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The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases.

In this paper, we introduce the use of ontologies to implement the information developed and organized by resource planning tools into standard project management documents covering integrated cost, resource modeling and analysis, and visualization. The basic upper ontology used for NASA Space Operations is explained and the results obtained are discussed. This ontology-centered approach is looking for tighter connections between software, hardware, and systems engineering.

A sub-scale testbed for characterizing the dynamic performance of regenerable adsorbents for filtering trace contaminants (TCs) from cabin atmospheres was built and tested. Regenerable adsorbents employed in pressure-swing adsorption (PSA) systems operate in a dynamic environment, where they undergo repeated loading / regeneration cycles. Adsorbents have a given chemical specificity for non-methane TCs depending on their composition, and on the humidity and temperature at which they operate. However, their ability to filter TCs is also affected by contact time, cycle time, regeneration vacuum quality and thermal conditioning.

The paper presents a study on the prediction of wear for systems in which progressive wear affects the operating conditions responsible for the wear. A simple slider-crank mechanism with wear occurring at one of the joints is used to facilitate the study. For the mentioned mechanism, the joint reaction force responsible for the wear is, itself, affected by the progression of wear. It is postulated that the system dynamics and the wear are coupled and evolved simultaneously. The study involves integrating a dynamic model of the slider-crank mechanism (with an imperfect joint) into a wear prediction procedure. The prediction procedure builds upon a widely used iterative wear scheme. The accuracy of the predictions is validated using results from an actual slider-crank mechanism.

The current practice of gear design is based on the Lewis bending and Hertzian contact models. The former provides the maximum stress on the gear base, while the latter calculates pressure at the contact point between gear and pinion. Both calculations are obtained at the reference configuration and ideal condition; i.e., zero tolerances. The first purpose of this paper is to compare these two analytical models with the numerical results, in particular, using finite element analysis. It turns out that the estimations from the two analytical equations are closely matched with that from the numerical analysis. The numerical analysis also estimates the variation of contact pressure and bending stress according to the change in the relative position between gear and pinion. It has been shown that both the maximum bending stress and contact pressure occur at non-reference configuration, which should be considered in the calculation of safety factor.

In this paper, Bayesian statistics is utilized to update uncertainty associated with the fatigue life relation. The distribution for fatigue strain at a constant load cycle is determined using the initial uncertainty from analytical prediction and likelihood functions associated with test data. The Bayesian technique is a good method to reduce uncertainty and at the same time provides a conservative estimate, given the distribution of analytical prediction errors and variability of test data. First, the distribution of analytical fatigue model error is estimated using Monte Carlo simulation with uniformly distributed parameters. Then the error distribution is progressively updated by using the test variability as a likelihood function, which is obtained from field test data. The sensitivity of estimated distribution with respect to the initial error distribution and the selected likelihood function is studied.

Precision glass molding process is an attractive approach to manufacture small precision optical lenses in large volume over traditional manufacturing techniques because of its advantages such as low cost, fast time to market and being environment friendly. In this paper, we present a physics-based computational tool that predicts the final geometry of the glass element after molding process using the finite element method. Deformations of both glass and molds are considered at three different stages: heating, molding, and cooling. A 2D axisymmetric finite element model is developed to model the glass molding process. The proposed modeling technique is more efficient than the all-in-one modeling technique. The molds are assumed to be rigid, except for thermal expansion, at all time and glass treated as a flexible body during the compression. Details on identifying material parameters, modeling assumptions, and simplifications are discussed.

Operations involving autonomous vehicles require knowledge of the surrounding environment including other moving vehicles. The use of vision has been regarded as an enabling technology that can provide such information. Several important applications that would benefit from this technology is autonomous aerial refueling (AAR) and target tracking. This paper considers a sensor fusion approach using traditional IMU/GPS sensors with vision to facilitate the state estimation problem of moving targets. The proposed method makes use of a moving monocular camera to estimate the relative position and orientation of targets within the image by exploiting a known reference motion. The vision state estimation problem is solved using an homography approach that employs images containing both the reference and target vehicles. A simulation involving an unmanned aerial vehicle (UAV) and two ground vehicles is documented in this paper to demonstrate the algorithm and its accuracy.

The partial electrochemical reduction of carbon dioxide (CO2) using ceramic oxygen generators (COGs) is well known and widely studied. Conventional COGs use yttria-stabilized zirconia (YSZ) electrolytes and operate at temperatures greater than 700 °C. Operating at a lower temperature has the advantage of reducing the mass of the ancillary components such as insulation and heat exchangers (to reduce the COG oxygen output temperature for comfortable inhalation). Moreover, complete reduction of metabolically produced CO2 (into carbon and oxygen) has the potential of reducing oxygen storage weight if the oxygen can be recovered. Recently, the University of Florida developed novel ceramic oxygen generators employing a bilayer electrolyte of gadolinia-doped ceria and erbia-stabilized bismuth oxide (ESB) for NASA's future exploration of Mars.

The removal of volatile organic compounds (VOCs) from the air aboard spacecrafts is necessary to maintain the health of crewmembers. The use of photocatalysis has proven effective for the removal of VOCs. A majority of studies have focused on thin films, which have a low adsorption capacity for contaminants and intermediate oxidation byproducts. Thus, this study investigates the use of adsorbent materials impregnated or coated with titania to: (1) provide a system that can remove VOCs for a period of time in the absence of UV irradiation to reduce power requirements and/or offer contaminant removal in the event of lamp failure and (2) improve the photocatalytic oxidation efficiency by concentrating VOCs and intermediate oxidation byproducts near the surface of the photocatalyst. Two adsorbent materials (porous silica gel and BioNuchar120 activated carbon) and glass beads were tested as catalyst supports for the destruction of a target VOC, in this case methanol (Co = 50 ppmv).

A numerical modeling and design methodology for wear occurring in bodies that experience oscillatory contact is proposed. The methodology builds upon a widely used iterative wear prediction procedure. Two techniques are incorporated into the methodology to minimize the simulation computational costs. In the first technique, an extrapolation scheme that optimizes the use of resources while maintaining simulation stability is implemented. The second technique involves the parallel implementation of the wear prediction methodology. The methodology is used to predict the wear on an oscillatory pin joint and the predicted results are validated against those from actual experiments.

A magnetically agitated photocatalytic reactor (MAPR) has been developed and tested as a post-processor in the past using phenol and reactive red dye to simulate these waste components, yet these components ignore factors that may hinder a photocatalytic post processor including competitive adsorption of various organic compounds and their oxidation byproducts and the demonstrated detrimental effect of inorganic compounds such as ammonium bicarbonate on photocatalytic oxidation. To assess these effects, this work looks at photocatalytic oxidation of air evaporation subsystem (AES) ersatz water while modifying the photocatalyst mass, magnetic field current and frequency to find the optimal conditions. Additionally, the magnetic photocatalyst has been characterized to observe the assembled structures formed when exposed to the magnetic field array in the MAPR and the crystallinity of the titanium dioxide coating.

Finding a manner to effectively filter water to the purest standards is an ongoing battle for various sectors of science. We present a set of experiments that will report the preparation of the photocatalytic component of our composite particle via sol-gel coatings with titanium n-butoxide with subsequent heat treatment at 500°C for three hours in Argon. Our ultimate goal is to create a particle with regenerative capabilities along with a surface enhanced Raman scattering effect. Characterization techniques were performed using SEM-EDS, and XRD.

The main principles of artificial atmospheric design for a Martian Greenhouse (MG) are described based on: 1. Cost-effective approach to MG realization; 2. Using in situ resources (e.g. CO2, O2, water); 3. Controlled greenhouse gas exchange by using independent pump in and pump out technologies. We show by mathematical modeling and numerical estimates based on reasonable assumptions that this approach for Martian deployable greenhouse (DG) implementation could be viable. A scenario of MG realization (in terms of plant biomass/photosynthesis, atmospheric composition, and time) is developed. A list is given of technologies (natural water collection, MG inflation, oxygen collection and storage, etc.) that are used in the design. The conclusions we reached are: 1. Initial stocks of oxygen and water probably would be required to initiate plant germination and growth; 2. Active control of MG ventilation could provide proper atmospheric composition for each period of plant growth; 3.

The initial task in the preparation for Flight Experiment PGIM-01 (Plant Growth in Microgravity - 01) was the optimization of the plant nutrient system within the environment of the Plant Growth Facility (PGF – a Space Shuttle middeck locker plant growth unit). PGIM-01 entailed using the Transgenic Arabidopsis Gene Expression System (TAGES) to monitor effects of spaceflight-associated stress on gene expression. TAGES plants are genetically engineered arabidopsis plants designed with a sensitive reporter gene system that responds to a variety of environmental stresses. However, transgene expression can also be influenced by background environmental conditions. Thus, minimizing sources of background stress on the plants was crucial to ensure optimal growth and a high scientific return.

Once the infrastructure and in-vehicle systems can support dynamic route guidance, commercial vehicles may be among the early adopters. In order to estimate the value of an information system to the commercial vehicle operator, we consider the value of information in the context of a stochastic shortest path problem. In the presence of a dynamic route guidance system, there may be advantage to re-routing in-route based on real-time traffic information. After developing a mathematical model, we solve a numerical example in which dynamic route guidance produced a travel time savings of almost 11%.

A theoretical and experimental investigation into the modeling and design of piezoelectric flap actuators is described. The motivation for this study is to develop design tools for piezoelectric actuators in active flow control systems. In line with this goal, structural dynamic models of varying complexity must first be assessed. Theoretical modeling of the flaps is carried out using finite element analysis. For comparison, a companion experimental parametric study is executed in which ten otherwise identical piezo flaps with varying piezo patch sizes are fabricated in the Dynamics and Controls Laboratory at the University of Florida. The flaps are characterized using a laser displacement sensor and a scanning laser vibrometer to obtain the frequency response functions between the input voltage signal and the tip displacement and velocity of the flaps.

In this study, a model is developed in which a portion of the reacting flow in a plug flow reactor is recirculated back onto the inlet flow. In addressing the inherent non-uniformities in the primary zone of a combustor, the Recirculating Plug Flow Reactor should provide a superior method of correlating combustor performance over previous methods. This model was found to be governed by two parameters: the recirculation time required to complete the circuit and the ratio of the recirculated flow to the inlet flow. For a sufficiently large recirculation time, the characteristic reaction rate varied with this ratio. For a sufficiently small recirculation time, a distinct flame stability limit was observed.

The veiling glare effect in automotive vehicles consists of diffuse and specular scattering of sunlight onto and from the windshield. This effect occurs over a wide range of solar elevation angles and increases with increased degree of inclination of the windshield. Thus its effect on visual acuity must be considered in automotive design. The present research on the subject of veiling glare only addresses scattering from a clean windshield and ignores the larger effect of scattering from dust, dirt or haze on the front and back faces of the windshield since the latter is operator dependent (can be removed by cleaning the windshield). In this paper, we present an analysis of autmotive veiling glare that takes into account windshield reflectivity without and with coatings, and the characteristics of dashboard cover materials.

Finite element analysis postprocessor animation is a simple, easy to use tool in the visualization of occupant motion in crash simulation where finite element modeling is used. Based on a simple upper torso model, interpolated motion of a belt restrained occupant subjected to a 10g acceleration is animated.