Computational intelligence in aerospace sciences / edited by Massimiliano Vasile, Victor M. Becerra.

Format:

Book

Contributor:

Becerra, Victor M., editor.

Vasile, Massimiliano, editor.

Series:

Progress in astronautics and aeronautics ; Volume 244.

Progress in Astronautics and Aeronautics ; Volume 244

Language:

English

Subjects (All):

Computational intelligence.

Aerospace engineering--Technological innovations.

Aerospace engineering.

Physical Description:

1 online resource (115 pages) : illustrations.

Edition:

1st ed.

Place of Publication:

[Place of publication not identified] : [American Institute of Aeronautics and Astronautics], [2014]

Summary:

This book is intended for practitioners seeking an overview of different computational intelligence techniques with aerospace applications, and for newcomers looking for fundamental information with advanced examples. It provides a look into the world of computational intelligence, detailing techniques across four main areas of aerospace sciences: robotics, multidisciplinary design, aerodynamics, and space.

Contents:

Intro

Multiobjective Optimization for Space Mission Design Problems

Introduction

Multiobjective Optimization

Mathematical Programming Techniques for MOPs

Scalarization Methods

Pareto Descent Methods

Multiobjective Continuation Methods

Set Oriented Approaches

Evolutionary Multiobjective Optimization

Non-Pareto based algorithms

Pareto-based approaches

Indicator-based algorithms

Use of Decomposition

Other metaheuristics

MOO for Space Mission Design Problems

Future Research Trends

Function Landscapes and theDifficulty of Global Optimization

Local minimizers at different levels

Perturbation operators

Selection operators

A Markov chain perspective

Conclusions

Stochastic Methods for SingleObjective Global Optimization

Problem definition

A landscape perspective on global optimization problems

A generic stochastic global optimization framework

Stochastic global optimization methods

Methods from mathematical programming

Physics-inspired methods

Biology-inspired methods

Stochastic optimization from a computationalstatistics view point

Markov Chain Monte Carlo methods

Approximate Bayesian Computation

Modern benchmark test suites for stochasticglobal optimization

The IEEE CEC 2005 benchmark test suite

Alternative benchmark test suites

Final remarks and further reading

Uncertainty Quantification in Computational Science

Introduction and Motivation

Definitions and Basic Concepts

Errors vs Uncertainties

Aleatory Uncertainty

Epistemic Uncertainty

Sensitivity vs Uncertainty Analysis

Predictions Under Uncertainty

Data Assimilation

Probabilistic Uncertainty Propagation

Sampling Techniques

Quadrature Methods

Spectral Methods

Examples

Uncertainties in High-Speed Flows.

Radiative Heat Flux Modeling for Titan Atmospheric Entry

Conclusions and Outlook

Basic Concepts of Game Theoryfor Aerospace EngineeringApplications

A Brief History of Game Theory

Cooperative and Noncooperative Games

Terminology

Game Forms

Strategic-Form Games

Examples of Strategic-Form Games

Extensive-Form Games

Equilibrium Solution

Dominated Strategies

Nash Equilibrium Solution

Existence of Nash Equilibrium Solutions

Leader-Follower Models

Stackelberg Games

Security Strategy

Extensions to n-person Games

Applicative Examples

Multiobjective Aerodynamics Optimization

Multidisciplinary Decision Making

Concluding Remarks

Nonlinear State Estimation Algorithms for Autonomous Vehicles

Extended Kalman Filter

Nonlinear Transformation and the effects of Linearization

Polar to Cartesian Coordinates Transformation:First-order linearization

Unscented Kalman Filter

Unscented Transformation

Cubature Kalman Filter

CKF Theory

Cubature Transform

Simultaneous Localization and Mapping

The Vehicle, Landmark, and Sensor Models

CKF SLAM

Simulation Results

Path Planning Algorithms in 2-Dand 3-D Obstacle-RichEnvironments

Visibility Line (VL) method

2-D Path Planning Using VL Method

Demonstration of VL

Related work on VL

Base Line Oriented Visibility Lines (BLOVL) Algorithm

The Core algorithm

The BLOVL algorithm

Limited horizon BLOVL (LH-BLOVL)

Performance Comparison of VL And BLOVL

3-D Path Planning Algorithm

Finding a path on a vertical plane

Finding a path on a base plane

BLOVL3D2 algorithms

Demonstration of BLOVL3D2

BLOVL3D2 Performance

Using different numbers of rotation angles

Using different numbers of obstacles

Conclusions.

Semantics of Perception and Actionfor Symbolic Reasoning inAerospace Systems

UAV Operations for Remote Dull, Dirty,and Dangerous Missions

UAV Operation for Commercial Purposes

Space Applications

A Closer Look at the Knowledge-based Approach

A Mathematical Presentation of Knowledge Systems

Human Thinking Based on Conceptual Graphs

Documents in Terms of a Natural Language Program

Meaning Definitions of CGs

Abstraction Levels

Abstraction Layers of Models and Actions

Initial Beliefs and Actions

Classes of Object for Environment Modeling

Processes of Perception

Preparatory Basic Rules

Messages and ``Service'' Behavior

Rules of Physical Action in the Environment

A case study

Space Robotics: Towards anArchitecture for AutonomousMobile Manipulation

Use Cases: AILA, Sherpa, and Asguard

System Design

Low-Level Control

High-Level Control-Planning and Plan Execution

Embodied Localization and Mapping

High-Level Navigation Path Planning

High-Level Manipulation Control

Conclusion

Advances in Space Robotics Autonomy

Entry Descent Landing

Rover Localization

Autonomous Hazard Navigation

Autonomous Instrument Placement

Autonomous Opportunistic Science

Dense Real-Time Stereo Ranging

Rover Global Path Planning

Targeted Driving Using Visual Tracking on Mars:From Research to Flight

Functional Description

Infusion into MER

Deployment on MARS

First Operational Checkout

Second Operational Checkout

Third Operational Checkout

Single-SOL Instrument Placement

Lander Digability Assessment of Planetary Surface

Lander Instrument Placement on Planetary Surface

Vision Technologies for Small-Body Proximity Operations

Landmark Detection and Recognition.

Generating 3-D Landmark Positions

Catalog Components

Localization from Landmarks

Experimental Validation

Localization: Twice Around Case Study

Bundle Adjustment and Landmark Catalog: Twice Down Case Study

Optimum Structural Design Using Bio-Inspired Search Methods: A Survey and Applications

An Overview of Bio-Inspired Search Methods in Optimum Structural Design

Single Objective Methods

Multiobjective Methods

Structural Applications

Structural Problem

Test Cases

Results

Discussion

Research Trends

Composition, Management, and Exploration of Computational Studies at Early Design Stage

BACKGROUND AND DEFINITIONS

PREAMBLE

Configuration of Computational Workflows

Design Optimization

Design Robustness

Isocontours

Computational Design Study Formulation

Intelligent Model Selection in the Assembly of Workflows

Study Formulation

Design Space Exploration and Redefinition

Exploration of Feasible Region(S) in the Design Space

Design Space Redefinition

Robust Optimization Study

EXTENDING THE SCOPE

MOTIVATION

GEOMETRIC MODELING BRIEF

Integration With Flops

Summary and Conclusions

Surrogate Modeling in the Serviceof Multidisciplinary Design

Surrogate Modeling

Kriging

Cross-Validation of a Surrogate Model

Dealing with Constraints-Support Vector Classification

Sampling Plans

Multidisciplinary Design Optimization (MDO)

Multiobjective Optimization (MO)

A `Real-World' Application

Over-Wing Engine Installations

An Experiment Investigating Airframe Noise Shielding

The Over-Wing Engine Configuration: an MDO Approach

Aerodynamic Investigation

Description of the CFD Setup

Inlet Efficiency Results

Aerodynamic Efficiency Results.

TradeOff Study

Results Summary

Multidisciplinary Design Optimization of Aerospace Transportation Systems

Multidisciplinary Design Optimization Framework

Optimization Approaches

Uncertainty Propagation Techniques

Robust Multidisciplinary Design Approach

Multiobjective Algorithm

Robust Design Optimization Under Uncertainty

Multifidelity Evolution Control

Surrogate Model

Rocket Ascent Case Study

Rocket Ascent Results

Unmanned Space Re-entry Vehicle Case Study

Geometry and Shape Model

Aerodynamic Models

TPS and Thermal Model

Mass Model

Dynamic Equations

USV Optimization Set-Up

Shape Optimization

Trajectory Optimization

USV Results

Aerodynamic Shape Design Using Evolutionary Computation: A Tutorial with Examples and Case Studies

Hybrid Evolutionary Optimization Algorithm

Approximate fitness evaluators

Approximation problem analysis

Elitist asymmetric multiobjective optimization algorithm

Shape parameterization and handling in aerodynamic design

Geometry representation building blocks

RAE2822 design optimization example

Problem definition and shape handling

Grid generation, flow solver, and gradient computation

Hybrid optimization run

Hybrid optimization example through adjointand aerofunctions

Adjoint solver

Optimization algorithm

Multipoint airfoil example

AMOGAe application to a wing design problem

Multiobjective Design Optimization Using Nash Games

Design optimization for antagonistic disciplines

Concurrent structural and thermal design optimizationby a split of the primitive variables

Two weakly coupled state problems

A game between heat transfer and thermo-elasticityin topology design

A Numerical Experiment.

Nash game by adaptive split of territory.

Notes:

Includes bibliographical references and index.

Description based on online resource; title from PDF cover (ebrary, viewed October 20, 2017).

ISBN:

1-62410-271-9

OCLC:

1004846429