International audienceThe present paper is the first comprehensive review of the integration of phase change materials in building walls. Many considerations are discussed in this paper including physical considerations about building envelope and phase change material, phase change material integration and thermophysical property measurements and various experimental and numerical studies concerning the integration. Even if the integrated phase change material have a good potential for reducing energy demand, further investigations are needed to really assess their use
International audienceEmerging many-core processors, like CUDA capable nVidia GPUs, are promising platforms for regular parallel algorithms such as the Lattice Boltzmann Method (LBM). Since the global memory for graphic devices shows high latency and LBM is data intensive, the memory access pattern is an important issue for achieving good performances. Whenever possible, global memory loads and stores should be coalescent and aligned, but the propagation phase in LBM can lead to frequent misaligned memory accesses. Most previous CUDA implementations of 3D LBM addressed this problem by using low latency on chip shared memory. Instead of this, our CUDA implementation of LBM follows carefully chosen data transfer schemes in global memory. For the 3D lid-driven cavity test case, we obtained up to 86% of the global memory maximal throughput on nVidia's GT200. We show that as a consequence highly efficient implementations of LBM on GPUs are possible, even for complex models
Graphics Processing Units (GPUs), originally developed for computer games, now provide computational power for scientific applications. In this paper, we develop a general purpose Lattice Boltzmann code that runs entirely on a single GPU. The results show that: (1) simple-precision floating point arithmetic is sufficient for LBM computation in comparison to double-precision; (2) the implementation of LBM on GPUs allows to achieve up to about one billion lattice update per second using single-precision floating point; (3) GPUs provide an inexpensive alternative to large clusters for fluid dynamics prediction.
Many computational approaches exist to estimate heating and cooling energy demand of buildings at city scale, but few existing models can explicitly consider every buildings of an urban area, and even less can address hourly-or less-energy demand. However, both aspects are critical for urban energy supply designers. Therefore, this paper gives an overview of city energy simulation models from the point of view of short energy dynamics, and reviews the related modeling techniques, which generally involve detailed approaches. Analysis highlights computational costs of such simulations as key issue to overcome towards reliable microsimulation of the power demand of urban areas. Relevant physical and mathematical simplifications as well as efficient numerical and computational techniques based on uncertainties analysis and error quantification should thus be implemented.
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