The authors examine the problem of how to provide a time code for staff to use in pursuit of innovation. Four potential options are explored ranging from not providing funds for this activity, to charging such efforts against existing or expanded program management and program development funds. One solution that provides funded time without raising laboratory overhead rates is identified and referred to as Innovation Flex Time. This would consist of capturing hours worked in excess of the standard work week but not charged to customers and making those hours available to fund time for exploring new ideas. A brief examination of labor relations laws, and laws regulating laboratory directed research and development suggests that Innovation Flex Time is a viable option for the laboratory. However, implementation of Innovation Flex Time would require NNSA approval and modification of the existing management and operations contract.
A common problem in developing high-reliability systems is estimating the reliability for a population of components that cannot be 100% tested. The radiation survivability of a population of components is often estimated by testing a very small sample to some multiple of the required specification level, known as an overtest. Given a successful test with a sufficient overtest margin, the population of components is assumed to have the required survivability or radiation reliability. However, no mathematical justification for such claims has been crafted without making aggressive assumptions regarding the statistics of the unknown distribution. Here we illustrate a new approach that leverages geometric bounding arguments founded on relatively modest distribution assumptions to produce conservative estimates of component reliability.
Modern space based optical sensors place substantial demands on the focal plane array readout integrated circuit. Active pixel readout designs offer direct access to individual pixel data but require analog to digital conversion at or near each pixel. Thus, circuit designers must create precise, fundamentally analog circuitry within tightly constrained areas on the integrated circuit. Rapidly changing phenomena necessitate tradeoffs between sampling and conversion speed, data precision, and heat generation adjacent the detector array, especially of concern for thermally sensitive space grade infrared detectors. A simplified parametric model is presented that illustrates seeker system performance and analog to digital conversion requirements trends in the visible through mid-wave infrared, for varying sample rate. Notional limiting-case Earth optical backgrounds were generated using MODTRAN4 with a range of cloud extremes and approximate practical albedo limits for typical surface features from a composite of the Mosart and Aster spectral albedo databases. The dynamic range requirements imposed by these background spectra are discussed in the context of optical band selection and readout design impacts.
The National Ecological Observatory Network (NEON) is an ambitious National Science Foundation sponsored project intended to accumulate and disseminate ecologically informative sensor data from sites among 20 distinct biomes found within the United States and Puerto Rico over a period of at least 30 years. These data are expected to provide valuable insights into the ecological impacts of climate change, land-use change, and invasive species in these various biomes, and thereby provide a scientific foundation for the decisions of future national, regional, and local policy makers. NEON's objectives are of substantial national and international importance, yet they must be achieved with limited resources. Sandia National Laboratories was therefore contracted to examine four areas of significant systems engineering concern; specifically, alternatives to commercial electrical utility power for remote operations, approaches to data acquisition and local data handling, protocols for secure long-distance data transmission, and processes and procedures for the introduction of new instruments and continuous improvement of the sensor network. The results of these preliminary systems engineering evaluations are presented, with a series of recommendations intended to optimize the efficiency and probability of long-term success for the NEON enterprise.