To improve the flame retardancy of Polymethacrylimide (PMI) foam, in this study, a series of flame-retardant PMI foams were prepared by grafting with flame retardant amino-terminated phosphorous polyborosiloxane (N-PBSi), using tert-butanol (TBA) as the foaming agent. The structure, mechanical properties, thermal behavior, and flame retardancy of the resultant PMI foams were characterized. These as-prepared foams tended to be more compact in structure as N-PBSi content increased. The tensile, compressive, and bending strength of these PMI foams therefore was greatly enhanced, which were about 2 times, 9 times, and 3 times that of pure PMI foam, respectively. Besides, the introduction of N-PBSi also attributed to PMI foams better performance in char forming, especially in the air, which is beneficial for obtaining better retardancy against flame. Their advantages in flame retardancy and smoke inhabitation were confirmed by limiting oxygen index (LOI) and cone calorimeter tests (CCT). The total heat release (THR) and the peak of smoke generation rate (pSPR) of PMI/N-PBSi-20 were reduced by 23.1 % and 69.9 %, respectively. The N-PBSi incorporated were thought to not only generate phosphorus-containing fragments to capture free radicals in gas phase, but also rearrange in the solid phase to form a denser carbon layer to provide a better barrier between external heat and internal flammable pyrolysis gases. Given these, it can be envisaged that the flame-retardant PMI foams modified by N-PBSi may be more attractive in a wider range of applications.

As a part of Smart City, modeling the road network for indoor route planning has become a research hotspot in recent years. This paper presents an automatic extraction method of modeling for indoor route planning. At the very beginning, an optimized Constrained Delaunay Triangulation (CDT) was used to form indoor spatial routes, on the ArcGIS, ArcEngine and Microsoft Visual Studio 2012 (VS 2012) platforms. The optimization of CDT was achieved by increasing the constraint points at the edge of the region, resulting in a more refined division of the region. After the spatial routes connect with connection points, the indoor route planning model of the road network then was formed, implemented the Dijkstra algorithm to get the planned route. Finally, to further evaluate the optimized CDT. The CDT before and after optimization is used to automatically generate the road network model of a plane floor of the building, to provide an intuitive comparison. The results proved the effectiveness of the optimization method.