Modeling, simulation, and flight characteristics of an aircraft designed to fly at 100,000 feet

A manned real time simulation of a conceptual vehicle, the stratoplane, was developed to study the problems associated with the flight characteristics of a large, lightweight vehicle. Mathematical models of the aerodynamics, mass properties, and propulsion system were developed in support of the simulation and are presented. The simulation was at first conducted without control augmentation to determine the needs for a control system. The unaugmented flying qualities were dominated by lightly damped dutch roll oscillations. Constant pilot workloads were needed at high altitudes. Control augmentation was studied using basic feedbacks. For the longitudinal axis, flight path angle, and pitch rate feedback were sufficient to damp the phugoid mode and to provide good flying qualities. In the lateral directional axis, bank angle, roll rate, and yaw rate feedbacks were sufficient to provide a safe vehicle with acceptable handling qualities. Intentionally stalling the stratoplane to very high angles of attack (deep stall) was studied as a means of enable safe and rapid descent. It was concluded that the deep stall maneuver is viable for this class of vehicle

A novel model of learning in design

Learning in design is a phenomenon that has been observed in design practice by many researchers. The observation that designers learn is supported by protocol studies in design that experienced designers can reach satisfactory design solutions more effectively than novice/naive designers. That there was no comprehensive model or theory of learning in design to explain the phenomenon was identified by Sim. Hence a need was raised to develop a comprehensive model of learning in design that can describe the phenomenon and therefore serve as a basis to develop effective and efficient design support system(s)

A foundation for machine learning in design

This paper presents a formalism for considering the issues of learning in design. A foundation for machine learning in design (MLinD) is defined so as to provide answers to basic questions on learning in design, such as, "What types of knowledge can be learnt?", "How does learning occur?", and "When does learning occur?". Five main elements of MLinD are presented as the input knowledge, knowledge transformers, output knowledge, goals/reasons for learning, and learning triggers. Using this foundation, published systems in MLinD were reviewed. The systematic review presents a basis for validating the presented foundation. The paper concludes that there is considerable work to be carried out in order to fully formalize the foundation of MLinD

Knowledge transformers : a link between learning and creativity

The purpose of this paper is to investigate whether knowledge transformers that are featured in the learning process are also present in the creative process. First, this was achieved by reviewing accounts of inventions and discoveries with the view of explaining them in terms of knowledge transformers. Second, this was achieved by reviewing models and theories of creativity and identifying the existence of the knowledge transformers. The investigation shows that there is some evidence to show that the creative process can be explained through knowledge transformers. Hence, it is suggested that one of links between learning and creativity is through the knowledge transformers

A formalism for coupled design learning activities

This paper presents a formalism to represent the inextricable link that exists between design and learning. It provides an approach to study and analyse the complex relationships that may exist between design and learning. It suggests that design and learning are linked at the knowledge level (epistemic link), in a temporal manner and in a purposeful manner through the design and learning goal

Knowledge transformers : a link between learning and creativity

The purpose of this paper is to investigate whether knowledge transformers which are featured in the learning process, are also present in the creative process. This is achieved by reviewing models and theories of creativity and identifying the existence of the knowledge transformers. The investigation shows that there is some evidence to show that the creative process can be explained through knowledge transformers. Hence, it is suggested that one of links between learning and creativity is through the knowledge transformers

Flight characteristics of the AD-1 oblique-wing research aircraft

The AD-1 is a low-speed oblique-wing research airplane. This report reviews the vehicle's basic flight characteristics, including many aerodynamic, stability, and control effects that are unique to an oblique-wing configuration. These effects include the change in sideforce with angle of attack, moment changes with angle of attack and load factor, initial stall on the trailing wing, and inertial coupling caused by a roll-pitch cross product of inertia. An assessment of the handling qualities includes pilot ratings and comments. Ratings were generally satisfactory through 30 deg of wing sweep but degraded with increased sweep. A piloted simulation study indicated that a basic rate feedback control system could be used to improve the handling qualities at higher wing sweeps

Flight characteristics of a modified Schweizer SGS1-36 sailplane at low and very high angles of attack

A manned flight research program using a modified sailplane was conducted to very high angles of attack at the NASA-Ames. Piloting techniques were established that enabled the pilot to attain and stabilize on an angle of attack in the 30 to 72 deg range. Aerodynamic derivatives were estimated from the flight data for both low and very high angles of attack and are compared to wind tunnel data. In addition, limited performance and trim data are presented

Botnet Detection Using Recurrent Variational Autoencoder

Botnets are increasingly used by malicious actors, creating increasing threat to a large number of internet users. To address this growing danger, we propose to study methods to detect botnets, especially those that are hard to capture with the commonly used methods, such as the signature based ones and the existing anomaly-based ones. More specifically, we propose a novel machine learning based method, named Recurrent Variational Autoencoder (RVAE), for detecting botnets through sequential characteristics of network traffic flow data including attacks by botnets. We validate robustness of our method with the CTU-13 dataset, where we have chosen the testing dataset to have different types of botnets than those of training dataset. Tests show that RVAE is able to detect botnets with the same accuracy as the best known results published in literature. In addition, we propose an approach to assign anomaly score based on probability distributions, which allows us to detect botnets in streaming mode as the new networking statistics becomes available. This on-line detection capability would enable real-time detection of unknown botnets

Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. On a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.Comment: 14 pages, 40 figure