Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.

The Perception of the Visual World. By James J. Gibson. U.S.A.: Houghton Mifflin Company, 1950 (George Allen & Unwin, Ltd., London). Price 35s.

The increasing complexity of engineering systems has sparked increasing interest in multidisciplinary optimization (MDO). This paper presents a survey of recent publications in the field of aerospace where interest in MDO has been particularly intense. The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focused on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design- oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the authors'' main expertise being in the structures area, the bulk of the references focus on the interaction of the structures discipline with other disciplines. In particular, two sections at the end focus on two such interactions that have recently been pursued with a particular vigor: Simultaneous Optimization of Structures and Aerodynamics, and Simultaneous Optimization of Structures Combined With Active Control.

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Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments

A fundamental aspect of autonomous vehicle guidance is planning trajectories. Historically, two fields have contributed to trajectory or motion planning methods: robotics and dynamics and control. The former typically have a stronger focus on computational issues and real-time robot control, while the latter emphasize the dynamic behavior and more specific aspects of trajectory performance. Guidance for Unmanned Aerial Vehicles (UAVs), including fixed- and rotary-wing aircraft, involves significant differences from most traditionally defined mobile and manipulator robots. Qualities characteristic to UAVs include non-trivial dynamics, three-dimensional environments, disturbed operating conditions, and high levels of uncertainty in state knowledge. Otherwise, UAV guidance shares qualities with typical robotic motion planning problems, including partial knowledge of the environment and tasks that can range from basic goal interception, which can be precisely specified, to more general tasks like surveillance and reconnaissance, which are harder to specify. These basic planning problems involve continual interaction with the environment. The purpose of this paper is to provide an overview of existing motion planning algorithms while adding perspectives and practical examples from UAV guidance approaches.

A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance

This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird's eye view of today's scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is more » then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science. « less

Mapping the backbone of science.

The increasing complexity of engineering systems has sparked increasing interest in multidisciplinary optimization (MDO). This paper presents a survey of recent publications in the field of aerospace where interest in MDO has been particularly intense. The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focussed on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design-oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the authors' main expertise being in the structures area, the bulk of the references focus on the interaction of the structures discipline with other disciplines. In particular, two sections at the end focus on two such interactions that have recently been pursued with a particular vigor: Simultaneous Optimization of Structures and Aerodynamics, and Simultaneous Optimization of Structures Combined With Active Control.

/pdf/multidisciplinary-aerospace-design-optimization-survey-of-ghzjxaiur6.pdf

Multidisciplinary aerospace design optimization: Survey of recent developments

Although direct methods using sequential quadratic programming, such as direct collocation, have been widely applied to trajectory optimization problems, optimization results for these methods are sensitive to initial solutions in some cases. For the purpose of finding an appropriate initial solution to gradient-based direct trajectory optimization, a numerical trajectory optimization method using a real-coded genetic algorithm (GA) is considered. Because a typical GA solves unconstrained optimization problems, the penalty function has usually been used as the selection criterion of surviving individuals. However, the convergence properties of this conventional method are sensitive to the penalty parameter. Therefore, a new method that robustly achieves global optimization of the objective function and the feasibility search even with a large penalty parameter is proposed. The proposed method is applied to the constrained brachistochrone problem and a space plane reentry problem. Results indicate promising performance of the proposed method in providing appropriate initial solutions for gradient-based trajectory optimization.

Modified Genetic Algorithm for Constrained Trajectory Optimization

A new design for a tail-sitter vertical takeoff and landing unmanned aerial vehicle was proposed. A nonlinear mathematical model of the vehicle dynamics was constructed by combining simple estimation methods. The flight characteristics were revealed through a trim analysis and an optimized transitional flight path analysis by using the mathematical model. The trim analysis revealed the existence of a flight path constraint to avoid stall; the vehicle could not descend in low-speed flight without high-lift devices such as flaps and slats. These devices improved the descentperformance. Inparticular, slatsprovidedasubstantialimprovement; theyenabled adescent rateof2 m=s. In the optimized transitional flight path analysis, a level outbound transition without high-lift devices was achieved althoughatrimmedlevel flightatlowspeed,aswasshowninthetrimanalysis,wasnotpossible;thiswasbecausethe outboundtransition wasanaccelerative flight.Onthe contrary,without high-lift devices, the vehicle could notavoid climbing to avoid stall during inbound transitions. The slats provided a satisfactory improvement during the transition and enabled a level inbound transition. These results showed the necessity of leading-edge slats for the proposed tail-sitter vertical takeoff and landing unmanned aerial vehicle.

Tail-Sitter Vertical Takeoff and Landing Unmanned Aerial Vehicle: Transitional Flight Analysis

Knowledge combination modeling: The measurement of knowledge similarity between different technological domains

Sustainability science requires the development of a theoretical framework to understand, analyze, and design innovation to solve social, economic, and environmental issues. This paper extends the framework of multi-level perspectives (MLP) by introducing a technology readiness level (TRL), and analyzes the innovation of the advanced turboprop (ATP) engine in the aviation industry, also known as a propfan or an open rotor engine, which is one of the most promising engine innovations expected to mitigate climate change. The concept of TRL was introduced to explain the mechanisms of ATP failure in the late 1980s as well as the transition of the geared turbofan (GTF). In this paper, we discuss why ATP and GTF faced different fates although both were developed under the same landscape in the aviation industry. We also discuss the different roles of the socio-technical regime, such as uneven and dynamic opportunity windows, technological readiness, niche stock, institutional support of export products, and the risk of a ‘launch’ customer, at different TRLs. As illustrated in this paper, MLP with TRL is expected to facilitate future interdisciplinary collaboration between social scientists and engineers, and also transdisciplinary expertise between academia and practitioners by supporting analysis and design of the industry’s transition toward a more environmentally friendly regime as well as its effective management.

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Multi-level perspectives with technology readiness measures for aviation innovation

Human pilot landing control has been analyzed by the authors using neural network modeling. Although the previous research considered only longitudinal control, analysis of the lateral control is the focus of this paper. The lateral control can be quite difficult under crosswind conditions, because the combination of two lateral control methodologies (crab method and wing-low method) is needed for a successful landing. To analyze lateral control, this paper makes a first step: a lateral pilot control model is established. The necessary visual cues for lateral control are defined, and neural network models for aileron and rudder controls are constructed. The adequacy of the proposed neural network model is checked by Monte Carlo simulations.

Shinji Suzuki

Papers

Modified Genetic Algorithm for Constrained Trajectory Optimization

Tail-Sitter Vertical Takeoff and Landing Unmanned Aerial Vehicle: Transitional Flight Analysis

Knowledge combination modeling: The measurement of knowledge similarity between different technological domains

Multi-level perspectives with technology readiness measures for aviation innovation

Neural Network Modeling of Lateral Pilot Landing Control