Sensors and Instrumentation (Lee)

3-6pm, Tuesday May 13 

Optional homework help session - 4-5pm,  Friday May 16 

Overview

This module covers the basic theory behind sensors and instrumentation of infrastructure monitoring and condition assessment. Topics include the purpose of using sensors and instrumentation, the types of sensors that can be used to measure different infrastructure conditions, the interpretation of sensor data for rehabilitation decision analysis and the limitations and errors associated with sensors and instrumentation. Visual and subjective evaluation, non-destructive testing and video image analysis are covered. Examples of field deployments are presented and exercises involve both simulated and actual data.

Curriculum

1.      Visual and subjective evaluation

2.      Non-destructive testing sensors

3.      Instrumentation

4.      Video image analysis

Instructor: Lee

Deterioration Modeling (Chamorro and Torres Machi)

3-6pm, Thursday May 15 

Optional homework help session - 4-5pm, Wed May 21 

Overview

The module introduces the concepts related to modeling and predicting infrastructure condition and performance over time and discusses the uses of deterioration models.  The different types of models that are used to model infrastructure deterioration are introduced and exercises include the development of regression and Markov models. The advantages and disadvantages of the various approaches are discussed. 

Curriculum

1.      Review concepts: infrastructure performance, service life, deterioration

2.      Predicting modeling approaches

3.      Model development

4.      Examples

Instructors: Alondra Chamorro and Cristina Torres-Machi

PERFORMANCE AND LEVEL OF SERVICE  (AMEKUDZI-KENNEDY)

3-6pm, Monday May 19 

Optional homework help session -  4-5pm,  Fri May 23 

Overview

This module introduces the concept of performance, how performance is measured, used and managed. This concept is present in the context of the laws, policies and regulations for transportation agencies and in the broader context of strategic planning, asset management and performance management. The module moves from the concept to the process of selecting performance measures and targets. Exercises connect the concepts to goals and measures. Examples and best practices from international organizations and state agencies are presented.

Curriculum

1.      Performance: What is it? How is it envisioned, delivered, measured and managed?

•        Laws/Policies/Regulations

•        Strategic Planning

•        Asset Management

•        Performance Management

2.      Selecting Performance Measures and Targets

•        Guidelines

3.      Best Practices

Instructors: Adjo Amekudzi Kennedy

Risk, Reliability, and Resilience (Gao)

3-6pm, Tuesday May 20 

Optional homework help session - 4-5pm, Wednesday May 28 

Overview

This module introduces methods to quantify risk and reliability of both components and systems.  The module begins with a review of basic probability and then develops the models and tools needed for rigorous analysis in the context of the larger decision making strategies.  Examples are presented to illustrate the concept and exercises provide an opportunity to apply the concepts.

Curriculum

1.      Why infrastructure management?

2.      Review – why model?

3.      Reliability theory and failure rates

4.      Optimal replacement policy

5.      Reliability of systems

6.      Concepts of infrastructure resilience

7.      Infrastructure resilience modeling

8.      Applications

Instructors: Gao

GUEST LECTURE: TBD

3-4 pm, Thursday May 22

Overview

Stay tuned.......

Instructors:  TBD

Decision Making and Optimization (Labi)

3-6pm, Tuesday May 27

Optional homework help session - 4-5pm, Fri May 30 

Overview

This module provides a comprehensive introduction to optimization in infrastructure management. The module begins by recognizing the role of optimization in the life cycle of physical assets and the different problem contexts for optimization.  Optimization problems are then characterized by the decisions being made, the scale and the resources available. Participants are introduced to continuous variable optimization, discrete variable optimization and both project and network level contexts. Examples are used to illustrate the application of different methods and highlight the importance of understanding the context.

Curriculum

1.      Introduction

·        The process of optimization; Problem contexts; Objectives, constraints and decision variables; Characterizing problems

2.      Continuous variable optimization

3.      Discrete variable optimization

4.      Project level contexts

5.      Network level contexts

Instructor: Labi

ECONOMICS, ASSET VALUE AND FINANCING (MCNEIL AND PALESE)

3-6pm, Thursday May 29

Optional homework help session -  4-5pm, Wednesday June 4  

Overview

This module connects investment in infrastructure to economic benefits and losses as motivation for making better decisions about infrastructure investment recognizing the different scales (project, network, community, regional and national) using examples. Analysis tools are also introduced. Building on these concepts, asset valuation methods are introduced and in-class exercises demonstrate the application of the methods. The module then focuses on financial viability for both projects and organizations and the connections between different financing and revenue generating options.

Curriculum

1.      Review performance measurement

2.      Economics

a.      Economic impact and economic analysis

b.      Engineering economics and project evaluation

3.      Asset valuation

4.      Finance

5.      Project delivery

Instructor: Sue McNeil and Joe Palese

DATA science (Attoh Okine)

3-6pm, Monday June 2 

Optional homework help session -  4-5pm,  Fri June 6 

Overview

Advances in technology have allowed us to collect massive amounts of data. A data scientist is a person who has the skills, knowledge, and ability to extract actionable knowledge from the data for the good of society, advancement of science and technology. This module will examine the central question of "what is BIG DATA?", and “how can infrastructure engineers, statisticians, and other professionals employ tools and techniques of data science?” This module will help you develop a deeper understanding of the various phases of Big Data and major aspects of data science for engineering decision making.

Curriculum

1.      "What is BIG DATA?"

2.      How can infrastructure engineers, statisticians, and other professionals employ tools and techniques of data science?

3.      Topics needed to solve data-science problems:

•       Data preparation (collection & integration),

•       Data characterization & presentation,

•       Data analysis (experimentation & observational studies), and

•       Data products.

Instructor: Attoh Okine

SUSTAINABILITY AND LIFECYCLE ASSESSMENT (FLINTSCH)

3-6 pm, Tuesday June 3 

Optional homework help session - 4-5pm, Wed June 11 

Overview

Awareness of the importance of social, economic and environmental impacts of infrastructure decisions has grown in the past decades. This module explores strategies for integrating sustainability into the decision-making process and lifecycle assessment tools.   

Curriculum

1. Introduction 

• Definitions - sustainability, lifecycle assessment

• Background

• Impacts

2. Assessing sustainability

3. Lifecycle assessment tools

4. Case studies

5. Integration with decision-making

Instructors:  Flintsch

Research Methods for Infrastructure Management (SUE McNeil)

3-6 pm, Thursday June 5 

Overview

Most of us are never taught how to do research, it is something we learn by example, either watching others or by actually doing research.  This module aims to define the research process, including the elements and the types of tools needed to support research in infrastructure management, an inherently interdisciplinary field.  This module is only available to course participants.

Curriculum

1.      What is research?

2.      Writing a research proposal

3.      Research tools

4.      Career planning

Instructor:  McNeil