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AbstractBuilding thermal inertia and operation control strategies have impacted on the thermal performance of a radiant floor heating system. This study conducts a two-dimensional numerical analysis of an intermittently operated radiant floor heating system using the Re-Normalization Group model with Discrete Ordinates Radiation model. A detailed numerical simulation setups and various analyses are provided, including grid independency analysis, initial condition, time step sizes and external boundary conditions. Three different weekend day intermittent operation strategies are investigated. The results showed that Case 3 designed with pre-heating of 20?h has better performance compared to Case 1 designed with pre-heating of 8?h and Case 2 designed with pre-heating of 14?h. The average indoor air temperature differences of approximate 2.1, 1.6 and 1.2 K are observed for Case 1, Case 2 and Case 3, respectively, when comparing two-time slot at 8:00am on Friday morning and Monday morning. This significantly highlights the effect of thermal inertia and the potential of energy saving due to the utilization of intermittent operation. Therefore, the current study presents numerical simulation potential in evaluating the radiant floor heating effects on indoor thermal environment, taking into account building thermal inertia and transient external climatic conditions. 相似文献
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Yao Dajie Liu Xiaofei Wu Jian 《International Journal of Control, Automation and Systems》2020,18(9):2251-2258
International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive... 相似文献
56.
To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction,
optimization model decoupling and optimization was presented. In feasible region
reduction, the dimensions of the feasible design region were reduced by selecting dominant
design variables from numerous multilevel parameters by sensitivity analyses, and the
feasible regions of variables were reduced by influence mechanism analyses. In model
decoupling, the optimization model with a large number of variables was divided into
various sub-models with fewer variables by variance analysis. In the third step, the
optimization sub-models were solved one by one using a genetic algorithm, and the
modified characteristic curve method was adopted as the failure prediction method. Based
on the proposed optimization method, optimization of a double-lap single-bolt joint was
performed using the ANSYS® code. The results show that the bearing failure load increased
by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of
the joint, which validated the effectiveness of the three-step optimization strategy. 相似文献
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59.
Neural Machine Translation (NMT) is an end-to-end learning approach for
automated translation, overcoming the weaknesses of conventional phrase-based translation
systems. Although NMT based systems have gained their popularity in commercial
translation applications, there is still plenty of room for improvement. Being the most
popular search algorithm in NMT, beam search is vital to the translation result. However,
traditional beam search can produce duplicate or missing translation due to its target
sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural
machine translation improvements based on a novel beam search evaluation function. And
we use reinforcement learning to train a translation evaluation system to select better
candidate words for generating translations. In the experiments, we conducted extensive
experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual
corpora of NiuTrans are used in our experiments. The experiment results prove that the
proposed methods can effectively improve the English to Chinese translation quality. 相似文献
60.
Shuang Shao Yong Liu Chun-Shui Xu Ying-Xuan Xu Bin Wu Xiao-Shu Zeng Xian-Feng Lu Xiang-Jie Yang 《金属学报(英文版)》2015,(1):7-14
The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory. 相似文献