Testing a model for the well-posedness of the Cauchy-characteristic problem in Bondi coordinates

Gravity waves reveal colliding black holes, galaxies, the birth of a black hole in a supernova and the growth pains of our universe. Gravitational waves are unambiguous measured only at future null infinity

A New Algorithm for the Numerical Computation of Gravitational Waves

With gravitational waves, Gravitational Wave Astronomy can “see” colliding back holes and galaxies, the birth of a black hole in a supernova, the growth pains of our universe and the structure of spacetime

Well-posedness of Characteristic Evolution in Bondi Coordinates

Gravitational waves carry information about their source, and their detection will uncover facets of our universe, otherwise invisible. Recently, we made publicly available a waveform computation tool, the PITT code, as part of the Einstein Toolkit open software for relativistic astrophysics. The code implements the “characteristic method,” which computes the gravitational waves infinitely far from their source in terms of compactified light cones. We proved that our code produces waveforms that satisfy the demands of next generation detectors. However, the main problem is that the well-posedness of the Einstein equations in characteristic formulation is not proven. Here we present our progress towards developing and testing a new computational evolution algorithm based on the well-posedness of the characteristic evolution. We analyze the well-posedness of the problem for quasi-linear scalar waves propagating on an asymptotically flat curved space background with source, in null Bondi-Sachs coordinates. We design a new numerical boundary and evolution algorithm, and proved that is stable both numerically and analytically. We built and run numerical tests to confirm the well-posedness and stability properties of the new algorithm. The knowledge gained from the model problems considered here should be of benefit to a better understanding of the gravitational case. A new characteristic code based upon well-posedness would be of great value

Heating Methods and Detection Limits for Infrared Thermography Inspection of Fiber-Reinforced Polymer Composites

The use of fiber-reinforced polymer (FRP) composites to strengthen existing civil infrastructure is expanding rapidly. Many FRP systems used to strengthen reinforced concrete are applied using a wet lay-up method in which dry fibers are saturated on site and then applied to the surface. This research investigated using infrared thermography (IRT) as a nondestructive evaluation (NDE) tool for detecting air voids and epoxy-filled holes in FRP systems bonded to a concrete substrate. Four small-scale specimens with FRP thicknesses ranging from 1 to 4 mm (0.04 to 0.16 in.) containing fabricated defects were constructed and inspected in a laboratory setting. Three heating methods (flash, scan, and long pulse) were employed and a quantitative analysis of resulting IRT data was used to establish detection limits for each method. Scan heating was shown to be most effective for basic defect detection. Air-filled defects at the FRP/concrete interface as small as 2.9 cm2 (0.45 in.2) were detected in a 4 mm (0.16 in.) thick FRP system. Defects as small as 0.3 cm2 (0.05 in.2) were detected in a 1 mm (0.04 in.) thick FRP system

A Hyperbolic Solver for Black Hole Initial Data in Numerical Relativity

Initial data in numerical relativity. The constraints are formulated as elliptic equations, parabolic equations and strongly hyperbolic equations. This presentation is about a different approach to initial data for black holes, the strongly hyperbolic method

Assessing aspen using remote sensing

Large areas of aspen (Populus tremuloides) have disappeared and continue to disappear from western forests due to successional decline and sudden aspen decline (SAD). This loss of aspen ecosystems negatively impacts watersheds, wildlife, plants, and recreation. Much can still be done to restore aspen if timely and appropriate action is taken. However, land managers often lack fundamental information on the location, quantity, and status of aspen stands. This information is needed to plan, implement, and defend aspen restoration activities, but it is often difficult and costly to obtain. Advances in remote sensing technologies can provide cost-effective ways to obtain spatial and quantitative information about aspen to support restoration activities at multiple scales. With sponsorship from the U.S. Department of Agriculture Forest Service Remote Sensing Steering Committee, the Forest Service Remote Sensing Applications Center conducted three pilot studies to develop remote sensing methods for obtaining key information about aspen. Efforts were focused primarily on developing a method to create a stratified probability map of aspen cover from Landsat Thematic Mapper (TM) satellite imagery for a study area located in the Custer National Forest. Photo-interpreted samples of the strata yielded estimates of the aspen cover present in each stratum. This product can greatly increase the efficiency of planning restoration activities and collecting associated field data. Pilot studies were also conducted to develop remote sensing methods to map SAD across large areas and map small, isolated aspen patches for restoration planning