988 resultados para Cluster monitoring
Resumo:
Shellfish bed closures along the North Carolina coast have increased over the years seemingly concurrent with increases in population (Mallin 2000). More and faster flowing storm water has come to mean more bacteria, and fecal indicator bacterial (FIB) standards for shellfish harvesting are often exceeded when no source of contamination is readily apparent (Kator and Rhodes, 1994). Could management reduce bacterial loads if the source of the bacteria where known? Several potentially useful methods for differentiating human versus animal pollution sources have emerged including Ribotyping and Multiple Antibiotic Resistance (MAR) (US EPA, 2005). Total Maximum Daily Load (TMDL) studies on bacterial sources have been conducted for streams in NC mountain and Piedmont areas (U.S. EPA, 1991 and 2005) and are likely to be mandated for coastal waters. TMDL analysis estimates allowable pollutant loads and allocates them to known sources so management actions may be taken to restore water to its intended uses (U.S. EPA, 1991 and 2005). This project sought first to quantify and compare fecal contamination levels for three different types of land use on the coast, and second, to apply MAR and ribotyping techniques and assess their effectiveness for indentifying bacterial sources. Third, results from these studies would be applied to one watershed to develop a case study coastal TMDL. All three watershed study areas are within Carteret County, North Carolina. Jumping Run Creek and Pettiford Creek are within the White Oak River Basin management unit whereas the South River falls within the Neuse River Basin. Jumping Run Creek watershed encompasses approximately 320 ha. Its watershed was a dense, coastal pocosin on sandy, relic dune ridges, but current land uses are primarily medium density residential. Pettiford Creek is in the Croatan National Forest, is 1133 ha. and is basically undeveloped. The third study area is on Open Grounds Farm in the South River watershed. Half of the 630 ha. watershed is under cultivation with most under active water control (flashboard risers). The remaining portion is forested silviculture.(PDF contains 4 pages)
Resumo:
We propose a plasma channel scheme to obtain an improved table-top laser driven fusion neutron yield as a result of explosions of large deuterium clusters irradiated by an intense laser pulse. A cylindrical plasma channel is created by two moderate intensity laser prepulses at the edge of a deuterium cluster jet along which an intense main laser pulse propagates several nanoseconds later. With the aid of this plasma channel, the main laser pulse will be allowed to deposit its energy into the central region of the deuterium gas jet where the cluster sizes are larger and the atomic density is higher. The plasma channel formation and its impact on the deuterium ion energy spectrum and the consequent fusion neutron yield have been investigated. The calculated results show that a remarkable increase of the table-top laser driven fusion neutron yield would be expected.
Resumo:
The effect of the laser spot size on the neutron yield of table-top nuclear fusion from explosions of a femtosecond intense laser pulse heated deuterium clusters is investigated by using a simplified model, in which the cluster size distribution and the energy attenuation of the laser as it propagates through the cluster jet are taken into account. It has been found that there exists a proper laser spot size for the maximum fusion neutron yield for a given laser pulse and a specific deuterium gas cluster jet. The proper spot size, which is dependent on the laser parameters and the cluster jet parameters, has been calculated and compared with the available experimental data. A reasonable agreement between the calculated results and the published experimental results is found.
Cluster explosion investigated by linearly chirped spectral scattering of an expanding plasma sphere
Resumo:
Femtosecond explosive processes of argon clusters irradiated by linearly chirped ultraintense laser pulses have been investigated by 90 degrees side spectral scattering. The spectral redshift and blueshift, which correlate with the cluster explosion processes have been measured for negatively and positively chirped driving laser pulses, respectively. The evolution of the heated-cluster polarizability indicates that the core of the cluster is shielded from the laser field in the beginning of the explosion and enhanced scattering occurs after the fast explosion initiates. Evidence of resonant heating is found from the coincidence of enhanced scattering with enhanced absorption measured using the transmitted spectra. Anomalously large-size clusters with very low gas density have been observed in this way and can be used as clean and important cluster targets.
Resumo:
A Bayesian probabilistic methodology for on-line structural health monitoring which addresses the issue of parameter uncertainty inherent in problem is presented. The method uses modal parameters for a limited number of modes identified from measurements taken at a restricted number of degrees of freedom of a structure as the measured structural data. The application presented uses a linear structural model whose stiffness matrix is parameterized to develop a class of possible models. Within the Bayesian framework, a joint probability density function (PDF) for the model stiffness parameters given the measured modal data is determined. Using this PDF, the marginal PDF of the stiffness parameter for each substructure given the data can be calculated.
Monitoring the health of a structure using these marginal PDFs involves two steps. First, the marginal PDF for each model parameter given modal data from the undamaged structure is found. The structure is then periodically monitored and updated marginal PDFs are determined. A measure of the difference between the calibrated and current marginal PDFs is used as a means to characterize the health of the structure. A procedure for interpreting the measure for use by an expert system in on-line monitoring is also introduced.
The probabilistic framework is developed in order to address the model parameter uncertainty issue inherent in the health monitoring problem. To illustrate this issue, consider a very simplified deterministic structural health monitoring method. In such an approach, the model parameters which minimize an error measure between the measured and model modal values would be used as the "best" model of the structure. Changes between the model parameters identified using modal data from the undamaged structure and subsequent modal data would be used to find the existence, location and degree of damage. Due to measurement noise, limited modal information, and model error, the "best" model parameters might vary from one modal dataset to the next without any damage present in the structure. Thus, difficulties would arise in separating normal variations in the identified model parameters based on limitations of the identification method and variations due to true change in the structure. The Bayesian framework described in this work provides a means to handle this parametric uncertainty.
The probabilistic health monitoring method is applied to simulated data and laboratory data. The results of these tests are presented.
Resumo:
The 45 degrees scattering of a femtosecond (60 fs) intense laser pulse with a 20 nm FWHM (the full width at half maximum) spectrum centered at 790 nm has been studied experimentally while focused in argon clusters at intensity similar to 10(16) W/cm(2). Scattering spectra under different backing pressures and laser-plasma interaction lengths were obtained, which showed spectral blueshifting, beam refraction and complex modulation. These ionization-induced effects reveal the modulation of laser pulses propagating in plasmas and the existing obstacle in laser cluster interaction at high laser intensity and high electron density.
Resumo:
Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.
The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.
In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.
Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.
Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.