Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures

✍ Scribed by MZ Naser (editor), Glenn Corbett (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 347
• Edition: 1st ed. 2022
• Category: Library

✦ Synopsis

This handbook aims at modernizing the current state of civil engineering and firefighting, especially in this era where infrastructures are reaching new heights, serving diverse populations, and being challenged by unique threats. Its aim is to set the stage toward realizing contemporary, smart, and resilient infrastructure.

The Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures draws convergence between civil engineering and firefighting to the modern realm of interdisciplinary sciences (i.e., artificial intelligence, IoT, robotics, sensing, and human psychology). As such, this work aims to revolutionize the current philosophy of design for one of the most notorious extreme events: fire. Unlike other publications, which are narrowed to one specific research area, this handbook cultivates a paradigm in which critical aspects of structural design, technology, and human behavior are studied and examined through chapters written by leaders in their fields.

This handbook can also serve as a textbook for graduate and senior undergraduate students in Civil, Mechanical, and Fire Protection engineering programs as well as for students in Architectural and social science disciplines. Students, engineers, academics, professionals, scientists, firefighters, and government officials involved in national and international societies such as the American Society of Civil Engineers (ASCE), Society of Fire Protection Engineers (SFPE), National Fire Protection Association (NFPA), and Institute of Electrical and Electronics Engineers (IEEE), among others, will benefit from this handbook.

✦ Table of Contents

Preface
References
Contents
1 Toward a Sociotechnical Systems Framing for Performance-Based Design for Fire Safety
1.1 Current Structure/Process for PBD of Fire Safety
1.2 Sociotechnical Systems (STS) Concept
1.3 Evaluating PB Design for Fire Through a STS Lens
1.4 Advancing PBD for Fire Safety by Incorporating STSConcepts
1.5 Summary
References
2 A Twenty-First Century Approach to Fire Resistance
2.1 History of Fire Resistance Concepts
2.2 Principles of Standardized Fire Resistance Tests
2.3 Simulation of Fires and Control of Fire Test Furnaces
2.4 Modern Data on Room Fire Temperatures
2.5 Multiple Time/Temperature Curves?
2.6 Petrochemical Industry Tests
2.6.1 Pool Fires
2.6.2 Jet Fires
2.7 What Is the Basis for the Required Fire Resistance Rating?
2.8 Design Practice
2.9 Hose Stream Testing
2.10 Additional Issues
2.11 Conclusions
References
3 Integrating Modern Technologies to Realize Fire-Resistant Infrastructures
3.1 Introduction and Background
3.2 Fundamentals of Fire Protection and Emergency Management
3.2.1 Event Time Spectrum
3.2.2 Passive and Active Approaches
3.2.3 Fire Safety Goals
3.2.4 Fire Protection Measures
3.2.5 Fire Protection Enforcement
3.2.6 Manual Intervention Techniques
3.2.7 Emergency Responders
3.2.8 Fire Service
3.3 Fundamentals of Cyber Physical Systems
3.3.1 The Era of Cyber Physical Systems
3.3.2 Data, Data, in a Sea of Data
3.3.3 The Three Realms of Cyber Physical Systems
3.3.4 Architecture and Design of Cyber Physical Systems
3.4 Systems Integration
3.4.1 All-Hazards Approach
3.4.2 Unified Functionality
3.4.3 Time Critical Events
3.4.4 Communication Pathways
3.5 Case Study Scenarios
3.5.1 Case Study Emergency Event Scenarios
3.5.2 The DIKW Hierarchy
3.5.3 Innovative Applications
3.5.4 Next Generation Cyber Fire Fighter
3.5.5 Las Vegas Active Shooter Case Study
3.6 Cybersecurity: The New Frontier
3.6.1 Need for Resiliency
3.6.2 The Interconnectedness Risk
3.6.3 Other Threats
3.7 Future Directions
3.7.1 The Lexicon Gap
3.7.2 Smart Fire Fighting Research Priorities
3.7.3 Non-Technical Barriers
3.7.4 Final Thoughts
References
4 Intelligent Science Empowers: Building Fire Protection Technology Development
4.1 A Look into Fire Prevention in Buildings
4.2 Build Intelligent Fire Detection and Response System
4.2.1 Fire System Based on Internet of Things
4.2.2 Fire Risk Monitoring System Based on Big Data Analyses
4.2.2.1 Big Data Sources
4.2.2.2 Big Data Fire Risk Forecasting Process
4.2.3 Fire Inspection Based on Indoor A Geographic Information System (GIS Technology)
4.2.3.1 Detective Robots
4.2.3.2 Fire-Fighting Robots
4.2.3.3 Rescue Robots
4.3 Combined with MEP System
4.3.1 Temperature and Humidity Warning and Control
4.3.2 Intelligent Electrical Fire Warning System
4.3.2.1 Cloud Service Platform
4.3.2.2 Big Data Analysis
4.3.2.3 Early Warning of Electrical Accidents
4.3.3 HVAC Control
4.3.3.1 Pre-accident Prevention
4.3.3.2 Post-incident Response
4.3.4 Elevator Assisted Evacuation
4.3.4.1 Elevator Assisted Evacuation
4.4 Combined with Security System
4.4.1 Camera Assisted Fire Detection and Confirmation
4.4.2 Fire Smoke Detection Equipment
4.4.3 Image Flame Monitoring System
4.4.4 The Combination of Fire Detection and VideoSystems
4.4.5 Fire Monitoring Confirmation
4.4.6 Access Management and Personnel Positioning
4.5 Building DNA Mapping
4.5.1 Foundation for All Smart Building Applications
4.5.2 Data-Driven Mapping
4.5.3 Model-Driven Mapping
4.5.4 What Building DNA Map Delivers
4.5.5 Fire-Fighting Instance
References
5 Building Codes and the Fire Regulatory Context of Smart and Autonomous Infrastructure
5.1 Introduction
5.2 Active Fire Protection
5.2.1 Fire Suppression Systems
5.2.2 Fire Detection/Alarm Systems
5.3 Passive Fire Protection
5.3.1 Compartmentalization
5.3.2 Structural Fire Protection
5.4 Means of Egress
5.4.1 Notification and Directives
5.4.2 Exit Passage
5.4.3 Exit Discharge
5.5 Damage Assessment
5.5.1 Site Reconnaissance
5.5.2 Data Collection and Synthesis
5.6 Building Recommissioning
5.6.1 Condition Analyses
5.6.2 Repairs and Alterations
5.7 Retrospective
References
6 Perspectives of Using Artificial Intelligence in Building FireSafety
6.1 Introduction
6.2 Foundations of AI-Based Fire Engineering
6.2.1 AI vs. CFD in Fire Engineering
6.2.2 Establishment of Fire Scenario Database
6.2.2.1 Experimental Fire Database
6.2.2.2 Numerical Fire Database
6.2.3 AI Methods for Detecting and Forecasting Fire
6.3 Applications of AI in Building Fire Safety
6.3.1 AI-Based Fire Engineering Design
6.3.2 Building Fire Digital Twin
6.3.3 Smart Fire Forecast and Fighting
6.4 Summary
References
7 Intelligent Firefighting
7.1 Introduction
7.2 Sizing Up and Planning
7.3 Firefighter Situational Awareness
7.4 Firefighting Activities
7.4.1 Suppression
7.4.2 Search and Rescue
7.4.3 Strength Augmentation
7.5 Summary
References
8 The Role of Artificial Intelligence in Firefighting
8.1 Introduction
8.2 Artificial Intelligence
8.3 Pre-incident Planning
8.3.1 Data Collection
8.3.2 Risk-Informed Inspection Prioritization
8.3.3 Inspection Assistance
8.3.4 Pre-incident Planning Prioritization
8.3.5 Training Personnel
8.4 Incident Response
8.4.1 Early Detection
8.4.2 Deployment
8.4.3 Size-Up/Data Collection and Analysis
8.4.3.1 Occupant Load Estimation
8.4.3.2 Fire Origin and Size Estimation
8.4.3.3 Occupant Survivability Profile Assessment
8.4.3.4 Additional Fact Finding
8.4.4 Incident Action Planning
8.4.4.1 Offensive Extinguishment
8.4.4.2 Defensive Extinguishment
8.4.4.3 Salvage and Overhaul
8.5 Summary
References
9 Implementing AI to Assist Situation Awareness: Organizational and Policy Challenges
9.1 Introduction
9.2 Definitions
9.3 Conceptual Use Cases
9.3.1 Humans as Sensors and AI Inputs
9.3.1.1 Wearables
9.3.2 Physical Infrastructure-Based AI
9.3.2.1 Buildings
9.3.2.2 Highways and Streetscape
9.3.3 Emergency Reporting
9.3.3.1 NG9-1-1
9.3.3.2 FirstNet and Wireless Broadband Data
9.4 Barriers to Utilization
9.4.1 Emergent Standards for BIM Data Exchange
9.4.2 Analytics and Display
9.4.3 CONOPS
9.4.4 Organization Scale (Command Overhead)
9.4.5 Market Failure Due to Variation
9.4.6 Cost Effectiveness/How to Measure
9.5 Ethical Implications of AI in Situation Awareness
9.6 Future Outlook
References
10 Probabilistic Reliability Analysis of Steel Mezzanines Subjected to the Fire
10.1 Introduction
10.2 Materials and Methods
10.2.1 Natural Fire Safety Concept
10.2.2 Risk Model and Matrices
10.2.2.1 Model Parameters
10.2.2.2 Stochastic Sampling
10.2.2.3 Risk Ranking
10.2.3 Deterministic Models
10.2.4 Workflow
10.3 Case Study
10.3.1 Analysis of Load-Bearing Capacity of the Structure in Fire Conditions
10.3.2 Stochastic Analysis of the Thermal Response
10.3.3 Numerical Analysis of Thermal and Mechanical Response
10.3.3.1 Estimation and Categorization of Risks
10.4 Conclusion
References
11 Autonomous Sensor-Driven Pressurization Systems: Novel Solutions and Future Trends
11.1 Introduction
11.2 Concepts of Pressurization and Smoke Exhaust
11.2.1 Basic Principles
11.2.2 Adaptive Pressurization Systems
11.2.3 Pressurization of Vestibules
11.3 Countering the Stack Effect
11.4 PDS and Other Smoke Control Systems in the Building
11.5 Verification of PDS Systems
11.5.1 Laboratory Tests
11.5.2 Electromagnetic Compatibility (EMC)
11.5.2.1 Commissioning and In Situ Testing
11.6 Conclusions
References
12 Hybrid Fire Testing: Past, Present and Future
12.1 Introduction
12.2 Hybrid Fire Testing Fundamentals
12.2.1 The Influence of the Mechanical Boundary Conditions on the Fire Test Results
12.2.2 Introduction to HFT
12.2.3 Components and Procedure
12.2.4 Advantages and Challenges
12.2.5 State of the Art
12.3 Hybrid Fire Testing Case Study
12.3.1 Time Integration Algorithm
12.3.2 Description of the Test Setup and Quantification of Experimental Errors
12.3.3 Verification of the HFT Setup
12.3.4 HFT of a GPB-Based Wall Assembly
12.3.4.1 Description of the Case Study
12.3.4.2 Discussion of Experimental Results
12.4 Cognitive and Autonomous Systems
12.5 Future of HFT in the Context of ML
12.5.1 HFT-Assisted ML
12.5.2 ML Assisted HFT
12.5.3 Combined Approach
12.6 Conclusions and Future Work
References
13 Realistic Fire Resistance Evaluation in the Context of Autonomous Infrastructure
13.1 Introduction
13.2 Complexity Embedded in Fire Induced Collapses
13.2.1 Collapse of WTC Towers
13.2.2 Collapse of WTC7 Building
13.2.3 Plasco Building Collapse
13.2.4 Resolve the Complexity of Fire Induced Structural Damage, Failure, and Collapse
13.3 Realistic Fire Impacts in Modern Built Environment
13.3.1 Localised Fires
13.3.2 Horizontally Travelling Fires
13.3.3 Vertically Travelling Fires
13.4 Failure Patterns and Mechanisms of Structures in Fires
13.4.1 Local Failure
13.4.2 Progressive Collapse
13.4.3 Global Failure Mechanism
13.5 AI Application in Structural Fire Engineering
13.5.1 Automatic Identification of Fire Scenarios
13.5.2 AI Prediction of Infrastructure Fires
13.5.3 AI Prediction of Structural Response
13.6 A Full-Scale Fire Test Demonstrating Failure-to-Collapse Mechanism
13.6.1 Experimental Design and Instrumentation
13.6.2 Experimental Results
13.6.3 Collapse Warning Based on LAMS
13.6.4 Performance of Different Remote MonitoringSystems
13.7 Concluding Remarks on a Vision of Structural Fire Safety Evaluation
13.7.1 Potential Estimation Framework for Fire Impact
13.7.2 Future Application for Predicting Structural Behaviour in Fire
References