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This work proposes a new method for using reduced order models in lieu of high fidelity analysis during the sensitivity analysis step of gradient based design optimization. The method offers a reduction in the computational cost of finite difference based sensitivity analysis in that context. The method relies on interpolating reduced order models which are based on proper orthogonal decomposition. The interpolation process is performed using radial basis functions and Grassmann manifold projection. It does not require additional high fidelity analyses to interpolate a reduced order model for new points in the design space. The interpolated models are used specifically for points in the finite difference stencil during sensitivity analysis. The proposed method is applied to an airfoil shape optimization (ASO) problem and a transport wing optimization (TWO) problem. The errors associated with the reduced order models themselves as well as the gradients calculated from them are evaluated. The effects of the method on the overall optimization path, computation times, and function counts are also examined. The ASO results indicate that the proposed scheme is a viable method for reducing the computational cost of these optimizations. They also indicate that the adaptive step is an effective method of improving interpolated gradient accuracy. The TWO results indicate that the interpolation accuracy can have a strong impact on optimization search direction.

Variations in vehicle noise, vibration and harshness (NVH) response from one vehicle to the next can have significant impact on an automotive company’s profile and profitability. The warranty claims due to excessive NVH response end up costing the manufacturers a large sum of money each year. In addition, the OEM will suffer a larger financial loss due to the poor perception of quality and customer dissatisfaction with their products due to the unacceptable NVH response. Therefore, measures must be taken to ensure less warranty claims and higher levels of customer satisfaction. This research focuses on aspects of design variations that are costly or difficult to be avoided in the design process such as variations with rubber parts and variations due to rotating components. Vibrations induced at the tire/wheel assembly due to variations in the radial and tangential forces and radial runout are responsible for the driverelt vibrations that can lead to a large number of warranty claims. The purpose of this research is to improve the process of determining and analyzing vibration sources in the tire/wheel assembly in order to benefit the automotive manufacturer during the development and manufacturing phases. This research identifies the relationship between non-uniformity forces of the tire/wheel assemblies and the driverelt vibrations during typical highway driving speeds. The contribution from each assembly location is analyzed and sensitivities are determined. A Monte Carlo process is used to predict numerous non-uniformity properties that are statistically representative of the assembly properties that can be expected at the manufacturing plant. The Monte Carlo produced non-uniformity properties are combined with the sensitivities to predict driverelt vibrations that can be expected from vehicles leaving the manufacturing plant. This process provides the tools to determine an acceptable level of non-uniformities based on targets for interior vibration levels or determine if the vehicle sensitivities to non-uniformities need to be improved.

Streambank erosion is a major problem and a major known source of sediment in impaired streams. Stream deterioration is mainly due to the excess sediment in the United States. Many models have been developed to predict streambank erosion and sediment transport in the streams. Determining the most sensitive soil-specific parameters of the CONCEPTS Model for Goodwin Creek, MS was the focus of the study. The Latin Hypercube Oneactor-At-a-Time (LH-OAT) method was used to complete the sensitivity analysis on soil-specific parameters in CONCEPTS. Overall results demonstrate that erodibility and critical shear stress parameters should be determined very carefully and realistic to determine streambank erosion and sediment transport rate more accurately. This sensitivity analysis also shows the minimum effects of suction angle and cohesion on results. In this case, making an assumption in a literal range, or safely ignoring them should not cause a big variation on CONCEPTS results.

Since bio-gasification is a potentially more efficient way to utilize bio-energy, the economic feasibility becomes one of the greatest issues when we apply this new technology. Evaluation of economic feasibility of a bio-gasification facility needs understanding of its production unit cost under different capacities and different working shift modes. The objectives of this study were to evaluate the unit cost of bio-syngas and biouel products at different capacities by using economic modeling method. Result showed that economic feasibility of a power facility was significantly affected by its production capacity and operating mode (one shift, two shifts, or three shifts mode). Economic feasibility could be improved by increasing production capacity or by changing operating mode to two or three shifts from one shift. The economic evaluation model and cost analysis software developed in this study could be a good tool for economic analysis of bio-syngasand biouel products from biomass gasification.

Battery electric buses (BEBs) bring several advantages to public transportation systems. With fixed routes and scheduled trips, the implementation of BEBs in the transit context is considered a seamless transition towards a zero greenhouse gases transit system. However, energy consumption uncertainty is a significant deterrent for mainstream implementation of BEBs. Demonstration and trial projects are often conducted to better understand the uncertainty in energy consumption (EC). However, the BEB's energy consumption varies due to uncertainty in operational, topological, and environmental attributes. This thesis aims at developing simulation, data-driven, and low-resolution models using big data to quantify the EC of BEBs, with the overarching goal of developing a comprehensive planning framework for BEB implementation in bus transit networks. This aim is achieved through four interwind objectives. 1) Quantify the operational and topological characteristics of bus transit networks using complex network theory. This objective provides a fundamental base to understanding the behaviour of bus transit networks under disruptive events. 2) Investigate the impacts of the vehicular, operational, topological, and external parameters on the EC of BEBs. 3) Develop and evaluate the feasibility of big-data analytics and data-driven models to numerically estimate BEB's EC. 4) Create an open-source low-resolution data-based framework to estimate the EC of BEBs. This framework integrates the modelling efforts in objectives 1-3 and offers practical knowledge for transit providers. Overall, the thesis provides genuine contributions to BEB research and offers a practical framework for addressing the EC uncertainty associated with BEB operation in the transit context. Further, the results offer transit planners the means to set up the optimum transit operations profile that improves BEB energy utilization, and in turn, reduces transit-related greenhouse gases. / Thesis / Doctor of Engineering (DEng)

There are experimental based software packages as well as traffic simulation models that are used for analyzing life cycle cost of road projects. Among those our study was focused on currently available models to analyze the road user delay costs and to identify factors affecting road user delay costs. Sensitivity analyses were performed to identify the important factors that influence the user delay cost. Finally, prediction of future traffic demand as well as user delay cost, using the binomial lattice model, were presented to include the uncertainty of future traffic and user delay costs. The results of this study could help the highway designers with evaluating the future traffic.

A method of sensor location selection is introduced for distributed parameter systems. In this method, the sensitivities of spatial outputs to model parameters are computed by a model and transformed via continuous wavelet transforms into the time-scale domain to characterize the shape attributes of output sensitivities and accentuate their differences. Regions are then sought in the time-scale plane wherein the wavelet coefficient of an output-sensitivity surpasses all the others’ as indication of the output sensitivity’s uniqueness. This method yields a comprehensive account of identifiability each output provides for the model parameters as the basis of output selection. This output selection strategy is evaluated for a numerical case of pollutant dispersion by advection and discussion in a two-dimensional area.

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