Matching Items (5)
Description
Woven fabric composite materials are widely used in the construction of aircraft engine fan containment systems, mostly due to their high strength to weight ratios and ease of implementation. The development of a predictive model for fan blade containment would provide great benefit to engine manufactures in shortened development cycle time, less risk in certification and fewer dollars lost to redesign/recertification cycles. A mechanistic user-defined material model subroutine has been developed at Arizona State University (ASU) that captures the behavioral response of these fabrics, namely Kevlar® 49, under ballistic loading. Previously developed finite element models used to validate the consistency of this material model neglected the effects of the physical constraints imposed on the test setup during ballistic testing performed at NASA Glenn Research Center (NASA GRC). Part of this research was to explore the effects of these boundary conditions on the results of the numerical simulations. These effects were found to be negligible in most instances. Other material models for woven fabrics are available in the LS-DYNA finite element code. One of these models, MAT234: MAT_VISCOELASTIC_LOOSE_FABRIC (Ivanov & Tabiei, 2004) was studied and implemented in the finite element simulations of ballistic testing associated with the FAA ASU research. The results from these models are compared to results obtained from the ASU UMAT as part of this research. The results indicate an underestimation in the energy absorption characteristics of the Kevlar 49 fabric containment systems. More investigation needs to be performed in the implementation of MAT234 for Kevlar 49 fabric. Static penetrator testing of Kevlar® 49 fabric was performed at ASU in conjunction with this research. These experiments are designed to mimic the type of loading experienced during fan blade out events. The resulting experimental strains were measured using a non-contact optical strain measurement system (ARAMIS).
ContributorsFein, Jonathan (Author) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012
Description
In the U.S., less than 20 percent of wildlife strikes are reported, which leaves a large portion of incidents unaccounted for. Although wildlife strikes at airports often go unreported, since the early 1990's the number of wildlife strikes has increased five-fold and the number of damaging strikes has increased 1.5-fold. Goals for this project include determining if biological and landscape variables are good predictors of wildlife strikes. We define response variables as the number of reported wildlife strikes per 10,000 airport operations. We studied seven major airports around Phoenix, Arizona and 30 large airports in the western U.S. In the Phoenix metro valley, airports varied from having 0.3 strikes per year per 10,000 operations to having 14.5 strikes from 2009 to 2013. We determined bird richness by using the citizen-science database "eBird,"and measured species richness within a 15 kilometer area of each airport. Species richness between hotspots ranged from 131 to 320. Seasonal differences were determined using an analysis of variance (ANOVA) analysis for the seven Phoenix metro airports as well as the 30 western U.S. airports. Our results showed that there was a seasonal difference in wildlife strikes in the majority of our airports. We also used land use data from CAP LTER to determine any environmental factors such as vicinity to water or fence line located within five kilometers from airports using ArcGIS. These results are important because they are helpful in determining the factors influencing wildlife strikes based on the number of strikes reported.
ContributorsSalaki, Logan (Co-author) / Montgomery, Brett (Co-author) / Bateman, Heather (Thesis director) / Niemczyk, Mary (Committee member) / Barrett, The Honors College (Contributor)
Created2015-05
Description
My project analyzes the air traffic control tower (ATCT) system of the Federal Aviation Administration (FAA) to determine if a rebalancing of ATCT ownership and operation should occur. The government currently faces a problem of a tight financial budget and sequestration, which often times means mandatory budget cuts. This project provides one possible solution for the FAA to save money in their budget without adversely affecting safety. The FAA could establish appropriate criteria to compare all ATCTs. The FAA could then apply these criteria in a policy that would contract the operation of certain low-level ATCTs and conversely handle the operations at high-activity ATCTs. Additionally, the FAA could include a policy to transfer the ownership of certain low-activity towers, but transfer the ownership of high-activity towers to the FAA. The research was completed by studying various documents from the FAA, Department of Transportation (DOT), and industry groups. Most of the data analysis was conducted by creating tables, queries, and graphs from FAA data. The FAA data was found on their Air Traffic Activity Data System (ATADS). From my data analysis, I was able to identify sixty-nine ATCTs that are currently operated by the FAA that could become federal contract towers (FCT) and forty-six FCTs that could be operated by the FAA. Each FCT saves the FAA approximately $1.488 million, so the FAA could save $34.2 million per year by implementing my solutions. I have also established sample criteria for determining which ATCTs could be maintained by the FAA.
ContributorsJuri, William Joseph (Author) / Denny, Casey (Thesis director) / Niemczyk, Mary (Committee member) / Barrett, The Honors College (Contributor) / Department of Technological Entrepreneurship and Innovation Management (Contributor)
Created2013-12
Description
Pilot suicide has been a topic that has seen increased discussion in the past decade, Aviation regulating bodies have introduced antidepressant programs to aid in reducing the harm depression and other mental illnesses cause pilots. These programs are varied in their structure however they all revolve around SSRI medications. The FAA HIMS SSRI program for American pilots issues a pathway that is long in duration and can place undue stress on pilots that choose to participate. This has led to high rates of under-reporting and non-treatment of mental illnesses in pilots.
ContributorsBjork, Ivar (Author) / Drew, John (Thesis director) / Martin, Thomas (Committee member) / Barrett, The Honors College (Contributor) / Aviation Programs (Contributor)
Created2023-05
Description
Differences in climatic conditions, aircraft traffic, and maintenance practices drive airfield pavements to perform differently. Through the Federal Aviation Administration’s (FAA’s) PAVEAIR online database and the National Oceanic and Atmospheric Administration’s (NOAA’s) online public platform, historical pavement condition and climate data from nearly 200 airfields in the dry freeze (DF), dry no-freeze (DNF), wet freeze (WF), and wet no-freeze (WNF) climatic regions were collected to evaluate pavement performance and distress trends. This research details the methodologies employed in the PAVEAIR pavement inspection data retrieval and dataset organization, and further presents the results of a two-part analysis. First, rate of deterioration (ROD) of various pavement families were evaluated by fitting a linear regression to the pavement condition index (PCI). Then, historical distresses data were analyzed for various pavement families in the different climatic regions. Families were assigned with respect to climate, pavement structure (conventional asphalt or asphalt overlays), and branch type (apron, taxiway, and runway).
The regression results showed that pavements in the WF region have the highest ROD, followed by the pavements in the DNF region. In terms of branch type, in three of four climatic regions, aprons have the fastest rate of deterioration, followed by taxiways and runways, respectively. The distress analytics revealed that cracking type of distresses were the most common in all the regions regardless of the pavement family.
The results showed that climatic data alone were not adequate to characterize airfield pavement behavior due to the multivariate factors affecting pavement deterioration. An accurate pavement and distress prediction modeling effort should at least include additional information on the structure and traffic level.
ContributorsDuah, Ebenezer (Author) / Ozer, Hasan (Thesis advisor) / Kaloush, Kamil E (Committee member) / Mamlouk, Michael S (Committee member) / Arizona State University (Publisher)
Created2021