Modeling and coupling effect evaluation of thermal conductivity of ternary opacifier/fiber/aerogel composites for super-thermal insulation

Yang, Jianming; Wu, Huijun; Huang, Gongsheng; Liang, Yingjing; Liao, Yundan

doi:10.1016/j.matdes.2017.07.056

Cited by 83 publications

(16 citation statements)

References 43 publications

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“…Numerical results have been given to validate our analysis. In future works, we will consider the application of this work for IoT networks, such as urban environment improvement [34][35][36] and environmental monitoring [37][38][39][40]. Moreover, we will incorporate the intelligent algorithms such as learning-based algorithms [41,42], deep learning [43,44], and reinforcement learning [45][46][47] into the considered system, in order to further enhance the network performance.…”

Section: Discussionmentioning

confidence: 99%

Cache-aided mobile edge computing for B5G wireless communication networks

Xia

Lai

et al. 2020

J Wireless Com Network

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This paper investigates a cache-aided mobile edge computing (MEC) network, where the source offloads the computation task to multiple destinations with computation capacity, with the help of a cache-aided relay. For the proposed cache-aided MEC networks, two destination selection criteria have been proposed to maximize the computation capacity of the selected destination, the channel gain of relay link and the channel gain of direct link, respectively. Similarly, three destination selection criteria have been proposed for the cache-free MEC networks based on the computation capacities of destinations and the channel gains of transmission links, respectively. To evaluate the system performance regarding the latency constraint, we provide the outage probability for the proposed network which is defined based on the transmission-plus-computation time. Our analysis suggests that caching can significantly alleviate the impact of increasing the size of computation task, since only half of the transmission time of cache-free network is required. However, the cache-aided network can not fully exploit the signal from both direct and relay links, thus the improvement by caching is less significant in the high signal-to-noise ratio (SNR) region, compared with the cache-free network employing the destination with maximal channel gain of direct link. Numerical results are given to validate our analysis.

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Section: Discussionmentioning

confidence: 99%

Cache-aided mobile edge computing for B5G wireless communication networks

Xia

Lai

et al. 2020

J Wireless Com Network

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“…Note that the analytical expression of SER in (25) contains some elementary functions only, and hence we can easily evaluate the system SER for the traditional DF relaying networks without cache aid. The details about the numerical computation can be found in [44][45][46]. We now propose to derive the asymptotic SER for the traditional DF relaying networks without cache, in the high regime of transmit power .…”

Section: Without Cachementioning

confidence: 99%

Cache Aided Decode‐and‐Forward Relaying Networks: From the Spatial View

Xia

Zhou

Lai

et al. 2018

Wireless Communications and Mobile Computing

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We investigate cache technique from the spatial view and study its impact on the relaying networks. In particular, we consider a dual-hop relaying network, where decode-and-forward (DF) relays can assist the data transmission from the source to the destination. In addition to the traditional dual-hop relaying, we also consider the cache from the spatial view, where the source can prestore the data among the memories of the nodes around the destination. For the DF relaying networks without and with cache, we study the system performance by deriving the analytical expressions of outage probability and symbol error rate (SER). We also derive the asymptotic outage probability and SER in the high regime of transmit power, from which we find the system diversity order can be rapidly increased by using cache and the system performance can be significantly improved. Simulation and numerical results are demonstrated to verify the proposed studies and find that the system power resources can be efficiently saved by using cache technique.

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“…Kistle first prepared SiO 2 aerogel in 1931 using sodium silicate as a precursor and ethanol supercritical drying technology . Since then, silica aerogels embrace a potential to be applied in thermal insulators, catalysis, energy technology, aerospace field, and adsorption in virtue of their low density (80‐100 kg/cm), low thermal conductivity (0.013‐0.14 W/(m·K)), and high porosity (>90%) . Although silica aerogels have these excellent properties, they are inherently fragile due to its weak pearl‐like structure, which limit their practical application.…”

Section: Introductionmentioning

confidence: 99%

Nanofibers reinforced silica aerogel composites having flexibility and ultra‐low thermal conductivity

Zhang

Zhao

et al. 2020

Int J Applied Ceramic Tech

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For the sake of enhancing the performance of flexible silica aerogel in practical applications, flexible SiO2/SnO2 nanofibers (SSNF) reinforced flexible silica aerogel composites (abbreviated as SiO2‐SSNF) were successfully prepared. Firstly, the SiO2/SnO2 nanofibers with fine diameter (~320 nm) and excellent flexibility were prepared by electrospinning technology. Then the aerogel composites were synthesized by adding the flexible SSNF to the silica solution and through the sol‐gel method and ethanol supercritical drying technology. The effects of different content of the nanofibers on thermal conductivity and Yong's modulus of SiO2‐SSNF aerogel composites were investigated. The SiO2/SnO2 nanofibers were randomly dispersed in the flexible silica aerogel and the great integrity of the material result in smaller linear shrinkage, better thermal protection, and mechanical properties compared with those pure SiO2 aerogels. The final SiO2‐SSNF aerogel composites possess excellent thermal conductivity (0.025‐0.029 W/(m∙K)) and higher Yong's modulus (70 kPa), which was twice than that of the pure silica aerogel. This prepared SiO2‐SSNF aerogel composites can be better used in thermal insulation due to its excellent flexible and thermal insulation property.

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Modeling and coupling effect evaluation of thermal conductivity of ternary opacifier/fiber/aerogel composites for super-thermal insulation

Cited by 83 publications

References 43 publications

Cache-aided mobile edge computing for B5G wireless communication networks

Cache-aided mobile edge computing for B5G wireless communication networks

Cache Aided Decode‐and‐Forward Relaying Networks: From the Spatial View

Nanofibers reinforced silica aerogel composites having flexibility and ultra‐low thermal conductivity

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