This project develops a quantitative method to evaluate the seismic risk for portable GSE at Vandenberg Air Force Base. Using the latest probability data available from the USGS, risk thresholds are defined for portable GSE having the potential to cause a catastrophic event. Additionally, an example tool for design engineers was developed from the seismic codes showing the tipping hazard case can be simplified into strict geometrical terms. The misinterpretation and confusion regarding the Range Safety 24 Hour Rule exemption can be avoided by assessing seismic risk for portable GSE. By using the methods herein to quantify and understand seismic risk, more informed risk decisions can be made by engineering and management. The seismic codes and requirements used and referenced throughout include but are not limited to IBC, ASCE 7, EWR 127-1, and AFSPCMAN 91-710.

Unmanned Aerial Systems (UAS) are a growing asset. Currently UAS are on the cutting edge with resources being spent developing the capabilities mostly for military use. This project is intended to create a system for non-defense customers. Specifically, the Operationally Responsive Aircraft (ORA) will appeal to academic institutions, individual consumers, future customers new to the UAS industry, as well as anybody trying to get airtime for custom sensors. The system developed in this project utilizes dual aluminum external payload bays attached to a ParkZone Radian aircraft. Each external payload bay can contain approximately 500 $\text{cm}^3$, with a height and width limit of 4.1 cm and 11.0 cm respectively. The custom sensors must weigh less than or equal to 3.2 lbs combined. The external payload bays were designed to hold an imaging payload which produces a composite map of the land surveyed. The system incorporates an Arduino Uno, SD Shield, as well as a CMOS camera and board. The processor saves individual images to an SD card. Once the aircraft has landed, the operator combines the images with Microsoft Research Image Composite Editor to create the composite map. This imaging payload has a NIIRS value of 4.0 +/- 0.4, which is equivalent to identifying a basketball court within a residential environment.

The Naval Postgraduate School is currently developing their first CubeSat, the Solar Cell Array Tester CubeSat, or NPS-SCAT. Launching a CubeSat, such as NPS-SCAT, requires environmental testing to ensure not only the success of the mission, but also the safety of other CubeSats housed in the same deployer. This thesis will address the development of CubeSat vibration testing methodology at NPS, including subsystem testing, engineering unit qualification, and flight unit testing. In addition, the new Cal Poly CubeSat Test POD Mk III will be introduced and evaluated based upon comparison with the Poly Picosatellite Orbital Deployer (P-POD). Using examples from the development of NPS-SCAT and test data from Cal Poly’s Test POD Mk III and P-POD, the current CubeSat testing methodology will be verified and an improved method for NPS CubeSat subsystem testing will be presented.

Truely optimal solutions to system design can only be obtained if the entire system is considered. In this research we consider design of commercial aircraft, but we expand the system to include a family of planes. A multidisciplinary design optimization framework is developed in which multiple aircraft, each with different missions, can be optimized simultaneously. Results are presented for a two-member family whose individual missions differ significantly. We show that both missions can be satisfied with common designs, and that by optimizing both planes simultaneously rather than following the traditional baseline plus derivative approach, the common solution is vastly improved. The new framework is also used to gain insight to the effect of design variable scaling on the optimization algorithm. / Singapore-MIT Alliance (SMA)

The demand for energy and cost efficient buildings has made architects and contractors more aware of the resources consumed by the built environment. While the actual economic and environmental costs of future construction can never be completely predicted, energy simulations and cost modeling have become accepted ways to guide the design and construction process by comparing possible outcomes. These tools are now commonplace in the construction industry, and researchers are continuing to develop new and innovative strategies to optimize building design and construction. Previous research has proven that genetic algorithms are effective methods to evaluate and optimize building design in situations that contain a large number of possible solutions. The technique makes a computationally difficult multi-optimization process possible but is still a reactive and time consuming process that focuses on evaluation rather than solution generation. This research presented in this paper builds upon established multi-objective optimization techniques that use an energy simulator to estimate a conceptual building’s energy use as well as construction cost. The study compares simulations of a simplified model of a 3-story inpatient hospital located in Atlanta, Georgia using a defined set of variables. A combined global minimum of annual energy consumption and total construction is sought after using a method that utilizes a genetic algorithm. The second phase of this research uses a modified approach that combines the traditional genetic algorithm with a seeding method that utilizes previous results. A new set of simulations were established that duplicates the initial trials using a slightly modified set of design variables. The simulation was altered, and the phase one trials were utilized as the first generation of simulated solutions. The objective of this thesis is to explore one method of making energy use and cost estimating more accessible to the construction industry by combining simulation optimization and indexing. The results indicate that this study’s proposed augmented approach has potential benefits to building design optimization, although more research is required to validate this hypothesis in its entirety. This study concludes that the proposed approach can potentially reduce the time needed for individual optimization exercises by creating a cumulative, robust catalog of previous computations that will inform and seed future analyses. The research was conducted in five general stages. The first part defines the research problem and scope of research to be conducted. In the second part, the concepts of genetic algorithms and energy simulation are explored in a comprehensive literature review. The remaining parts explain the trial simulations performed in this study. Part three explains the experiment’s methodology, and part four describes the simulation results. The fifth and final part looks at what the possible conclusions that can be made from analyzing the study’s results.

In this study an automated multidisciplinary design optimization code is developed for the minimum weight design of a composite wing box. The multidisciplinary static strength, aeroelastic stability, and manufacturing requirements are simultaneously addressed in a global optimization environment through a genetic search algorithm. The static strength requirements include obtaining positive margins of safety for all the structural parts. The modified engineering bending theory together with the coarse finite element model methodology is utilized to determine the stress distribution. The nonlinear effects, stemming from load redistribution in the structure after buckling occurs, are also taken into account. The buckling analysis is based on the Rayleigh-Ritz method and the Gerard method is used for the crippling analysis. The aeroelastic stability requirements include obtaining a flutter/divergence free wing box with a prescribed damping level. The root locus method is used for aeroelastic stability analysis. The unsteady aerodynamic loads in the Laplace domain are obtained from their counterparts in the frequency domain by using Rogers rational function approximations. The outer geometry of the wing is assumed fixed and the design variables included physical properties like thicknesses, cross sectional dimensions, the number of plies and their corresponding orientation angles. The developed code, which utilizes MSC/NASTRAN&reg / as a finite element solver, is used to design a single cell, wing box with internal metallic substructure and composite skins.

As the feature size of the transistor shrinks into nanometer scale, it becomes a grand challenge for semiconductor manufacturers to achieve good manufacturability of integrated circuits cost-effectively. In this dissertation, we aim at layout optimization algorithms from both manufacturing and design perspectives to address problems in this grand challenge. Our work covers three topics in this research area: a redundant via enhanced maze routing algorithm for yield improvement, a shuttle mask floorplanner, and optimization of post-CMP topography variation. Existing methods for redundant via insertion are all post-layout optimizations that insert redundant vias after detailed routing. In the first part of this dissertation, we propose the first routing algorithm that conducts redundant via insertion during detailed routing. Our routing problem is formulated as a maze routing with redundant via constraints and transformed into a multiple constraint shortest path problem, and then solved by Lagrangian relaxation technique. Experimental results show that our algorithm can find routing solutions with remarkably higher rate of redundant via insertion than conventional maze routing. Shuttle mask is an economical method to share the soaring mask cost by placing different chips on the same mask. Shuttle mask floorplanning is a key step to pack these chips according to certain objectives and constraints related to mask manufacturing and cost. In the second part of this dissertation, we develop a simulated annealing based floorplanner that can optimize these objectives and meet the constraints simultaneously. Chemical-mechanical polishing (CMP) is a crucial manufacturing step to planarize wafer surface. Minimum post-CMP topography variation is preferred to control the defocus in lithography process. In the third of this dissertation, we present several studies on optimization of the variation. First, we enhance the shuttle mask floorplanner to minimize the post-CMP topography variation. Then we study the following singleblock positioning problem: given a shuttle mask floorplan, how to determine a movable block's optimal position with respect to post-CMP topography variation. We propose a fast incremental algorithm achieving 6x to 9x speedup. Finally, we formulate a novel CMP dummy fill problem that targets at minimizing the height variance, which is key to reduce the image distortion by defocus. Experimental results show that with the new formulation, we can significantly reduce the height variance without sacrificing the height spread much.

A modular structural design methodology for composite blades is developed. This design method can be used to design composite rotor blades with sophisticate geometric cross-sections. This design method hierarchically decomposed the highly-coupled interdisciplinary rotor analysis into global and local levels. In the global level, aeroelastic response analysis and rotor trim are conduced based on multi-body dynamic models. In the local level, variational asymptotic beam sectional analysis methods are used for the equivalent one-dimensional beam properties. Compared with traditional design methodology, the proposed method is more efficient and accurate. Then, the proposed method is used to study three different design problems that have not been investigated before. The first is to add manufacturing constraints into design optimization. The introduction of manufacturing constraints complicates the optimization process. However, the design with manufacturing constraints benefits the manufacturing process and reduces the risk of violating major performance constraints. Next, a new design procedure for structural design against fatigue failure is proposed. This procedure combines the fatigue analysis with the optimization process. The durability or fatigue analysis employs a strength-based model. The design is subject to stiffness, frequency, and durability constraints. Finally, the manufacturing uncertainty impacts on rotor blade aeroelastic behavior are investigated, and a probabilistic design method is proposed to control the impacts of uncertainty on blade structural performance. The uncertainty factors include dimensions, shapes, material properties, and service loads.

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Choi, Seung-Kyum; Committee Member: Allen, Janet K.; Committee Member: Paredis, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.