Recent work in air transit efficiency has increased en-route efficiency to a point that airport efficiency is the bottleneck. With the expected expansion of air transit it will become important to get the most out of airport capacity. Departure scheduling is an area where efficiency stands to be improved, but due to the complicated nature of the problem an optimal solution is not always forthcoming. A heuristic approach can be used to find a sub-optimal take-off order in a significantly faster time than the optimal solution can be found using known methods. The aim of this research is to explore such heuristics and catalog their solution characteristics. A greedy approach as well as a k-interchange approach were developed to find improved takeoff sequences. When possible, the optimal solution was found to benchmark the performance of the heuristics, in general the heuristic solutions were within 10-15% of the optimal solution. The heuristic solutions showed improvements of up to 15% over the first-in first-out order with a running time around 4 ms.

Award-winning actress, Maggie Benedict has dropped Generations. Tshepiso Makhele traces her quest for success, her challenges and the reason for her departure

Droplets and bubbles are important for understanding natural phenomena such as falling raindrops, airborne disease transmission, and plant respiration systems, and also for engineering contexts such as semiconductor fabrication, nuclear power plants, and electronics cooling. However, still, more understanding is needed of these complex dynamics problems. This dissertation will talk about the droplet impact and bubble departure dynamics that are happening on various surfaces. In Chapters 2 and 3, we will explore how raindrops can transmit plant pathogens. When the raindrop impacts the infected wheat leaf, the micron-sized dry spore can liberate from the surface in two different ways: dry dispersal and wet dispersal. The dry spore can liberate from the surface by the inertia of the drop, after that, the air vortex generated by the drop impact can carry the dry spores above the laminar boundary layer, with the potential for long-distance transport. For the wet dispersal, spore-laden droplets can be generated after raindrop impact, but how these spore-laden droplets can make neighboring plant diseases is still a mystery. We have shown that the splashed droplets can stick to the adjacent healthy leaf depending on the inertia of the impacting droplet, anisotropic leaf orientation, and whether it is treated with fungicide or not. In Chapter 4, We design a micropillar aluminum substrate that preferentially grows frost on top of the pillars. When deposited droplets impact the frost-tipped pillars, the dynamic pressure causes the water to wick within the frost faster than it can impale the gaps between the pillars. Upon freezing, this safely suspends the resulting ice sheet in the air-trapping Cassie state, without any surface coatings required. For the last part (Chapter 5), we investigated the bubble coalescence dynamics that can depart the bubble with a micrometer size. We made the micro-structured surfaces tailored to nucleation sites to enable the coalescence-induced departure of micro-bubbles. A scaling model reveals two different modes of bubble departure following the coalescence-induced depinning: capillary-inertial jumping for micrometric bubbles and a buoyant-inertial departure for millimetric ones. Eventually, this small bubble departure can delay film boiling which can be the barrier to the boiling heat transfer. / Doctor of Philosophy / Dynamic interaction of droplets and bubbles with different surfaces is ubiquitous: an impacting rain droplet on a plant leaf is responsible for transmitting thousands of plant pathogens, or decreasing the departure size of bubbles on the surface of heat exchangers would increase their efficiency. It is now well-understood that the departure of condensed droplets on water repellent surfaces exhibits superior heat transfer compared to all other modes of condensation and also enables self-cleaning, delayed frosting, and anti-fogging surface technology.In Chapters 2 and 3, we are studying the dynamic interaction of raindrops and wheat leaves. By depositing water droplets on diseased leaves, we found out a raindrop can transmit wheat pathogens. This simple but important phenomenon would adversely affect the quality of our wheat which is the most widely grown crop in the world, contributing to a large amount of portion the global food supply. Chapter 4 sheds light on another example of the dynamic interaction of raindrops and an icy surface. We designed a pillared aluminum substrate that preferentially grows condensation frosting on top of the pillars. With this passive anti-frosting technology, we are able to trap water droplets and ice in the suspending water droplets in the air-trapping Cassie state without using a fragile nanotextured structure or a complex re-entrant structure. Upon freezing, this safely suspends the resulting ice sheet in the air-trapping Cassie state, without any surface coatings required. Under a cold and humid environment, Cassie water freezes into Cassie ice which is advantageous for its low surface adhesion. In Chapter 5, we show that rationally micro-structured surfaces tailor nucleation sites to enable the coalescence-induced departure of micro-bubbles. With this technique, we are able to remove surface bubbles at smaller sizes that would result in enhancing the critical heat flux of nucleate boiling. We have used a blend of experiments and scaling to understand the underlying physics of this phase-change problem.

Driving Assistance Systems such as lane departure and front collision warning has caught great attention for its promising usage on road driving. This, this research focus on implementing lane departure and front collision warning at same time. In order to make the system really useful for real situation, it is critical that the whole process could be near real-time. Thus we chose Hough Transform as the main algorithm for detecting lane on the road. Hough Transform is used for that it is a very fast and robust algorithm, which makes it possible to execute as many frames as possible per frames. Hough Transform is used to get boundary information, so that we could decide if the car is doing lane departure based on the car's position in lane. Later, we move on to use front car's symmetry character to do front car detection, and combine it with Camshift tracking algorithm to fill the gap for failure of detection. Later we introduce camera calibration, stereo calibration, and how to calculate real distance from depth map.

This study explores the mathematical programming aspects of the air cargo fleet assignment problem for one international air cargo carrier - Korean Air - under given origin-destination (O-D) pairs, departure and arrival times, and frequencies. A pure cargo service is taken as the basis for this study, since such a service is not constrained by passenger route determinants and the schedule of a combination air carrier. The objectives of the study include: to identify the pure air cargo network representation of the combination air carriers; to develop and solve a conventional branch-and-bound mathematical programming model for optimising the assignment of aircraft to flight routes given a set of constraints, including aircraft fleet size, schedule balance, and `required through' constraints; to develop and solve the fleet assignment problem using a novel neural network optimisation modelling approach; to investigate methods of implementing the neural network model, and to analyse the performance of the model when compared with conventional solution methods; and finally to analyse the utility of the neural network model and identify how it may be used in the design and development of air cargo networks for combination air carriers like Korean Air. There are four main parts to the thesis: the first part outlines the schedule design process of an airline and some details of the fleet assignment problem are reviewed. The air cargo flight network is represented and the fleet assignment problem is formulated as a mixed integer programming problem of cost minimisation with various constraints. The complexity of the problem is discussed; the second part outlines the various techniques available to solve optimisation problems and neural network models are presented and discussed as a promising alternative solution method. Neural network applications in the transport field are reviewed and the neural network process for optimisation and for solving the general assignment problem are studied and presented; the third part incorporates the practical application of both the conventional fleet assignment problem solving method and the proposed neural network method to a combination airline's case - Korean Air. The detailed process of constructing a time line network and formulating a mathematical programming model are described and equivalent neural network models are formulated. The results from the two solution approaches are compared and evaluated; and the final part summarises the main findings, presents the significant conclusions, the contribution of the research is discussed and some recommendations for further research are presented. Overall, the conventional branch-and-bound optimisation model yielded plausible results which were demonstrably superior to those produced using the novel neural network optimisation models.

Indiana University-Purdue University Indianapolis (IUPUI) / An important topic in autonomous vehicle related research in recent times is road departure warning (RDW) and road keeping assistance (RKA). RDW or RKA should be able to recognize and avoid roadside objects. Standard tests are needed to evaluate the performance of RDW and RKA feature of cars from different manufacturers. To avoid damage to the cars under test and the test environment during testing, there is a need of soft, durable and reusable surrogate targets representing various real roadside objects such as curb, concrete divider and metal guardrail. These surrogate objects should have representative characteristics of real roadside objects from the point of view of various commonly used object detection sensors on the vehicles such as camera, radar and LIDAR. Transportation Active Safety Institute (TASI) at Indian University-Purdue University Indianapolis (IUPUI) is in the process of developing surrogate concrete divider, curb metal guardrail and grass that should be recognized as real roadside objects by LIDAR sensors, can be crashed without damage to the test vehicle and can be reused even after multiple crashes. The first step is to understand what the representative roadside objects should look like from the point of view of LIDAR units using laser of various wavelengths, and the next step is to design surrogate objects that successfully emulate the properties of the real roadside objects. Reflectance of an object is an important property for LIDAR detection. This thesis describes an approach for the determination of infrared reflectance property of concrete, metal guardrail and grass for different LIDAR view angles. Various samples of each of these roadside objects were evaluated. Based on these measurements, the suggested reflectance of surrogate roadside objects in the common LIDAR wavelength range of 800-1100 nm is specified. Finally, the design of surrogate roadside objects that satisfy these requirements is described, and the infrared reflectance of these surrogate objects are compared to the suggested reflectance bounds for different LIDAR view angles.

A generalized dynamic programming based algorithm and a local search heuristic are used to solve the Two Runway Departure Scheduling Problem that arises at an airport. The objective of this work is to assign the departing aircraft to one of the runways and find a departing time for each aircraft so that the overall delay is minimized subject to the timing, safety, and the ordering constraints. A reduction in the overall delay of the departing aircraft at an airport can improve the airport surface operations and aircraft scheduling. The generalized dynamic programming algorithm is an exact algorithm, and it finds the optimal solution for the two runway scheduling problem. The performance of the generalized dynamic programming algorithm is assessed by comparing its running time with a published dynamic programming algorithm for the two runway scheduling problem. The results from the generalized dynamic programming algorithm show that this algorithm runs much faster than the dynamic programming algorithm. The local search heuristic with k − exchange neighborhoods has a short running time in the order of seconds, and it finds an approximate solution. The performance of this heuristic is assessed based on the quality of the solution found by the heuristic and its running time. The results show that the solution found by the heuristic for a 25 aircraft problem has an average savings of approximately 15 percent in delays with respect to a first come-first served solution. Also, the solutions produced by a 3-opt heuristic for a 25 aircraft scheduling problem has an average quality of 8 percent with respect to the optimal solution found by the generalized dynamic programming algorithm. The heuristic can be used for both real-time and fast-time simulations of airport surface operations, and it can also provide an upper limit for an exact algorithm. Aircraft arrival scheduling problems may also be addressed using the generalized dynamic programming algorithm and the local search heuristic with slight modification to the constraints.

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A stability analysis and departure prediction method has been developed and coded in a MATLAB®-based software package called the Stability And Departure Analysis Tool using Eigenvalue Sensitivity (SADATES). Using eigenvalue and eigenvector analysis, SADATES is capable of performing a full-envelope stability analysis, returning both quantitative and qualitative data regarding the stability of the airplane at a static reference condition. SADATES not only supplies the analyst with information describing where and when an aircraft is likely to depart, but also information about the departure characteristics, enabling the analyst to design for better departure resistance. While the eigenvalue and eigenvector approach is straightforward, it is a broader approach than many traditional stability parameters, yielding more accurate and reliable results than traditional methods. SADATES also analyzes the aircraft dynamics from a standpoint of eigenvalue sensitivity. Using this feature, the analyst may directly study the impact of data uncertainty and non-zero angular rates on the nominal stability of the aircraft. Of particular interest are the effects of the dynamic damping derivatives, as these derivatives are particularly difficult to estimate. In addition, the effect of an unsteady reference condition may be examined by studying the sensitivity of the eigenvalues to changes in angular rates, thereby using a static approach to give answers to a dynamic problem. Given the development of eigenvalue sensitivity data, the analyst is able to determine the margin of error on nominal aircraft stability. The utility of the SADATES package is tested using aerodynamic data of the McDonnell-Douglas F / A-18C Hornet. Bare airframe, controls fixed stability is analyzed, and its sensitivity to data uncertainty and to non-zero angular rates is examined. The Hornet's bare airframe stability characteristics are then compared to those using an active feedback control system to drive an automatic leading and trailing edge flap schedule, demonstrating the accuracy and versatility of the program. / Master of Science