LLNL’s Distributed Implicit Neural Representation (DINR) is a novel approach to 4D time-space reconstruction of dynamic objects. DINR is the first technology to enable 4D imaging of dynamic objects at sufficiently high spatial and temporal resolutions that are necessary for real world medical and industrial applications.
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Rapid monolith development at scale is achieved through use of a functionally equivalent optic simulant made from a low-cost material to substitute the functional optic. Monolith optical performance is affected not only by thermal expansion but also by temperature inhomogeneity due to the temperature dependence of refractive index.
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Aeroptics are a proposed new class of monolithic optical system in aerogel fabricated by molding around a master mandrel. This approach combines the intrinsic stability of proven monolithic telescopes, with the ultralow density of silica aerogels. In Aeroptics, the monolith is hollow with an aerogel substrate providing a supporting structure. Theoretically, Aeroptics could enable 1-m aperture…
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This invention achieves both a wider field of view and faster f-number within a monolithic substrate by incorporating an aspheric convex refractive first surface and a planar aspheric field corrector surface on the final refractive surface. These two refractive surfaces work in conjunction with a concave aspheric primary and convex aspheric secondary mirror (e.g. Cassegrain type) to improve…
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Livermore researchers have developed a method for implementing closed-loop control in extrusion printing processes by means of novel sensing, machine learning, and optimal control algorithms for the optimization of printing parameters and controllability. The system includes a suite of sensors, including cameras, voltage and current meters, scales, etc., that provide in-situ process monitoring…
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The LiDO code combines finite element analysis, design sensitivity analysis and nonlinear programming in a High-Performance Computing (HPC) environment that enables the solution of large-scale structural optimization problems in a computationally efficient manner. Currently, the code uses topology optimization strategies in which a given material is optimally distributed throughout the domain…
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Monolithic Telescopes are a novel implementation of a solid catadioptric design form, instantiated in a monolithic block of fused silica.
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LLNL researchers have developed a system that relies on machine learning to monitor microfluidic devices. The system includes (at least) a microfluidic device, sensor(s), and a local network computer. The system could also include a camera that takes real-time images of channel(s) within an operating microfluidic device. A subset of these images can be used to train/teach a machine learning…
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LLNL is developing the Space-based Telescopes for Actionable Refinement of Ephemeris (STARE). STARE is a constellation of low cost nano-satellites (less than 5Kg) in low-earth orbit dedicated to the observation of space debris in conjunction with a ground-based infrastructure for maintenance, coordination and data processing. Each nano-satellite in the constellation is capable of recording an…