Design of Experiments and Sample Surveys Commons^™

Factors Affecting Dimensional Precision Of Consumer 3d Printing, David D. Hernandez

International Journal of Aviation, Aeronautics, and Aerospace

This paper investigates the factors affecting dimensional precision of consumer-grade 3D printing, attempting to isolate and mitigate sources of error. The focus is on creating engineering prototypes of, tooling for, or finalized instances of mechanical devices. A specific fused deposition modeling printer – the Ultimaker 2 – is analyzed in terms of meeting precise physical dimensions, consistent shapes, and predictable surface finish. Extensive trial and error resulted in removal of several sources of bias, with square test articles exhibiting a lower-than-anticipated mean percentage error of -0.387% (SD = 0.559), a value comparable to other modern manufacturing techniques. A full …

Construction, Analysis, And Data-Driven Augmentation Of Supersaturated Designs, Alex J. Gutman

Theses and Dissertations

Screening designs are used in the early stages of industrial and computer experiments to find the most important input factors affecting a system's output. They provide an economical way to remove unimportant factors from further, potentially costly, experimentation. However, when an experiment has a large number of control factors and limited number of available runs, it is infeasible to run a traditional screening design. In these situations, experimenters can use supersaturated designs. A supersaturated design is a fractional factorial design that can screen a set of k factors in n runs, where k is greater than n -1. Unfortunately, they …

Blunt Impact Performance Evaluation Of Helmet Lining Systems For Military And Recreational Use, Jaclyn Siniora, Ryan Taylor, Darren Suey

Industrial Technology and Packaging

With the increasing problem in collegiate athletes experiencing injuries to the brain, different helmet liners where put to the test to see which liner provided athletes the greatest protection under specific conditions.

This senior project evaluates five different liners in football helmets. Each of the helmet liners were tested at three different temperatures: hot, cold, and ambient. Each helmet had seven different impact locations which were put to the test. The project was designed to be used to test ACH military combat liners as well. Due to shipping bottle necks the ACH combat liners have been left to future Cal …

An Investigation Of Process Parameters To Optimize The Fiber Diameter Of Electrospun Vascular Scaffolds Through Experimental Design, Steffi Wong

Biomedical Engineering

No abstract provided.

Detecting Near-Earth Objects Using Cross-Correlation With A Point Spread Function, Anthony P. O'Dell

Theses and Dissertations

This thesis describes a process to help discover Near-Earth Objects (NEOs) of larger than 140 meters in diameter from ground based telescopes. The process involves using Nyquist sampling rate to take data from a ground-based telescope and measuring the atmospheric seeing parameter, r₀, at the time of data collection. r0 is then used to create a point spread function (PSF) for a NEO at the visual magnitude limit of the telescope and exposure time. This PSF is cross-correlated with the Nyquist sampling rate image from the telescope to reduce the noise and therefore increase the detection probability of …

Maximizing Warfighter Capability Using Surveyed Necessity Measurement: Application To The Usaf F-15c Fleet, John M. Colombi, David R. Jacques, Dennis D. Strouble

Faculty Publications

Within the Department of Defense, with changing missions to counter dynamic and asymmetrical threats, the acquisition workforce strives to maximize capability for joint warfighting. How acquisition professionals measure and select capability improvements for the nation’s weapon systems is a perpetual challenge, made even more complex with constrained defense budgets. This study identifies a method for determining which upgrades should be purchased (production) for which aircraft in the F- 15C fleet by optimizing a capability proxy measure. Each upgrade’s “necessity” for a given mission area was obtained by conducting a survey of over 250 experienced F-15C pilots. The solution presented in …

Improving Mixed Variable Optimization Of Computational And Model Parameters Using Multiple Surrogate Functions, David Bethea

Theses and Dissertations

This research focuses on reducing computational time in parameter optimization by using multiple surrogates and subprocess CPU times without compromising the quality of the results. This is motivated by applications that have objective functions with expensive computational times at high fidelity solutions. Applying, matching, and tuning optimization techniques at an algorithm level can reduce the time spent on unprofitable computations for parameter optimization. The objective is to recover known parameters of a flow property reference image by comparing to a template image that comes from a computational fluid dynamics simulation, followed by a numerical image registration and comparison process. Mixed …

An Experimental Technique For The Evaluation Of Strain Dependent Material Properties Of Hard Coatings, Shad A. Reed, Anthony N. Palazotto, William P. Baker

Faculty Publications

A novel vibration experiment consisting of a free-free boundary condition, an electromagnetic excitation source, a vacuum chamber, and a laser vibrometer based surface measurement system has been developed that permits high levels of excitation on highly damped specimens with a minimal amount of unwanted systematic error. While some of the aspects of this experiment are not unique, when combined with a processing technique that accounts for the nonlinearities present in the system, this experiment permits, accurate measurement of strain dependent stiffness and damping properties of hard coatings at high strain levels. This procedure has been demonstrated using a titanium beam …

Improved Hyperspectral Image Testing Using Synthetic Imagery And Factorial Designed Experiments, Joseph P. Bellucci

Theses and Dissertations

The goal of any remote sensing system is to gather data about the geography it is imaging. In order to gain knowledge of the earth's landscape, post-processing algorithms are developed to extract information from the collected data. The algorithms can be intended to classify the various ground covers in a scene, identify specific targets of interest, or detect anomalies in an image. After the design of an algorithm comes the difficult task of testing and evaluating its performance. Traditionally, algorithms are tested using sets of extensively ground truthed test images. However, the lack of well characterized test data sets and …

Quantifying Initial Condition And Parametric Uncertainties In A Nonlinear Aeroelastic System With An Efficient Stochastic Algorithm, Daniel R. Millman

Theses and Dissertations

There is a growing interest in understanding how uncertainties in flight conditions and structural parameters affect the character of a limit cycle oscillation (LCO) response, leading to failure of an aeroelastic system. Uncertainty quantification of a stochastic system (parametric uncertainty) with stochastic inputs (initial condition uncertainty) has traditionally been analyzed with Monte Carlo simulations (MCS). Probability density functions (PDF) of the LCO response are obtained from the MCS to estimate the probability of failure. A candidate approach to efficiently estimate the PDF of an LCO response is the stochastic projection method. The objective of this research is to extend the …

An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap

Theses and Dissertations

This thesis extends the research found in Storm, Bauer, and Oxley, 2003. Data correlation effects and sample size effects on three classifier fusion techniques and one data fusion technique were investigated. Identification System Operating Characteristic Fusion (Haspert, 2000), the Receiver Operating Characteristic Within Fusion method (Oxley and Bauer, 2002), and a Probabilistic Neural Network were the three classifier fusion techniques; a Generalized Regression Neural Network was the data fusion technique. Correlation was injected into the data set both within a feature set (autocorrelation) and across feature sets for a variety of classification problems, and sample size was varied throughout. Total …

Computer-Based Methods For Constructing Two-Level Fractional-Factorial Experimental Designs With A Requirement Set, Steven L. Forsythe

Theses and Dissertations

This dissertation developed four methodologies for computer-aided experimental design of two-level fractional factorial designs with requirement sets (DOE/RS). The requirement sets identify all the experimental factors and the appropriate interaction terms to be evaluated in the experiment. Taguchi graphs and similar manual methods provide techniques for solving the DOE/RS problem. Unfortunately, these methods are limited because they become difficult to use as the number of factors or interaction terms exceeds ten. This research showed that the DOE/RS problem belongs to a class of difficult-to-solve problems known as NP-Complete. It is the combinatorial nature of NP-Complete problems that causes them to …

A Parametric Regression Of The Cost Of Base Realignment Action (Cobra) Model, Douglas D. Hardman, Michael S. Nelson

Theses and Dissertations

This study develops a parametric model that is capable of generating accurate estimates of the costs to close Air Force installations. The new model is based upon, but much simpler to use than, the Cost of Base Realignment Action (COBRA) model. COBRA is an economic cost analysis model that requires a minimum of 250 inputs and as many as 700 inputs. The new parametric model requires just 10 input variables and was developed using least squares multiple regression. Comparison of the new parametric model to COBRA indicates that it captures 91 percent of the variance in cost estimates generated by …