با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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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.
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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 |
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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 |
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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 |
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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 |
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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 |