Gamma Sled for Seafloor Lithology Survey

Abstract

The Gamma Isotope Mapping System (GIMS) has two main components. The first component is a stainless steel sled that is towed on the seafloor by a survey vessel. The second component is the shipboard electronics. The sled houses a gamma radiation detector and battery pack. As the sled is towed along the seafloor at approximately 3 knots, the detector measures the natural gamma radioactivity of the surface sediment. The signal from the detector is sent by armored cable to the ship. The gamma signal is received and processed by a spectrometer mounted in the electronics package. The gamma radiation data, along with time, latitude, longitude, and water depth is logged automatically at 60 second intervals on a computer diskette. During the survey, two- and three-dimensional maps are created with the collected data. These maps show the differences in the sediment seafloor lithology. This data can be used in the location of surface mineral deposits on the seafloor or to track sediment distribution as a result of disposal activities during dredging operations from near-shore environments. Since the results are obtained during the survey, additional studies can proceed immediately after the GIMS survey allowing for a more economical merging of various studies. INTRODUCTION Due to the vast regions of the unknown marine environment, a method for rapidly exploring and mapping the surface lithology would be very useful to geologists and environmentalists. In addition to this, the ability to have the final results displayed in two- and three-dimensional maps immediately after the region is covered would be extremely helpful. The gamma detection sled was originally developed during the early 1970's for mineral exploration (Noakes et al, 1974). It was tested off the Georgia-South Carolina coast in an exploration effort to locate phosphate deposits (Harding & Noakes, 1976). Several anomalous areas were detected during the offshore exploration efforts. Sampling of the anomalies indicated that these areas consisted of heavy mineral sands and phosphatic material. The general design of the sled performed extremely well with little damage due to the abrasive nature of the seafloor. The system proved it's capabilities to detect changes in the bottom lithology during the testing in the 1970's with the location of heavy minerals and phosphatic deposits. This led to the possibility of using the gamma sled for tracking and mapping the changes in the seafloor lithology; not for minerals, but for environmental purposes. The Environmental Protection Agency (EPA) monitors all of the Ocean Dredged Material Disposal Sites (ODMDS) located directly offshore the coastal regions of the United States. In the past, the primary methods used to monitor the sites were sediment traps, box coring devices, biological sampling, and diver collected samples. All of these methods required considerable amounts of time and manpower to survey one ODMDS which can cover an average of 52 km2. Data collected over a long period of time are no longer representative of the current condition due to the effects of ocean currents and storms.

Structural stability and hyperbolicity violation in high-dimensional dynamical systems

“…The motivation and construction of the set of mappings we will use for our investigation of dynamical systems follows via two directions, the embedding theorem of Takens ([16], [17]) and the neural network approximation theorems of Hornik, Stinchomebe, and White [18]. We will use the Takens embedding theorem to demonstrate how studying time-delayed maps of the form f : R d → R is a natural choice for studying standard dynamical systems of the form F :…”

“…All this information can be summarized in Fig. (17) which addresses the mean fraction of exponents that are near zero versus parameter variation.…”

“…There are four important features to notice about Fig. (17): there are no sharp discontinuities in the curves; there exists an interval in parameter space such that there is always at least one Lyapunov exponent in the interval (−0.01, 0.01) and the length of that parameter interval is increasing with dimension; the curves are concave -implying that exponents are somehow leaving the interval (−0.01, 0.01); and there is a higher fraction of exponents near zero at the same s value for higher dimension. The first property is important because holes in the parameter space where there are no exponents near zero would imply the absence of the continuous zero crossings we will need to satisfy conjecture (2).…”