No description available.

No description available.

No description available.

Gait is the method of human locomotion using limbs. Recently, the analysis of human motion, specifically human gait, has received a large amount of research attention. Human gait can contain a wide variety of information that can be used in biometrics, disease diagnosis, injury rehabilitation, and load determination. In this dissertation, the development of a model-based gait analysis technique to classify external loads is presented. Specifically, the effects of external loads on gait are quantified and these effects are then used to classify whether an individual gait pattern is the result of carrying an external load or not. First of all, the reliability of using continuous relative phase as a metric to determine loading condition is quantified by intra-class correlation coefficients (ICC) and the number of required trials is computed. The ICC(2, 1) values showed moderate reliability and 3 trials are sufficient to determine lower body kinematics under two external load conditions. Then, the work was conducted to provide the baseline separability of load carriage conditions into loaded and unloaded categories using several lower body kinematic parameters. Satisfactory classification of subjects into the correct loading condition was achieved by resorting to linear discriminant analysis (LDA). The baseline performance from 4 subjects who were not included in training data sets shows that the use of LDA provides an 88.9% correct classification over two loaded and unloaded walking conditions. Extra weights, however, can be in the form of an external load carried by an individual or excessive body weight carried by an overweight individual. The study now attempts to define the differences in lower body gait patterns caused by either external load carriage, excessive body weight, or a combination of both. It was found significant gait differences due to external load carriage and excessive body weight. Principal Component Analysis (PCA) was also used to analyze the lower body gait patterns for four loading conditions: normal weight unloaded, normal weight loaded, overweight unloaded and overweight loaded. PCA has been shown to be a powerful tool for analyzing complex gait data. In this analysis, it is shown that in order to quantify the effects of external loads for both normal weight and overweight subjects, only two principal components (PCs) are needed. The results in this dissertation suggest that there are gait pattern changes due to external loads, and LDA could be applied successfully to classify the gait patterns with an unknown load condition. Both load carriage and excessive body weight affect lower body kinematics, but it is proved that they are not the same loading conditions. Methods in the current work also give a potential for new medical and clinical ways of investigating gait effects in osteoarthritis patients and/or obese people. / Ph. D.

A study was performed to investigate the factors that affect the accuracy of the procedures used by the Virginia Department of Transportation for design of drilled shaft sound wall foundations. Field load tests were performed on eight inch and nine inch diameter drilled shafts, and the results were compared to theoretical solutions for ultimate lateral load capacity. Standard Penetration Tests were run in the field and laboratory strength tests were performed on the soils from the test sites. It was found that published correlations between blow count and friction angle for sands and gravels can be used to estimate friction angles for the partly saturated silty and clayey soils encountered at the test sites. A spreadsheet program was developed to automate the process of determining design lengths for drilled shaft sound wall foundations. The spreadsheet was used to investigate the effects of different analysis procedures and parameter values on the design lengths of drilled shaft sound wall foundation. / Master of Science

To improve the recoverability and survivability of aircraft after damage, a better understanding of the flight dynamics and the structural loads is needed. However, damage can introduce asymmetries that complicate the modeling. An extended vortex lattice code is used to model the quasi-steady aerodynamic forces. The vortex lattice method provides the force distribution which is not available elsewhere. Snapshots from the vortex lattice model are used to generate a reduced order model (ROM). This ROM contains non-linear terms to account for non-linearities that the damage can introduce. The ROM is coupled with equations of motion which are able to account for instantaneous shifts in the center of gravity caused by the damage. This methodology is applied to the generic transport model (GTM) with the loss of a portion of the port wing tip. This model is used to examine the effects of the damage on the aircraft's trim and the stability of that trim. This model is also used to calculate the aerodynamic, inertial, and propulsive loads on the wing as the aircraft is maneuvering. / Master of Science

This paper presents a framework for tuning, validating, and quantifying uncertainties for flight loads. The flight loads are computed using a Nastran doublet lattice model and are validated using measured data from a flight loads survey for a Cessna Model 525B business jet equipped with Tamarack® Aerospace Group’s active winglet modification, ATLAS® (Active Technology Load Alleviation System). ATLAS® allows for significant aerodynamic improvements to be realized by reducing loads to below the values of the original, unmodified airplane. Flight loads are measured using calibrated strain gages and are used to tune and validate a Nastran doublet-lattice flight loads model. Methods used to tune and validate the model include uncertainty quantification of the Nastran model form and lead to an uncertainty quantified model which can be used to estimate flight loads at any given flight condition within the operating envelope of the airplane. The methods presented herein improve the efficiency of the loads process and reduce conservatism in design loads through improved prediction techniques. Regression techniques and uncertainty quantification methods are presented to more accurately assess the complexities in comparing models to flight test results. / Master of Science / This paper presents a process for correlating analytical airplane loads models to flight test data and validating the results. The flight loads are computed using Nastran, a structural modeling tool coupled with an aerodynamic loads solver. The flight loads models are correlated to flight test data and are validated using measured data from a flight loads survey for a Cessna Model 525B business jet equipped with Tamarack ® Aerospace Group’s active winglet modification, ATLAS ® (Active Technology Load Alleviation System). ATLAS ® allows for significant aerodynamic improvements and efficiency gains to be realized by reducing loads to below the values of the original, unmodified airplane. Flight loads are measured using a series of strain gage sensors mounted on the wing. These sensors are calibrated to measure aerodynamic loads and are used to tune and validate the Nastran flight loads model. Methods used to tune and validate the model include quantification of error and uncertainties in the model. These efforts lead to a substantially increased understanding of the model limitations and uncertainties, which is especially valuable at the corners of the operating envelope of the airplane. The methods presented herein improve the efficiency of the loads process and reduce conservatism in design loads through improved prediction techniques. The results provide a greater amount of guidance for decision making throughout the design and certification of a load alleviation system and similar airplane aerodynamic improvements.

The use of the squat exercise (and its derivatives) in gym-based settings is widespread owing to perceived functional performance enhancing effects. In particular, there has been preponderance amongst practitioners with loads that maximise power outputs (Pmax) based on a perception that mechanical peak power is directly related to explosive functional performance such as sprinting ability. The optimal muscular quality associated with squats remains elusive though, mostly due to methodological limitations in the research. The four experimental studies in this thesis sought to quantify the kinetic and kinematic outputs of a machine squat-jump and their relationship to sprinting ability, both descriptively and across a training period. First, an analysis of the kinetic and kinematic outputs of a machine squat-jump across a spectrum of loads was performed, with an emphasis on power output. Then, the relationship of these outputs with sprint ability was investigated. Correlations do not imply cause and effect, thus a training intervention was undertaken to quantify the relationships of the change in performance measures over time, and allow a comparison of different training protocols. Specifically, one training group was prescribed training loads based on individually determined peak power outputs, and the other based on traditional maximal strength training loads. Because the intention of this thesis was to enhance our knowledge of best strength training practice for elite sporting performance, highly trained athletes were specifically chosen as subjects, cognizant of the population specific nature of training adaptation. In study one, it was determined that the point on the power-load spectrum where peak and mean power occurred in the machine squat-jump was 21.6 ± 7.1 %1RM (mean ± SD) and 39.0 ± 8.6 %1RM respectively although there was considerable individual variation in these points. A broad plateau in power outputs was evident for most subjects with at most a 9.9% (90% confidence limits ±2.4%) difference in peak or means power at loads up to 20 %1RM either side of the peak. Studies two and three established that, of the multiple kinetic and kinematic measures investigated, only 1RM strength, work and impulse (all relative to body mass) provided any indication of useful kinetic / kinematic outputs that were potentially worthwhile developing for enhancing sprint performance, albeit with only moderate correlations (r = ~ -0.3). Additionally, the intercorrelations between maximal strength and explosive kinetic and kinematic measures were only moderate (r = ~0.3), casting doubt on the common practice of pursuing high 1RM strength with the intention of improving explosive muscle performance. The training study provided evidence that training at the load that maximised individual peak power output was no more effective for improving sprint ability than training at heavy loads and the changes in kinetic and kinematic outputs were not usefully related to changes in sprint ability.

Future management of helicopter fleets will be more heavily based on individual component damage tracking and less on legacy usage monitoring (flight parameter-based) methods. This enhances health assessment capabilities by taking into account the actual loads on a component-by-component basis. However, accurate loads prediction in rotating frame components remains a challenge. Even with advanced computational fluid dynamics (CFD) techniques, prediction of the unsteady aerodynamic loads acting on the rotor blades is computationally intensive and problematic in terms of accurate loads prediction across the entire flight regime of the helicopter. High-speed flight can potentially introduce both shock and near-stall effects within a given rotor rotation. Low-speed flight can include blade-vortex interaction effects, wherein flow from a given blade (vorticity loading from tip vortices) impinges upon the preceding blade, causing unsteady aerodynamic loading that is difficult to quantity and predict numerically. Vehicle maneuvering can produce significantly higher blade pitching moments than steady flight. All of these regimes combine to represent the loading history of the rotor system. Therefore, accurate loads prediction methods, in terms of matching peak-to-peak, magnitude, phase, as well as vibratory/harmonic content, are required that capture all flight regimes for all critical structural components. This research focuses on the development of a loads prediction method, known as the Load Confluence Algorithm (LCA), and its application to the analysis of a large set of flight test data from the NASA/US Army UH-60A Airloads Program. The LCA combines measured response at a prescribed set of locations with a numerical model of the rotor system. For a given flight condition (steady flight, maneuvers, etc.) the numerical simulation's predicted loads distribution is iteratively incremented (by harmonic) until convergence with measured loads is reached at the prescribed locations (control points). Predicted loads response at non-instrumented locations is shown to be improved as well, thus enhancing fatigue lifing methods for these components. The procedure specifically investigates the harmonic content of the applied loads and the improved prediction of the harmonic components. The impact of the enhanced accuracy on loads predictions on component structural fatigue is illustrated by way of an example. Results show that, for a limited sensor set (two 3-axis sensors per blade), blade loads are accurately predicted across a full range of flight regimes. Hub loads are best modeled using the pushrod as the control point. Results also show that load magnitude has a tremendous influence on damage, with a 25% over-estimation of vibratory load resulting in a damage factor of nearly 3. This research highlights the importance of accurate loads prediction for a rotorcraft life tracking program. Small inaccuracies in loads lead to dramatic errors in damage assessment.

There is a growing interest for the use of mechanistic procedures and analytical methods in the design and evaluation of pavement structure rather than empirical design procedures. The mechanistic procedures rely on predicting pavement response under traffic and environmental loading (i.e., stress, strain, and deflection) and relating these responses to pavement field performance. A research program has been developed at the Center for Pavement and Transportation Technology (CPATT) test track to investigate the impact of traffic and environmental parameters on flexible pavement response. This unique facility, located in a climate with seasonal freeze/thaw events, is equipped with an internet accessible data acquisition system capable of reading and recording sensors using a high sampling rate. A series of controlled loading tests were performed to investigate pavement dynamic response due to various loading configurations. Environmental factors and pavement performance were monitored over a two-year period. Analyses were performed using the two dimensional program MichPave to predict pavement responses. The dynamic modulus test was chosen to determine viscoelastic properties of Hot Mix Asphalt (HMA) material. A three-step procedure was implemented to simplify the incorporation of laboratory determined viscoelastic properties of HMA into the finite element (FE) model. The FE model predictions were compared with field measured pavement response. Field test results showed that pavement fully recovers after each wheel pass. Wheel wander and asphalt mid-depth temperature changes were found to have significant impact on asphalt longitudinal strain. Wheel wander of 16 cm reduced asphalt longitudinal strains by 36 percent and daily temperature fluctuations can double the asphalt longitudinal strain. Results from laboratory dynamic modulus tests found that Hot Laid 3 (HL3) dynamic modulus is an exponential function of the test temperature when loading frequency is constant, and that the HL3 dynamic modulus is a non-linear function of the loading frequency when the test temperature is constant. Results from field controlled wheel load tests found that HL3 asphalt longitudinal strain is an exponential function of asphalt mid-depth temperature when the truck speed and wheel loading are constant. This indicated that the laboratory measured dynamic modulus is inversely proportional to the field measured asphalt longitudinal strain. Results from MichPave finite element program demonstrated that a good agreement between field measured asphalt longitudinal strain and MichPave prediction exists when field represented dynamic modulus is used as HMA properties. Results from environmental monitoring found that soil moisture content and subgrade resilient modulus changes in the pavement structure have a strong correlation and can be divided into three distinct Seasonal Zones. Temperature data showed that the pavement structure went through several freeze-thaw cycles during the winter months. Daily asphalt longitudinal strain fluctuations were found to be correlated with daily temperature changes and asphalt longitudinal strain fluctuations as high as 650m/m were recorded. The accumulation of irrecoverable asphalt longitudinal strain was observed during spring and summer months and irrecoverable asphalt longitudinal strain as high as 2338m/m was recorded.