Showing papers by "Stephen Ekwaro-Osire published in 2017"

An improved numerical method for the mesh stiffness calculation of spur gears with asymmetric teeth on dynamic load analysis

Abstract: Gears are one of the most crucial parts of power transmission systems in various industrial applications. Recently, there emerged a need to design gear drivers due to the rising performance require...

Evaluation of Fatigue Crack Propagation of Gears Considering Uncertainties in Loading and Material Properties

Abstract: Failure prediction of wind turbine gearboxes (WTGs) is especially important since the maintenance of these components is not only costly but also causes the longest downtime. One of the most common causes of the premature fault of WTGs is attributed to the fatigue fracture of gear teeth due to fluctuating and cyclic torque, resulting from stochastic wind loading, transmitted to the gearbox. Moreover, the fluctuation of the torque, as well as the inherent uncertainties of the material properties, results in uncertain life prediction for WTGs. It is therefore essential to quantify these uncertainties in the life estimation of gears. In this paper, a framework, constituted by a dynamic model of a one-stage gearbox, a finite element method, and a degradation model for the estimation of fatigue crack propagation in gear, is presented. Torque time history data of a wind turbine rotor was scaled and used to simulate the stochastic characteristic of the loading and uncertainties in the material constants of the degradation model were also quantified. It was demonstrated that uncertainty quantification of load and material constants provides a reasonable estimation of the distribution of the crack length in the gear tooth at any time step.

Probabilistic Prognostics and Health Management: A Brief Summary

Abstract: This chapter gives a brief summary of probabilistic prognostics and health management (PPHM) and presents a framework to implement PPHM to predict remaining useful life (RUL) of energy systems efficiently and with minimal uncertainty. The chapter also presents the way forward by indicating that an interdisciplinary research is critical so as consortium of multidiscipline experts will come together and discuss the implementation of the framework for enhanced RUL prediction. The prediction of RUL with minimal uncertainty will significantly lower or avoid the downtime of energy systems and thereby reduce the cost of energy. The reduction in cost will make renewable energy, like wind energy, cheaper.

Uncertainty in Communication with a Sketch

Abstract: Sketches are one of the main tools for the communication of design ideas during the conceptual phase of the design process. In design communication, one of the major problems is the uncertainty associated with imprecisely defined sketches. There is a need to understand the uncertainty in the communication with sketches. This motivated the formulation of the research question: can uncertainty in communication with a sketch be quantified? To answer the research question, three specific aims were developed, namely, (1) determine the ranking of the features in a sketch, (2) determine the probability of importance of the features in a sketch, and (3) quantify the uncertainty of a sketch using Shannon’s normalized entropy. This paper demonstrates the effective use of the established framework for the quantification of uncertainty and contributes to the improvement of design communication with a sketch.

Determining Probability of Importance of Features in a Sketch

Abstract: Sketches can be categorized as personal, shared, persuasive, and handover sketches. Depending on each category, their level of ambiguity also varies. The applications of sketches include conceptual...

Probabilistic Model-Based Prognostics Using Meshfree Modeling

Abstract: Improved system reliability and reduced maintenance cost are guaranteed if the prediction of remaining useful life (RUL) is deemed to be accurate. Energy systems, like wind turbines, are the primary beneficiaries of this achievement as they tend to suffer from an unexpected early life failure of components that resulted in the loss of revenue and high maintenance costs. The issue of uncertainty in the prediction of a future state is yet a prevailing issue in prognostics and due attention is paramount. Hence, there is a need for establishing a comprehensive framework to quantify uncertainty in prognostics and this research addresses this issue by considering a research question that reads ‘can uncertainty considerations improve the prediction of RUL?’ The following specific aims were developed to answer the research question: (1) develop a meshfree cantilever beam with uncertainty in loading conditions, and (2) predict remaining useful life reliably. A probabilistic framework was developed that efficiently predicts remaining useful life of a component using a combination of meshfree model and degradation model. To account for prediction uncertainty, modeling and loading uncertainties are quantified and incorporated into the framework. As an example, the problem of a cantilever beam subjected to a fatigue loading was considered and local radial point interpolation method was used to find the stresses. The cyclic stresses and the damage model, constructed using the S-N equation, are implemented in the prognostics framework to predict the RUL. Uncertainties in the RUL were quantified in terms of probability density functions, cumulative distribution functions, and 98% confidence limit. The prognostics framework is flexible and can be used as a starting point for RUL prediction of other physical phenomena such as crack propagation, by incorporating more sources of uncertainties in order to make it comprehensive.