Several previous studies have compared design storms with continuous simulation results for the purposes of estimating flood frequency distributions. These previous studies were limited in scope to primarily urban single lumped catchments. This thesis attempted to perform a more detailed comparison of design storm and continuous simulation flood frequency distributions by extending the analysis to different basin types, as well as examining the effect of more complex watershed systems and storage elements (detention ponds). It was found that design storms could reasonably reproduce continuous simulation flood frequency distributions if an appropriate distribution and antecedent conditions were selected. Design storms were found to compare increasingly well to continuous simulation results in more complex watershed systems and through storage elements. / Thesis / Master of Applied Science (MASc)

1 / xu zhou

An enormous and urgent energy demand is predicted due to the growing global population, increase in power intensive industries, higher living standards, electrification of remote areas, and globalisation (transportation). Moreover, the global consciousness about the harmful effects of traditional methods of power generation on the environment. That, in turn, has created a need to strategically plan and develop renewable and sustainable energy generation systems. This study presents a wind resource assessment of seven locations proximate to the largest industrial hub in the Middle East, Jubail Industrial City, Kingdom of Saudi Arabia, and a Geographic Information System, GIS based model considering a multi-criteria wind farm site suitability approach for the entire Kingdom of Saudi Arabia and elsewhere. The hourly mean wind speed data at 10, 50 and 90 m above the ground level (AGL) over a period of five years was used for a meteorological station at the Industrial Area (Central) of Jubail. At the remaining six sites, the meteorological data were recorded at 10 m AGL only. Five years of wind data were used for five sites and three years of data were available for the remaining one site. At the Industrial Area (East), the mean wind speeds were found to be 3.34, 4.79 and 5.35 m/s at 10, 50 and 90 m AGL, respectively. At 50 and 90 m AGL, the availability of wind speed above 3.5 m/s was more than 75%. The local wind shear exponent, calculated using measured wind speed values at three heights, was found to be 0.217. The mean wind power density values at measurement heights were 50.92, 116.03 and 168.46 W/m2, respectively. After the assessment and comparison of wind characteristics of all seven sites, the highest annual mean wind speed of 4.52 m/s was observed at Industrial Area (East) and the lowest of 2.52 m/s at the Pearl Beach with standard deviations of 2.52 and 1.1 m/s, respectively. In general, at all sites, the highest monthly mean wind speed was observed in February/June and the lowest in September/October. The period of higher wind availability coincides with a high power demand period in the region attributable to the air conditioning load. The wind rose plots show that the prevailing wind direction for all sites was from the north-west. Weibull parameters for all sites were estimated using maximum likelihood, least-squares regression method (LSRM), and WAsP algorithm. In general, at all sites, the Weibull parameter, c, was the highest in the months of February/June and the lowest in the month of October. The most probable and maximum energy carrying wind speed was determined by all three methods. The highest value of most probable wind speed was found to be in the range of 3.2 m/s to 3.6 m/s at Industrial Area (East) and the highest value of maximum energy carrying wind speed was found to be in the range 8.6 m/s to 9.0 m/s at Industrial Area 2 (South) by three estimation methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE), and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM, followed by WAsP algorithm. The wind power output at all seven sites, from five commercially available wind turbines of rated power ranging from 1.8 to 3.3 MW, showed that Industrial Area (East) is most promising for wind farm development. At all sites, based on percentage plant capacity factor, PCF, the 1.8 MW wind turbine was found to be the most efficient. At Industrial Area (East), this wind turbine was found to have a maximum PCF of 41.8%, producing 6,589 MWh/year energy output. The second best wind turbine was 3 MW at all locations except the Al-Bahar Desalination Plant and Pearl Beach. At both of these locations, 3.3 MW was the next best option. The energy output from the 3 MW wind turbine at Industrial Area (East) was found to be 11,136 MWh/year with a PCF of 41.3%. The maximum duration of rated power output from all selected wind turbines was observed to be between 8 to 16.6% at Industrial Area 2 (South). The minimum duration of rated power output, less than 0.3% for all wind turbines, was observed at Pearl Beach. The maximum duration of zero power output of between 35 to 60% was also observed at Pearl Beach. / Thesis (PhD)--University of Pretoria, 2017. / Mechanical and Aeronautical Engineering / PhD / Unrestricted

In the 21st century, the proliferation of steer-by-wire systems has become a central issue in the automobile industry. With such systems there is often an objective to minimise vibrations on the steering wheel to increase driver comfort. Nevertheless, steering wheel vibration is also recognised as an important medium that assists drivers in judging the vehicle's subsystems dynamics as well as to indicate important information such as the presence of danger. This has led to studies of the possible role of vibrational stimuli towards informing drivers of environment conditions such as road surface types. Numerous prior studies were done to identify how characteristics of steering wheel vibrational stimuli might influence driver road surface detection which suggested that there is no single, optimal, acceleration gain that could improve the detection of all road surface types. There is currently a lack of studies on the characteristics of transient vibrations of steering wheel as appear to be an important source of information to the driver road surface detection. Therefore, this study is design to identify the similarity characteristics of transient vibrations for answering the main research question: "What are the time-domain features of transient vibrations that can optimise driver road surface detection?" This study starts by critically reviewing the existing principles of transient vibrations detection to ensure that the identified transient vibrations from original steering wheel vibrations satisfy with the definition of transient vibrations. The study continues by performing the experimental activities to identify the optimal measurement signal for both identification process of transient vibrations and driver road surface detection without taking for granted the basic measurement of signal processing. The studies then identify the similarity of transient vibrations according to their time-domain features. The studies done by performing the high-dimensional reduction techniques associated with clustering methods. Result suggests that the time-domain features of transient vibrations that can optimise driver road surface detection were found to consist of duration (Δt), amplitude (m/s2), energy (r.m.s) and Kurtosis.

No description available.

No abstract provided. / Thesis / Doctor of Philosophy (PhD) / Scope and contents: The atomic vibrations in rubidium have been studied by the method of slow neutron spectrometry. The results have been analysed to yield atomic force constants which are used to compute the phonon frequency distribution. An interesting effect in the [00ζ]L branch has been examined, and an explanation of the observations is offered. Anharmonic calculations of frequency shifts and widths are presented, as well as a calculation of the anharmonic heat capacity. The third and fourth derivatives of the real space interatomic potential, which are required for these computations, are estimated in various ways. A determination of the lattice spacing of rubidium by neutron diffraction is described.

No description available.

No description available.

<p dir="ltr">Vibration is ubiquitous in the modern world, making it a topic that cannot be avoided during design, manufacture, and maintenance. Systems, such as civil structures and suspension of cars, are normally designed to stay in the attenuation zone to avoid harsh vibrations. Designing and manufacturing systems with the desired natural frequency distribution is easy. However, it is much harder to maintain the frequency response since materials keep aging as time goes by. To counter the effect of aging and attenuate vibrations, this thesis designed a meta-material that is capable of reprogramming its natural frequency distribution by inserting various masses at different locations. This ability to specifically adjust the system's natural frequency distribution is what we define as "Digital Inertia Programming".</p><p dir="ltr">The model consists of 12 identical unit cells, with each unit cell comprising two types of springs. By determining whether to insert a mass into the unit cell at various locations, the model achieves its programmability to adjust its natural frequency distribution. A "Binary Representation" is used to label the patterns of mass inserted in the model. Each unit cell is represented by a binary bit and a total of 12 bits are used to indicate the presence of mass in each unit cell. In the thesis, we mainly discuss bilaterally symmetrical patterns to avoid unwanted twisting. For the 12 unit cells, we can obtain a total of 128 bilaterally symmetrical patterns, resulting in 896 independent natural frequencies for the model. The number of patterns and independent natural frequencies will increase exponentially with the increase of the number of unit cells in the model.</p><p dir="ltr">An ideal one-dimensional analytical metamaterial model is developed. Lagrange's method is used to determine the system's mass matrix and stiffness matrix directly from the kinetic energy and potential energy equations. The natural frequencies and mode shapes are then calculated from the eigenvalue equation. Based on free response analysis and sensitivity analysis, the model successfully showed great programmability on frequency distribution by varying the insert patterns, as well as changing the value of the variables in the model, such as the weight of the inserts, the weight of the top mass, the stiffness of the unit cell wall spring and the stiffness of the connecting spring. When continuously varying the parameter, the model's natural frequency distribution also changes continuously, giving a possibility to adjust the natural frequency distribution by carefully adjusting the weight of the mass inserted at each location. Lastly, a forced-response analysis is performed, and the amplitude of the model's frequency response is plotted. This provides a straightforward view of the changes in the band gaps and the overall stiffness of the model by altering the patterns with two inserts.</p><p dir="ltr">A two-dimensional model is developed based on the one-dimensional model. The model retains the same 12 unit cells setup as the one-dimensional model. Aiming to ensure stability, the rectangular-shaped unit cell is now configured as a combination of two triangles. Taylor expansion and small angle approximation are used to eliminate nonlinear terms and triangular function terms in the stiffness matrix respectively. The model again shows its programmability by adjusting the variables of the model. Since the results of asymmetrical patterns are bounded by the results of symmetrical patterns, including the asymmetrical patterns increases the model's precision. However, the symmetrical patterns already provide a good representation of the model. The rotational motion is added to the inserts in the model, which further increases the model's complexity. In the model, the mode shapes are characterized by the rotational motion of inserts and the horizontal motion of inserts, which correspond to a zero strain mode of the model. A linear regression model is trained based on 100 bilaterally symmetrical patterns to predict the second lowest natural frequencies of the two-dimensional model for both symmetrical and asymmetrical patterns. The success in the linear regression model indicates the potential for applying machine learning algorithms to the design of meta-materials in the future.</p>

In this work, we constructed a new model for the collisional evolution of the Main Asteroid Belt. Our goals are to test the scaling law from the work of Benz & Asphaug (1999) and ascertain if it can be used for the whole belt. We want to find initial size-frequency distributions (SFDs) for the considered six parts of the belt, and to verify if the number of asteroid families created during the simulation matches the number of observed families as well. We used new observational data from the WISE satellite (Masiero et al., 2011) to construct the observed SFDs. We simulated mutual collisions of asteroids with a modified Boulder code (Morbidelli et al., 2009), in which the results of hydrodynamic (SPH) simulations from the work of Durda et al. (2007) are included. Because material characteris- tics can affect breakups, we created two models - for monolithic asteroids and for rubble-piles (Benavidez et al., 2012). The results for monolithic and rubble- -pile asteroids are comparable and in both cases the number of created families is, within uncertainties, consistent with the observations. A disagreement of the SFDs for a limited size range D 1 to 5 km a is a good motivation to conduct new SPH simulations with relatively small targets. 1