Short courses

The course will focus on the engineering challenges involved in evaluating bridge structures during demolition and will highlight examples where shortcuts in structural analysis or inadequate field oversight proved costly. It will also cover common removal methods and equipment used for deck removal and replacement projects, along with the engineering principles behind these methods. More complex demolition techniques—such as strand‑jack lowering and explosive removal—will also be discussed.

Temporary works commonly associated with girder installation are also frequently used during demolition. The course will review typical temporary‑work systems and the design criteria that govern these structures.

The course will include several case studies. The purpose of these case studies is to learn from past experiences—some of which did not go as planned.

Learning Objectives
Upon completion, of this course you will be able to:

Transportation geotechnics deals with the geotechnical challenges involved in designing, constructing, and maintaining infrastructure systems such as highways, railways, airfields, ports, and embankments. These systems are influenced by complex interactions among soils, environmental conditions, loading patterns, and construction practices, which introduce significant uncertainty in predicting performance and long-term behavior. Artificial intelligence (AI) and machine learning have recently emerged as powerful tools to address these challenges. By enabling data-driven modeling, these methods can effectively capture complex and nonlinear geotechnical behaviors that are difficult to represent using traditional approaches. Advances in sensing technologies, field monitoring systems, and the availability of large infrastructure datasets have further supported the integration of AI into transportation geotechnics. This workshop presents an overview of recent developments in AI applications, focusing on data-driven modeling, performance prediction, and intelligent monitoring systems. It highlights how machine learning, deep learning, and predictive analytics can improve the characterization, design, and evaluation of transportation geotechnical systems. Key application areas include soil and geomaterial characterization, pavement and railway foundation systems, embankments, ground improvement, slope stability, and earth-retaining structures. Emerging topics such as digital twins, intelligent infrastructure monitoring, and machine learning-based surrogate models derived from numerical simulations are also discussed. Through technical presentations and case studies, the workshop demonstrates how AI can enhance understanding of complex system behavior and support better engineering decision-making. It also explores the integration of AI with laboratory testing, field monitoring, remote sensing, and infrastructure asset management. The workshop aims to show how AI-driven approaches can improve prediction accuracy, optimize design processes, reduce lifecycle costs, and contribute to more resilient and sustainable transportation infrastructure systems.

Learning Objectives
Upon completion, of this course you will be able to:

A broad, cross-cutting workshop addressing flood risks affecting both coastal and inland (riverine) environments. The intent is to attract a wide audience across ASCE institutes and allied professionals, not limited to structural engineers.

Learning Objectives
Upon completion of this course, you will be able to:

The objectives of this workshop are to (a) provide an overview of ASCE Manual of Practice (MOP) 150 “TMDL Development and Implementation: Models, Methods, and Resources” and (b) present the latest advances in TMDL modeling and holistic watershed management, such as applying artificial intelligence (AI) and remote sensing.

Workshop participants will learn directly from the authors of MOP 150 about watershed and receiving water quality modeling practices, along with detailed case studies demonstrating AI and remote sensing techniques for TMDL modeling and watershed management. In addition, participants will benefit from interacting with speakers from municipalities and other practitioners to gain real-world perspectives on TMDLs and holistic watershed management. The workshop will begin with an in-depth overview of ASCE MOP 150 and how it can advance holistic watershed management. Additionally, a summary will be provided on evolving issues such as watershed PFAS modeling, climate impact modeling, and digital transformation. The workshop will feature two central themes: (A) “Advances of AI in TMDLs and Watershed Management,” and (B) “Real-World Perspectives on TMDLs and Holistic Watershed Management.”

Learning Objectives
Upon completion of this course, you will be able to:

Quantifying uncertainty and its effects on geotechnical hazard assessments is increasingly important in practice, but scaling from deterministic to probabilistic analysis is a challenge. Many practitioners rely on spreadsheets or graphical user interface (GUI) tools that offer limited support for uncertainty propagation. Python-based open-source tools substantially expand what is practical: by expressing analyses as code, engineers gain the ability to propagate parameter uncertainty and automate analyses at scales that spreadsheet and GUI-driven workflows cannot support. This short course introduces a framework for probabilistic geotechnical hazard analysis in Python, demonstrated through two problems of broad practical relevance: co-seismic slope stability and liquefaction hazard analysis. Participants will work through detailed examples using provided templates in a web-based environment — no local software installation required. The templates are designed to be readable and modifiable, and the course will demonstrate how AI coding assistants can help participants adapt them to their own projects. Participants do not need Python proficiency or prior coding experience, only a willingness to read and work with code. The course aims to leave participants with a reusable set of templates and a transferable probabilistic workflow applicable beyond the specific examples covered.

Learning Objectives
Upon completion, of this course you will be able to:

This specialized technical course introduces engineers to the principles and practices of designing structures to withstand bomb blast loads and chemical explosions. Emphasizing the application of ASCE 59 standards, the course explores blast load characterization, structural response mechanisms, and performance-based design strategies for extreme loading events. Participants will learn to evaluate vulnerabilities, apply code‑aligned design provisions, and develop resilient structural solutions for high‑risk environments.

Learning Objectives
Upon completion of this course, you will be able to:

Intelligent Construction Technologies (ICT) is reshaping how Infrastructure construction projects are executed, documented, and integrated into long-term infrastructure management. This 4-hour workshop presents an end-to-end, implementation-focused overview of ICT-enabled digital workflows, demonstrating how field-generated data is transformed into validated, actionable information. The workshop topics follow the complete construction lifecycle—from eTicketing and Material Delivery Management Systems (MDMS), through milling, paving, thermal profiling, intelligent compaction, and dielectric profiling systems—highlighting how these technologies collectively support quality control (QC), quality assurance (QA), and the development of “living models” for pavement and asset management systems. Drawing on real-world applications and lessons learned, presenters from transportation agencies, contractors, equipment manufacturers, and consultants will discuss practical strategies for adopting, integrating, and scaling digital delivery workflows. The session emphasizes measurable value in construction quality, documentation, and data-driven decision-making. A panel discussion concludes the workshop, providing cross-sector insights on current implementation challenges and opportunities to advance digital delivery in practice.

Learning Objectives
Upon completion of this course, you will be able to:

Small uncrewed aerial systems (sUAS) are increasingly being adopted for transportation infrastructure monitoring, including bridges, highway and airfield pavement systems, traffic control devices, and railroad assets, due to their ability to provide high-resolution, safe, and cost-effective data collection. Traditional inspection methods for bridges, pavements, and railroads are often labor-intensive and post hazards to personnel, whereas sUAS-based approaches enable rapid, safe, and repeatable assessment of structural components and surface conditions. For traffic and rail corridor monitoring, sUAS can provide efficient aerial observation of flow patterns, right-of-way conditions, and potential safety issues without disrupting operations.

By integrating photogrammetry, thermal sensing, and LiDAR, sUAS platforms can capture detailed structural information for condition evaluation. When combined with deep learning (DL) techniques, sUAS imagery, digital elevation models (DEMs) and three-dimensional point cloud renderings can be automatically processed to detect and quantify surface defects. Advanced computer vision models, including object detection and semantic segmentation networks enable the extraction of quantitative and measurable infrastructure parameters from sUAS imagery. This course will provide an overview of sUAS technologies, data collection and processing workflows, integration with DL workflows, and present a case study on artificial intelligence (AI)-based pavement distress detection. Challenges and future trends in intelligent infrastructure monitoring will also be discussed.

Learning Objectives
Upon completion of this course, you will be able to:

This course provides an overview of the newly released ASCE Manuals of Practice 160 and 161, focusing on the design of foundations for overhead transmission lines and substations. Participants will explore key design principles, load considerations, and practical guidance for utility and transmission infrastructure. Emphasis is placed on applying the updated MOP provisions to real‑world foundation design scenarios.

Learning Objectives
Upon completion of this course, you will be able to:

This course will provide an overview of the essential elements of EJCDC documents, including how to use them and the guidance available. This will be accompanied by a more detailed examination of how to package various documents together for different situations.

Learning Objectives
Upon completion of this course, you will be able to:

Short span bridges are vital links in the nation’s infrastructure, yet many are aging, structurally deficient, or beyond their intended service life. With constrained budgets, programs underscore the need for cost-effective, durable solutions that deliver long-term value and workforce development. This workshop - hosted by the Short Span Steel Bridge Alliance - will equip local and state bridge owners, designers, consultants and contractors with practical, up-to-date guidance on steel bridge design, fabrication, installation and maintenance. Industry experts will highlight the latest advancements in efficient, resilient and sustainable steel solutions to help owners, engineers and agencies tackle infrastructure challenges and maximize project resources.

Learning Objectives
Upon completion, of this course you will be able to:

Artificial intelligence has reached a turning point at which the Civil Engineering (CE) profession must move with it - not incrementally, but deliberately. Although civil engineering professionals and organizations have begun adopting AI in daily workflows, pressing questions beyond AI specification remain unanswered. To name a few, what systems thinking is required to ensure that errors in AI do not propagate unchecked through the whole system pipeline? A practical question also arises: how can engineers without coding expertise still engage meaningfully with AI and leverage it as a problem-solving partner rather than being sidelined by it? Social and ethical questions follow closely, yet are more critical: as AI systems lack agency, where does accountability reside? How should professional judgment, liability, and code compliance be maintained in AI-augmented practice?

This four-hour professional program is organized into three complementary short courses that together provide a forward-looking perspective on Artificial Intelligence in Civil Engineering.

Module 1 - Structural Engineering + AI explores how AI agents, subagents, and tool orchestration can assist structural engineers in code interpretation, technical documentation, automated analysis, and preliminary design workflows. It also addresses responsible AI use, emphasizing engineer-of-record accountability, risk mitigation, and ethics in multi-agent environments. Module 2 - Systems Approach to AI for Transportation Infrastructure and Safety presents a lifecycle-based framework for AI project development. Participants learn how to structure AI solutions from stakeholder need identification through data management, modeling, validation, and feasibility assessment. Case studies include automated pavement distress detection and intelligent roadway safety assessment using sensor and smartphone data. Module 3 - Introduction to AI and AI-Assisted Workflows for Transportation Professionals provides foundational AI concepts tailored to transportation practice. Through real-world examples and browser-based exercises, participants explore AI-assisted productivity tools and agentic workflows that augment engineering decision-making.

Learning Objectives
Upon completion, of this course you will be able to:

This short course introduces the essential concepts and practical applications of ASCE 41 for evaluating and retrofitting existing buildings. Participants will learn how to interpret and apply key provisions, understand seismic performance expectations, and recognize ASCE 41 as a foundational structural standard within modern engineering practice.

Learning Objectives
Upon completion of this course, you will be able to:

Water utilities face increasingly complex and interrelated challenges driven by climate change, aging infrastructure, and evolving regulatory requirements. Nature-based solutions (NbS) have emerged as promising alternatives or complements to conventional grey infrastructure because they provide multiple ecosystem services while addressing water quality and quantity objectives. However, the wider implementation of NbS remains limited due to the lack of standardized decision-support frameworks that can effectively compare their costs and benefits with those of conventional and hybrid infrastructure. This workshop introduces NbS4Water, a system dynamic–based decision-support tool that builds upon and integrates existing tools, extending their capabilities by addressing key gaps in typologies, spatial and temporal scales, and long-term benefit assessment. This tool enables utilities and municipalities to transparently compare NbS, grey, and mixed infrastructure implementation against a baseline (no action) using multiple criteria across defined scenarios. Tool development was informed by an extensive literature review, analysis of industry case studies, a structured practitioner survey, and expert engagement across academia and practice. These activities established consensus on relevant ecosystem services and disservices, as well as standardized computational approaches for their quantification. NbS4Water integrates implementation costs, operational, maintenance and avoided costs over the project lifespan, and both monetary and non-monetary ecosystem service valuations. The framework incorporates expert-informed parameterization, Monte Carlo analysis to address uncertainty, user-defined weighting of decision criteria, and multi-criteria decision analysis. All financial metrics account for the time value of money, enabling lifecycle cost comparisons across spatial and temporal scales. Outputs are dynamically updated, allowing users to iteratively adjust assumptions and evaluate tradeoffs among alternatives to meet the management objectives. In this workshop, the research conducted to develop NbS4Water will be presented along with case studies. Attendees will then have an opportunity to view and use the tool during the workshop and to provide feedback to the development team.

Learning Objectives
Upon completion of this course, you will be able to:

Deep Foundations are used to support all types of structures in various geotechnical conditions. Their engineering design includes structural, geotechnical, and constructability considerations; and their construction involves drilling, installations, driving, testing, and inspection. Testing and inspections are an integral part of the design process and construction work for verification, quality control, quality assurance, and foundation acceptance/certification. This short course covers the main deep foundations types installations and testing methods for assessments of geotechnical load bearing capacity and structural integrity of driven piles, drilled shafts, and auger-cast piles. It includes conventional static load testing, wave equation analysis, dynamic load testing, bi-directional-static load testing, low-strain integrity testing, Cross-hole Sonic Logging, Thermal Integrity Profiling, and other testing and inspection methods and tools. Basic principles, capabilities, limitations, and suggested best practices of each method are discussed and illustrated with data from actual projects.

Learning Objectives
Upon completion, of this course you will be able to:

Introduction to ASCE/SEI 7-22 for New Graduate Structural Engineers, is intended to be an introduction to the more commonly used provisions of ASCE/SEI 7-22 and be targeted at recently graduated structural engineers. ASCE/SEI 7 is the primary document for determining the required loads to design structures and is used by virtually every structural engineer in the United States and in many international locations. The short course would make use of the soon to be published ASCE/SEI 7-22 Primer. The short course would be led primarily by current and past members of the ASCE/SEI 7 Committee. The purpose of the ASCE/SEI 7 Primer is to serve as an introduction to the loading provisions of the ASCE/SEI 7-22 standard, Minimum Design Loads and Associated Criteria for Buildings and Other Structures. It is intended to familiarize newly graduated structural engineers just starting out their careers with the basics of structural loadings. The overall organization of the ASCE/SEI 7-22 Primer reflects the design process, starting with classifying the building, calculating various loads, and ending with load combinations. A common design example is used in each section to illustrate how to apply the standard and includes brief explanations of structural concepts, as necessary.

Learning Objectives
Upon completion of this course, you will be able to:

This course will familiarize attendees with the Federal Aviation Administration’s (FAA’s) software FAARFIELD 2.1 (FAA Rigid and Flexible Iterative Elastic Layered Design) that was introduced in June, 2021, and FAA PAVEAIR. FAARFIELD 2.1 is the FAA’s software for airport pavement thickness design and evaluation (AC 150/5320-6G, Airport Pavement Design and Evaluation) and pavement strength reporting using the ACR/PCR method (AC 150/5335-6D, Standardized Method of Reporting Pavement Strength – PCR). FAA PAVEAIR is a web-based airport pavement management system that provides users with historic and current information about airport pavement construction, maintenance and management.The workshop is intended for airport Operators, Consultants, and others with a practical interest in airport pavement design.

Learning Objectives
Upon completion of this course, you will be able to:

Small Unmanned Aerial Systems (sUAS), commonly referred to as drones, have recently emerged as highly effective tools for transportation infrastructure non-destructive inspection. Iowa State University (ISU) and its collaborators have been working with federal and state agencies to evaluate their performance across paved highways, unpaved roads, airfield pavements, and bridge inspections. The ISU team demonstrated sUAS’s promising performance in detecting a wide range of flexible and concrete airfield pavement distress at varying levels of severity. Additionally, the technology has proven useful in complementing traditional pavement inspection methods. Consumer-grade, photography-focused sUAS can capture high-quality imagery essential for pavement inspection workflows without the need for additional equipment. In this workshop, the presenter will discuss airfield pavement data collection protocols and demonstrate how to process these data using Agisoft Metashape. Furthermore, the session will cover analysis using GIS software to identify and rate airfield pavement distress for use in pavement condition assessments.

Learning Objectives
Upon completion of this course, you will be able to:

Project managers, designers, and contractors all face increasing pressure to continue to deliver quality projects that incorporate client goals and meet building code and certification requirements while condensing project schedules and cost. As a result, proactive and collaborative strategies to execute work that are effective, efficient, and consider the needs of all project disciplines have become critical to building successful teams.

By engaging in proactive conversations and collaborative work planning sessions, a Lean approach to design and construction benefits project delivery, strengthens team alignment, and minimizes delays and constraints to the project. The use of collaborative and interactive work planning engages all team members earlier on in project design development, ensuring the consideration of all client requirements and team members' needs, timelines, and questions in an effective manner. This collaborative approach to work planning, known as pull planning, emphasizes handoffs between team members and serves to develop a team work plan that all team members have aligned across and built together.

The teams and clients we’ve worked with have seen tangible benefits in implementing Lean tools on their projects, including better communication and teamwork across different engineering disciplines, contractors, subconsultants, and stakeholders and improvements to scope control and schedule management. Lean project delivery tools primarily focus on three categories: Collaborative Work Planning, Decision Making, and Continuous Improvement. This presentation will introduce the Lean design tools in all three categories but will focus on an interactive exercise that will engage audience members to participate in a mock Pull Planning session.

Learning Objectives
Upon completion of this course, you will be able to:

This advanced session offers a deeper exploration of Progressive Design-Build (PDB), focusing on the contractual, technical, and collaborative nuances that shape project outcomes. Using high‑profile case studies—including the Seattle‑Tacoma International Airport International Arrivals Facility (Sea‑Tac), one of the most visible PDB projects to encounter major litigation—participants will examine both the strengths and vulnerabilities of the PDB model. The course highlights lessons learned from real-world challenges such as design capacity disputes, cost escalation, and stakeholder misalignment. Attendees will gain practical strategies for managing contractual risk, optimizing team collaboration, and protecting their firms while navigating the evolving landscape of PDB delivery.

Learning Objectives
Upon completion of this course, you will be able to: