According to the European Union, buildings account for 40% of overall energy use and 36% of ${\mathrm{CO}}_2$ emissions, with existing energy-inefficient buildings the main source of losses. Efforts to enhance the thermal comfortability of users in buildings can result in overheating if not appropriately designed, which in turn could lead to health issues as well as continual emission of greenhouse gases. To provide further insights into this dilemma and contribute to improving energy-efficient building designs, we undertake a new modeling technique encompassing a complete analysis of the existing building 3D model as well as solar radiation behavior on buildings. The technique involves 3D building information modeling (3D BIM) that is reconstructed using computer-aided design (CAD). Ladybug and Honeybee plugins for Grasshopper for Rhino are then used to evaluate environmental and building performance using the energy plus weather (EPW) file of Wuhan city, China, as a case study. An assessment of ‘with’ and ‘without’ built architectural surroundings contexts is also carried out in relation to summer and winter solstices. An overall change of approximately 29.56% is observed between ‘with’ and ‘without’ surrounding contexts, which suggests that both have a significant influence on the solar potential of individual buildings. Investigation of internal and external thermal energy consumption behaviors in relation to building comfort lead us to suggest an optimized smart solution which is validated using our case study site in Wuhan. Our findings suggest that the building energy lifespan can be increased while reducing environmental consequences if an estimated 50% of monthly energy savings are made. The findings of this study provide useful insights for decision-makers, engineers, and designers of energy-efficient buildings.

The subduction zone along the northern Tonga Trench has the highest plate convergence rate in the world, but limited records of its seismic and tsunamigenic activities. In 2009, a tsunami generated by an M_W 8.1 earthquake doublet caused severe impacts in the region including damage and loss of life on the south shores of Upolu and Savaii Islands, Samoa. Here, we use numerical modeling aided by recorded data and eyewitness accounts to evaluate and identify the published source models in the Tonga Trench region that most suitably represent the 2009 event for use in hazard assessment around Samoa. We show that only a few of the published sources are suitable to reproduce the large inundation observed in Samoa, and none reproduces runup as high as observed in the areas that were most severely impacted on the southeast Upolu coast. The distribution and intensity of runup and inundation are dependent on source model, local topographic and bathymetric features, regional coastal geomorphology, and trapping of short‐period waves over the reef flats. The computed results are also influenced by model approximation and grid resolution especially for areas with extreme runup records. Comparison of the relative contributions from the doublet to the southeast Upolu inundation indicates that the initial intraplate normal faulting dominated the east‐northeastward tsunami propagation and inundation compared with the subsequent interplate thrust faulting. Overall, two key source models are discussed and identified for future refinement.

Rapid and profound changes in the technology used for data acquisition, computing and information management provides a framework that has the potential to allow communities to consider acquiring, analyzing and managing data in new ways. Improving the collection and management of data, immediately in post-disaster reconnaissance and in long-term impact assessments, is central to enabling knowledge of such events to be used and applied to improving community resilience to those disasters. This paper presents the development and applications of an integrated and extensible framework for the capture of attribute data that describes pre-disaster physical characteristics and post-disaster damage of assets within our communities. The framework, referred to as Real-time Individual Asset Attribute Collection Tool (RiACT) and its associated Asset Repository Web Portal, enables data capture by direct field observations of asset attributes. It also includes the real-time transfer of these field observations to the web portal and/or the download of previously acquired history and metadata of any specific asset of interest to the observer whilst they are in the field. The use of this framework enables improved understanding of asset portfolios within the context of risk reduction and readiness, as well as facilitating efficient and rapid capture of damage distribution across the affected region. This in turn supports better decision making for a quicker disaster response and recovery. This paper presents a review of the existing state-of-art data collection methodologies and describe the development of an improved tool and its Information Technology architecture. Experiences and challenges in applying the framework are highlighted through: (1) the capture of community data in Viet Nam for a multi-hazard assessment in 2014 and 2018, the refinement of asset data related to residential buildings in the Greater Wellington region in 2016, and a survey of building types in Tanna, Vanuatu in 2018; (2) facilitating training in field data capture processes in Indonesia in 2015, as well as in Samoa and Vanuatu in 2017; (3) collection of asset damage data following the 2016 Kaikoura earthquake in New Zealand, the 2016 Tropical Cyclone Winston in Fiji and the 2015 Illapel earthquake and tsunami in Chile.