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In society, personal load carriage systems (backpacks) are commonly used to transport loads by foot, however, they have also been implicated in causing injuries. The aim of this study was to develop a model for load carriage which could be used to determine safety limits in humans. To start, a number of experiments were conducted to determine the appropriateness of using pressure mapping technology to measure peak and mean pressures acting on humans during load carriage limits. Tests of accuracy and repeatability were performed using three common pressure mapping technologies: capacitance, piezoresistive and resistive ink. Pressure mapping was tested statically and dynamically on a human-like flat surface, as well as on human shoulder-shaped model. Error was found to be ≥ 20% on static flat and curved surfaces and it rose to 36-51% under dynamic conditions. Since pressure mapping would require significant modifications before it could be used to study human load carriage, a psychophysical approach was used instead. For this approach, an epidemiological study of pain was conducted based on 48 subjects who used multiple backpack designs to complete occupationally relevant tasks. As a result, pain trends and new methods of data analysis were identified that had potential use on human trials. In a final study, pain mapping, quantification of pain intensity, and physiological/motor testing were conducted on humans performing endurance exercise with light to heavy payloads. Results showed that all subjects were able to exercise with a 15-35 kg payload for 45 minutes and with a 50 kg payload for 30 minutes, without stopping. As well, pain was found to be highest in the anterior acromial (shoulder) region, particularly for the 50 kg payload (mean peak pain = 3.4/10). Based on these findings, two models were proposed: an assertive model and a conservative model to allow prediction of human load carriage limits for endurance exercise. / Thesis (Ph.D, Rehabilitation Science) -- Queen's University, 2007-10-06 15:33:31.933

The Ergonomics Research Group at Queen’s University, supported by the Workplace and Safety Insurance Board, has been developing an on-line system to estimate peak and cumulative joint loading in the workplace. This study will aid the project by examining the muscle activation levels (MALs) in upper extremity and trunk muscles during a manual lifting task using both hands. It was hypothesized that MAL’s are correlated with the magnitude of the load in the hands and thus could be used to predict the load which in turn will be used to predict the lower back moments. Alterations in the muscle activation patterns due to lifting different loads were examined. Electromyographic signals (EMG) and kinematic data were recorded from different sites on the trunk and upper limb as subjects lifted a load from the floor to a shelf using squat, stoop and freestyle lift techniques. All raw EMG data were processed to obtain the linear envelopes (LE) which provides estimates of the MAL’s. The peak, mean and area of the linear envelopes were calculated. Using regression analysis, a relationship between the parameters and load lifted was found to exist. A non-linear parallel cascade type architecture was used to develop a model to predict the load in the hands. The model uses the EMG parameters as inputs and fits the data via linear and non-linear cascades to the output, i.e. the load in the hands. A model was successfully developed for the squat lift posture using the area, peak and mean of the zero-normalized EMG LE recorded from the erector spinae (L4 level), with a prediction error of ± 1.03kg and for the stoop posture, a prediction error of ± 2.34kg. Given the predicted loads, moments in the lower back were computed using the method of Hof (1992). / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-09-28 16:15:23.077

This thesis is the result of an investigation to assess the potential of the continuation method to solve the minimum cost optimal power flow problem. For this purpose, a restart homotopy continuation method algorithm is developed, which contains in essence two phases. / The pertinent steps of the first phase are as follows: (1) Create a sub-problem of the complete optimal power flow problem by relaxing boundary limits on all functional variables, namely voltages at load buses, line flows and reactive generations. (2) Parameterize a subset of the whole set of controls which comprises initially of tap-changers, phase-shifters, shunt controllers, and the voltages at generation buses. (3) Optimize the resulting problem. / The solution in step (3) is used as an initial starting point in a continuation process, designed to track this solution to the optimal solution of the sub-problem defined in step (1). The tracking is accomplished via a predictor-corrector path following algorithm embodying certain special features, such that the solution accuracy can be improved to any desired degree through a flexible restart feature developed in this study. Within the tracking process only a subset (identified in step 2 above) of the whole set of controls require specific monitoring for break-points. This feature greatly reduces the computational burden. Termination of the first phase marks an operating point in which all controls are strictly feasible. / If, following the termination of the first phase, functional variables previously ignored prove to be within their respective bounds, the solution to the sub-problem becomes the solution to the complete optimal power flow problem. However, should functional variables violate their bounds the second phase of the algorithm is invoked, which in essence creates a new sub-problem by changing the roles of the control and violated dependent variables, such that the newly modified sub-problem maintains the same basic structure as its predecessor. / Phase I is invoked again at this juncture to solve the modified sub-problem. This process is repeated in cycles until the Kuhn-Tucker optimality conditions are satisfied. Simulations suggest that convergence is usually achieved within two or three Phase I/II cycles. / This being a method unique to the minimum cost optimal power flow problem, numerous examples (up to 118 buses) have been tested and compared against the commercial code MINOS. The newly proposed algorithm appears to be faster and more reliable.

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