Doctor of Philosophy, University of Akron, 2020, Civil Engineering

The study aims to explore advanced tools for air crash analysis with universal meaning in air-crash analysis and uses the crash of Tu-154M large transport airplane in Smolensk, Russia on April 10, 2010, as an example. The crash was initiated by the impact of the left wing into a large birch tree according to the Russian investigation report. Nevertheless, some facts caused the attention and suspicion to this explanation. The research is devoted to investigate how far the wing has to be damaged for the airplane to lose balance, how a pilot can compensate the degraded aerodynamic performance of the aircraft, how to reconstruct the trajectory of a fall of major debris separated from the airplane in the air are critical in the air-crash analysis, what the most possible mechanism of airplane door is to end up one meter deep and perpendicular berried in the ground, and what the most possible outcome of the airplane wing impact into the birch tree. First of all, the aircraft in landing configuration with various wingtip damage on the left wing was under consideration while the no-damaged case was also studied as the baseline. Wind tunnel test results with a 1:100 scale model were correlated using CFD simulations. The variations of lift force, drag force, and asymmetric rolling moment with respect to the angle of attack and sideslip were investigated for different damage situations. The methods to compensate for the lift force and the asymmetric rolling moment were also investigated for the possibility of a safe landing. Secondly, estimating the trajectory of separated objects after disintegration caused by the impact will be useful in crashes analysis of airplane, especially in the circumstance when the impact condition cannot be determined. Since the motion of an airplane's fragments in the air is highly affected by the aerodynamic loads, computational fluid dynamics with an automated unstructured tetrahedral mesh approach using spring-based smoothing and remeshing a (open full item for complete abstract)

Committee: Wieslaw Binienda (Advisor); Qingdan Huang (Committee Member); Atef Saleeb (Committee Member); Xiaosheng Gao (Committee Member); Lingxing Yao (Committee Member) Subjects: Aerospace Engineering; Civil Engineering

Doctor of Philosophy, University of Akron, 2015, Civil Engineering

To reduce the occurrence of motor-vehicle crashes, professionals in education, enforcement, and engineering are continually tasked with implementing safety solutions. Identifying locations of high rates of crashes allows safety solutions to more adequately target their intended audience. This research examines advances in identifying hot spots of motor-vehicle crashes. These advancements come from improving: 1) the calculation of spatial autocorrelation and interpolation, 2) the identification of spatio-temporal patterns, and 3) the influence of geographical patterns on the spatial distribution of crashes. Overall, by improving the hot spot analysis, concerned professionals may be better prepared and lower the number of alcohol-related crashes. The location of hot spots is important in the implementation of enforcement campaigns. A lapse in accuracy may allow a vehicle operator suspected of disobeying traffic laws from being properly disciplined. Improvements in the calculation of spatial autocorrelation and interpolation result from the use of network distances instead of Euclidean based distances. Network based distances increase the accuracy of resulting hot spots. With the accuracy of hot spots improved, the optimal times to implement safety campaigns in their identified areas become important. Many hot spots purely analyze crashes as if they all occurred at the same time. By investigating crashes in this manner, some key influences may be lost and the efficiency of the implemented campaign may be reduced. Spatio-temporal hot spot are examined and show that as time progresses, clusters of crashes occur and disappear throughout space. By moving campaign sites as the location of crashes move, the overall efficiency of campaign tactics would benefit. Hot spots of crashes have continually been scrutinized for their focus on areas of large populations. In an effort to rectify this belief, the normalization of hot spot is examined in relation to population dens (open full item for complete abstract)

Committee: William Schneider IV Dr. (Advisor); Stephen Duirk Dr. (Committee Member); Anil Patnaik Dr. (Committee Member); Scott Sawyer Dr. (Committee Member); Mark Fridline Dr. (Committee Member) Subjects: Civil Engineering; Transportation

Doctor of Philosophy, The Ohio State University, 2015, City and Regional Planning

This study investigates the effects of the surrounding environment on crashes, with a focus on crash severity and at-fault drivers characterized by gender and age. Crashes where a vehicle is the guilty party are investigated. The study adopts two approaches: aggregate and disaggregate. In the aggregate approach, the numbers of crashes, classified in terms of severity (fatalities, injuries, property damages only), and gender and age of the driver (with several age groups covering the 15-100 age span), represent the variables to be investigated, and have been derived for the Central Ohio Region from the multiple files of the crash database of the Ohio Department of Public Safety, over the period 2006-2011. These data are aggregated at the level of Traffic Analysis Zones (TAZ). OLS models are first estimated, but spatial autocorrelation tests point the existence of spatial autocorrelation (SA). Spatial econometrics models are then used to eliminate the SA bias: the Spatial Autoregressive Model (SAR) and the Spatial Error Model (SEM). Subsequent analyses are conducted using the SEM estimates, as the SEM model is successful in completely eliminating spatial autocorrelation. The aggregate approach uses a large set of explanatory variables classified into six groups: Regional and Locational, Socio-Economic, Land-Use, Public Transit and Traffic Flow, Circulation and Network, and Physical Characteristics. The results show that variables in all these groups have significant impacts on crash severity and frequencies. The disaggregate approach accounts for more variables that influence crash severity, but cannot be captured in the aggregate approach, such as weather conditions, light conditions, road conditions, type of intersection, and type of vehicle. All these variables are directly related to an individual crash. The logit model is used to explain the probability of a Bodily Injury (BI) crash at the crash scene, where the alternative is Property Damage Only (PDO) crash. (open full item for complete abstract)

Committee: Jean-Michel Guldmann (Advisor); Burkhard von Rabenau (Advisor); Philip Viton (Committee Member) Subjects: Behavioral Sciences; Land Use Planning; Transportation; Transportation Planning; Urban Planning

Master of Science (MS), Ohio University, 2001, Mechanical Engineering (Engineering)

Design and analysis of seat and restraint systems for crash simulation

Committee: Bhavin Mehta (Advisor) Subjects: Engineering, Mechanical

Master of Science, The Ohio State University, 2023, Mechanical Engineering

Around the world, millions of people use powered two-wheelers (PTWs) as a mode of transportation (Insurance Institute for Highway Safety, 2022; Ordonez de Barraicua, 2023). In the United States in 2020, over 82,000 motorcyclists were injured, and over 5,500 fatalities occurred (National Center for Statistics and Analysis, 2022). Past research investigating these high injury and fatality rates has focused on literature reviews and crash databases. Previous studies have focused mainly on safety technology and how to better protect the occupant, but there is a gap in knowledge regarding the development and validation of current safety tools like anthropomorphic test devices (ATDs) and finite element (FE) human body models. These safety tools can be improved and validated with data from full-scale PMHS crash tests. This study used two 50th percentile male PMHS with the objective of better understanding the injuries that occur and their injury mechanism in a PTW versus motor vehicle impact. To determine injury and injury mechanism, strain gage data was collected from strain gages, and kinematic data were collected from 6 degrees of freedom (6DOF) sensors. Strain gages were placed on regions where possibly injury could occur based on previous research, and 6DOF sensors were placed on major body segments to analyze the kinematic response of those segments. The strain gage and kinematic data were compared to high-speed video to provide insight into possible injury mechanism at the time of injury. Two PMHS subject tests were run with a 2022 KTM 390 Duke traveling down a track at 50 kph and impacting the front right door of a modern sedan. Both tests provided similar injury results and kinematic responses, with overall ISS scores being 36 (Test 1) and 34 (Test 2). Matching the high-speed video with the strain gauge data and kinematic data provided insight into injury mechanisms, for example serious pelvis fractures for both tests (AIS4) were caused by the interaction of the p (open full item for complete abstract)

Committee: Yun-Seok Kang (Committee Member); John Bolte IV (Advisor) Subjects: Biomechanics; Mechanical Engineering

Master of Science, The Ohio State University, 2017, Materials Science and Engineering

Hot stamped boron steels, such as Usibor® 1500, have been increasingly used in automotive structural components for light-weighting and impact resistance. Classified as an ultra-high strength steel, these alloys have superior strength with tensile strengths exceeding 1500 MPa. The rapid heating and cooling thermal cycle during resistance spot welding can significantly alter the martensitic base metal microstructure, resulting in formation of coarse-grained and subcritical heat-affected zones (CGHAZ and SCHAZ) with inferior mechanical properties. The martensitic CGHAZ is adjacent to the weld nugget and experiences the most time above the AC3, which allows for austenite grain growth. The SCHAZ is next to the unaffected base metal and does not reach the AC1¬ during welding, thus the base metal microstructure is over-tempered into cementite and ferrite. The present research aims at developing the fundamental knowledge of plastic deformation and fracture behaviors of ultra-high strength steel resistance spot welds. As a resistance spot weld comprises highly inhomogeneous microstructure, the overall research approach is based on studying the local (or microstructure-dependent) mechanical properties for individual regions in the weld as well as their interactions with weld geometry on the deformation behavior. Specifically, optimal welding parameters are determined to produce welds of appropriate nugget diameter for 2T Usibor 1500 with a gauge thickness of 1.5 mm. Micro-hardness mapping and metallographic analysis allow for characterization of the weld metal, CGHAZ, SCHAZ, and base metal of the spot weld. Quasi-static tensile testing with digital image correlation (DIC) is used to determine the local stress-strain behaviors of each region using bulk microstructural samples created in a Gleeble® thermal-mechanical simulator. Conventional and innovative resistance spot weld mechanical testing methods are used to generate more knowledge on the deformation of joints un (open full item for complete abstract)

Committee: Wei Zhang PhD (Advisor); Menachem Kimchi (Advisor); David Phillips PhD (Committee Member) Subjects: Automotive Engineering; Automotive Materials; Engineering; Materials Science; Metallurgy; Transportation

Master of Environmental Science, Miami University, 2015, Environmental Sciences

This report summarizes my activities as Planning Intern for the Miami Valley Regional Planning Commission (MVRPC) from May 2014 through May 2015. The following report is organized by a history of Metropolitan Planning Organizations, MVRPC, and common aspects involved in transportation planning. This is followed by the role that MVRPC plays in environmental planning, transportation safety planning and the work that I contributed to the programs in that area. Major work that I contributed includes a preliminary analysis of traffic safety data in the Miami Valley Region for the years 2011 to 2013. Finally, I discuss how MVRPC may enhance safety planning as well as how the Institute for the Environment and Sustainability (IES) program at Miami University has impacted my education and career goals.

Committee: Amélie Davis (Advisor); Mary Henry (Committee Member); Steven Elliot (Committee Member) Subjects: Environmental Science; Geographic Information Science; Transportation Planning

MS, University of Cincinnati, 2014, Engineering and Applied Science: Computer Science

The process of manually debugging programs can be difficult and time consuming. The goal of this thesis is to aid developers in debugging their crashed programs by identifying common programming mistakes using information collected during the execution of the crashed program. Specifically, the solution proposed by this thesis calculates a dynamic slice with respect to conditions at the time of the crash and inspects the dynamic slice for characteristics that are only present when certain types of programming errors occur. Common programing mistakes explored by this thesis include: uninitialized heap variables, uninitialized stack variables, dangling pointers, and stack overflow. A prototype, based on the GNU Debugger, was developed to implement the concepts of this thesis and was used to identify common programming mistakes made in a set of example C programs. Experimental results showed that the solutions presented in this thesis performed very well. The prototype was able to identify all occurrences of uninitialized stack variables, uninitialized heap variables, and stack overflow, and only a few instances of dangling pointers were missed. Upon identifying a common programming mistake in the dynamic slice, the prototype was able to produce a high level debug report indicating source code lines relevant to the coding mistake.

Committee: John Franco Ph.D. (Committee Chair); Raj Bhatnagar Ph.D. (Committee Member); Paul Talaga Ph.D. (Committee Member) Subjects: Computer Science