Engineering

Thirteen volunteer panelists were trained according to Standard Method 2170, flavor profile analysis (FPA). Following training these panelists underwent triangle test screening to determine whether or not they could detect the odorants used in this study. Following triangle testing, panelists underwent directional difference testing to determine if temperature affected odor perception when presented with two water samples. Following directional difference testing, panelists used FPA and evaluated water samples that contained odorants at either 25 C or 45 C. Samples containing geosmin cooled to 5 C were also evaluated.

In an attempt to reach a better understanding of the properties and critical behavior of non-equilibrium systems, we investigate the steady state properties of three simple models, variations of the prototype, the driven Ising lattice gas. Our first system studied is the bilayer model, a stack of two driven Ising lattice gases allowed to interact. We study this model using a very simple analytic approximation, the high temperature expansion. Building on existing simulation data and field theory results, our goal is to test how faithfully the series expansion can reproduce the Monte Carlo phase diagram. We find that the agreement between our calculations and the already reported simulations results is remarkably good. Next, we investigate the critical behavior of a two-dimensional Ising lattice gas driven into a non-equilibrium steady state, subject to a local modification of the dynamics, namely, having anisotropic attempt frequencies for exchanges along different spatial directions.

Nanoparticle based devices are becoming of great interest because of their single-electron transport behavior, and high surface charge density. Nanoparticle based devices operate at low power, and are potentially highly stable and extremely robust. Making interconnections to nanoparticle devices, however, has been an impending issue. Also percolating/conductive array of nanoparticles is not easy to build since repulsion between the charged nanoparticles causes them to deposit at distance significantly larger for electron tunneling. In this study, we resolve these challenges to make nanoparticle based electronic devices. Using biological (bacteria) or physical (polyelectrolyte fiber) scaffolds, we selectively deposited percolating array of 30 nm Au nanoparticles, to produce a highly versatile nanoparticle-organic hybrid device.

An investigation was conducted to assess the usefulness of anti-optimization in the process of validating of aerodynamic codes. Anti-optimization is defined here as the intentional search for regions where the computational and experimental results disagree. Maximizing such disagreements can be a useful tool in uncovering errors and/or weaknesses in both analyses and experiments.

The codes chosen for this investigation were an airfoil code and a lifting line code used together as an analysis to predict three-dimensional wing aerodynamic coefficients. The parameter of interest was the maximum lift coefficient of the three-dimensional wing, CL max. The test domain encompassed Mach numbers from 0.3 to 0.8, and Reynolds numbers from 25,000 to 250,000.

A simple rectangular wing was designed for the experiment. A wind tunnel model of this wing was built and tested in the NASA Langley Transonic Dynamics Tunnel. Selection of the test conditions (i.e., Mach and Reynolds numbers) were made by applying the techniques of response surface methodology and considerations involving the predicted experimental uncertainty. The test was planned and executed in two phases. In the first phase runs were conducted at the pre-planned test conditions. Based on these results additional runs were conducted in areas where significant differences in CL max were observed between the computational results and the experiment – in essence applying the concept of anti-optimization. These additional runs were used to verify the differences in CL max and assess the extent of the region where these differences occurred.

Since the end of the cold war the United States is the single dominant naval power in the world. The emphasis of the last decade has been to reduce cost while maintaining this status.

As the Navy’s infrastructure decreases, so too does its ability to be an active participant in all aspects of ship operations and design. One way that the navy has achieved large savings is by using the Military Sealift Command to manage day to day operations of the Navy’s auxiliary and underway replenishment ships. While these ships are an active part of the Navy’s fighting force, they infrequently are put into harm’s way. The natural progression in the design of these ships is to have them fully classified under current American Bureau of Shipping (ABS) rules, as they closely resemble commercial ships. The first new design to be fully classed under ABS is the T-AKE. The Navy and ABS consider the T-AKE program a trial to determine if a partnership between the two organizations can extend into the classification of all new naval ships. A major difficulty in this venture is how to translate the knowledge base which led to the development of current military specifications into rules that ABS can use for future ships.

The specific task required by the Navy in this project is to predict the inherent availability of the new T-AKE class ship. To accomplish this task, the reliability of T-AKE equipment and machinery must be known. Under normal conditions reliability data would be obtained from past ships with similar mission, equipment and machinery. Due to the unique nature of the T-AKE acquisition, this is not possible. Because of the use of commercial off the shelf (COTS) equipment and machinery, military equipment and machinery reliability data can not be used directly to predict T-AKE availability. This problem is compounded by the fact that existing COTS equipment and machinery reliability data developed in commercial applications may not be applicable to a military application. A method for deriving reliability data for commercial equipment and machinery adapted or used in military applications is required.