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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LLNL’s novel approach utilizes a number of techniques to improve reconstruction accuracy:
- Better coding scheme-based techniques
- Hardware-assisted techniques
- Adaptive fringe projection techniques
- Multi-exposure based techniques
The method requires specific calibration procedures and control of the hardware, which is achieved through a digital twin…
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Versatile Cold Spray (VCS) enables deposition of brittle materials, such as thermoelectrics, magnets, and insulators, while retaining their functional properties. Materials can be deposited on substrates or arbitrary shapes with no requirement to match compositions. The VCS system is low cost, easily portable, and easy to use.
VCS has been developed in a collaboration between Lawrence Livermore…
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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…