Occupant behavior in buildings might result into gap between predicted and actual energy use and cause indoor thermal comfort fluctuations, due to its uncertainty and unpredictability. Previous studies mainly focus on the investigations of occupant behavior impact and modeling methods, whereas few concludes strategic solutions. It is hard to narrow the negative impact of occupant behavior without a clear Impact-Modeling-Solution clue. Thus, the major objective of this research is to review and analyze the impact of occupant behavior and then to summarize modeling methods and strategic solutions by connecting specific techniques and approaches. This paper first investigates the characteristics of occupant behavior and then discusses the impact. It indicates that thermal comfort (environmental condition) triggers occupant actions with corresponding building systems, resulting in energy load changes. The occupant behavior in turn causes thermal comfort fluctuations. The strategic approaches of traditional methods such as surveys, experiments/tests and simulations, and artificial intelligence (AI)-based techniques are analyzed respectively. It is found that the intelligent approach shows high robustness in addressing the uncertain and unpredictable characteristics of occupant behavior in buildings, compared with traditional methods. The AI-based methods and data-driven approaches can enhance the prediction of building energy consumption and the recognition of occupant's thermal comfort. Typical modeling methods and flowchart for occupant behavior are presented with comparisons. The novel physics-based and data-driven model which performs strong adaptability, high decision-making efficiency and fast response of the controller is especially introduced. The corresponding improvements and future directions are also proposed to reach optimal effects. 

Occupant behavior impact in buildings and the artificial intelligence-based techniques and data-driven approach solutions

State of the art review on the HVAC occupant-centric control in different commercial buildings

Numerical investigation of effects of artificial excavation pit on transformation and runup processes of tsunami-like wave over fringing reef

Occupant behavior (OB) contributes significantly to uncertainties in the results of building performance simulation (BPS). However, a consensus regarding the appropriate level of detail (LoD) for OB modeling in BPS is yet to be reached. Hence, this study focuses on district cooling simulation applications. A systematic technical framework for determining the most appropriate LoD for modeling occupant air-conditioning (AC) use behavior is proposed herein. The framework includes three steps: defining applications and the key performance indicators (KPIs), defining comparable LoDs for AC use behavior modeling, and selecting LoDs based on KPI analysis. Appropriate LoDs for different applications are concluded. For the application related to total cooling demand evaluation, LoD O-1, representing average occupant with stochastic models, is recommended. For the design (sizing) of cooling equipment, LoD O-2, considering the diversity behaviors of occupants, is recommended. For the design of district thermal energy storage (TES) system, LoD O-2 is appropriate. For electricity pricing strategy-making, the most detailed LoD O-3 is recommended. The proposed analytics framework of modelling different LoDs of AC behavior can inspire researchers and modelers on understanding and determination of OB modeling LoDs for various future projects. 

Application-driven level-of-detail modeling framework for occupant air-conditioning behavior in district cooling

Recognition of typical environmental control behavior patterns of indoor occupants based on temporal series association analysis

Study of “time-lag” of occupant behavior occurrences for establishing an occupant-centric building control system

The low-lying reef islands distributed in the tropical and subtropical coastal regions are highly vulnerable to the devastating damages of surges and waves during the severe weather events. Over the past two decades, extreme waves have caused tremendous loss and damages to the tropical and subtropical coastal regions. Previous research has focused on the wave hydrodynamics of tsunami waves, as well as regular and irregular waves on the fringing reefs. The complex wave hydrodynamics of extreme waves on the fringing reefs are rarely studied. By applying the nonhydrostatic numerical flow solver (NHWAVE), transformation and breaking process of the crest- and trough-focused wave groups on the fringing reef are analyzed in this study. Influences of the major factors, i.e., water depth, significant wave height, peak wave period, forereef slope and backreef slope, and ridge width, are discussed in detail. The results show that there are complex interactions between the fringing reef and the focused wave group. Breaking waves of high intensity can form at the reef crest. Meanwhile, due to the wave breakings at the reef crest and bottom friction of the reef flat, the local wave height can be effectively reduced. Within the complex wave hydrodynamics of focused waves on the fringing reef, most of the wave energy can be dissipated. In addition, hydrodynamic difference between the crest- and trough-focused waves on the fringing reef is very limited. The research results of this study will further help researchers to better understand the wave hydrodynamics of extreme waves over the fringing reefs.

/pdf/numerical-investigation-on-hydrodynamic-processes-of-extreme-3bk305m3.pdf

Numerical Investigation on Hydrodynamic Processes of Extreme Wave Groups on Fringing Reef

Effects of drying–rewetting on soil CO2 emissions and the regulatory factors involved: a meta-analysis

During severe weather, the runup of the devasting surges and waves can cause extensive damages to the coastal facilities and results in significant loss of life. Therefore, it becomes necessary to find reliable measures to reduce the wave runup in coastal regions. As a natural barrier to the shorelines, coastal vegetation has great potential to attenuate wave runup and to prevent the coastal communities from extreme floodings and huge land loss. This study numerically discusses the influences of the emergent vegetation patch on the runup processes of extreme wave groups by applying a nonhydrostatic flow solver. Influences of the major factors, i.e., water depth, peak wave period, significant wave height, and density and length of the vegetation patch, are analyzed in detail. Research findings indicate that the presence of the emergent vegetation patch can substantially dissipate most of the incident wave energy and effectively reduce the maximum wave runup heights of extreme wave groups at the sloped beach. It is hoped that the research results of this study will be helpful to the design of coastal soft protection measures.

/pdf/numerical-analysis-on-influences-of-emergent-vegetation-3c8cweod.pdf

Numerical Analysis on Influences of Emergent Vegetation Patch on Runup Processes of Focused Wave Groups

Extreme rainfall and drought events attributed to climate change are anticipated to occur in the current century, resulting in frequent drying and rewetting cycles (DWCs) in soils, which will, in turn, influence soil properties and microorganisms. Sample plots of Sophora japonica, Pinus tabulaeformis, and Ginkgo biloba were selected, and undisturbed soil columns were collected. CK was the constant drying treatment; the precipitation intensities of R80, R40, and R20 were 80 mm, 40 mm, and 20 mm, respectively, and the total precipitation for the four treatments was 160 mm. Significant differences were observed in the cumulative CO2 emissions among the various DWC frequencies for the same woodland soils. A significant correlation was observed between the Birch effect and the DWC frequencies of the three woodland soils. A Pearson’s correlation analysis revealed that background nutrient contents were the key factors influencing alpha diversity. In conclusion, DWCs generally increased CO2 fluxes, cumulative CO2 emissions, and the Birch effect in addition to decreasing the alpha diversity of soil microorganisms when compared to those in the constant drying treatment.

/pdf/effects-of-drying-and-rewetting-cycles-on-carbon-dioxide-2jvauyf7.pdf

Effects of Drying and Rewetting Cycles on Carbon Dioxide Emissions and Soil Microbial Communities

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