A novel miniaturized tri-band frequency selective surface (FSS) based on convoluted design has been proposed in this letter. The proposed FSS is a low-profile structure, and it is composed of two periodic metallic arrays separated by a thin dielectric substrate. The top metallic array is composed of four branched spiral triangles connected in the center, and the bottom one is consisting of gridded tortuous cross-dipole. The proposed FSS can provide three passbands operating at 3.28, 4.2, and 5.4 GHz, respectively. The unit cell is only 0.066 λ 0 × 0.066 λ 0 in size, where λ 0 is the wavelength of the first resonant frequency in free space. In addition, the proposed FSS provides a stable performance under oblique incidence for both TE and TM polarizations. For verification, an FSS prototype has been fabricated and measured. Good agreements between the simulated and the measured results can be observed.
Few studies have examined the psychological experience of drivers of manned vehicles sharing the road with driverless vehicles. To judge whether drivers think they are in a vulnerable state and find out what makes drivers feel they will be in a state we called “expected psychological vulnerability”, this paper conducted a questionnaire to collect information about the attitude, perceived usefulness, trust, perceived risk, and demographic information of drivers in a hypothetical situation involving driving on the same road as driverless vehicles. Our goal was to identify areas where the drivers felt that they would be in a “vulnerable psychological state”, i.e., that they would be more vulnerable to making poor psychological judgments. The survey results indicated that 43.7 % of the respondents believed that they would be in a vulnerable state in mixed traffic competition, 30.2 % of the respondents did not know whether they would be in a vulnerable state. Further, women, people with a higher education, people with a more aggressive driving personality, older people, and those with more driving experience were more inclined to think that they would not be in a vulnerable state. Attitude, trust, and perceived usefulness all had positive impacts on judgments regarding psychological vulnerability, and perceived risk had a negative impact. Therefore, the early promotion of driverless technology should give priority to people with a higher education, more driving experience, older age, and more aggressive driving personality, and focus on attitudes towards this technology, including perceived usefulness, trust, and perceived risk.
A novel dual-band miniaturized frequency selective surface adopting fractal elements is proposed. The proposed structure is composed of interconnected four SZ curves of second generation. Such a design is to provide two pass-bands with stable performance, the first band resonates at S-band with a center frequency of 3.02 GHz and the second band is at C-band centered at 7.22 GHz. In addition, the compact structure employing the space filling curve can further reduce the size of the FSS. The dual-band FSS achieves better miniaturization compared with other single layer FSS in previous literature, the dimension of the unit cell is only 0.072λ × 0.072λ, where λ represents the free space wavelength at first resonant frequency. Furthermore, the proposed FSS exhibits great resonance stability for different polarizations and incidence angles. Both the simulation and measurement verify the stable performance of the FSS.
Decarbonizing the building stock plays an important role in realizing climate change mitigation targets. To compare the decarbonization potential of different strategies, this study presents a spatiotemporal bottom-up dynamic building stock model that integrates material flow analysis, building energy modeling, and life cycle assessment. It can simulate future building stock evolution at the component level and track the associated material flows, energy demand and generation, and GHG emissions with the consideration of both endogenous factors (e.g. building energy efficiency upgrade) and exogenous factors (e.g. policies, occupant behavior, and climate scenarios). The model is applied in the residential building stock of Leiden, a municipality in the Netherlands. Results show that annual GHG emissions are reduced by about 40% under the reference scenario while annual GHG emissions can be reduced by about 90% under the ambitious scenario where all the decarbonization strategies are simultaneously implemented. Natural-gas-free heat transition and renewable electricity supply are the most effective strategies, respectively reducing the annual GHG emissions in 2050 by an additional 21% and 19% more than the reference scenario. Rooftop PV, green lifestyle, and wood construction have similar decarbonization potential (about 10%). Surplus electricity can be generated if rooftop PV systems are installed as much as possible. The decarbonization potential of demolition waste recycling is much smaller than other strategies. The model can support policymakers in assessing the decarbonization potential of different policy scenarios and prioritizing decarbonization strategies in advance.
Extreme weather has been more frequent in recent years. Urban agglomerations, as areas with a high density of human activities, have been plagued by storm flooding. Historically, the main focus of attention on flood control in urban agglomerations has gradually shifted from underground pipe networks to the impervious surface, reflecting profound changes in the influencing mechanism of urban flooding. Exploring the evolution of the mechanisms influencing urban flooding in the Guangdong Hong Kong Macao Greater Bay Area (GBA) urban agglomeration is of great reference significance for formulating flood prevention and control measures and promoting high-quality development of the GBA city cluster. In this paper, we fully use the collected information on urban flooding events from 1980 to 2018 in the GBA city cluster. Correlation analysis and geographically weighted regression (GWR) are used to analyze the influence of impervious surface percentage (ISP), impervious surface aggregation index (AI), impervious surface mean shape index (Shape_MN), vegetation cover (FVC), water surface ratio (WSR), relative elevation (RE) and slope on flooding in urban clusters and their evolution characteristics over time from a global perspective and spatial heterogeneity, respectively. The results show that: 1) ISP, AI, Shape_MN, and WSR are positively correlated with urban flooding, while FVC, RE, and Slope are negatively correlated with urban flooding. The correlations of each factor showed a general trend of gradual strengthening over time, and the increase rate slowed down after 2000, while the correlation of WSR showed a relatively noticeable decrease. 2) The GWR results show that each factor’s influence on urban flooding has pronounced spatial-temporal heterogeneity, and each factor shows different distribution characteristics. This study uses long time series of urban flooding point data to explore the spatial-temporal evolution of the influencing mechanism of urban flooding in the GBA urban agglomeration. We hope to provide a scientific basis for an in-depth understanding of the causes of urban flooding in the GBA, intending to provide auxiliary decision-making support for the formulation of waterlogging prevention and control measures.
This paper presents a design method for frequency selective surface (FSS) based on the deep neural network and improved particle swarm algorithm (IPSO). In the proposed method, the forward prediction network (FPN) based on the fully connected network is established to fast predict the transmission coefficient of FSS. Combined with the FPN, the IPSO is used to optimize the structural parameters of FSS. Compared with the traditional iterative optimization method based on full-wave simulation, this method greatly improves the optimization efficiency of FSS. For example, a band-stop FSS is optimized with the proposed method in 210.6s, and the optimization efficiency increases by more than 99%. Simulation results show that the transmission coefficient errors of key frequency points between optimization results and objectives are less than 1 dB. And the deviation of the center frequency and the bandwidth of the target frequency bands is less than 0.81% and 4.1%, respectively.
A new car-following model is proposed in this study, and it considers the comprehensive information of the preceding and the following vehicles (i.e., the CIPF model) including the headway, speed difference, and acceleration. This model can be considered as a further extension of the existing forward-backward velocity difference (FBVD) model. Based on the linear stability analysis of the CIPF model, the judgment basis of the traffic flow stability is obtained. Compared with the optimal velocity (OV) model, the full velocity difference (FVD) model, and the FBVD model, the CIPF model has the largest stable region and the smallest unstable region. Using the reductive perturbation method, the nonlinear analysis of the CIPF model is performed, and the modified Korteweg-de Vries (mKdv) equation, which is used to describe the traffic flow characteristics of the system near the critical point, is obtained. Finally, the numerical simulation results show that the CIPF model can respond to the state of traffic flow better and faster than the FBVD model in vehicle start and stop simulation, and can better alleviate traffic congestion and improve the traffic flow stability in the simulation of circular road. The kink-antikink wave described by mKdV equation is simulated in the unstable region after the perturbation is added to the traffic flow, which also validates the CIPF model.
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