Global wave predictions produced at two U. S. forecasting centers, Fleet Numerical Meteorology and Oceanography Center and the National Centers for Environmental Prediction are evaluated with spectral buoy measurements. In this study, the fidelity of frequency-directional spectra predicted by WAM and WAVEWATCH III at the operational centers is examined with data from 3-meter discus and 6-meter nomad buoys operated by the National Data Buoy Center in the Atlantic and Pacific Oceans and Datawell Directional Waverider buoys deployed along the California coast by the Scripps Institution of Oceanography Coastal Data Information Program. Only buoys located in deep water are used in the comparisons. Model nowcasts of frequency spectra and mean wave directions are compared to buoy measurements over a six-month period from 1 October 2000 to 31 March 2001. At the Pacific buoy locations, individual swell events were identified in the spectra from the three models and the buoy data. Predicted and observed swell frequencies and arrival directions are compared as well as the total energy transported past the buoy over the duration of each individual event. At all buoy locations, predicted and observed wave energy fluxes integrated over fixed frequency ranges are compared. All three models yield reliable nowcasts of swell arrivals at the buoy locations. In most cases, the models under-predict the energy measured by the buoys. WAVEWATCH III better resolves low-frequency swells than WAM, possibly owing to a superior numerical scheme. Swell predictions at NCEP forced with AVN winds are more accurate than those at FNMOC forced with NOGAPS winds. / US Navy (USN) author

Thesis (M.S. in Meteorology and Physical Oceanography) Naval Postgraduate School, December 2001. / "December 2001". Thesis advisor(s): Herbers, Thomas H.C.; Wittmann, Paul A. Includes bibliographical references (p. 39). Also available online.

A study was conducted to quantify weather conditions at specific growth stages of Canadian western Spring wheat (Triticum aestivum) and relate those growing conditions to variations in wheat grade and quality characteristics and to develop pre-harvest prediction models for wheat quality using weather input data. Six Canadian western spring wheat genotypes were grown in five locations across the Canadian prairies during the 2003 and 2004 growing seasons. Intensive weather data was collected during the growing season at each location and used to calculate accumulated heat stress, useful heat, moisture demand, moisture supply, moisture use and moisture stress variables for numerous crop development stages. Grain samples were graded, milled and underwent an extensive analysis of flour, dough, and bread making quality. ANOVA indicated that genotype, environment and their interactions had significant effects on most quality parameters tested. Environmental contribution to wheat quality variance was considerably larger than the variance contribution of either genotype or GxE interaction. Using the weather and crop development stage information, significant regression equations with high regression coefficients were developed for most quality parameters using just a single independent weather variable. Multiple regression equations with even higher R2 values were developed using three complex weather variables, leading to the opportunity to predict wheat quality 2-5 weeks prior to harvest. Equally strong prediction models were developed utilizing basic weather variables which could be obtained from weather stations monitoring only daily maximum and minimum air temperature and precipitation. The development periods of planting to jointing and anthesis to soft dough were the stages most frequently exhibiting the highest correlation to wheat quality indicating weather needs to be monitored during the entire growing season to accurately predict quality. Grain quality forecast models were validated using 2005 weather and crop data. Prediction models developed from the 2003 and 2004 data required modification in order to accurately and consistently predict the grain properties in 2005. / February 2007

A study was conducted to quantify weather conditions at specific growth stages of Canadian western Spring wheat (Triticum aestivum) and relate those growing conditions to variations in wheat grade and quality characteristics and to develop pre-harvest prediction models for wheat quality using weather input data. Six Canadian western spring wheat genotypes were grown in five locations across the Canadian prairies during the 2003 and 2004 growing seasons. Intensive weather data was collected during the growing season at each location and used to calculate accumulated heat stress, useful heat, moisture demand, moisture supply, moisture use and moisture stress variables for numerous crop development stages. Grain samples were graded, milled and underwent an extensive analysis of flour, dough, and bread making quality. ANOVA indicated that genotype, environment and their interactions had significant effects on most quality parameters tested. Environmental contribution to wheat quality variance was considerably larger than the variance contribution of either genotype or GxE interaction. Using the weather and crop development stage information, significant regression equations with high regression coefficients were developed for most quality parameters using just a single independent weather variable. Multiple regression equations with even higher R2 values were developed using three complex weather variables, leading to the opportunity to predict wheat quality 2-5 weeks prior to harvest. Equally strong prediction models were developed utilizing basic weather variables which could be obtained from weather stations monitoring only daily maximum and minimum air temperature and precipitation. The development periods of planting to jointing and anthesis to soft dough were the stages most frequently exhibiting the highest correlation to wheat quality indicating weather needs to be monitored during the entire growing season to accurately predict quality. Grain quality forecast models were validated using 2005 weather and crop data. Prediction models developed from the 2003 and 2004 data required modification in order to accurately and consistently predict the grain properties in 2005.

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A study was conducted to quantify weather conditions at specific growth stages of Canadian western Spring wheat (Triticum aestivum) and relate those growing conditions to variations in wheat grade and quality characteristics and to develop pre-harvest prediction models for wheat quality using weather input data. Six Canadian western spring wheat genotypes were grown in five locations across the Canadian prairies during the 2003 and 2004 growing seasons. Intensive weather data was collected during the growing season at each location and used to calculate accumulated heat stress, useful heat, moisture demand, moisture supply, moisture use and moisture stress variables for numerous crop development stages. Grain samples were graded, milled and underwent an extensive analysis of flour, dough, and bread making quality. ANOVA indicated that genotype, environment and their interactions had significant effects on most quality parameters tested. Environmental contribution to wheat quality variance was considerably larger than the variance contribution of either genotype or GxE interaction. Using the weather and crop development stage information, significant regression equations with high regression coefficients were developed for most quality parameters using just a single independent weather variable. Multiple regression equations with even higher R2 values were developed using three complex weather variables, leading to the opportunity to predict wheat quality 2-5 weeks prior to harvest. Equally strong prediction models were developed utilizing basic weather variables which could be obtained from weather stations monitoring only daily maximum and minimum air temperature and precipitation. The development periods of planting to jointing and anthesis to soft dough were the stages most frequently exhibiting the highest correlation to wheat quality indicating weather needs to be monitored during the entire growing season to accurately predict quality. Grain quality forecast models were validated using 2005 weather and crop data. Prediction models developed from the 2003 and 2004 data required modification in order to accurately and consistently predict the grain properties in 2005.

This thesis proposes the methodology and guidelines for community-based macro-level CPM transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region. In doing this. the macro-level CPMs developed for the Greater Vancouver Regional District (GVRD) by Lovegrove and Sayed (2006, 2007) was used in a model transferability study. Using those models from GVRD and data from Central Okanagan Regional District (CORD), in the Province of British Columbia. Canada. a transferability test has been conducted that involved recalibration of the 1996 GVRD models to Kelowna, in 2003 context. The case study was carried out in three parts. First, macro-level CPMs for the City of Kelowna were developed using 2003 data following the research by GVRD CPM development and use. Next, the 1996 GVRD models were recalibrated to see whether they could yield reliable prediction of the safety estimates for Kelowna, in 2003 context. Finally, a comparison between the results of Kelowna’s own developed models and the transferred models was conducted to determine which models yielded better results. The results of the transferability study revealed that macro-level CPM transferability was possible and no more complicated than micro-level CPM transferability. To facilitate the development of reliable community-based, macro-level collision prediction models, it was recommended that CPMs be transferred rather than developed from scratch whenever and wherever communities lack sufficient data of adequate quality. Therefore, the transferability guidelines in this research, together with their application in the case studies, have been offered as a contribution towards model transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region.

This thesis proposes the methodology and guidelines for community-based macro-level CPM transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region. In doing this. the macro-level CPMs developed for the Greater Vancouver Regional District (GVRD) by Lovegrove and Sayed (2006, 2007) was used in a model transferability study. Using those models from GVRD and data from Central Okanagan Regional District (CORD), in the Province of British Columbia. Canada. a transferability test has been conducted that involved recalibration of the 1996 GVRD models to Kelowna, in 2003 context. The case study was carried out in three parts. First, macro-level CPMs for the City of Kelowna were developed using 2003 data following the research by GVRD CPM development and use. Next, the 1996 GVRD models were recalibrated to see whether they could yield reliable prediction of the safety estimates for Kelowna, in 2003 context. Finally, a comparison between the results of Kelowna’s own developed models and the transferred models was conducted to determine which models yielded better results. The results of the transferability study revealed that macro-level CPM transferability was possible and no more complicated than micro-level CPM transferability. To facilitate the development of reliable community-based, macro-level collision prediction models, it was recommended that CPMs be transferred rather than developed from scratch whenever and wherever communities lack sufficient data of adequate quality. Therefore, the transferability guidelines in this research, together with their application in the case studies, have been offered as a contribution towards model transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region.

This thesis proposes the methodology and guidelines for community-based macro-level CPM transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region. In doing this. the macro-level CPMs developed for the Greater Vancouver Regional District (GVRD) by Lovegrove and Sayed (2006, 2007) was used in a model transferability study. Using those models from GVRD and data from Central Okanagan Regional District (CORD), in the Province of British Columbia. Canada. a transferability test has been conducted that involved recalibration of the 1996 GVRD models to Kelowna, in 2003 context. The case study was carried out in three parts. First, macro-level CPMs for the City of Kelowna were developed using 2003 data following the research by GVRD CPM development and use. Next, the 1996 GVRD models were recalibrated to see whether they could yield reliable prediction of the safety estimates for Kelowna, in 2003 context. Finally, a comparison between the results of Kelowna’s own developed models and the transferred models was conducted to determine which models yielded better results. The results of the transferability study revealed that macro-level CPM transferability was possible and no more complicated than micro-level CPM transferability. To facilitate the development of reliable community-based, macro-level collision prediction models, it was recommended that CPMs be transferred rather than developed from scratch whenever and wherever communities lack sufficient data of adequate quality. Therefore, the transferability guidelines in this research, together with their application in the case studies, have been offered as a contribution towards model transferability to do road safety planning applications, with models developed in one spatial-temporal region being capable of used in a different spatial-temporal region. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Concrete undergoes volumetric changes throughout its service life. These changes are a result of applied loads and shrinkage. Applied loads result in an instantaneous recoverable elastic deformation and a slow, time dependent, inelastic deformation called creep. Creep without moisture loss is referred to as basic creep and with moisture loss is referred to as drying creep. Shrinkage is the combination of autogeneous, drying, and carbonation shrinkage. The combination of creep, shrinkage, and elastic deformation is referred to as total strain. The prestressed concrete beams in the Chickahominy River Bridge have been fabricated with a lightweight, high strength concrete mixture (LTHSC). Laboratory test specimens have been cast using the concrete materials and mixture proportions used in the fabrication of the bridge beams. Two standard cure and two match cure batches have been loaded for 329 and 251 days, respectively. Prestress losses are generally calculated with the total strain predicted by the American Concrete Institute Committee 209 recommendations, ACI 209, or the European design code, CEB Model Code 90. Two additional models that have been proposed are the B3 model by Bazant and Baweja, and the GL2000 model proposed by Gardner and Lockman. The four models are analyzed to determine the most precise model for the LTHSC mixture. Only ACI 209 considered lightweight aggregates during model development. GL2000 considers aggregate stiffness in the model. ACI 209 was the best predictor of total strain and individual time dependent deformations for the accelerated cure specimens. CEB Mode Code 90 was the best predictor of total strain for the standard cure specimens. The best overall predictor of time dependent deformations was the GL2000 model for the standard cure specimens. / Master of Science