57 research outputs found
Sensing the gas metal arc welding process
Control of gas metal arc welding (GMAW) requires real-time sensing of the process. Three sensing techniques for GMAW are being developed at the Idaho National Engineering Laboratory (INEL). These are (1) noncontacting ultrasonic sensing using a laser/EMAT (electromagnetic acoustic transducer) to detect defects in the solidified weld on a pass-by-pass basis, (2) integrated optical sensing using a CCD camera and a laser stripe to obtain cooling rate and weld bead geometry information, and (3) monitoring fluctuations in digitized welding voltage data to detect the mode of metal droplet transfer and assure that the desired mass input is achieved
Roll Maneuver Control of UCAV Wing Using Anisotropic Piezoelectric Actuators
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76333/1/AIAA-2002-1720-656.pd
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New technologies for item monitoring
This report responds to the Department of Energy`s request that Sandia National Laboratories compare existing technologies against several advanced technologies as they apply to DOE needs to monitor the movement of material, weapons, or personnel for safety and security programs. The authors describe several material control systems, discuss their technologies, suggest possible applications, discuss assets and limitations, and project costs for each system. The following systems are described: WATCH system (Wireless Alarm Transmission of Container Handling); Tag system (an electrostatic proximity sensor); PANTRAK system (Personnel And Material Tracking); VRIS (Vault Remote Inventory System); VSIS (Vault Safety and Inventory System); AIMS (Authenticated Item Monitoring System); EIVS (Experimental Inventory Verification System); Metrox system (canister monitoring system); TCATS (Target Cueing And Tracking System); LGVSS (Light Grid Vault Surveillance System); CSS (Container Safeguards System); SAMMS (Security Alarm and Material Monitoring System); FOIDS (Fiber Optic Intelligence & Detection System); GRADS (Graded Radiation Detection System); and PINPAL (Physical Inventory Pallet)
Validation of a single-stage submaximal treadmill walking test.
The single-stage treadmill walking test of Ebbeling et al. is commonly used to predict maximal oxygen consumption (.VO(2max)) from a submaximal effort between 50% and 70% of the participant\u27s age-predicted maximum heart rate. The purpose of this study was to determine if this submaximal test correctly predicts .VO(2max) at the low (50% of maximum heart rate) and high (70% of maximum heart rate) ends of the specified heart rate range for males and females aged 18 - 55 years. Each of the 34 participants completed one low-intensity and one high-intensity trial. The two trials resulted in significantly different estimates of .VO(2max) (low-intensity trial: mean 40.5 ml . kg(-1) . min(-1), s = 9.3; high-intensity trial: 47.5 ml . kg(-1) . min(-1), s = 8.8; P \u3c 0.01). A subset of 22 participants concluded their second trial with a .VO(2max) test (mean 47.9 ml . kg(-1) . min(-1), s = 8.9). The low-intensity trial underestimated (mean difference = -3.5 ml . kg(-1) . min(-1); 95% CI = -6.4 to -0.6 ml . kg(-1) . min(-1); P = 0.02) and the high-intensity trial overestimated (mean difference = 3.5 ml . kg(-1) . min(-1); 95% CI = 1.1 to 6.0 ml . kg(-1) . min(-1); P = 0.01) the measured .VO(2max). The predictive validity of Ebbeling and colleagues\u27 single-stage submaximal treadmill walking test is diminished when performed at the extremes of the specified heart rate range
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