Innovative spatial timber structures: workshops with physical modeling explorations from small to full scale

Architects and Engineers are educated and work within two separate cultures yet they are both concerned with conceptual structural design. The collaboration between the professions is especially important when designing buildings where the structure to a great degree forms the spaces, as in the cases of form generating structures such as gridshells, reciprocal frames, space trusses etc . This paper describes several specialist research based workshops developed at KA over the last two years that use physical modelling of 1:1 innovative timber load-bearing structures such as gridshells and reciprocal frames

Supernova Blastwaves in Low-density Hot Media: a Mechanism for Spatially Distributed Heating

Most supernovae are expected to explode in low-density hot media, particularly in galactic bulges and elliptical galaxies. The remnants of such supernovae, though difficult to detect individually, can be profoundly important in heating the media on large scales. We characterize the evolution of this kind of supernova remnants, based on analytical approximations and hydrodynamic simulations. We generalize the standard Sedov solution to account for both temperature and density effects of the ambient media. Although cooling can be neglected, the expansion of such a remnant deviates quickly from the standard Sedov solution and asymptotically approaches the ambient sound speed as the swept-up thermal energy becomes important. The relatively steady and fast expansion of the remnants over large volumes provides an ideal mechanism for spatially distributed heating, which may help to alleviate the over-cooling problem of hot gas in groups and clusters of galaxies as well as in galaxies themselves. The simulations were performed with the FLASH code.Comment: 12 pages, 3 figures, 1 table, accepted for ApJ, uses aaste

Universally Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs

In this work we show that, using the eigen-decomposition of the adjacency matrix, we can consistently estimate latent positions for random dot product graphs provided the latent positions are i.i.d. from some distribution. If class labels are observed for a number of vertices tending to infinity, then we show that the remaining vertices can be classified with error converging to Bayes optimal using the $k$-nearest-neighbors classification rule. We evaluate the proposed methods on simulated data and a graph derived from Wikipedia

Scalability of Hydrodynamic Simulations

Many hydrodynamic processes can be studied in a way that is scalable over a vastly relevant physical parameter space. We systematically examine this scalability, which has so far only briefly discussed in astrophysical literature. We show how the scalability is limited by various constraints imposed by physical processes and initial conditions. Using supernova remnants in different environments and evolutionary phases as application examples, we demonstrate the use of the scaling as a powerful tool to explore the interdependence among relevant parameters, based on a minimum set of simulations. In particular, we devise a scaling scheme that can be used to adaptively generate numerous seed remnants and plant them into 3D hydrodynamic simulations of the supernova-dominated interstellar medium.Comment: 12 pages, 1 figure, submitted to MNRAS; comments are welcom