an extremely slow process. Genuinely new approaches which might include improved fusion energy technology, or ultra large batteries, or even devices built on systems employing superconductivity are also possible, although it seems unlikely that any such technologies will play a critical role in achieving greenhouse goals in the next decade, but they might well become important to achieve 2050 targets. Renewables remain one of the most promising frontiers, but they need to be made cheaper and combined with better energy storage.
مقاله انگلیسی
2 Performance evaluation for scientific balloon station-keeping strategies considering energy management strategy
ارزیابی عملکرد برای استراتژی نگهداری ایستگاه های بالون علمی با توجه به استراتژی مدیریت انرژی-2020
The combination of solar array and rechargeable battery is the main trend of energy system for scientific balloon station-keeping, when the performances of station-keeping strategies are evaluated, energy problem should be considered. In this paper, the performances of air ballast system and double balloon system are evaluated with the consideration of energy management strategy. The theoretical model consisting of thermal model, solar array power model, energy consumption model and energy evaluation model is proposed. The energy management strategy containing solar array and lithium battery is designed. Based on the theoretical model and energy management strategy, a MATLAB program is developed. The feasibility is verified by comparison analysis. The energy harvesting characteristics, effects of the station-keeping duration and effects of the station-keeping region radius are analyzed carefully. The results show that the double balloon is superior than air ballast system from the perspective of energy. The air ballast system requires more energy than double balloon system and the energy difference increases over time. Air ballast system lithium battery capacity requirement is higher than double balloon system, the total energy consumption and the energy differences decrease with expected radius increasing. It would be helpful in selecting station-keeping strategies for scientific balloon mission.
Keywords: Energy management strategy | Lithium battery | Performance evaluation | Scientific balloon | Solar array | Station-keeping
مقاله انگلیسی
3 Scaling laws of electromagnetic and piezoelectric seismic vibration energy harvesters built from discrete components
مقررات مقیاس بندی برداشت انرژی لرزه ای الکترومغناطیسی و پیزو الکتریک ساخته شده از اجزای گسسته-2020
This paper presents a theoretical study on the scaling laws of electromagnetic and piezoelectric seismic vibration energy harvesters, which are assembled from discrete components. The scaling laws are therefore derived for the so called meso-scale range, which is typical of devices built from distinct elements. Isotropic scaling is considered for both harvesters such that the shape of the components and of the whole transducers do not change with scaling. The scaling analyses are restricted to the case of linearly elastic seismic transducers subject to tonal ambient vibrations at their fundamental natural frequency, where the energy harvesting is particularly effective. Both resistive-reactive and resistive optimal electric harvesting loads are considered. The study is based on equivalent formulations for the response and power harvesting of the two transducers, which employ the so called electromagnetic and piezoelectric power transduction factors, P2 cm and P2 pe. The scaling laws of the transduction coefficients and electrical and mechanical parameters for the two transducers are first provided. A comprehensive comparative scaling analysis is then presented for the harvested power, for the power harvesting efficiency and for the stroke of the two harvesters. Particular attention is dedicated to the scaling laws for the dissipative effects in the two harvesters, that is the Couette air losses and eddy currents losses that develop in the electromagnetic harvester and the material, air and dielectric losses that arise in the piezoelectric harvester. The scaling laws emerged from the study, are thoroughly examined and interpreted with respect to equivalent mechanical effects produced by the harvesting loads.
Keywords: Seismic vibration energy harvesting | Vibration energy harvesting scaling laws | Electromagnetic seismic vibration harvester | Piezoelectric seismic vibration harvester
مقاله انگلیسی
4 Construction of various nanostructures on carbon nanotube films
ساخت انواع نانوساختارها بر روی فیلم های نانولوله کربنی-2020
Construction of nanostructures on surfaces has appealed intensive attention due to its significant applications in diverse fields. Especially, engineering surface properties via surficial nanostructures is actually the creation of functional interface-based materials and slated to be the key aspect for the future of materials science. Although many efforts have been made, there are only a few reports about the construction of nanostructures on carbon nanotube film surfaces. The big challenge for constructing on carbon films is that these carbon assemblies are easy to be dispersed by immersion in a chemical solution. Here, in this paper, we have shown for the first time the fabrication of different kinds of nanostructures, i.e. nanoneedles, nanoparticles, nanospirals, on carbon nanotube films by using facile and cheap electrodeposition method and precise physical deposition method. We pretreat the films by an electrical method to strengthen the films to avoid dispersion during the electrodeposition process. These composite films are still very flexible after coating with nanostructures. Compared with those precise physical deposition methods, the facile electrodeposition method is more suitable for constructing nanostructures on carbon nanotube films, due to the low requirement for planeness of films. It is interesting to find that these nanostructures can endow superhydrophobicity or higher conductivity for these flexible composite films, which greatly broaden the potential applications for carbon nanotube films in the fields of battery, moisture self-cleaning, electrostatic energy harvesting, and enhancing condensation heat transfer for more efficiency of energy utilization, environmental, and thermal management
Keywords: Arrays of nanostructures | Nano films | Superhydrophobicity | Environmental and energy management
مقاله انگلیسی
5 Adaptive data and verified message disjoint security routing for gathering big data in energy harvesting networks
داده تطبیقی و تایید امنیت پیام متلاشی شدن مسیریابی برای جمع آوری داده های بزرگ در شبکه های برداشت انرژی-2020
To improve the data arrival ratio and the transmission delay and considering that the capacity for determining malicious nodes and energy are limited, a security disjoint routing-based verified message (SDRVM) scheme is proposed. The main contributions of SDRVM are as follows: (a) two connected dominating sets (a data CDS and a v-message CDS) are created for disseminating data and verified messages (v-messages), respectively, based on the remaining energy of nodes. (b) Nodes record the ID information in data packets with a specified probability, namely, the marking probability, which is adjusted according to the remaining energy of the nodes. (c) The duty cycle of the nodes is adjusted, and the energy of the nodes is divided into three levels. In the data CDS, the duty cycle of the sensor nodes is the longest and the duty cycle of the nodes that do not belong to either of the CDSs is the shortest. (d) If the energy of the sensor nodes is sufficient, data packets are transmitted several times and the v-messages that are stored in the nodes are transmitted to the destination nodes. The proposed scheme has been evaluated using different parameters where the results obtained prove its effectiveness in comparison to the existing solutions.
Keywords: Energy harvesting networks | Security | Disjoint routing | Marking probability | Network lifetime
مقاله انگلیسی
6 برداشت انرژی خورشیدی زیرپوستی - روشی جدید برای تامین نیروی ایمپلنت‌های الکتریکی مستقل
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 29
برداشت خورشیدی زیرپوستی این پتانسیل را دارد که نیاز به تعویض دوره‌ای باتری را همانطور که در بیماران دارای ضربان ساز قلبی مورد نیاز است، مرتفع سازد. خروجی توان قابل‌ دستیابی ماژول خورشیدی زیرپوستی در عمق کاشت، ویژگی‌های پوست نوری و به بخش مهمی در ویژگی‌های سلول خورشیدی کاهش می‌یابد. برای تخمین توان خروجی سلولهای خورشیدی زیر پوستی تحت قرار گرفتن در معرض نور خورشید در اواسط عرض جغرافیایی به عنوان تابعی از عمق کاشت و اندازه صفحه خورشیدی، از شبیه سازی توزیع نور مونت کارلو استفاده شد. برای تاریک‌ترین نوع پوست، تامین انرژی روزانه یک ضربان ساز قلبی مدرن (‏۰.۸۶۴ ژول در تقاضای توان ۱۰ وات) ‏می‌تواند توسط یک سلول خورشیدی2 cm2 که به صورت زیر پوستی در عمق ۳ میلی متر وقتی که در معرض تنها ۱۱ دقیقه، تابش روشن آسمان هنگام ظهر قرار می‌گیرد، تامین شود. مطالعه ما نشان می‌دهد که برداشت خورشیدی با سلول‌های خورشیدی نسبتا کوچک در صورتی که برای تاثیر زیرپوستی طیفی بهینه شده ‌باشد، پتانسیل قدرت ضربان سازها در تمام انواع پوست در زمان‌های تابش دهی معقول را دارد. برداشت انرژی خورشیدی برای تامین انرژی ایمپلنت های الکترونیکی بسیار امیدوار کننده است.
کلمات کلیدی: ضربانساز قلب یا پیس میکر | ایمپلنت یا کاشت زیرپوستی | ویژگی‌های سلول خورشیدی | سلول‌های خورشیدی نقطه کوانتومی | منبع تغذیه ایمپلنت | جایگزینی باتری
مقاله ترجمه شده
7 Deep Reinforcement Learning-based resource allocation strategy for Energy Harvesting-Powered Cognitive Machine-to-Machine Networks
استراتژی تخصیص منابع مبتنی بر یادگیری تقویتی عمیق برای شبکه های شناختی ماشین به ماشین با قدرت برداشت انرژی-2020
Machine-to-Machine (M2M) communication is a promising technology that may realize the Internet of Things (IoTs) in future networks. However, due to the features of massive devices and concurrent access requirement, it will cause performance degradation and enormous energy consumption. Energy Harvesting- Powered Cognitive M2M Networks (EH-CMNs) as an attractive solution is capable of alleviating the escalating spectrum deficient to guarantee the Quality of Service (QoS) meanwhile decreasing the energy consumption to achieve Green Communication (GC) became an important research topic. In this paper, we investigate the resource allocation problem for EH-CMNs underlaying cellular uplinks. We aim to maximize the energy efficiency of EH-CMNs with consideration of the QoS of Human-to-Human (H2H) networks and the available energy in EH-devices. In view of the characteristic of EH-CMNs, we formulate the problem to be a decentralized Discrete-time and Finite-state Markov Decision Process (DFMDP), in which each device acts as agent and effectively learns from the environment to make allocation decision without the complete and global network information. Owing to the complexity of the problem, we propose a Deep Reinforcement Learning (DRL)-based algorithm to solve the problem. Numerical results validate that the proposed scheme outperforms other schemes in terms of average energy efficiency with an acceptable convergence speed.
Keywords: Energy Harvesting | M2M communication | Resource allocation | Deep Reinforcement Learning
مقاله انگلیسی
8 Data interpretation framework integrating machine learning and pattern recognition for self-powered data-driven damage identification with harvested energy variations
چارچوب تفسیر داده ها ادغام یادگیری ماشین و شناخت الگو برای شناسایی آسیب خود محور داده با تغییرات انرژی برداشت شده-2019
Data mining methods have been widely used for structural health monitoring (SHM) and damage identification for analysis of continuous signals. Nonetheless, the applicability and effectiveness of these techniques cannot be guaranteed when dealing with discrete binary and incomplete/missing signals (i.e., not continuous in time). In this paper a novel data interpretation framework for SHM with noisy and incomplete signals, using a through-substrate self-powered sensing technology, is presented within the context of artificial intelligence (AI). AI methods, namely, machine learning and pattern recognition, were integrated within the data interpretation framework developed for use in a practical engineering problem: data-driven SHM of platelike structures. Finite element simulations on an aircraft stabilizer wing and experimental vibration tests on a dynamically loaded plate were conducted to validate the proposed framework. Machine learning algorithms, including support vector machine, k-nearest neighbor, and artificial neural networks, were integrated within the developed learning framework for performance assessment of the monitored structures. Different levels of harvested energy were considered to evaluate the robustness of the SHM system with respect to such variations. Results demonstrate that the SHM methodology employing the proposed machine learning-based data interpretation framework is efficient and robust for damage detection with incomplete and sparse/missing binary signals, overcoming the notable issue of energy availability for smart damage identification platforms being used in structural/infrastructure and aerospace health monitoring. The present study aims to advance data mining and interpretation techniques in the SHM domain, promoting the practical application of machine learning and pattern recognition with incomplete and missing/sparse signals in smart cities and smart infrastructure monitoring.
Keywords: Structural health monitoring | Machine learning | Low-rank matrix completion | Pattern recognition | Self-powered sensors | Plate-like structures | Incomplete signals | Energy harvesting
مقاله انگلیسی
9 An ultra-low voltage chaos-based true random number generator for IoT applications
مولد عدد تصادفی حقیقی مبتنی بر هرج و مرج ولتاژ فوق العاده کم برای برنامه های اینترنت اشیا-2019
Low-power consumption and low-voltage operation are critical enabling features for Internet of Things (IoT) devices that are powered from energy harvesting. This paper presents a chaos-based true random number generator (TRNG) that can operate at an ultra-low voltage (ULV) and be integrated into energy-constrained IoT devices for secure communications. Folded Bernoulli maps are adopted for random number generation. Switchedcapacitor chaotic circuits utilize bulk-driven amplifiers to mitigate gate leakage issue, two-stage comparators to increase voltage headroom, and low-complexity calibration schemes to ensure robustness. This system covers a wide range of process and temperature variations while consuming 142 nW from a 0.4 V supply at a bit rate of 10 kb/s. The generated bits pass National Institute of Standards and Technology (NIST) Pub-800.22 randomness tests successfully.
Keywords: Chaotic map | Cryptography | Encryption | Security | True random number generators (TRNGs) | Ultra-low voltage (ULV)
مقاله انگلیسی
10 An algorithmic framework for reconstruction of time-delayed and incomplete binary signals from an energy-lean structural health monitoring system
یک چارچوب الگوریتمیک برای بازسازی سیگنالهای باینری با تأخیر زمان و ناقص از یک سیستم نظارت بر سلامت ساختاری کم انرژی-2019
Recent advances in energy harvesting technologies have led to the development of self-powered structural health monitoring (SHM) techniques that are power-efficient. Energy-aware data transmission protocols, on the other hand, have evolved due to the emergence of self-powered sensing. The pulse switching architecture is among such protocols employing ultrasonic pulses for event reporting through the substrate material. However, the noted protocol raises the necessity for new types of signal/data interpretation methods for SHM purposes. This is because a system using such technology demands dealing with power budgets for sensing and communication of binary signals that leads to unique time delay constraints. This study presents a novel computational approach to reconstruct delayed and incomplete binary signals provided by a through-substrate ultrasonic self-powered sensor network for SHM of plate-like structures. An algorithmic framework incorporating low-rank matrix completion, a data fusion model, and a statistical approach is proposed for damage identification. Performance and effectiveness of the proposed method for the case of dynamically loaded plates was evaluated using finite element simulations and experimental vibration tests. Results demonstrate that the energy-lean damage identification methodology employing the proposed algorithmic framework enables dependable detection of damage using reconstructed time-delayed binary signals.
Keywords: Structural health monitoring | Matrix completion | Pattern recognition | Self-powered sensor network | Time-delayed binary signals
مقاله انگلیسی
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