Beatrice / Sam Rivers -- Pent-up house / Sonny Rollins -- Everything I love / Cole porter -- Darn that dream / Jimmy van Heusen -- Django / John Lewis -- Laverne walk / Oscar Pettiford. / text

The writer of this master thesis was acquiring an education in classical percussion and deeply respecting the music genre named djent. He was so impressed by metal music that he taught himself how to use the notation programme Sibelius 7 and arranged a number of his favourite songs for the percussion ensemble so he would be able to play them. The following text supports and describes the process. A short analysis of 16 arrangements is included as well.

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Concerto for violin and wind ensemble is a 25-minute virtuosic work for the violin and accompanying winds, brass, and percussion. As a trained violinist, among the first works I learned were the concerti of J.S. Bach. Thus, I pay special homage to Bach in this piece by using the famous B-A-C-H motive (each letter corresponding to a pitch) to generate much of the musical material in the work. The analysis of the Concerto details the processes in which B-A-C-H affected and shaped the melodic and harmonic language of the piece, while also touching upon the use of orchestration and the problems associated with balancing a single solo instrument against a large ensemble. I also discuss the several existing works for violin that were highly influential in composing the Concerto and the "anxiety of influence" associated with each model. / text

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This document details the creation of a new type of multiple percussion solo from pre-composed percussion ensembles. The author transcribes three works for percussion ensemble by Lou Harrison (1917-2003): Suite for Percussion, movement I, Bomba and Simfony #13 so that they can be performed as percussion solos. Each composition requires a different type of solo version because of the diverse instruments and musical materials in the original scores. Learning to perform these new versions will expand the technical capabilities of a soloist and offers complex challenges not found in the original ensembles. The document includes complete scores and set-ups for each new solo version and discussion of performance practice and techniques to play each work. Although Harrison’s original works were conceived for amateur players, the solo versions require the skills of a virtuoso performer. The new versions confirm the artistic merit of Harrison’s work in a format both practical and satisfying to the solo percussionist. The project illustrates new methods for further developing percussion technique to enable ensemble works to be performed by soloists. The solo versions of Lou Harrison percussion ensembles presented herein result in new repertoire for the percussion soloist.

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This dissertation describes research designed to enhance hydrometeorological forecasts. The objective of the research is to deliver an optimal methodology to produce reliable, skillful and economically valuable probabilistic temperature and precipitation forecasts. Weather plays a dominant role for energy companies relying on forecasts of watershed precipitation and temperature to drive reservoir models, and forecasts of temperatures to meet energy demand requirements. Extraordinary precipitation events and temperature extremes involve consequential water- and power-management decisions. This research compared weighted-average, recursive, and model output statistics bias-correction methods and determined optimal window-length to calibrate temperature and precipitation forecasts. The research evaluated seven different methods for daily maximum and minimum temperature forecasts, and three different methods for daily quantitative precipitation forecasts, within a region of complex terrain in southwestern British Columbia, Canada. This research then examined ensemble prediction system design by assessing a three-model suite of multi-resolution limited area mesoscale models. The research employed two different economic models to investigate the ensemble design that produced the highest-quality, most valuable forecasts. The best post-processing methods for temperature forecasts included moving-weighted average methods and a Kalman filter method. The optimal window-length proved to be 14 days. The best post-processing methods for achieving mass balance in quantitative precipitation forecasts were a moving-average method and the best easy systematic estimator method. The optimal window-length for moving-average quantitative precipitation forecasts was 40 days. The best ensemble configuration incorporated all resolution members from all three models. A cost/loss model adapted specifically for the hydro-electric energy sector indicated that operators managing rainfall-dominated, high-head reservoirs should lower their reservoir with relatively low probabilities of forecast precipitation. A reservoir-operation model based on decision theory and variable energy pricing showed that applying an ensemble-average or full-ensemble precipitation forecast provided a much greater profit than using only a single deterministic high-resolution forecast. Finally, a bias-corrected super-ensemble prediction system was designed to produce probabilistic temperature forecasts for ten cities in western North America. The system exhibited skill and value nine days into the future when using the ensemble average, and 12 days into the future when employing the full ensemble forecast.

The increase in energy demand throughout the world has forced the oil industry to develop and expand on current technologies to optimize well productivity. Distributed temperature sensing has become a current and fairly inexpensive way to monitor performance in hydraulic fractured wells in real time by the aid of fiber optic. However, no applications have yet been attempted to describe or estimate the fracture parameters using distributed temperature sensing as the observation parameter. The Ensemble Kalman Filter, a recursive filter, has proved to be an effective tool in the application of inverse problems to determine parameters of non-linear models. Even though large amounts of data are acquired as the information used to apply an estimation, the Ensemble Kalman Filter effectively minimizes the time of operation by only using “snapshots” of the ensembles collected by various simulations where the estimation is updated continuously to be calibrated by comparing it to a reference model. A reservoir model using ECLIPSE is constructed that measures temperature throughout the wellbore. This model is a hybrid representation of what distributed temperature sensing measures in real-time throughout the wellbore. Reservoir and fracture parameters are selected in this model with similar properties and values to an unconventional well. However, certain parameters such as fracture width are manipulated to significantly diminish the computation time. A sensitivity study is performed for all the reservoir and fracture parameters in order to understand which parameters require more or less data to allow the Ensemble Kalman Filter to arrive to an acceptable estimation. Two fracture parameters are selected based on their low sensitivity and importance in fracture design to perform the Ensemble Kalman Filter on various simulations. Fracture permeability has very low sensitivity. However, when applying the estimation the Ensemble Kalman Filter arrives to an acceptable estimation. Similarly fracture halflength, with medium sensitivity, arrives to an acceptable estimation around the same number of integration steps. The true effectiveness of the Ensemble Kalman Filter is presented when both parameters are estimated jointly and arrive to an acceptable estimation without being computationally expensive. The effectiveness of the Ensemble Kalman Filter is directly connected to the quantity of data acquired. The more data available to run simulations, the better and faster the filter performs.