Mechanical Engineering - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 164
-
ItemNo Preview Available
-
ItemNo Preview Available
-
ItemDirect Numerical Simulation of Riblets Applied to Gas Turbine Compressor Blades at On- and Off- Design Incidences(ASME, 2023-06-26)Any realizable increase in gas turbine efficiency has significant potential to reduce fuel burn and environmental impact. Streamwise micro-groove surfaces (‘riblets’) are well-known as a passive surface treatment to reduce drag, which may be useful in the context of increasing overall gas turbine efficiency. This paper presents the first direct numerical simulation of potentially performance-enhancing riblets on an axial flow high pressure compressor blade, where the micro-geometry of the riblets is fully resolved. The midspan section of a NACA6510 profile is considered at an engine-relevant true chord Reynolds number of 700,000 and Mach number 0.5 based on inlet conditions. Fixed triangular (or sawtooth) riblets are considered in the present numerical campaign. The current high-fidelity computational method permits the extraction of data such as the wall shear stress directly from the riblet surface. At the design incidence, the riblets tend to promote earlier transition to a turbulent flow over the suction side, yet significantly reduce the skin friction over the entire downstream chord to the trailing edge. The riblets reduce the viscous force over the blade by up to 18% at this nominal inflow incidence. Thus the current dataset permits new insight into the action of the riblets, since most studies of riblets on turbomachinery blades have been conducted experimentally where direct measurements of skin friction are not possible. The riblets are also able to reduce the skin friction over the high pressure compressor blade at off-design incidences, a promising result given axial flow compressors must cope with variable operating conditions.
-
ItemNo Preview AvailableExploring the Utility of Crutch Force Sensors to Predict User Intent in Assistive Lower Limb Exoskeletons(IEEE, 2022)The adoption of assistive lower limb exoskeletons in built environments is reliant on the further development of these devices to handle the varied conditions experienced in everyday life. The required development includes more varied and flexible gait patterns, but also appropriate user interfaces to enable fluid gait. This work explores the properties of an algorithm used to predict user intent based on sensors onboard a user-balanced robotic exoskeleton system. Specifically, classification algorithms built with different input data sets are compared - with varying detail of the interaction forces between the crutches and the ground, and the duration of the data sample used to make the prediction. Data were collected with one able-bodied participant using an exoskeleton, training three independent classifiers corresponding to different exoskeleton states. The results indicate the value of including information about the interaction forces between the crutches and the ground in improving prediction accuracy, with increasing prediction window also generally resulting in an increase in prediction accuracy. Whilst no categorical recommendation can be made with respect to either parameter, these results provide a baseline which can be used in conjunction deliberate consideration of the costs associated with implementation.
-
ItemNo Preview AvailableInvestigating User Volitional Influence on Step Length in Powered Exoskeleton Designed for Users with SCI(IEEE, 2022)Volitional movement from users of assistive lower limb exoskeletons may be exploited to increase the controlled variability in the movements of a human-exoskeleton system. This may in turn allow these devices to handle the variability encountered in the terrain of everyday life. This study aimed to investigate the degree to which users can volitionally influence step length, when using an assistive exoskeleton designed for users with spinal cord injury (SCI) running a fixed robotic exoskeleton trajectory. An experiment was conducted to investigate the accessible range of step lengths when five able-bodied participants and one participant with SCI piloted a user-balanced exoskeleton. Participants were asked to take steps as large as possible ("large") and as small as possible ("small"), with the able-bodied individuals asked to minimise use of their leg muscles, with step length of each step measured. Surface electromyography (sEMG) data were collected on major leg muscles of the able-bodied subjects to monitor their muscle activities with a novel processing method introduced to facilitate discussion in the context of users with SCI. The results demonstrate that a user can intentionally manipulate the resulting step length, with every participant having significantly different large and small step sizes (p < 0.05). However, large variations were observed between individuals in terms of absolute step lengths and difference between large and small steps. Moreover, the range of step length (normalised by the leg length) ranged from 0.237 to 0.375 for the able-bodied subjects and 0.245 for the individual with SCI. Although positive correlation was present between the sEMG data and resulting step lengths, the result was not statistically significant (p > 0.05).
-
ItemEffect Of Arm Deweighting Using End-Effector Based Robotic Devices On Muscle Activity.(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.
-
ItemNo Preview AvailableA Practical Post-Stroke Elbow Spasticity Assessment Using an Upper Limb Rehabilitation Robot: A Validation Study(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.
-
Item
-
ItemNo Preview AvailableUncertainty quantification and reduction using sensitivity analysis and Hessian derivatives(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.
-
ItemNo Preview AvailableIntegrated LCA-MFA Framework for Gold Production from Primary and Secondary Sources(Elsevier BV, 2021-01-01)