Doctoral Degrees (Mechanical and Mechatronic Engineering)

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Browsing Doctoral Degrees (Mechanical and Mechatronic Engineering) by browse.metadata.advisor "Bekker, Annie"

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    Inverse models for ice-induced propeller moments on a polar vessel.
    (Stellenbosch : Stellenbosch University, 2021-03) Nickerson, Brendon Mark; Bekker, Annie; Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering.
    ENGLISH ABSTRACT: It is necessary to quantify the loads experienced by the propellers of ice-going vessels.Knowledge of these loads will serve to improve propulsion design specifications and maintenance strategies for polar class ships. Recent developments include the inverse solutions of the external ice-induced propeller moments from indirect measurements on the propulsion shaft. These inverse solutions are performed using models that account for the dynamic influence of the shaft. Although torsional vibration calculations are required by design rules there is little information on the methodology external propeller moments as their use, in this context, is still relatively new. Full-scale propulsion shaft measurements were conducted on board the S.A. Agulhas II, in which the torque and angular velocity were captured, to be trans-formed into external propeller moments. Two inverse models of the propulsion shaft were investigated. The first is an existing model which represents the shaft as a combination of lumped masses. The inverse problem in this case is ill-posed and requires regularization. It was found that the assumptions made in the derivation of this model, that both the hydrodynamic and motor torques were constant, and its computational expense made it ill-suited for use in the inverse estimation of propeller moments. The second inverse model is newly developed and based on the superposition of the shaft modes, resulting in a well-posed problem. This model accounts for the modal inertia in the flexible modes of the shaft, as full-scale data indicated that this was important, and has increased accuracy and efficiency. To the author’s knowledge, this is the first model that has been efficiently applied to determine the inverse propeller moments from full-scale measurements for a complete voyage. The derivation of the corresponding estimated propeller load profiles is presented. The new model is suitable for the real-time monitoring of propeller loads, which can assist in ship operation.
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    The psychoacoustics of electric vehicle signature sound
    (Stellenbosch : Stellenbosch University, 2018-03) Swart, Daniel Johannes; Bekker, Annie; Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering.
    ENGLISH ABSTRACT: The automotive industry is currently exploring the global sound sphere to identify a pleasant, safe and unique electric vehicle signature sound. Drive-train acoustics contribute to the performance benchmark of vehicles in the marketplace. Electric vehicle sound signatures differ vastly from those of internal combustion engines. Questions arise as to how these signature sounds relate to consumer experiences, and how the positive attributes of these sounds can be extracted and enhanced. The presented work aimed to investigate the objectively and subjectively evaluated attributes of electric vehicle signature sound, and the associated consumer satisfaction. A subjective evaluation procedure for the classification of the noise produced by electric vehicles was adapted from existing methodologies for internal combustions engines. Itwas found that ‘Calm’, ‘Deep’, ‘Rumbling’,‘Creative’ and ‘Futuristic’ semantics should be added to existing tests to typically describe electric vehicle sound character. The sound signatures of six standard production electric vehicles and one hybrid electric vehicle were benchmarked through constant speed andWide Open Throttle drives. Time and frequency domain analyses were used to compare the different vehicles, and results revealed that electric vehicles contain substantial sound energy in the upper frequency bands due to the tonal components. Lower sound pressure levels were achieved in a multi-stage gearbox, with regards to the high frequency content associated with electric motors. High Prominence Ratio levels, in excess of 10 dB,were found for electric vehicles and current literature points to diminished consumer satisfaction as a result. Furthermore, standard production electric vehicle sound signatures were evaluated against enhanced sound stimuli, based on subjective semantics and objective metrics, to determine the dimensions of electric vehicle sound quality that can lead to improved consumer satisfaction. The methodologywas to undertake two independent subjective evaluations, performed by a jury of 32 and 52 members respectively, to determine the perceived electric vehicle sound experience. Results showed that Sharpness is fundamental to governing the electric vehicle sound experience. Secondly, the underlying dimensions of electric vehicle sound quality are sparsely described in literature and was therefore investigated. A factor analysis found that additional to the dimensions of refinement and powerfulness of internal combustion vehicle sound, electric vehicles also have a third dimension associated with a ‘Futuristic’ factor. Lastly, a consumer satisfaction model was proposed through multiple linear regression and the 95th percentile Sharpness value. The model yielded promising results for both interior and motorbay sound signatures and is proposed as a means of gauging consumer satisfaction for electric vehicle sound quality. The complexity of electric vehicle sound character was discussed and recommendations were offered with respect to the design considerations of future electric vehicle sound signatures. A holistic approach regarding both subjective and objective evaluation methods is recommended for future electric vehicle research, in order to fully understand the attributes that govern electric vehicle sound quality.
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    System identification and modal tracking on ship structures
    (Stellenbosch : Stellenbosch University, 2018-03) Soal, Keith Ian; Bekker, Annie; Bienert, J.; Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering.
    ENGLISH SUMMARY: are currently based mainly on dynamic response feedback. Navigators decide on how to operate the vessel based on how they feel it pitching, heaving, rolling and vibrating. The aim of this thesis is to investigate the idea of using system identification and modal tracking on polar vessels towards the development of a decision aiding system. System identification provides a powerful tool for building mathematical models of dynamic systems. An open source toolbox (openSID) for system identification using Stochastic Subspace Identification (SSI) was developed as a research and learning tool. Full scale measurements were performed on the research vessel Polarstern during an expedition to the Arctic. This is the first comprehensive data set including vibration responses and environmental parameters to span the entire operational profile of a research voyage to the Arctic. System identification successfully identified seven global modes in the bandwidth 2 - 10 Hz. Comparisons between different methods were used to cross validate results. A modal tracking algorithm was developed and relationships between identified modes and system inputs were observed. A novel method is developed to improve the uncertainty and sensitivity of system identification and tracking, based on a data driven statistical model and a Kalman filter. A key objective is to make experimental data maximally informative by using additional system inputs. The model was found to accurately re-create the training data set and was used to make predictions based on future system inputs. The Kalman filter estimates were observed to produce balanced and consistent results. These results demonstrate the potential of an ice force estimation and structural health monitoring system.