ASU Scholarship Showcase

In-process laser heating technique delivers a cost-efficient way to improve mechanical and geometrical properties to nearly isotropic and extremely smooth, respectively. The technique involves the incorperation of a solid-state laser into a commercial off-the-shelf 3D printer, mechanical system to allow controllable laser allumination on desired surfaces, and a gcode postprocesser to proper control of the mechanical system. This process uses laser for local heating, to enhance mass transfer between boundaries or to enhance surface reflow to smooth surface irregularity, to improve mechanical and geometrical properties. Only less than 3 W of laser power (CO2 laser) was used for high temperature material like PEEK and Ultem; less than 1 W (808nm laser) was found to be sufficient for achieving optimal properties for PLA. This technique has the potential for after-market integration into most commercial FFF 3D printers to achieved nearly isotropic and smooth 3D printed objects with various thermoplastic polymers.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.