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Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants' air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into simulations, in order to improve the prediction performance of AC energy consumption. Based on long-term onsite monitoring of household thermal environments and AC usage patterns, two stochastic models were built using unsupervised cluster and statistical methods. Based on the Monte Carlo method, the AC operation schedule was generated through AC opening duration, setpoints, and other relevant parameters, and was further incorporated into EnergyPlus. The results show that the ideally deterministic AC operation settings from the standard significantly overestimate the cooling energy consumption, where the value based on the fixed mode was 6.35 times higher. The distribution of daily AC energy consumption based on the stochastic modeling was highly consistent with the actual situation, thanks to the accurate prediction of the randomness and dynamics of residents' AC usage patterns. The total cooling energy consumption based on two stochastic models was found to be much closer to the actual values. The work proposes a method of embedding stochastic AC usage models to EnergyPlus 22.1 benefits for an improvement in building energy consumption simulation and the energy efficiency evaluation regarding occupant behavior in the future. [ABSTRACT FROM AUTHOR]

We conducted anchoring performance, stress distribution, and full-scale indoor pulling tests on glass-fiber-reinforced polymer (GFRP) bolts. The tests were conducted using finite element software while considering the multi-interface contact and BK criterion by using the cohesive element to simulate the contact relations between the anchor rod body and concrete and building an axial symmetry calculation model of the GRFP bolt and concrete. The results indicated that the finite element model based on cohesive element accurately represents the load–displacement relationship of the GFRP bolt and the distribution law of axial stress along the anchoring length. In addition, the simulation outcomes of the load–displacement relationship were in good agreement with the measured test values. Under the same load, the axial-force-transferred depth of the bolt body was identical regardless of the anchorage length. As anchoring length increases, the pull load on the bolt and the decay rate of axial stress along the anchoring length rises gradually. There is a critical value for the anchorage length of the bolt. [ABSTRACT FROM AUTHOR]

A new type of composite anion-exchange membrane is fabricated using benzoxazine (Bz) monomer and polytetrafluoroethylene (PTFE) via a green and facile method. Membrane fabrication is achieved via in situ ring-opening polymerization of Bz within the PTFE matrix, followed by quaternization and ion-exchange reactions. The quaternized PBz works as a self-cross-linked and anion conductive polymer. The synthesized membranes show improved conductivity (26 to 70 mS/cm) at a reasonable water uptake and a low swelling ratio; they also show improved alkaline stability for 150 h at 60 °C in 1 M KOH solution, the decrease in conductivity being only ca. 10%. Our method of AEM fabrication is advantageous over conventional ones due to facile process and the avoidance of chloro- or bromomethylation as well as the self-cross-linked structure; the resulting membranes show relatively good performance as compared with some of those obtained from conventional techniques. [ABSTRACT FROM AUTHOR]

Geospatial dashboards have attracted increasing attention from both user communities and academic researchers since the late 1990s. Dashboards can gather, visualize, analyze and advise on urban performance to support sustainable development of smart cities. We conducted a critical review of the research and development of geospatial dashboards, including the integration of maps, spatial data analytics, and geographic visualization for decision support and real-time monitoring of smart city performance. The research about this kind of system has mainly focused on indicators, information models including statistical models and geospatial models, and other related issues. This paper presents an overview of dashboard history and key technologies and applications in smart cities, and summarizes major research progress and representative developments by analyzing their key technical issues. Based on the review, we discuss the visualization model and validity of models for decision support and real-time monitoring that need to be further researched, and recommend some future research directions. [ABSTRACT FROM AUTHOR]