- Mechanical Engineering - Research Publications
Mechanical Engineering - Research Publications
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ItemEffect Of Arm Deweighting Using End-Effector Based Robotic Devices On Muscle Activity.Fong, J ; Crocher, V ; Haddara, R ; Ackland, D ; Galea, M ; Tan, Y ; Oetomo, D (IEEE, 2018)Deweighting of the limb is commonly performed for patients with a neurological injury, such as stroke, as it allows these patients with limited muscle activity to perform movements. Deweighting has been implemented in exoskeletons and other multi-contact devices, but not on an end-effector based device with single contact point between the assisting robot and the human limb being assisted. This study inves-tigates the effects of deweighting using an end-effector based device on healthy subjects. The muscle activity of five subjects was measured in both static postures and dynamic movements. The results indicate a decrease in the activity of muscles which typically act against gravity - such as the anterior deltoid and the biceps brachii - but also suggest an increase in activity in muscles which act with gravity - such as the posterior deltoid and the lateral triceps. This can be explained by both the change in required muscle-generated torques and a conscious change in approach by the participants. These observations have implications for neurorehabilitation, particularly with respect to the muscle activation patterns which are trained through rehabilitation exercises.
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ItemNo Preview AvailableA Practical Post-Stroke Elbow Spasticity Assessment Using an Upper Limb Rehabilitation Robot: A Validation StudyGuo, X ; Tang, J ; Crocher, V ; Klaic, M ; Oetomo, D ; Xie, Q ; Galea, MP ; Niu, CM ; Tan, Y (IEEE, 2022-07)Spasticity is a motor disorder characterised by a velocity-dependent increase in muscle tone, which is critical in neurorehabilitation given its high prevalence and potential negative influence among the post-stroke population. Accurate measurement of spasticity is important as it guides the strategy of spasticity treatment and evaluates the effectiveness of spasticity management. However, spasticity is commonly measured using clinical scales which may lack objectivity and reliability. Although many technology-assisted measures have been developed, showing their potential as accurate and reliable alternatives to standard clinical scales, they have not been widely adopted in clinical practice due to their low usability and feasibility. This paper thus introduces an easy-to-use robotic based measure of elbow spasticity and its evaluation protocol. Preliminary results collected with one post-stroke patient and one healthy control subject are presented and demonstrate the feasibility of the approach.
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ItemDigital Food Supply Chain Traceability FrameworkReddy, P ; Kurnia, S ; Tortorella, GL (MDPI, )
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ItemNo Preview AvailableUncertainty quantification and reduction using sensitivity analysis and Hessian derivativesSánchez, J ; Otto, K (American Society of Mechanical Engineers, 2021-01-01)Abstract We study the use of Hessian interaction terms to quickly identify design variables that reduce variability of system performance. To start we quantify the uncertainty and compute the variance decomposition to determine noise variables that contribute most, all at an initial design. Minimizing the uncertainty is next sought, though probabilistic optimization becomes computationally difficult, whether by including distribution parameters as an objective function or through robust design of experiments. Instead, we consider determining the more easily computed Hessian interaction matrix terms of the variance-contributing noise variables and the variables of any proposed design change. We also relate the Hessian term coefficients to subtractions in Sobol indices and reduction in response variance. Design variable changes that can reduce variability are thereby identified quickly as those with large Hessian terms against noise variables. Furthermore, the Jacobian terms of these design changes can indicate which design variables can shift the mean response, to maintain a desired nominal performance target. Using a combination of easily computed Hessian and Jacobian terms, design changes can be proposed to reduce variability while maintaining a targeted nominal. Lastly, we then recompute the uncertainty and variance decomposition at the more robust design configuration to verify the reduction in variability. This workflow therefore makes use of UQ/SA methods and computes design changes that reduce uncertainty with a minimal 4 runs per design change. An example is shown on a Stirling engine design where the top four variance-contributing tolerances are matched with two design changes identified through Hessian terms, and a new design found with 20% less variance.
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ItemNo Preview AvailableIntegrated LCA-MFA Framework for Gold Production from Primary and Secondary SourcesFarjana, SH ; Li, W (Elsevier BV, 2021-01-01)
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ItemNo Preview AvailableOn Singular Perturbation for a Class of Discrete-Time Nonlinear Systems in the Presence of Limit Cycles of Fast DynamicsLIU, H ; Tan, Y ; Bacek, T ; SUN, M ; Chen, Z ; Kulic, D ; Oetomo, D (IEEE, 2022)This paper extends the existing singular perturbation results to a class of nonlinear discrete-time systems whose fast dynamics have limit cycles. By introducing the discrete-time reduced averaged system, the main result (Theorem 1) shows that for a given fixed time interval, the solutions of the original system can be made arbitrarily close to the solutions of the reduced averaged system and the boundary layer system. From this result, the stability properties of the original system are obtained from the stability properties of the reduced averaged system and the boundary layer system. Simulation results support the theoretical findings.
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ItemVarying Joint Patterns and Compensatory Strategies Can Lead to the Same Functional Gait Outcomes: A Case StudyBacek, T ; SUN, M ; LIU, H ; Chen, Z ; Kulic, D ; Oetomo, D ; Tan, Y (IEEE, 2022)This paper analyses joint-space walking mechanisms and redundancies in delivering functional gait outcomes. Multiple biomechanical measures are analysed for two healthy male adults who participated in a multi-factorial study and walked during three sessions. Both participants employed varying intra- and inter-personal compensatory strategies (e.g., vaulting, hip hiking) across walking conditions and exhibited notable gait pattern alterations while keeping task-space (functional) gait parameters invariant. They also preferred various levels of asymmetric step length but kept their symmetric step time consistent and cadence-invariant during free walking. The results demonstrate the importance of an individualised approach and the need for a paradigm shift from functional (task-space) to joint-space gait analysis in attending to (a)typical gaits and delivering human-centred human-robot interaction.
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ItemAveraging for nonlinear systems on Riemannian manifoldsTaringoo, F ; Nesic, D ; Tan, Y ; Dower, PM (IEEE, 2013)This paper provides a derivation of the averaging methods for nonlinear time-varying dynamical systems defined on Riemannian manifolds. We extend the results on ℝ n to Riemannian manifolds by employing the language of differential geometry.
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ItemControl oriented modeling of turbocharged (TC) spark ignition (SI) engineSharma, R ; Nesic, D ; Manzie, C (SAE International, 2009-01-01)
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ItemIdle speed control using linear time varying model predictive control and discrete time approximationsSharma, R ; Nesic, D ; Manzie, C (IEEE, 2010-01-01)This paper addresses the problem of idle speed control of hydrogen fueled internal combustion engine (H2ICE) using model predictive control (MPC) and sampled data control (SDC) theories. In the first step, results from SDC theory and a version of MPC are collectively employed to obtain a rigorously developed new generic control strategy. Here, a controller, based on a family of approximate discrete time models, is designed within a previously proposed framework to have guaranteed practical asymptotic stability of the exact (unknown) discrete time model. Controller design, accomplished using MPC theory, is facilitated by successive online linearizations of the nonlinear discrete time model at each sampling instant. In the second step, the technique is implemented in the idle speed control of hydrogen internal combustion engine (H2ICE). Various conditions under which this theory can be implemented are presented and their validity for idle speed control problem are discussed. Simulations are presented to illustrate the effectiveness of the control scheme.