A Comparative Study of Methods for Delineating Sphere of Urban Influence: A Case Study on Central China

A number of urban and regional plans have been developed with the advancement of urbanization and regional integration, among which the delineation of sphere of urban influence and improvement of integration between the city and its hinterland have be- come vital important for guiding practices. In terms of delineating sphere of urban influence, existing studies have been focused on static study by using single year data or single method, resulting in a lack of time-series longitudinal analysis or comprehensive analysis based on multiple methods This study emphasizes on comparing two methods from both the theoretical and empirical perspective. Both gravity model and improwd field model are applied to the selected study area for measurements and comparison, to explore their strengths and weaknesses. A research framework for comprehensive analysis on delineating sphere of urban influence is proposed. In the end, the differences of deli：aeating methods are illustrated and the feasibility of comprehensive analysis is discussed. Recommendations are provided for selecting appropriate methods for delineating sphere of urban influence or developing regional hierarchy system plans and urban spatial structure schemes.

Developing the Commons: Models of Rural Land Trust in China

In recent years,experiments on land trusts(xin tuo)have been made in the rural areas of China.To better understand such practice,this research identifies four case studies based on their operational structures and divides them into government-led models and market-led models.The government-led models include the Yiyang Model in Hunan Province,and the Longgang Model in Hubei Province.The market-led models include the Suzhou Model in Anhui Province,and the Golden Field Series Model in Jiangsu Province.This paper compares their profit-sharing mechanisms with specific attention given to the incentives for the villagers.Findings suggest that the villagers’profits are limited in both models.The government-led models concern less about profits but more on reusing the desolated agricultural land.The market-led models are profit-driven therefore tend to exclude the villagers from the profit-sharing process.

SUSTAINABLE DESIGN IN PROJECT DELIVERY:A DISCUSSION ON CURRENT AND FUTURE TRENDS

Sustainability principles have become an integral part of the design and construc-tion process for many new construction projects. The selection of the project delivery method (PDM) is extremely important in the effective execution of the project, and plays a critical role in establishing communication and coordination between the key entities: owner, architect, and contractor. The goal of this paper is to hopefully serve as a starting point for further discussion to improve on the AEC industry’s current integration of sustainability principles in PDMs. The first step consists of an assessment of current project delivery systems from a sustainable design perspective. This is followed by a determination of the current limitations, and examination of the various disrup-tions in the industry. Various literature sources are analyzed to form a framework to discuss improvements and optimization strategies beyond the current system. Thereafter, proposed solutions are introduced at both stakeholders, as well as PDM scales. In this paper, the focus for the conducted analysis and proposed method-ologies is predicated on new construction projects instead of retrofits due to the resources available. However, the principles can similarly be applied to retro-fit scenarios as well, depending on the specific requirements of the individual project at play.

EMERGING FORMS OF SUSTAINABLE URBANISM: CASE STUDIES OF VAUBAN FREIBURG AND SOLARCITY LINZ

This study is an ongoing interdisciplinary collaboration, which discusses possible emerging forms of sustainable urbanismin the 21st century. The idea of sustainable urbanism is examined in this paper in more than environmental andecological aspects, to highlight the emergent forms of urbanism based on new paradigms that inform on the shape ofcities to come. The two case studies discussed embody complex topics of design, dwelling, community in space, buildingtechnologies, environmental strategies, as well as models of affordability. At the same time, new trajectories in thedevelopment of sustainable urban housing are explored. It is based on the following case studies:Case Study 1: The new city district of Vauban Freiburg, in Germany, describes the guiding principles and theirimplementation in the planning and design of this new major development: Vauban comprises 2,000 homes to house5,000 people, as well as business units to provide about 500 to 600 jobs.Case Study 2: solarCity Linz, in Austria, currently comprises about 1,300 homes and 3,000 inhabitants. It wasdesigned as a fl agship development for renewable energies in urban design and includes projects by architects likeFoster and Partners, Richard Rogers, and Thomas Herzog. Construction time of the nucleus of solarCity took placefrom 1995 to 2005.

The impact of cultural assumptions on simulated energy, comfort, and investment returns of design decisions in two desert climates

In Latin America, default assumptions and borrowed templates and methodologies are often used in energy modeling, resulting in models that might not represent their cultural context and leading to policies awkwardly fit to local practices. Policy-driving low-income housing studies in Mexico, for example, activated both heating and cooling in energy models even though less than 5% of the homes in the country have heating systems. This paper illustrates the importance of modeling local sociocultural habits and practices, and how this can affect design outcomes. Here, we modeled low-income housing representative of typical residences in two desert climates-Hermosillo, Mexico, and Copiapo, Chile-using EnergyPlus. Settings representing local practices in each region were tested against default values, including occupancy settings, regional construction systems, and importantly, HVAC settings related to partial conditioning. Their impacts were measured via variation in energy use, comfort conditions, and the payback period of design upgrades. Results demonstrated how certain assumptions can have a high “design significance”, a term we propose for inputs that completely change optimal design decisions, as well as the importance of considering thermal comfort in such decisions. Including partial conditioning, for example, resulted in at least double the payback period and discomfort degrees for design upgrades in 16 of 24 instances.

CoolVox:Advanced 3D convolutional neural network models for predicting solar radiation on building facades

Data-driven models have become increasingly prominent in the building,architecture,and construction industries.One area ideally suited to exploit this powerful new technology is building performance simulation.Physics-based models have traditionally been used to estimate the energy flow,air movement,and heat balance of buildings.However,physics-based models require many assumptions,significant computational power,and a considerable amount of time to output predictions.Artificial neural networks(ANNs)with prefabricated or simulated data are likely to be a more feasible option for environmental analysis conducted by designers during the early design phase.Because ANNs require fewer inputs and shorter computation times and offer superior performance and potential for data augmentation,they have received increased attention for predicting the surface solar radiation on buildings.Furthermore,ANNs can provide innovative and quick design solutions,enabling designers to receive instantaneous feedback on the effects of a proposed change to a building's design.This research introduces deep learning methods as a means of simulating the annual radiation intensities and exposure level of buildings without the need for physics-based engines.We propose the CoolVox model to demonstrate the feasibility of using 3D convolutional neural networks to predict the surface radiation on building facades.The CoolVox model accurately predicted the radiation intensities of building facades under different boundary conditions and performed better than ARINet(with average mean square errors of 0.01 and 0.036,respectively)in predicting the radiation intensity both with(validation error=0.0165)and without(validation error=0.0066)the presence of boundary buildings.