Innovative Applications of UHPC in Columns, Part 1 of 2

Sunday, October 29, 2023  8:00 AM - 10:00 AM, W-Marina Ballroom IV

Ultra-high-performance concrete (UHPC) is a material with impressive mechanical and durability properties which can allow for more resilient, durable, and sustainable structures. One promising application of UHPC is in columns, where its high compressive capacity can allow for more efficient and compact designs. The high energy absorption capacity of UHPC also makes it ideal for seismic and extreme load applications. UHPC also shows great potential as retrofit material which can be used to strengthen and rehabilitate existing building and bridge columns.

The objective of this session is to present the latest innovative applications in UHPC columns in new and existing structures. The session will invite international speakers to share their latest research and practical applications of UHPC in columns.

Learning Objectives:
(1) Report on the performance of UHPC columns under axial and earthquake blast loads;
(2) Investigate the use of UHPC for the retrofitting of corroded columns/piles;
(3) Interpret the analysis and modelling of UHPC columns;
(4) Discuss the use of machine learning for modelling the behaviour of UHPC.

Using UHPC for Repair of Corroded Steel H-Piles

Presented By: Mohamed ElGawady
Affiliation: Missouri S&T
Description: This presentation will discuss the novel and practical application of UHPC to repair corroded steel H-piles.

Seismic Behavior of Fully Precast UHPC Columns with Recycled Fibers

Presented By: Allan Romero
Affiliation: University of Nevada, Reno
Description: Through a collaboration between the University of Nevada, Reno (UNR) and Con-Fab Precast Inc., several UHPC columns were fabricated using production scale techniques such as ready-mix trucks. Two different types of steel fibers were used: manufactured virgin steel fibers and recycled tires steel fibers and wires. The columns are connected to conventional concrete footings using different Accelerated Bridge Construction (ABC) seismic connections to be tested at one of UNR’s shake tables under combined axial and lateral earthquake loading. An overview of the construction experience and preliminary findings from the specimens assembly and testing at UNR are discussed in this presentation.

Confinement Effects of Spirals and Hoops on Axial Behavior of UHPC Columns

Presented By: Milana Cimesa
Affiliation: University of Nevada Reno
Description: This presentation will discuss recent experimental results from large scale axial testing of circular UHPC columns at the 4000-kip testing facility at the University of California, Berkeley. Four 16-inch diameter and 9-ft high columns were fabricated at a precast plant in CA with varying transverse reinforcement detailing that included spiral versus hoops with 1.5-inch and 3-inch spacings. The tests results are summarized and practical findings on the effects of spiral and hoop reinforcement detailing on the axial behavior of UHPC columns are presented.

Bond-Slip Behavior of Reinforced UHPC Under Flexure

Presented By: Yi Shao
Affiliation: McGill University
Description: T Ultra-high performance concrete (UHPC) is an advanced class of concrete materials that show superior mechanical and durability performance. While several studies have investigated the bond-slip behavior of steel reinforced UHPC using traditional pullout tests, very limited information is available on the bond-slip behavior of reinforced UHPC from beam-type tests, which produce flexural stress states commonly seen in structural members. We will first present a large-scale experimental program that investigates the bond-slip behavior of reinforced UHPC using beam-end specimens. Test variables include fiber volumes (0%, 1%, 2%), bar diameter (16mm to 32 mm), cover thickness (16mm to 51mm), and loading types (monotonic versus reversed cyclic). Afterwards, we will introduce a recently-developed model that can predict the bond-slip behavior of reinforced UHPC under monotonic or cyclic loadings.

Moment-Rotation Response of Reinforced UHPC Columns under Varying Axial Loads

Presented By: Matthew Bandelt
Affiliation: New Jersey Institute of Technology
Description: Reinforced concrete lateral resisting frames in seismic applications rely on adequate strength, stiffness, and deformation capacity of columns. This presentation will explore the deformation capacity of reinforced UHPC columns with varying axial loads. Comparisons to other ductile concrete materials with fiber-reinforcement will be provided. Both computational simulation results and on-going experiments will be presented.

Modeling of Peak and Ultimate Stress-Strain States in Confined Ultra-High-Performance Concrete (UHPC) Using Novel Hybrid Machine Learning Approach with Conditional Tabular Generative Adversarial Network

Presented By: Tadesse Gemeda Wakjira
Affiliation: University of British Columbia
Description: Owing to its outstanding physical and mechanical properties, as well as sustainability, ultra-high-performance concrete (UHPC) has emerged as a highly desirable material for use in concrete structures. To realize its potential in large-scale structural applications, a comprehensive understanding of the compressive behavior of confined UHPC is essential. A significant number of analytical studies have focused on predicting the peak and ultimate conditions of unconfined UHPC. In comparison, a comprehensive framework for stress-strain characterization of confined UHPC has yet to be established, making efficient design and wider use of UHPC, particularly in seismic areas, challenging. Developing an accurate, design-oriented model for UHPC confined with either normal or high-strength steel is crucial for ensuring the safe design and modelling of UHPC structures. This study offers a solution by introducing a novel framework that integrates a novel hybrid machine learning (ML) model and a state-of-art-the art conditional tabular generative adversarial network (CTGAN) for accurate prediction of the stress-strain response of UHPC confined with either normal strength or high strength steel. An existing database of confined UHPC stress-strain response was compiled from the literature. To overcome the problem of limited database, CTGAN was developed by conditioning on the compiled experimental dataset to sample hypothetical synthetic confined UHPC samples. The generated synthetic data was then utilized to develop a novel hybrid ML model for predicting the stress-strain response of confined UHPC at peak and ultimate conditions. The predictive accuracy of the proposed hybrid ML model is benchmarked against various ML models with varying complexity and prediction accuracy. The results demonstrated that the proposed ML model is the most accurate and robust model for predicting the stress-strain response of confined UHPC with either normal strength or high strength steel.