<p> Reliability based analysis is a well-established tool in probability-based structural design. The load equation from the ACI Code along with several others ACI design methods are analyzed in order to verify that the reliability index using limit state functions are consistent across both determinate and indeterminate beams. This research provides an in-depth analysis and comparison of reliability indices for types of structures. Literature review describes the different probabilistic models used in the analysis. Several different probabilistic models are used in order to determine the reliability index of determinate and indeterminate structures. Standard reliability methods, such as the first-order reliability method (FORM), modified Rackwitz-Fiessler method, and Monte Carlo Simulations, are used in order to evaluate the reliability index of determinate beams and indeterminate beams designed with moment redistribution. </p><p> The research also presents the methodology and results of the reliability index of structures using different analysis methods. Reliability analysis methods are used to verify the safety of structures under different loading conditions for both determinate and indeterminate structures. The key outcomes of the research outlined in this Master&rsquo;s thesis are the following: </p><p> 1) Reliability index a. Closed-form solution is independent of the structure type b. Remains consistent across range of live load to dead load ratios 2) Reliability index did not vary greatly, regardless of: a. Structure b. Loading type c. Moment redistribution 3) The closed-form solution is more conservative and results in a lower reliability index. The refined method using the ACI design results in a higher reliability index.</p>

<p> This dissertation attempts to develop simple and direct approaches to estimate the vehicle queue length and travel time along signalized arterial links for real-time traffic operations. This dissertation is the first to demonstrate a process using vehicle trajectory data to generate detector volume, speed and time occupancy data, along with the generalized flow rate, density and space mean speed data. This approach minimizes detector over-counting and miss-counting issues. The detection zone can be of any shape or size and at any location along the trajectory. The relationships among detector volume, speed and time occupancy along signalized arterials are analyzed theoretically and experientially. If the generalized definitions of flow rate, density and space mean speed are used, the fundamental relationship, <i>v</i> = <i>ds</i>, holds valid in a signalized arterial environment. The fundamental relationship diagram plotted using field signalized arterial data has not been seen in any of the literatures reviewed.</p><p> Within the defined time-space region, the scatter diagram of the generalized density and the detector time occupancy presents a strong linear correlation. Simply converting detector volume counts within one data collection time period to use as the generalized flow rate introduces estimation errors. There are two major reasons. The first is that vehicles don&rsquo;t completely cross the detector during the data collection time period. The second is that it assumes vehicles would evenly spread across the data collection time period when crossing the detection zone. Traffic flow intensity is introduced and defined within the time-space regions to provide much more accurate description of the traffic flow arrival and departure conditions.</p><p> This dissertation attempts to make improvements to the input-output technique for queue estimation along signalized links. Based on analyses of the theoretical and experiential cumulative input-output diagrams, also known as the Newell Curves, two major improvements are proposed to improve the performance of the input-output technique. The improvements take into account vehicles stop on top of detectors in the estimation, make necessary adjustments to detector vehicle counts, and introduce a reset mechanism to remove the accumulated estimation errors during a long time period. The improvements are tested using two sets of field data. One set of data are 10-second queue and virtual detector data generated using the Federal Highway Administration Next Generation Simulation Peachtree Street dataset. The other set of data are field manually collected 20-second queue, and loop detector vehicle count and time occupancy data at metered on-ramps. It is concluded that both improvements help to produce estimation results far better than the original input-output technique. With adjusted detector vehicle counts, the performance of the Kalman Filter queue estimation model is also improved.</p><p> A simple conservation law approach is developed to estimate travel time along signalized arterial links. Inputs used include the traffic flow intensity at input and out detectors, plus the initial vehicle queue. The estimated travel time is tested with the field travel time data to evaluate the performance of the estimation. The developed model is also compared with the NCHRP Project 3-79 model and the Little&rsquo;s Law queueing theory model. The developed model performs much better for per short interval travel time estimation. </p><p> The proposed travel time estimation approach only uses the detector volume and time occupancy data. It does not rely on signal timing data to estimate the control delay or a delay model to estimate the queueing delay. In addition, neither roadway geometry nor vehicle length data are used.</p>

<p> The objective of this study is to create and evaluate if finite element modeling is a feasible approach to modeling different wedge geometries of post tensioned systems by comparing the experimental data from two wedges to analytical data. The motivation to develop an accurate finite element model of a wedge, tendon, and anchor system is to better understand the internal stresses the system is subjugated to and the interactions between components. By not fully understanding what is occurring within the anchor, the most efficient anchor cannot be designed. This can lead to premature failures of the strand which can result in total collapse of the structure. In recent years the applications of post tensioned strands have grown rapidly. Some of these applications require the strand to withstand higher strains than can currently be reached. An example of one of these applications is a shear rocking wall in earthquake prone areas. To date there is some experimental data on strand testing, but very little research has been conducted examining a modified geometry wedge. There is even less in depth literature on finite element modeling of the interactions between the components. One reason for this lack of research is because of the great variability in anchor and wedge configurations. Therefore, the focus of this research is to develop the interaction laws for one type of anchorage from one manufacturer. Once these laws are established and considered scientifically sound, the most efficient anchor wedge mechanism can be designed. </p><p> This thesis presents one of the stepping stone models needed to help converge on the interaction laws. The experimental component of this report evaluated two different wedge geometries. In the experimental trials the modified wedges preformed more efficiently than the standard wedges. The modified wedges were able to reach much higher strains. These geometries were modeled in a finite element program and the experimental results were replicated by adjusting the interaction relationships. The starting point for the relationships were based off of the studies found in the literature review. The results from analytical model of the standard wedges matched the experimental results very accurately. The analytical model of the modified wedge requires refinement. The results of the analytical model did not match the experimental observations as well as they should. However, the results still support the theory that the computer software can differentiate between standard and modified wedge geometries.</p>

A system of interest usually consists of some unknown model parameters that affect its output. System diagnosis estimates these model parameters and track their evolution if the system is time-dependent. Subsequently, the prognosis predicts the system output at future inputs. An important challenge in diagnosis and prognosis is the presence of various uncertainty sources, such as natural variability, inadequate data, and approximate models. The first challenge is how to integrate the contributions of the different uncertainty sources towards the overall prediction uncertainty; dimension reduction is another challenge in the case of a large number of uncertainty sources; other challenges includes test design, computational efficiency, etc. This dissertation uses the Bayesian network and variance sensitivity analysis as major mathematical tools and develops multiple innovations to solve the aforementioned challenges in system diagnosis and prognosis. Regarding sensitivity analysis, this dissertation proposes a framework to incorporate both aleatory and epistemic uncertainty, and a new sample-based algorithm to significantly improve the computational efficiency. This leads to sensitivity analysis of the Bayesian network for dimension reduction. Regarding uncertainty integration, this dissertation proposes a roll-up method to incorporate the results from multiple uncertainty quantification activities, and a sensitivity-based optimization approach for test design. A dynamic Bayesian network is utilized for the diagnosis and prognosis of time-dependent systems, and illustrated with an aircraft wing digital model to monitor the health status of the wing. A fast Bayesian inference algorithm is also proposed to improve the computational efficiency, thus enabling real-time diagnosis and prognosis for decision support. In sum, this dissertation covers multiple topics in uncertainty quantification and system health monitoring, and the proposed methodologies/algorithms provide valuable breakthroughs for comprehensive uncertainty integration and higher computational efficiency without compromising accuracy.

<p> Traffic congestion is a daily occurrence in urban highway networks worldwide. It is not possible, however, for society to build its way out of congestion; rather, smarter roads and vehicles are needed. While the development of a smarter transportation system is underway, full implementation is years or decades from now. Yet, some of the sensing technology needed for smarter vehicles is already widely deployed in the form of smart phones. This thesis develops a novel method for recognizing traffic congestion using an artificially intelligent heuristic that could be implemented in a smart phone application or embedded system. Its goal is to provide intelligent feedback to a driver or autonomous vehicle control system to counteract stop-and-go traffic, a defining feature of urban highway congestion. Evaluation of the method indicates that a specific condition during stop-and-go traffic can be recognized accurately. A driver or control system acting upon feedback provided by the artificially intelligent system can improve traffic flow on the roadway by 1% to 3.5% over the course of the test duration.</p>

Composite materials are attractive for aerospace vehicles due to their low weight and high performance; however, predictive computational models are needed to lower the costs associated with their design and certification process. Furthermore, because aircraft structures are built up from many components fastened together, it is critical to understand and predict the mechanical behavior bolted joints introduce. The goal of this thesis is to advance the state of the art in fiber reinforced polymer composite bolted joint computational modeling and prediction using the multiscale reduced order computational model known as the Eigendeformation-based Homogenization Method (EHM). Preliminary blind predictions were performed for laminated [44/44/11] IM7/977-3 composite specimens in single-lap straight hole and countersunk bolt joints under static tension tests. To address stiffness and post-peak behavioral issues, an in-depth blind prediction study was conducted for open hole, filled hole, and single shear bearing configurations of countersunk laminated [44/44/11] IM7/977-3 specimens under static tension and compression tests. EHM performed very well in the open and filled hole cases, and the single shear bearing results show promise of EHM as a reliable choice for composite bolted joint damage analysis.

<p> Industry practitioners and researchers recognize project scope definition as a factor of project success in terms of cost and schedule. The Construction Industry Institute developed the Project Definition Rating Index (PDRI) as a tool to aid in the effectiveness of scope development. The Air Force has adopted use of this tool, though has yet to validate its effectiveness empirically. The objective of this study is to provide that empirical validation by comparing the cost, schedule, and budget estimate performance metrics of Air Force military construction (MILCON) projects that used the PDRI against those that did not. Project data for 263 (100 PDRI and 163 non-PDRI) MILCON projects worth $3.9 Billion were analyzed. The projects that used the PDRI performed better on all three metrics, with statistically significant results on both cost and schedule growth. This study provides empirical evidence of how the use of formal scope definition tools can improve performance for Air Force MILCON projects. When compared to previous research, the study also contributes to a broader understanding of scope definition in the design and construction industry.</p>

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