Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Vita. / Includes bibliographical references. / by Donald Arthur Dube. / Ph.D.

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This thesis describes a simple efficient and robust numerical technique for solving two-dimensional incompressible laminar steady flows at moderate-to-high Reynolds numbers. The method uses an incremental multigrid method and an extrapolation procedure based on minimum residual concepts to accelerate the convergence rate of a robust block-line-Gauss-Seidel solver for the vorticity-stream function equations. Results are presented for the driven cavity flow problem using uniform and nonuniform grids and for the flow past a backward facing step in a channel. / M.S.

In this dissertation large-eddy simulation(LES) is used to study the transitional and turbulent structures of vortices and free shear layers. The recently developed dynamic model and the basic Smagorinsky model are utilized to model the subgrid-scale(SGS) stress tensor. The dynamic model has many advantages over the existing SGS models. This model has the ability to vary in time and space depending on the local turbulence conditions. This eliminates the need to tune the model constants a priori to suit the flow field being simulated. Three different flow fields are considered. First, the evolution of large-scale turbulent structures in centrifugally unstable vortices is studied. It is found that these structures appear as counter rotating vortex rings encircling the vortex core. The interaction of these structures with the core results in the transfer of angular momentum between the core and the surroundings. The mean tangential velocity decays due to this exchange of angular momentum. Second, the generation and decay of turbulent structures in a vortex with an axial velocity deficit are studied. The presence of a destabilizing wake-like axial velocity field in an otherwise centrifugally stable vortex results in a very complex flow field. The inflectional instability mechanism of the axial velocity deficit amplifies the initial disturbances and results in the generation of large-scale turbulent structures. These structures appear as branches sprouting out of the vortex core. The breakdown of these structures leads to small-scale motions. But the stabilizing effects of the rotational flow field tend to quench the small-scale motions and the vortex returns to its initial laminar state. The mean axial velocity deficit is weakened, but the mean tangential velocity shows no significant decay. Third, a transitional mixing layer calculation is performed.The growth and breakdown to small scales of vortical structures are studied. Emphasis is given to the identification of late transition structures and their subsequent break down. Formation of streamwise vortices in place of the original Kelvin-Helmholtz vortices and the subsequent appearance of hair-pin vortices at the edges of the mixing layer mark the completion of transition. The basic Smagorinsky model is also used in the mixing layer simulations. The performance of the dynamic model is compared with the previous results obtained using the basic Smagorinsky model. As expected, the basic Smagorinsky model is found to be more dissipative. / Ph. D.

Developing real-time traffic diversion strategies is a major issue of Advanced Traffic Management Systems (ATMS), a component of Intelligent Vehicle Highway Systems (IVHS). Traffic diversion utilizes available capacity in the urban network during a congestion-causing event. If an alternative route selected for diversion is not congested at the current time, a certain part of the route may become congested by the time the diverted drivers reach that part of the network. Thus the ability to forecast future traffic variables on each link along various routes in a prompt and accurate fashion may be necessary to ensure the success of a diversion strategy. Forecasting future traffic variables would also be helpful for urban traffic control. In addition, the forecasting model may help assign the vehicles onto the alternate roads, if the information on driver destinations and the routes between a diversion point and the destinations are available. This dissertation is aimed at developing and evaluating two prediction models: link-based model and network-based model. The link-based prediction model has two components. One component is an Auto Regressive Integrated Moving Average (ARIMA) time series model based on the latest (current) traffic data. The other component is the smoothed historical traffic volume (historical average) for that period as obtained from previous days. These two components are combined to represent the dynamic fluctuations in the traffic flow behavior. The combined model is designed to produce the predicted traffic volumes for a look-ahead period of 30 minutes, divided into 6-minute time intervals. The results show that the combined model is promising for light to medium congested traffic conditions. The network-based prediction model combines current traffic, historical average, and upstream traffic. It is presumed that traffic volume on the upstream can be used to predict the downstream traffic in a specific time period. Three prediction models are developed for traffic prediction: a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models are evaluated through regression analysis. The third model is found to be the most applicable while the first model was the least. In order to consider current traffic conditions, a heuristic adaptive weighting system is devised based on the relationships between the origin of prediction and the previous periods. The developed models are applied to real freeway data in 15-minute time interval measured by regular induction loop detectors. The prediction models are shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-minute or 45-minute. It is noted that the combined models usually produce more consistent forecasts than the historical average. / Ph. D.

This research effort is motivated by the need to quickly obtain origin-destination (0-0) trip information for an urban area, without expending the excessive time and effort usually accompanying survey-based methods. The intent is to utilize this information to facilitate diversion of traffic in real time, in the event of congestion-causing incidents such as accidents. The O-D trip table information is a key to successful diversion planning, where user destinations are considered in developing the plans. Traffic volumes on the links of the road network contain information which can be exploited advantageously to derive the trip patterns. This approach of synthesizing a trip table from link volumes, and perhaps using a prior trip table to guide the derivation, has useful applications in the context of diversion planning. Unlike conventional O-D surveys, it has the potential of yielding results quickly, a requisite for real-time applications. This research work details a new methodology for synthesizing origin-destination (0-0) trip tables. The approach, which is based on a non-proportional assignment, user-equilibrium motivated, linear programming model, is the principal component of this dissertation. The model is designed to determine a traffic equilibrium network flow solution which reproduces the link volume data, if such a solution exists. If such alternate solutions exist, then it is designed to find that which most closely resembles a specified target trip table. However. it recognizes that due to incomplete information, the traffic may not conform to an equilibrium flow pattern, and moreover, there might be inconsistencies in the observed link flow data, or there might be incomplete information. Accordingly, the model permits violations in the equilibrium conditions as well as deviations from the observed link flows, but at suitable incurred penalties in the objective function. A column generation solution technique is presented to optimally solve the problem. The methodology also accommodates a specified prior target trip table, and drives the solution toward a tendency to match this table using user controlled parameters. Implementation strategies are discussed, and an illustration of the proposed method is presented using some sample test networks. The results from the model are discussed vis-a-vis other relevant, available approaches. The quality of the results and the computational effort required are used as a set of criteria in the comparisons. The comparisons of test results demonstrate the superiority of the linear programming model over the other models considered. The model is also applied to a real network of Northern Virginia, where congestion problems present a serious concern. As a result of this experience, several implementation strategies relevant to the application of the model on a real network are presented, and some general conclusions are derived. The potential application of the model in real-time traffic diversion planning for the study area is discussed. Recommendations for further research are also presented. / Ph. D.