Development of Low-Noise Smart Sensors for Small Explosion Monitoring

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-07ER84740
Agency Tracking Number: 82185
Amount: $99,999.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2007
Solicitation Topic Code: 43
Solicitation Number: DE-PS02-06ER06-30
Small Business Information
Rocky Mountain Geophysics, Llc
167 Piedra Loop, Los Alamos, NM, 87544
DUNS: 190172713
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Steven Taylor
 Dr
 (505) 412-2841
 srt-rmg@comcast.net
Business Contact
 Pamela Naugle
Title: Ms
Phone: (505) 412-2893
Email: pln-rmg@comcast.net
Research Institution
N/A
Abstract
In the absence of full-scale nuclear tests, a nuclear weapons state typically performs sub-critical nuclear explosions in order to study aging properties of nuclear components as part of a stockpile stewardship program. However, nascent nuclear states may be interested in weaponizing their first generation bombs by miniaturizing components so that they can be fitted onto a missile delivery system. It is therefore important for the United States to have the capability to monitor foreign sites in which these sub-critical experiments may be occurring. In the absence of bilateral or multilateral sub-critical explosion transparency agreements, it becomes important to develop an unobtrusive stand-alone Deployable Small Explosion Monitoring System (DSEMS) system that can be clandestinely deployed near suspected experimental sites. This project will develop a Low-Noise Smart Sensor (LNSS) that would be part of a DSEMS for remotely monitoring sub-critical nuclear explosions. In Phase I, data from sub-critical explosions conducted at the U1a underground facility at the Nevada Test Site will be assembled and analyzed in order to determine the operational characteristics of a low noise smart sensor that would be part of a DSEMS. Additionally, a ground truth noise experiment will be conducted at U1a in order to identify man-made and ambient noise sources that must be differentiated from sub-critical explosions. Through analysis of this U1a signal and noise data, simple and robust signal identification algorithms will be developed for implementation on a small microprocessor. In Phase II, the small microprocessor will be packaged with a low-noise Microelectromechanical System (MEMS) accelerometer, in order to develop an LNSS. Commercial Applications and other Benefits as described by the awardee: In addition to the application for nuclear explosion monitoring, LNSS systems also should have commercial applications to facility monitoring, perimeter monitoring, and border security.

* information listed above is at the time of submission.

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