Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate (217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (128)
- User Facilities (27)
Researcher
- Andrzej Nycz
- Chris Masuo
- Peter Wang
- Alex Walters
- Brian Gibson
- Joshua Vaughan
- Luke Meyer
- Udaya C Kalluri
- William Carter
- Adam Siekmann
- Akash Jag Prasad
- Amit Shyam
- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Dave Willis
- Gordon Robertson
- Hong Wang
- Hyeonsup Lim
- J.R. R Matheson
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- John Potter
- Luke Chapman
- Riley Wallace
- Ritin Mathews
- Sydney Murray III
- Vasilis Tzoganis
- Vasiliy Morozov
- Vincent Paquit
- Vivek Sujan
- Vladimir Orlyanchik
- Xiaohan Yang
- Yun Liu

We presented a novel apparatus and method for laser beam position detection and pointing stabilization using analog position-sensitive diodes (PSDs).

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Creating a framework (method) for bots (agents) to autonomously, in real time, dynamically divide and execute a complex manufacturing (or any suitable) task in a collaborative, parallel-sequential way without required human interaction.

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

In additive printing that utilizes multiple robotic agents to build, each agent, or “arm”, is currently limited to a prescribed path determined by the user.

This invention discusses the methodology to calibrating a multi-robot system with an arbitrary number of agents to obtain single coordinate frame with high accuracy.