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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The approach is to use peroxides to modify the reaction kinetics in the production of polysiloxanes. A radical initiator in the presence of a hydride-terminated polysiloxane will increase the rate of curing and reduce manufacturing costs. At a minimum a formulation would contain a hydride-terminated polysiloxane, a platinum catalyst, and an initiator that generates radicals. The content of…
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…
Simrev is a python library imported into a user-generated program. As the program grows in capability and complexity, the engineered product matures. The "software twin" handles all changes to product configuration and is the portal to running supercomputing analysis and managing workflow for engineering simulation codes. Assemblies become program modules; parts, materials, boundary conditions…
Dubbed the "LLNL Chemical Prism", the LLNL system has use wherever there is a need to separate components of a fluid. A few examples include:
- Chemical detection for known and previously unknown chemicals or substances
- Separation of biomolecules from a cellular extract
- Fractionation of a complex mixture of hydrocarbons
- Forensic analysis of…