Computational fluid dynamics at NASA Ames and the numerical aerodynamic simulation program

Computers are playing an increasingly important role in the field of aerodynamics such as that they now serve as a major complement to wind tunnels in aerospace research and development. Factors pacing advances in computational aerodynamics are identified, including the amount of computational power required to take the next major step in the discipline. The four main areas of computational aerodynamics research at NASA Ames Research Center which are directed toward extending the state of the art are identified and discussed. Example results obtained from approximate forms of the governing equations are presented and discussed, both in the context of levels of computer power required and the degree to which they either further the frontiers of research or apply to programs of practical importance. Finally, the Numerical Aerodynamic Simulation Program--with its 1988 target of achieving a sustained computational rate of 1 billion floating-point operations per second--is discussed in terms of its goals, status, and its projected effect on the future of computational aerodynamics

Computational fluid dynamics: Transition to design applications

The development of aerospace vehicles, over the years, was an evolutionary process in which engineering progress in the aerospace community was based, generally, on prior experience and data bases obtained through wind tunnel and flight testing. Advances in the fundamental understanding of flow physics, wind tunnel and flight test capability, and mathematical insights into the governing flow equations were translated into improved air vehicle design. The modern day field of Computational Fluid Dynamics (CFD) is a continuation of the growth in analytical capability and the digital mathematics needed to solve the more rigorous form of the flow equations. Some of the technical and managerial challenges that result from rapidly developing CFD capabilites, some of the steps being taken by the Fort Worth Division of General Dynamics to meet these challenges, and some of the specific areas of application for high performance air vehicles are presented

Towards the optimisation of the scheduling of aircraft rotations

The aim of this research is to investigate the schedule punctuality and reliability issue regarding the turnaround operations of an aircraft at an airport and further to explore the influence of aircraft turnaround operations on the scheduling of aircraft rotation in a multiple airport environment. An "aircraft rotation model" is developed in this research by using a stochastic approach to consider the uncertainties in flight schedule punctuality in the air and on the ground as well as operational uncertainties in aircraft turnaround operations. The aircraft rotation model is composed of two sub-models, namely the aircraft turnaround model, which represents the operational process of a turnaround aircraft, and the en route model, which describes the en route flight time of an aircraft between two airports. [Continues.

강화학습을 이용한 공항 임시폐쇄 상황에서의 항공 일정계획 복원

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2021. 2. 문일경.An airline scheduler plans flight schedules with efficient resource utilization. However, unpredictable events, such as the temporary closure of an airport, disrupt planned flight schedules. Therefore, recovering disrupted flight schedules is essential for airlines. We propose Q-learning and Double Q-learning algorithms using reinforcement learning approach for the aircraft recovery problem (ARP) in cases of temporary closures of airports. We use two recovery options: delaying departures of flights and swapping aircraft. We present an artificial environment of daily flight schedules and the Markov decision process (MDP) for the ARP. We evaluate the proposed approach on a set of experiments carried out on a real-world case of a Korean domestic airline. Computational experiments show that reinforcement learning algorithms recover disrupted flight schedules effectively, and that our approaches flexibly adapt to various objectives and realistic conditions.항공사는 보유하고 있는 자원을 최대한 효율적으로 사용하여 항공 일정계획을 수립하기 위해 비용과 시간을 많이 소모하게 된다. 하지만 공항 임시폐쇄와 같은 긴급 상황이 발생하면 항공편의 비정상 운항이 발생하게 된다. 따라서 이러한 상황이 발생하였을 때, 피해를 최대한 줄이기 위해 항공 일정계획을 복원하게 된다. 본 연구는 강화학습을 이용하여 공항 임시폐쇄 상황에서 항공 일정계획 복원 문제를 푼다. 본 연구에서는 항공기 복원 방법으로 항공편 지연과 항공기 교체의 두 가지 방법을 채택하였으며, 항공 일정계획 복원 문제에 강화학습을 적용하기 위해서 마르코프 결정 과정과 강화학습 환경을 구축하였다. 본 실험을 위해 대한민국 항공사의 실제 국내선 항공 일정계획을 사용하였다. 강화학습 알고리즘을 사용하여 기존의 연구에 비해 항공 일정계획을 효율적으로 복원하였으며, 여러 현실적인 조건과 다양한 목적함수에 유연하게 적용하였다.Abstract i Contents iv List of Tables v List of Figures vi Chapter 1 Introduction 1 Chapter 2 Literature Review 7 Chapter 3 Problem statement 11 3.1 Characteristics of aircraft, flights, and flight schedule requirements 11 3.2 Definitions of disruptions and recovery options and objectives of the problem 13 3.3 Assumptions 16 3.4 Mathematical formulations 19 Chapter 4 Reinforcement learning for aircraft recovery 24 4.1 Principles of reinforcement learning 24 4.2 Environment 27 4.3 Markov decision process 29 Chapter 5 Reinforcement learning algorithms 33 5.1 Q-learning algorithm 33 5.2 Overestimation bias and Double Q-learning algorithm 36 Chapter 6 Computational experiments 38 6.1 Comparison between reinforcement learning and existing algorithms 39 6.2 Performance of the TLN varying the size of delay arcs 46 6.3 Aircraft recovery for a complex real-world case: a Korean domestic airline 48 6.4 Validation for different objectives 54 6.5 Managerial insights 57 Chapter 7 Conclusions 59 Bibliography 61 국문초록 69Maste

Optimization of Cargo Handling Equipment at the Airport

Delaying an aircraft during ground handling costs the airline a lot of money. In critical situations, it is even possible that some flights have to be canceled due to delays. It is therefore the endeavor of all personnel involved in ground operations that they proceed without delay. This paper shows what methods can be used to optimize the required number of handling equipment and what can affect its number

Aerated blast furnace slag filters for enhanced nitrogen and phosphorus removal from small wastewater treatment plants

Rock filters (RF) are a promising alternative technology for natural wastewater treatment for upgrading WSP effluent. However, the application of RF in the removal of eutrophic nutrients, nitrogen and phosphorus, is very limited. Accordingly, the overall objective of this study was to develop a lowcost RF system for the purpose of enhanced nutrient removal from WSP effluents, which would be able to produce effluents which comply with the requirements of the EU Urban Waste Water Treatment Directive (UWWTD) (911271lEEC) and suitable for small communities. Therefore, a combination system comprising a primary facultative pond and an aerated rock filter (ARF) system-either vertically or horizontally loaded-was investigated at the University of Leeds' experimental station at Esholt Wastewater Treatment Works, Bradford, UK. Blast furnace slag (BFS) and limestone were selected for use in the ARF system owing to their high potential for P removal and their low cost. This study involved three major qperiments: (1) a comparison of aerated vertical-flow and horizontal-flow limestone filters for nitrogen removal; (2) a comparison of aerated limestone + blast furnace slag (BFS) filter and aerated BFS filters for nitrogen and phosphorus removal; and (3) a comparison of vertical-flow and horizontal-flow BFS filters for nitrogen and phosphorus removal. The vertical upward-flow ARF system was found to be superior to the horizontal-flow ARF system in terms of nitrogen removal, mostly thiough bacterial nitrification processes in both the aerated limestone and BFS filter studies. The BFS filter medium (whieh is low-cost) showed a much higher potential in removing phosphortls from pond effluent than the limestone medium. As a result, the combination of a vertical upward-flow ARF system and an economical and effective P-removal filter medium, such as BFS, was found to be an ideal optionfor the total nutrient removal of both nitrogen and phosphorus from wastewater. In parallel with these experiments, studies on the aerated BFS filter effective life and major in-filter phosphorus removal pathways were carried out. From the standard batch experiments of Pmax adsorption capacity of BFS, as well as six-month data collection of daily average P-removal, it was found that the effective life of the aerated BFS filter was 6.5 years. Scanning electron microscopy and X-ray diffraction spectrometric analyses on the surface of BFS, particulates and sediment samples revealed that the apparent mechanisms of P-removal in the filter are adsorption on the amorphous oxide phase of the BFS surface and precipitation within the filter