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Crash Performance of Pre-Impregnated Platelet Based Molded CompositesRebecca A Cutting (6996419) 13 August 2019 (has links)
Platelets made of slit and chopped unidirectional, carbon-fiber prepreg are becoming a popular option for use as a high performance molding compound because of their high fiber volume fraction and increased ability to flow compared to continuous fiber systems. As this molding compound is newly introduced to industry, increasing amounts of research have gone into understanding how platelets flow during molding and how components perform mechanically based on the final orientation state of platelets. This work investigates the performance of prepreg platelet molding compound (PPMC) as a viable alternative to continuous fiber systems for use with geometrically complex structural members on vehicles subjected to collisions. In doing so, the crash performance, energy absorption, and failure morphology of crush tubes made with PPMC are investigated and quantified. Then, a simulation methodology is developed to obtain manufacturing-informed performance models to predict the effect of platelet orientation state on mechanical behavior of PPMC components. This methodology uses a building block approach where each block in modeling is verified against closed-form solution (when available) and validated against experimental results. Once confidence is developed in a modeling block, the complexity of the simulation is increased until a component with full platelet orientation distribution is captured. The result is PPMC component models that are capable of predicting mechanical performance in orientation regimes that are not investigated experimentally.
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Improving Object Detection using Enhanced EfficientNet ArchitectureMichael Youssef Kamel Ibrahim (16302596) 30 August 2023 (has links)
<p>EfficientNet is designed to achieve top accuracy while utilizing fewer parameters, in addition to less computational resources compared to previous models. </p>
<p><br></p>
<p>In this paper, we are presenting compound scaling method that re-weight the network's width (w), depth (d), and resolution (r), which leads to better performance than traditional methods that scale only one or two of these dimensions by adjusting the hyperparameters of the model. Additionally, we are presenting an enhanced EfficientNet Backbone architecture. </p>
<p><br></p>
<p>We show that EfficientNet achieves top accuracy on the ImageNet dataset, while being up to 8.4x smaller and up to 6.1x faster than previous top performing models. The effectiveness demonstrated in EfficientNet on transfer learning and object detection tasks, where it achieves higher accuracy with fewer parameters and less computation. Henceforward, the proposed enhanced architecture will be discussed in detail and compared to the original architecture.</p>
<p><br></p>
<p>Our approach provides a scalable and efficient solution for both academic research and practical applications, where resource constraints are often a limiting factor.</p>
<p><br></p>
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IDENTIFICATION OF FAILURE-CAUSED TRAFFIC CONFLICTS IN TRACKING SYSTEMS: A GENERAL FRAMEWORKCristhian Lizarazo Jimenez (9375209) 16 December 2020 (has links)
<p><a>Proactive evaluation of road safety is
one of the most important objectives of transportation engineers. While current
practice typically relies on crash-based analysis after the fact to diagnose
safety problems and provide corrective countermeasures on roads, surrogate measures
of safety are emerging as a complementary evaluation that can allow engineers
to proactively respond to safety issues. These surrogate measures attempt to address
the primary limitations of crash data, which include underreporting, lack of
reliable insight into the events leading to the crash, and long data collection
times. </a></p>
<p>Traffic
conflicts are one of the most widely adopted surrogate measures of safety
because they meet the following two conditions for crash surrogacy: (1) they
are non-crash events that can be physically related in a predictable and
reliable way to crashes, and (2) there is a potential for bridging crash
frequency and severity with traffic conflicts. However, three primary issues
were identified in the literature that need to be resolved for the practical
application of conflicts: (1) the lack of consistency in the definition of traffic
conflict, (2) the predictive validity from such events, and (3) the adequacy of traffic conflict observations.</p>
<p>Tarko
(2018) developed a theoretical framework in response to the first two issues
and defined traffic conflicts using counterfactual theory as events where the lack
of timely responses from drivers or road users can produce crashes if there is
no evasive action. The author further introduced a failure-based definition to emphasize conflicts as an undesirable
condition that needs to be corrected to avoid a crash. In this case, the
probability of a crash, given failure, depends on the response delay. The
distribution of this delay is adjusted, and the probability is estimated using
the fitted distribution. As this formal theory addresses the first two issues,
a complete framework for the proper identification of conflicts needs to be
investigated in line with the failure mechanism proposed in this theory.</p>
<p>The
objective of this dissertation, in response to the third issue, is to provide a
generalized framework for proper identification of traffic conflicts by
considering the failure-based definition of traffic conflicts. The framework introduced
in this dissertation is built upon an empirical evaluation of the methods
applied to identify traffic conflicts from naturalistic driving studies and
video-based tracking systems. This dissertation aimed to prove the practicality
of the framework for proactive safety evaluation using emerging technologies
from in-vehicle and roadside instrumentation.</p>
<p>Two
conditions must be met to properly claim observed traffic events as traffic
conflicts: (1) analysis of longitudinal and lateral acceleration profiles for
identification of response due to failure and (2) estimation of the time-to-collision
as the period between the end of the evasion and the hypothetical collision.
Extrapolating user behavior in the counterfactual scenario of no evasion is
applied for identifying the hypothetical collision point.</p>
<p>The
results from the SHRP2 study were particularly encouraging, where the appropriate
identification of traffic conflicts resulted in the estimation of an expected
number of crashes similar to the number reported in the study. The results also
met the theoretical postulates including stabilization of the estimated crashes
at lower proximity values and Lomax-distributed response delays. In terms of area-wide
tracking systems, the framework was successful in identifying and removing failure-free
encounters from the In-Depth understanding of accident causation for Vulnerable
road users (InDeV) program.</p>
<p>This
dissertation also extended the application of traffic conflicts technique by considering
estimation of the severity of a hypothetical crash given that a conflict occurs.
This component is important in order for conflicts to resemble the practical
applications of crashes, including the diagnostics of hazardous locations and evaluating the effectiveness of the countermeasures. Countermeasures should not only reduce the
number of conflicts but also the risk of crash given the conflict. Severity
analysis identifies the environmental, road, driver, and pre-crash conditions
that increase the likelihood of severe impacts. Using dynamic characterization of
crash events, this dissertation structured a probability model to evaluate
crash reporting and its associated severity. Multinomial logistic models were
applied in the estimation; and quasi-complete separation in logistic regression
was addressed by providing a Bayesian estimation of these models.</p>
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DESIGN REQUIREMENTS OF HUMAN-DRIVEN,HYBRID, AND AUTONOMOUS TRUCKS FOR COLLISION-AVOIDANCE IN PLATOONINGShreyas Shanker (18136627) 03 June 2024 (has links)
<p dir="ltr">In this thesis, a MATLAB model was used to simulate a 2-vehicle platoon where the lead truck is a conventional class 8 vehicle while the key parameters of the following truck was tested in various road conditions to minimize Inter vehicular Distance (IVD) and maximize fuel savings
while ensuring safety</p>
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The Study of Behavior of Passenger Car-Semi-Autonomous Trailer Connections under LoadYury Kuleshov (11187051) 27 July 2021 (has links)
<div><p>A variety of passenger car-trailer connections exist on the market. One specific type of the connections provides a tensile force measurement capability for the purpose of providing feedback for the semi-autonomous trailer’s control system. Semi-autonomous trailer is an innovative technology that can encourage drivers to use smaller vehicles for towing, which will contribute to restoration and improvement of urban infrastructure (NAE Grand Challenges for Engineering, 2020). The vehicle-semi-autonomous trailer connection’s safety concerns depend on multiple factors, but start with either a mechanical, or an electrical failure. The topic of safety of passenger car-semi-autonomous trailer connections is not well present in literature. The connections’ mechanical failures under load are in the focus of this work. The author addressed the following research question and the sub question. How do the existing “passenger car-trailer” connections with tensile force measurement capability compare to one another under load in terms of the possible failure? What is the failure mode of each of the compared connections? The author selected three prototypes from the literature, built three-dimensional (3D) models in SolidWorks 2018 and simulated the tests in the program’s add-on in accordance with the requirements of an industry standard on real-life testing of specific vehicle systems. The author compared the three prototypes by a number of different parameters. The research showed that none of the three existing prototypes are public road-ready in terms of safety. The study can be useful for future designers of passenger-car-semi-autonomous trailer connections.</p></div>
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