Human-in-the-loop : probabilistic modeling of an aerospace mission outcome

Content: Cover
 Half Title
 Title Page
 Copyright Page
 Table of Contents
 Preface
 Author
 1. Introduction: Probabilistic Modeling Approach in Aerospace Engineering
 2. Fundamentals of Applied Probability
 2.1 Random Events
 2.2 Algebra of Events
 2.3 Discrete Random Variables
 2.3.1 Probability Characteristics
 2.3.2 Poisson Distribution
 2.4 Continuous Random Variables
 2.4.1 Probability Characteristics
 2.4.2 Bayes Formula for Continuous Random Variables
 2.4.3 Bayes Formula as a Technical Diagnostics Tool
 2.4.4 Uniform Distribution
 2.4.5 Exponential Distribution. 2.4.6 Normal (Gaussian) Distribution2.4.7 Rayleigh Distribution
 2.4.8 Weibull Distribution
 2.4.9 Beta-Distribution
 2.4.10 Beta-Distribution as a Tool for Updating Reliability Information
 2.5 Functions of Random Variables
 2.6 Extreme Value Distributions
 3. Helicopter-Landing-Ship and the Role of the Human Factor
 3.1 Summary
 3.2 Introduction
 3.3 Probability That the Operation Time Exceeds a Certain Level
 3.4 Probability That the Duration of Landing Exceeds the Duration of the Lull
 3.5 The Probability Distribution Function for the Extreme Vertical Velocity of Ship\'s Deck. 3.6 Allowable Landing Velocity When Landing on a Solid Ground3.7 Allowable Landing Velocity When Landing on a Ship Deck
 3.8 The Probability of Safe Landing on a Ship\'s Deck
 3.9 Conclusions
 References
 4. Fundamentals of Probabilistic Aerospace Electronics Reliability Engineering
 4.1 Today\'s Practices: Some Problems Envisioned and Questions Asked
 4.2 Accelerated Testing
 4.3 PDfR and Its Major Principles (\"10 Commandments\")
 4.4 FOAT (\"Transparent Box\") as an Extension of HALT (\"Black Box\")
 4.5 Design for Reliability of Electronics Systems: Deterministic and Probabilistic Approaches. 4.6 Two Simple PDfR Models4.7 BAZ Model: Possible Way to Quantify Reliability
 4.8 Multiparametric BAZ Model
 4.9 The Total Cost of Reliability Could Be Minimized: Elementary Example
 4.10 Possible Next Generation of the Qualification Tests (QTs)
 4.11 Physics-of-Failure BAZ Model Sandwiched between Two Statistical Models: Three-Step Concept
 4.11.1 Incentive/Motivation
 4.11.2 Background
 4.11.3 TSC in Modeling Aerospace Electronics Reliability
 4.11.3.1 Step 1: Bayes Formula as a Suitable Technical Diagnostics Tool
 4.11.3.2 Step 2: BAZ Equation as Suitable Physics-of-Failure Tool. 4.11.3.3 Step 3: Beta-Distribution as a Suitable Reliability Update Tool4.11.3.4 Step 1: Application of Bayes Formula
 4.11.3.5 Step 2: Application of BAZ Equation
 4.11.3.6 Step 3: Application of Beta-Distribution
 4.12 Conclusions
 References
 5. Probabilistic Assessment of an Aerospace Mission Outcome
 5.1 Summary
 5.2 Introduction
 5.3 DEPDF of Human Nonfailure
 5.4 Likelihood of the Vehicular Mission Success and Safety
 5.5 Equipment (Instrumentation) Failure Rate
 5.6 Human Performance Failure Rate
 5.7 Weibull Law.