3 resultados para Canonical correlation analysis (CCA)
em Digital Commons - Michigan Tech
Resumo:
Vegetation communities affect carbon and nitrogen dynamics in the subsurface water of mineral wetlands through the quality of their litter, their uptake of nutrients, root exudation and their effects on redox potential. However, vegetation influence on subsurface nutrient dynamics is often overshadowed by the influences of hydrology, soils and geology on nutrient dynamics. The effects of vegetation communities on carbon and nitrogen dynamics are important to consider when managing land that may change vegetation type or quantity so that wetland ecosystem functions can be retained. This study was established to determine the magnitude of the influences and interaction of vegetation cover and hydrology, in the form of water table fluctuations, on carbon and nitrogen dynamics in a northern forested riparian wetland. Dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), nitrate (NO3-) and ammonium (NH4+) concentrations were collected from a piezometer network in four different vegetation communities and were found to show complex responses to vegetation cover and water table fluctuations. Dissolved organic carbon, DIC, NO3- and NH4+ concentrations were influenced by forest vegetation cover. Both NO3- and NH4+ were also influenced by water table fluctuations. However, for DOC and NH4+ concentrations there appeared to be more complex interactions than were measured by this study. The results of canonical correspondence analysis (CCA) and analysis of variance (ANOVA) did not correspond in relationship to the significance of vegetation communities. Dissolved inorganic carbon was influenced by an interaction between vegetation cover and water table fluctuations. More hydrological information is needed to make stronger conclusions about the relationship between vegetation and hydrology in controlling carbon and nitrogen dynamics in a forested riparian wetland.
Resumo:
Mineral dust shape and roughness are important for a multitude of processes; it is known for aspherical shape but the true measurements in three dimensions are rare. Atomic Force Microscope was used for determine both 3D shape and roughness for two dust which are commonly used in laboratory experiments – Arizona Test Dust (ATD) and Kaolinite. We determined both of them are rather flat and round; an oblate spheroid would be a good model. Loess Filter was used to smooth the particles' surface and correlation analysis was used to examine the surfaces' properties of the dust; we found no features under 100nm scales. Also, our particles' surface area result is very similar to BET surface area.
Resumo:
The goal of this project is to learn the necessary steps to create a finite element model, which can accurately predict the dynamic response of a Kohler Engines Heavy Duty Air Cleaner (HDAC). This air cleaner is composed of three glass reinforced plastic components and two air filters. Several uncertainties arose in the finite element (FE) model due to the HDAC’s component material properties and assembly conditions. To help understand and mitigate these uncertainties, analytical and experimental modal models were created concurrently to perform a model correlation and calibration. Over the course of the project simple and practical methods were found for future FE model creation. Similarly, an experimental method for the optimal acquisition of experimental modal data was arrived upon. After the model correlation and calibration was performed a validation experiment was used to confirm the FE models predictive capabilities.