Model-based Design Development and Control of a Wind Resistant Multirotor UAV

Multirotor UAVs have in recent years become a trend among academics, engineers and hobbyists alike due to their mechanical simplicity and availability. Commercial uses range from surveillance to recreational flight with plenty of research being conducted in regards to design and control. With applications towards search and rescue missions in mind, the main objective of this thesis work is the development of a mechanical design and control algorithm aimed at maximizing wind resistance. To these ends, an advanced multirotor simulator, based on helicopter theory, has been developed to give an accurate description of the flight dynamics. Controllers are then designed and tuned to stabilize the attitude and position of the UAV followed by a discussion regarding disturbance attenuation. In order to study the impact of different design setups, the UAV model is constructed so that physical properties can be scaled. Parameter influence is then investigated for a specified wind test using a Design of Experiments methodology. These results are combined with a concept generation process and evaluated with a control engineering approach. It was concluded that the proposed final design should incorporate a compact three-armed airframe with six rotors configured coaxially

Development and Evaluation of Modeling Approaches for Extrusion-based Additive Manufacturing of Thermoplastics

This work focuses on evaluating different modeling approaches and model parameters for thermoplastic AM, with the goal of informing more efficient and effective modeling approaches. First, different modeling approaches were tested and compared to experiments. From this it was found that all three of the modeling approaches provide comparable results and provide similar results to experiments. Then one of the modeling approaches was tested on large scale geometries, and it was found that the model results matched experiments closely. Then the effect of different material properties was evaluated, this was done by performing a fractional factorial design of experiments where the factors were ±15% of the baseline material properties. From this it was found that coefficient of thermal expansion (CTE) is by far the most important material property for the simulated warpage. This test was repeated with a simulated desktop printer, simulated commercial printer and a simulated room scaled printer to evaluate if the relevant material properties change as a function of length scale; it was found that as length scale increases, conduction becomes increasingly important, but this effect was still small compared to that of CTE. Finally, the effect of the environment was evaluated by running a Latin hypercube Design of Experiments (DOE) over environmental factors; it was found that the most important effects are the bed and enclosure temperatures. It also pointed to the feasibility of using radiative heating to mitigate warpage, because as length scale increases natural convection becomes less important. This work is significant because it leverages modeling and simulation to evaluate the effects of the different phenomena in 3D printing and points out some of the gaps in the current state of the art that are not evident from performing simple experiments or simple simulations, namely implementing a model for build plate adhesion

SIMULTANEOUS OPTIMIZATION OF MACRONUTRIENT FACTORS IN PLANT TISSUE CULTURE USING TURMERIC (Curcuma longa L.) AS A MODEL

Murashige and Skoog 1962 performed one-factor-at-a-time (OFAT) experimentation in order to regenerate tobacco callus on semi-solid agar medium. This work became an established medium for tissue culture micropropagation and experimentation. Micropropagation is done in niche markets with herbaceous perennials, among other crops, and the optimization of various inputs to produce maximal responses is a necessary step towards process development. This current study of macronutrient factors simultaneously altered media volume, amount of tissue (plants per vessel), sucrose, nitrogen (as NO3- and NH4+ ions), and K+ in a d-optimal design space with only 55 experimental units (including 5 true replicates). The first study examined these macronutrients in a micronutrient limited environment, and probed further areas in the design space for exploration. The second study, at full MS meso- and micronutrient values, identified P and Mg to be deficient in standard formulations when compared with field-grown plantlets of turmeric, while identifying differences in the definition of plantlet quality. Plantlet quality was defined in three very distinct ways. These three optimization choices were demonstrated to have very different optima as defined in this experiment. First: multiplication is maximal with low plantlet density (3 plantlets per vessel), high media volume (45 ml), and 4% sucrose in the vessel. Secondly: the number of new plants produced per vessel was highest when the most plants were put in a vessel, at the highest media volume, and highest sucrose % tested. Lastly, those individual plantlets transferred to the greenhouse (100% plantlet survival) which grew the most (via fresh mass gains) were the most massive (fresh mass) came from vessels with: 3 plantlets per vessel, containing no NH4+ (all K+), 45 ml media volume (the highest amounts of media components holding concentrations constant), and the lowest concentration of sucrose tested (1.5%). These two experiments result in separation of optima demonstrating the need for differing tissue culture medium formulations that are dependent upon the process of interest, while identifying possible areas of future work necessary for in vitro nutritive media formulations in turmeric (Curcuma longa L.), an important medicinal herbaceous perennial

Use of orthogonal arrays, quasi-Monte Carlo sampling and kriging response models for reservoir simulation with many varying factors

Asset development teams may adjust simulation model parameters using experimental design to reveal which factors have the greatest impact on the reservoir performance. Response surfaces and experimental design make sensitivity analysis less expensive and more accurate, helping to optimize recovery under geological and economical uncertainties. In this thesis, experimental designs including orthogonal arrays, factorial designs, Latin hypercubes and Hammersley sequences are compared and analyzed. These methods are demonstrated for a gas well with water coning problem to illustrate the efficiency of orthogonal arrays. Eleven geologic factors are varied while optimizing three engineering factors (total of fourteen factors). The objective is to optimize completion length, tubing head pressure, and tubing diameter for a partially penetrating well with uncertain reservoir properties. A nearly orthogonal array was specified with three levels for eight factors and four levels for the remaining six geologic and engineering factors. This design requires only 36 simulations compared to (26,873,856) runs for a full factorial design. Hyperkriging surfaces are an alternative model form for large numbers. Hyperkriging uses the maximum likelihood variogram model parameters to minimize prediction errors. Kriging is compared to conventional polynomial response models. The robustness of the response surfaces generated by kriging and polynomial regression are compared using jackknifing and bootstrapping. Sensitivity analysis and uncertainty analysis can be performed inexpensively and efficiently using response surfaces. The proposed design approach requires fewer simulations and provides accurate response models, efficient optimization, and flexible sensitivity and uncertainty assessment

A practical protocol for the experimental design of comparative studies on water treatment

The design and execution of effective and informative experiments in comparative studies on water treatment is challenging due to their complexity and multidisciplinarity. Often, environmental engineers and researchers carefully set up their experiments based on literature information, available equipment and time, analytical methods and experimental operations. However, because of time constraints but mainly missing insight, they overlook the value of preliminary experiments, as well as statistical and modeling techniques in experimental design. In this paper, the crucial roles of these overlooked techniques are highlighted in a practical protocol with a focus on comparative studies on water treatment optimization. By integrating a detailed experimental design, lab experiment execution, and advanced data analysis, more relevant conclusions and recommendations are likely to be delivered, hence, we can maximize the outputs of these precious and numerous experiments. The protocol underlines the crucial role of three key steps, including preliminary study, predictive modeling, and statistical analysis, which are strongly recommended to avoid suboptimal designs and even the failure of experiments, leading to wasted resources and disappointing results. The applicability and relevance of this protocol is demonstrated in a case study comparing the performance of conventional activated sludge and waste stabilization ponds in a shock load scenario. From that, it is advised that in the experimental design, the aim is to make best possible use of the statistical and modeling tools but not lose sight of a scientific understanding of the water treatment processes and practical feasibility

Recent Developments in Nonregular Fractional Factorial Designs

Nonregular fractional factorial designs such as Plackett-Burman designs and other orthogonal arrays are widely used in various screening experiments for their run size economy and flexibility. The traditional analysis focuses on main effects only. Hamada and Wu (1992) went beyond the traditional approach and proposed an analysis strategy to demonstrate that some interactions could be entertained and estimated beyond a few significant main effects. Their groundbreaking work stimulated much of the recent developments in design criterion creation, construction and analysis of nonregular designs. This paper reviews important developments in optimality criteria and comparison, including projection properties, generalized resolution, various generalized minimum aberration criteria, optimality results, construction methods and analysis strategies for nonregular designs.Comment: Submitted to the Statistics Surveys (http://www.i-journals.org/ss/) by the Institute of Mathematical Statistics (http://www.imstat.org

Development of a Wireless Real-Time Productivity Measurement System for Rapid Bridge Replacement

Increased attention has been paid to rapid bridge replacement, one of the critical components of the nation’s transportation network, since the terrorist attacks on September 11, 2001. To enhance the capability of rapid replacement of damaged bridges after extreme events, a prototype wireless real-time productivity measurement system has been developed. The developed system has a potential not only to improve the accuracy of construction schedule but also to strengthen the communication and coordination among parties involved in the replacement process after extreme events by providing accurate productivity information in real time. To validate the developed system, field experiments were conducted at three construction sites. Results of data analyses indicate that it is feasible to use the developed system to measure on-site productivity in real time; and productivity measurements were accurate and could be shared among all parties involved in the replacement process

Ceramic processing: Experimental design and optimization

The objectives of this paper are to: (1) gain insight into the processing of ceramics and how green processing can affect the properties of ceramics; (2) investigate the technique of slip casting; (3) learn how heat treatment and temperature contribute to density, strength, and effects of under and over firing to ceramic properties; (4) experience some of the problems inherent in testing brittle materials and learn about the statistical nature of the strength of ceramics; (5) investigate orthogonal arrays as tools to examine the effect of many experimental parameters using a minimum number of experiments; (6) recognize appropriate uses for clay based ceramics; and (7) measure several different properties important to ceramic use and optimize them for a given application