1,727,254 research outputs found
Yujia Huang: Lecturer in Design Enterprise
No full textThis article is to introduce the author and her work on design for retailing innovation
Yujia Huang: Lecturer in Design Enterprise
No full textThis article is to introduce the author and her work on design for retailing innovation
Optimizing green space locations to reduce daytime and nighttime urban heat island effects in Phoenix, Arizona
No full textabstract: The urban heat island effect is especially significant in semi-arid climates, generating a myriad of problems for large urban areas. Green space can mitigate warming, providing cooling benefits important to reducing energy consumption and improving human health. The arrangement of green space to reap the full potential of cooling benefits is a challenge, especially considering the diurnal variations of urban heat island effects. Surprisingly, methods that support the strategic placement of green space in the context of urban heat island are lacking. Integrating geographic information systems, remote sensing, spatial statistics and spatial optimization, we developed a framework to identify the best locations and configuration of new green space with respect to cooling benefits. The developed multi-objective model is applied to evaluate the diurnal cooling trade-offs in Phoenix, Arizona. As a result of optimal green space placement, significant cooling potentials can be achieved. A reduction of land surface temperature of approximately 1–2 °C locally and 0.5 °C regionally can be achieved by the addition of new green space. 96% of potential day and night cooling benefits can be achieved through simultaneous consideration. The results also demonstrate that clustered green space enhances local cooling because of the agglomeration effect; whereas, dispersed patterns lead to greater overall regional cooling. The optimization based framework can effectively inform planning decisions with regard to green space allocation to best ameliorate excessive heat.Corresponding Author:
Yujia Zhang
Arizona State University
[email protected]
Weibo COVID dataset
No full textSina Weibo (新浪微博), commonly referred to as "Chinese Twitter", is a micro-blogging site. This Weibo dataset was used in Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements. The data was crawled on the Weibo platform from December 7, 2019, to April 4, 2020.
The data is crawled in two phases, covering a total of 4,047,389 Weibo posts. The first crawler ran on February 26, 2020, and collected 3.3 million Weibo posts from January 18, 2020, to February 26, 2020. The second crawler ran on April 4, crawling from December 7, 2020, to April 4, 2020, to complement the original dataset
A CFD study of the behavior of a crew transfer vessel in head seas using OpenFOAM
Full text linkCrew transfer vessels (CTV) were a fast means of transportation, providing inspection and maintenance services by transferring technicians from shore to offshore structures. These vessels had been designed to be efficient and effective at high speeds, though this means the ship motions were highly sensitive to the sea conditions. Accordingly, it was critical to be able to estimate a ship’s response among different wave conditions in the time domain. In this study, a Computational Fluid Dynamics (CFD) method was used for the analysis of Fluid-Structure interactions with a crew transfer vessel as a case study. The CFD codes were formulated to solve the unsteady Reynolds-Averaged Navier–Stokes equations using the finite-volume method with OpenFOAM, an open-source CFD software program. OpenFOAM offered high accuracy of ship motion predictions and high resolution of infield flow phenomena, taking into consideration both viscous and rotational effects in the flow and free surface waves. A comprehensive uncertainty analysis was presented, including verification and validation studies. The cases performed demonstrate that the results were found to be in good agreement with the available experimental results and showed the importance of a seakeeping analysis for such vessels
A fluid-structure interaction model on the hydroelastic analysis of a container ship using PRECICE
Full text linkCommercial vessels have recently shown a common trend in increasing their sizes to meet the growing demand for transportation and operations. This trend may however result in more flexible or 'softer' hulls. The flexible hull structure reduces the ship natural frequency close to the wave encounter frequency, increasing the probability of resonance or high-frequency vibrations. Meanwhile, the resulting structural deformations from flexible hull could significantly affect the flow field and the hydrodynamic loads cannot be estimated accurately. Hence, it is important to treat a flexible hull and its surrounding flow field as an interacting system to predict a ship's dynamic behaviour based on the hydroelastic theory. In this study, a novel fluid-structure interactions coupling scheme using the "preCICE" library to communicate with the fluid solver "OpenFOAM" and structure solver "calculiX" was first proposed to study the hydroelastic behavior of a container ship with a forward speed in regular waves. With the advantage of this numerical model, the flexible behaviour of this ship, such as its vertical bending displacement and corresponding bending moment can be quantified, and the "springing" and "whipping" responses can be calculated. It is believed that the present FSI model will exhibit more advantages over the traditional rigid-body methods currently used in the ship seakeeping field
A fluid-structure interaction model on the hydroelastic analysis of a container ship using precice
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