The THOR-ER program team, a collaborative effort between the United States and Norway to develop a solid fuel ramjet (SFRJ) vehicle, achieved an important milestone on August 17 at Andøya in northern Norway. The test vehicle successfully fired several times, showing the viability of ramjet propulsion technology and demonstrating significant increases in effective range. “The…
DSIAC subject matter experts performed a search of the open literature to locate new research pertaining to visible, infrared, and thermal signature management. The search focused on developments since 2018, when a previous summary was provided. Areas covered include manipulation of emissivity; reflectivity; adsorption; refraction and backscatter using multispectral camouflage materials; multilayered, cavity-coupled plasmonic systems; metamaterials; nanoparticles; carbon nanotubes; glass microspheres; nanofibers; electrochromatic fabric; metasurfaces;…
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November 9, 2022 12:00 pm
Improvised explosive devices have complex, intense, and injurious effects on seated occupants of ground vehicles. Testing these effects is important for the development and assessment of innovative safety designs that will improve survivability. However, generating laboratory tests that adequately simulate realistic blast/shock responses is a difficult task. Together, the U.S. Army Research Laboratory and Office…
The 2022 Aircraft Survivability Symposium is a SECRET//NOFORN event; attendees must hold at least a Secret clearance and be U.S. citizens. The goal of this three-day, classified symposium is to foster technical dialogue and exchange of…
DSI’s 2nd Military Vehicles Systems Summit is a Town Hall style forum that will bring together members from across the U.S. military services, Department of Defense, academia, and industry to discuss current efforts and programs…
This three-day course covers all the information required to plan, perform, and interpret the results of all types of dynamic testing. Some of the additional areas covered are fixture design, field data measurement, and interpretation,…
Researcher
Dr. Lasko conducts remote sensing and GIS research with machine learning, focusing on automation of land cover-type mapping using satellite imagery and creating custom ArcGIS Pro toolboxes to enable DoD end-users to leverage automated workflows. His previous work includes radar data fusion for improved mapping under cloudy conditions, wildland fire characterization, and cropland mapping. He has published 20+ peer-reviewed journal articles on a range of remote sensing and environmental science topics. Dr. Lasko completed his Ph.D. on modeling improved agricultural fire emissions, with extensive fieldwork in Vietnam.
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