Through the duration of the NNSA Office of Nuclear Nonproliferation Research and Development (NA-22) Miniature Spherical Retroreflectors lifecycle project, our research team focused on developing solutions to the fabrication bottleneck that has inhibited development and deployment of wide-angle optically interrogated chemical and radiological remote sensing technology. Our team advanced the concept of step-index clad retroreflectors to approximate an optimized, but yet unrealized spherical gradient index design. An intensive numerical simulation effort was undertaken that resulted in optimized step-index optical designs for mid-infrared applications. Geometric optics ray trace modeling was performed to better understand the geometrical dependencies of the miniature spherical retroreflector application. We adopted and advanced the concept of optical cross section, a metric that provides relative performance comparisons between different retroreflector designs and our cross-section analysis demonstrated that our step-index design provided 90% of the range capacity of the ideal spherical index design.

This is the annual report for an old project funded by NA22. The purpose of the project was to develop amorphous semiconductors for use as radiation detectors. The annual report contains information about the progress made in synthesizing, characterizing, and radiation response testing of these new materials.

This project investigated layout and compression techniques for large, unstructured simulation data to reduce bandwidth requirements and latency in simulation I/O and subsequent post-processing, e.g. data analysis and visualization. The main goal was to eliminate the data-transfer bottleneck - for example, from disk to memory and from central processing unit to graphics processing unit - through coherent data access and by trading underutilized compute power for effective bandwidth and storage. This was accomplished by (1) designing algorithms that both enforce and exploit compactness and locality in unstructured data, and (2) adapting offline computations to a novel stream processing framework that supports pipelining and low-latency sequential access to compressed data. This report summarizes the techniques developed and results achieved, and includes references to publications that elaborate on the technical details of these methods.