4 resultados para Data pre-processing

em Digital Commons - Michigan Tech


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The main purpose of this project is to understand the process of engine simulation using the open source CFD code called KIVA. This report mainly discusses the simulation of the 4-valve Pentroof engine through KIVA 3VR2. KIVA is an open source FORTRAN code which is used to solve the fluid flow field in the engines with the transient 2D and 3D chemically reactive flow with spray. It also focuses on the complete procedure to simulate an engine cycle starting from pre- processing until the final results. This report will serve a handbook for the using the KIVA code.

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The feasibility of carbon sequestration in cement kiln dust (CKD) was investigated in a series of batch and column experiments conducted under ambient temperature and pressure conditions. The significance of this work is the demonstration that alkaline wastes, such as CKD, are highly reactive with carbon dioxide (CO2). In the presence of water, CKD can sequester greater than 80% of its theoretical capacity for carbon without any amendments or modifications to the waste. Other mineral carbonation technologies for carbon sequestration rely on the use of mined mineral feedstocks as the source of oxides. The mining, pre-processing and reaction conditions needed to create favorable carbonation kinetics all require significant additions of energy to the system. Therefore, their actual net reduction in CO2 is uncertain. Many suitable alkaline wastes are produced at sites that also generate significant quantities of CO2. While independently, the reduction in CO2 emissions from mineral carbonation in CKD is small (~13% of process related emissions), when this technology is applied to similar wastes of other industries, the collective net reduction in emissions may be significant. The technical investigations presented in this dissertation progress from proof of feasibility through examination of the extent of sequestration in core samples taken from an aged CKD waste pile, to more fundamental batch and microscopy studies which analyze the rates and mechanisms controlling mineral carbonation reactions in a variety of fresh CKD types. Finally, the scale of the system was increased to assess the sequestration efficiency under more pilot or field-scale conditions and to clarify the importance of particle-scale processes under more dynamic (flowing gas) conditions. A comprehensive set of material characterization methods, including thermal analysis, Xray diffraction, and X-ray fluorescence, were used to confirm extents of carbonation and to better elucidate those compositional factors controlling the reactions. The results of these studies show that the rate of carbonation in CKD is controlled by the extent of carbonation. With increased degrees of conversion, particle-scale processes such as intraparticle diffusion and CaCO3 micropore precipitation patterns begin to limit the rate and possibly the extent of the reactions. Rates may also be influenced by the nature of the oxides participating in the reaction, slowing when the free or unbound oxides are consumed and reaction conditions shift towards the consumption of less reactive Ca species. While microscale processes and composition affects appear to be important at later times, the overall degrees of carbonation observed in the wastes were significant (> 80%), a majority of which occurs within the first 2 days of reaction. Under the operational conditions applied in this study, the degree of carbonation in CKD achieved in column-scale systems was comparable to those observed under ideal batch conditions. In addition, the similarity in sequestration performance among several different CKD waste types indicates that, aside from available oxide content, no compositional factors significantly hinder the ability of the waste to sequester CO2.

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Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

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By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.