Snapshot: The Home Energy Rebate Program

Alaska’s state government has spent an estimated $110 million since 2008 for better insulation, new furnaces, and other retrofits for roughly 16,500 homeowners—10% of all homeowners statewide.1 That spending was under the Home Energy Rebate Program, which rebates homeowners part of what they spend to make their houses more energy-efficient and less expensive to heat.2 The state legislature established the current program in 2008, as energy prices were spiking. The Alaska Housing Finance Corporation (AHFC) administers it, and the Institute of Social and Economic Research and the Cold Climate Housing Research Center did this analysis for AHFC, assessing the broad program effects from April 2008 through September 2011. Changes in fuel use and heating costs reported here are estimates from AHFC’s energy-rating software; figures based on actual household heating bills aren’t currently available. The software uses house characteristics and location-specific information on weather and other factors to produce the estimates—but remember they are estimates.3Cold Climate Housing Research Cente

High performance interior point methods for three-dimensional finite element limit analysis

The ability to obtain rigorous upper and lower bounds on collapse loads of various structures makes finite element limit analysis an attractive design tool. The increasingly high cost of computing those bounds, however, has limited its application on problems in three dimensions. This work reports on a high-performance homogeneous self-dual primal-dual interior point method developed for three-dimensional finite element limit analysis. This implementation achieves convergence times over 4.5× faster than the leading commercial solver across a set of three-dimensional finite element limit analysis test problems, making investigation of three dimensional limit loads viable. A comparison between a range of iterative linear solvers and direct methods used to determine the search direction is also provided, demonstrating the superiority of direct methods for this application. The components of the interior point solver considered include the elimination of and options for handling remaining free variables, multifrontal and supernodal Cholesky comparison for computing the search direction, differences between approximate minimum degree [1] and nested dissection [13] orderings, dealing with dense columns and fixed variables, and accelerating the linear system solver through parallelization. Each of these areas resulted in an improvement on at least one of the problems in the test set, with many achieving gains across the whole set. The serial implementation achieved runtime performance 1.7× faster than the commercial solver Mosek [5]. Compared with the parallel version of Mosek, the use of parallel BLAS routines in the supernodal solver saw a 1.9× speedup, and with a modified version of the GPU-enabled CHOLMOD [11] and a single NVIDIA Tesla K20c this speedup increased to 4.65×

Polymer Shell Structure

The initial intention of my independent studio was to study how digital design can improve the overall construction process. By understanding the real world constraints and solving structural and material connections, the digital design process will ideally reduce the overall time a project is in construction and solve problems before they occur