Darrel L. Lager

Cross-borehole electromagnetic probing to locate high-contrast anomalies

Electromagnetic (EM) probing between boreholes is useful for locating high‐contrast geophysical anomalies such as a tunnel. Theoretical and experimental studies of EM field interaction with a tunnel show that minima in the received signal can be used for locating the tunnel. The theoretical studies show that as a transmitter and receiver are lowered in separate boreholes, the minima can be interpreted easily to yield both the lateral and vertical positions of the tunnel. The main mechanism of EM field interaction with the tunnel appears to be diffraction, and the spatial variation of the field strength is affected by the tunnel shape. Frequencies from 10 to 70 MHz were studied to assess the usable frequencies. The field in the receiver borehole was an effective diagnostic when a half‐wavelength in the surrounding medium was less than or equal to the diameter of the tunnel. EM probing at two test sites gave the locations of tunnels within 1 ft of the surveyed locations.

COMPUTER MODELING OF ANTENNAS NEAR THE GROUND

ABSTRACT An accurate and efficient numerical method based on the rigorous Sommer-feld theory is described for modeling antennas near an interface such as the ground. The Sommerfeld integrals are evaluated by numerical integration along contours in the complex plane and two-dimensional interpolation is used subsequently to obtain the many Sommerfeld integral values needed for the moment-method solution of an integral equation. These methods permit modeling an antenna within 10-6 wavelengths of the ground for about two to four times the computation time for the same antenna in free space. Results showing currents and radiation patterns are included.

Measurements of reduced corkscrew motion on the ETA-II linear induction accelerator

The ETA-II linear induction accelerator is used to drive a microwave free-electron laser (FEL). Corkscrew motion, which previously limited performance, has been reduced by: (1) an improved pulse distribution system which reduces energy sweep, (2) improved magnetic alignment achieved with a stretched wire alignment technique (SWAT), and (3) a unique magnetic tuning algorithm. Experiments have been carried out on a 20-cell version of ETA-II operating at 1500 A and 2.7 MeV. The measured transverse beam motion is less than 0.5 mm for 40 ns of the pulse, an improvement of a factor of 2 to 3 over previous results. Details of the computerized tuning procedure, estimates of the corkscrew phase, and relevance of these results to future FEL experiments are presented.<<ETX>>

Subsurface Probing by High-Frequency Measurements of the Wave Tilt of Electromagnetic Surface Waves

An overview of the tilt of an electromagnetic surface wave propagating along the surface of the earth is given. High-frequency wave-tilt measurements can have important applications in low conductivity regions such as desert and permafrost areas. A specific application includes determining the depth of permafrost. Past applications of wave-tilt measurements were primarily with lower frequencies in regions with high ground conductivities. Thus low frequencies (<1 MHz) were needed to probe to significant depths. Wave-tilt calculations show that for low surface conductivities, it may be feasible to probe to significant depths using high frequencies (>1 MHz). This enables resolution of thicknesses of layers, a result that has not been possible at low frequencies in the higher conductivity media. It is noted that differences in wave tilt occur for vertically and horizontally polarized surface waves. These wave-tilt differences are useful because they indicate profile characteristics that are sensitive in different ways to the two polarizations.

Evaluation of Simple Algorithms for Spectral Parameter Analysis of the Electroencephalogram

Simple autoregressive moving-average (ARMA) and autoregressive (AR) algorithms were tested for use in spectral parameter analysis (SPA) of the background electroencephalogram (EEG). In studies on simulated EEG, both algorithms successfully extracted estimates of the spectral component parameters, and their performance was relatively independent of assumed model order. The ARMA algorithm was unbiased. The AR algorithm, though biased, was simpler and more precise and, thus, may be the most suitable for on-line use. The test results on simulated data were supported by the successful application of the algorithms to human EEG recorded during surgery.

Artificial intelligence techniques for tuning linear induction accelerators

An expert system has been developed that acts as an intelligent assistant for tuning particle beam accelerators. This system is called MAESTRO-Model and Expert System Tuning Resource for Operators. MAESTRO maintains a knowledge base of the accelerator containing not only the interconnections of the beamline components, but also their physical attributes such as measured magnetic tilts, offsets, and field profiles. MAESTRO incorporates particle trajectory and beam envelope models which are coupled to the knowledge base permitting large number of real-time orbit and envelope calculations in the control-room environment. This capability has been used (1) to implement a tuning algorithm for minimizing transverse beam motion, (2) to produce a beam waist with arbitrary radius at the entrance to a brightness diagnostic, and (3) to measure beam energy along the accelerator by fitting orbits to focusing and steering sweeps.<<ETX>>

Interpreting Signals With An Assumption-Based Truth Maintenance System

This paper presents an expert system that interprets seismic events. The general problem of signal interpretation is formally described. The system uses an assumption based truth maintenance system. The advantages of using this approach for this application are described.

MAESTRO — A model and expert system tuning resource for operators

Abstract We have developed MAESTRO, a m odel a nd e xpert s ystem t uning r esource for o perators. It provides a unified software environment for optimizing the performance of large, complex machines, in particular the Advanced Test Accelerator and Experimental Test Accelerator at Lawrence Livermore National Laboratory. The system incorporates three approaches to tuning: • - a mouse-based manual interface to select and control magnets and to view displays of machine performance; • - an automation based on “cloning the operator” by implementing the strategies and reasoning used by the operator; and • - an automation based on a simulator model which, when accurately matched to the machine, allows downloading of optimal sets of parameters and permits diagnosing errors in the beam line. The latter two approaches are based on the artificial-intelligence technique known as Expert Systems.

LIAM-a linear induction accelerator model

A flexible linear induction accelerator model (LIAM) was developed to predict both beam centroid position and the beam envelope. LIAM requires on-axis magnetic profiles and is designed to easily handle overlapping fields from multiple elements. Currently, LIAM includes solenoids, dipole steering magnets, and accelerating gaps. Other magnetic elements can be easily incorporated into LIAM due to its object-oriented design. LIAM is written in the C programming language and computes fast enough on current workstations to be used in the control room as a tuning and diagnostic aid. Combined with a non-linear least squares package, LIAM has been used to estimate beam energy at various locations within the ETA-II accelerator.<<ETX>>

AN EXPERT SYSTEM FOR TUNING PARTICLE BEAM ACCELERATORS

An expert system that acts as an intelligent assistant to operators tuning a particle beam accelerator was developed. The system incorporates three approaches to tuning: (1) Duplicating within a software program the reasoning and the procedures used by an operator to tune an accelerator. This approach has been used to steer particle beams through the transport section of Lawrence Livermore National Laboratorys Advanced Test Accelerator and through the injector section of the Experimental Test Accelerator. (2) Using a model to simulate the position of a beam in an accelerator. The simulation is based on data taken directly from the accelerator while it is running. This approach will ultimately be used by operators of the Experimental Test Accelerator to first compare actual and simulated beam performance in real time, then to determine which set of parameters is optimum in terms of centering the beam, and finally to feed those parameters to the accelerator. Operators can also use the model to determine if a component has failed. (3) Using a mouse to manually select and control the magnets that steer the beam. Operators on the Experimental Test Accelerator can also use the mouse to call up windows that display the horizontal and vertical positions of the beam as well as its current.