Physical artifacts in introductory-level reinforced concrete design instruction

Incorporating physical models and demonstrations in the introductory-level reinforced concrete design course has shown to be beneficial for students in clarifying and engraining fundamental concepts. The research study conducted at the author’s university during Spring 2015 involved the design, fabrication, and implementation of models to supplement traditional lectures on topics that students have found challenging in prior offerings of the course. Specifically, these demonstration tools illustrate: • Three-dimensional stress blocks for rectangular/flanged beams subjected to varying levels of flexural demand • Distinctions between the flexural behavior of one and two-way slabs • Placement of steel reinforcement for singly/doubly reinforced beams with shear stirrups • Design of one-way slab building systems including construction of slab, interior/edge beams, and columns as well as connection detailing The paper will include details intended to enable other civil engineering educators to: fabricate the models, incorporate them in a large-lecture setting, as well as facilitate activities that encourage students to engage with the physical artifacts.The author will also present student feedback on the use of these physical models that was acquired through an IRB-approved human studies research study during Spring 2015. This includes results from mid- and end-term surveys with two class sections of over ninety undergraduate and graduate students. The overall objective of this paper is to provide educators with sample teaching tools to help students better visualize three-dimensional ideas and systems – a skill which is critical as students transition to design industry. In addition, it is intended to stimulate a dialogue with educators about further needs for physical models in reinforced concrete design education, and more generally, in the civil engineering design classroom

Physical models in the reinforced concrete design classroom

An overview is presented of various physical demonstration tools intended to supplement lectures in topic areas that students consistently identify as being troublesome. The article describes the design, fabrication, and implementation of classroom models to help explain flexural behavior and detailing of beams, slabs, and frame systems

Developing a robust teaching portfolio as a doctoral student in a research-intensive engineering program

Successful faculty applications to teaching/undergraduate institutions can be difficult for doctoral students transitioning directly from a research-intensive engineering program. Oftentimes, these prospective faculty members have limited opportunities to engage in engineering education research, to serve as a primary instructor for a lecture course, or to receive adequate mentoring to prepare them for the environment of a teaching/undergraduate institution. This paper will highlight the lessons learned by a new faculty member at a top-ranked undergraduate institution (and recent doctoral candidate at a R1 research institution) about how students can build a comprehensive teaching portfolio outside of the traditional coursework and research path required for engineering doctoral degree. This paper includes a discussion of various approaches to leverage extracurricular, teaching-related activities that are available on a research campus

Kind gestures: Longtime ACI members shape the career of younger generations

In this article, an Assistant Professor at California Polytechnic State University describes how her involvement with ACI has helped her to embark on projects that, as a young faculty member, she could have never envisioned. She also tells of her first ACI convention in Spring 2013, her first interaction with ACI Committee 133, Disaster Reconnaissance, in 2014, and using the ACI 318 Building Code in the classroom

Inquiry-based learning to explore the design of the built environment

Typically in introductory structural engineering courses with a lab component, the instructional approach is to present the underlying theory via pre-lab lecture/reading and subsequently have students conduct guided experiments that affirm that theory. The new Fall 2015 course offering described in this paper takes the reverse approach where students’ hands-on exploration of a concept occurs prior to formal instruction. As such, the course is based upon Da Vinci’s perspective that: “[i]n the examination of physical problems I begin by making a few experiments,…we must commence with experience, and strive by means of it to discover truth.” In the course, student exploration of fundamental structural engineering concepts was facilitated through the following activities: • Full-class physical demonstrations led by the instructor during lecture • Small-group experimentation in a laboratory setting • Case studies highlighting both failures and exemplary natural/engineered structures presented via instructor lectures and supplementary multi-media materials The paper describes the open-ended course framework where instructors posed targeted questions for students/teams to investigate based on the demonstrations, experiments and case studies. The students explored these questions in the manner they (individually or in teams) deem appropriate, while documenting relevant quantitative and qualitative observations in their lab notebooks. Reflecting on their gathered information, students developed evidence-based responses to the questions. These learning exercises were followed by instructor-facilitated discussion where students/teams share their observations and collaboratively draw conclusions that point towards related engineering theory. Finally, the instructor formally defined the associated theory. The objective of this paper is demonstrate how the “exploration before theory” approach can be implemented and what is required to accomplish the hands-on, inquiry, discussion, and formal teaching aspects that comprise this teaching style. Associated with this objective, the authors also share student feedback on the course that will be collected through mid- and end-of-semester surveys for about twenty undergraduate students. These surveys solicited student input on the inquiry-based learning atmosphere as well as individual course activities. The authors believe that a classroom environment that emphasizes discovery – where students act as researchers and play an active role in building their own knowledge – is a format that can be readily adapted to other engineering disciplines; furthermore, it can inspire higher-level thinking and lead to a more engaging learning experience

Multidisciplinary research efforts in post-earthquake civil infrastructure reconnaissance

To address existing challenges with filtering and classification of post-earthquake structural damage images, the authors are engaged in a multidisciplinary project to develop and train a machine-learning algorithm that identifies relevant photographs and assigns damage tags to those images. The research team is predominantly comprised of undergraduate students and is led by a structural engineering and a computer science faculty. While machine-learning algorithms have been successfully used for image tagging in a variety of fields (health care, manufacturing, etc.), the extension of this approach for earthquake reconnaissance is only just beginning. As such, the creation and development of this tool is a new and dynamic project-based learning experience for both the students and faculty involved. This collaborative project emphasizes student initiative and innovation where they are active in all development stages of the tool ranging from collection and tagging of earthquake damage images, coding and testing the machine-learning algorithm, to writing papers for and presenting at conferences. In addition, the unique nature of this project exposes students to a field and possible career path they may not have encountered in their typical course of study. The authors provide a comprehensive discussion of the results of faculty and student surveys/ interviews and conclude by highlighting some of the greatest benefits of the multidisciplinary project. They also point out lessons learned engaging in a project with a large scope, diverse experts (who have limited knowledge of the partnering disciplines), and a number of undergraduate students who began as novices in their respective research area

Photo Tagging Tool for Rapid and Detailed Post-Earthquake Structural Damage Identification

A significant task in earthquake reconnaissance is to conduct rapid and accurate assessments of damage to built infrastructure. This can be accomplished, in part, by analyzing the large volumes of high-resolution image data collected after a seismic event. However, detailed image tagging remains a task for trained human volunteers, which is both time-intensive and error prone. The authors developed a software tool to simplify and standardize the process of assigning damage and structure pairs to sub-regions of images. The goal of the tool is to facilitate the tagging of thousands of images from historic and recent earthquakes to train a deep learning (DL) algorithm to automatically identify damage observed in civil infrastructure. DL is a subset of machine learning that can be used for image classification problems. This process requires thousands of expertly tagged images for robust and automatic visual recognition capabilities. In detecting specific structural damage after an earthquake, images must have explicit tags for the building material, damage and location, as well as the impacted structural members. To obtain such a descriptive set of images, there is a need for a task-specific tool that facilitated tagging of the most common post-earthquake structural damage types. The resulting software solution consists of a simple user interface that displays the most frequently used damage and structural member tags as pre-loaded radio buttons and includes the flexibility for users to customize tags when necessary. The program generates marked-up images that show location-specific damage and structural member labels, as well as output files in the PASCAL Visual Object Classes (VOC) format that are compatible with TensorFlow and most DL frameworks, such that tagged images are ready to be used for training a DL algorithm

Instruction manual: Photogrammetry as a non-contact measurement system in large scale structural testing

Photogrammetry is a non-contact measurement method that is being used in large scale structural experimentation to extract information about the overall geometry of the specimen as well as the XYZ motion of select points on the structure during testing. This is possible through the use of high-resolution still cameras that capture several photographs of the specimen and are processed using photogrammetric software. The following document will focus specifically on the application of PhotoModeler® as the image post-processing tool. This instruction manual aims to provide guidance to researchers who would like to adopt photogrammetric techniques to acquire experimental test data, especially in cases where a high density grid of displacement measurements is desired at a relatively low cost

Software toolset to enable image classification of earthquake damage to above-ground infrastructure

A critical task after a significant earthquake is determining the extent of damage to infrastructure networks. The decision-making process to dispatch emergency, repair, and in-field reconnaissance teams depends on whether road/railways and bridges are passible. Another concern is the rapid identification and resolution of physical disruptions to large-volume gas and water pipeline systems. After large seismic events, citizens, amateur photographers, and journalists now post thousands of photographs to formal/social media platforms. In the past, these images would have had to be reviewed by trained volunteers or expert engineers to evaluate whether: road/rail ways were significantly impacted by ground fracture, heaving, slope failure, or rock slides; bridges experienced severe damage or partial-to-complete collapse; and pipeline systems were interrupted by differential ground movement or liquefaction. The manual review of large imagesets for assessing damage has shown to be inefficient and, in cases, error-prone. This paper presents an automatic and rapid approach, based on computer vision techniques, to assessing damage to above-ground infrastructure networks via images uploaded in the immediate aftermath of the earthquake. The authors developed an algorithm based on deep learning (DL) that automatically tags images. Progress to date shows the algorithm correctly assigns individual tags to 92% of roadway images exhibiting cracking (of varying directionality and severities) and 80% of railways affected by horizontal offset (lateral translation). These results show promise and future research efforts entail tagging both of the aforementioned damage types in a single image

Impact of cross section, web reinforcement and load history on the seismic performance of slender concrete walls

Many reinforced concrete buildings in seismic regions employ reinforced concrete shear walls as part of the lateral force resisting system and these walls often have non-planar cross-sectional geometries. To date, the majority of experimental tests on slender concrete walls have been conducted on planar walls which have been subject to low shear stress demands. An experimental program was developed to examine the response of flanged C-shaped walls with respect of load history and a computational parametric study was conducted to focus more specifically on the impact of web reinforcement for walls subject to a range of shear stress demands. The experimental program investigated the impact of bi-directional loading on flanged C-shaped walls that were designed to meet the minimum ACI 318-08 special structural wall requirements. The results indicate that irrespective of load history the C-shaped walls have a similar damage progression leading to a buckling-rupture failure and a nearly identical strong-axis load-deformation response up to the peak flexural strength. However, bi-directionally loaded walls exhibit earlier onset of critical damage limit states and reduced strong-axis drift capacity. Compared to experimentally-tested planar walls that tend to fail via crushing-buckling, the flanged C-shaped wall geometry has a more ductile failure mode despite being subject to higher shear stress demands. The improved response can be attributed to the ability to redistribute forces to the boundary elements and flanges after considerable web damage. Damage to the unconfined web of the flanged C-shaped walls was substantial. Though walls developed distributed cracking, there was a single wide crack plane that developed near the wall base. Widening of this crack led to high tensile strains in web reinforcement and ultimately the widespread fracture of vertical web bars, limited fracture of horizontal web bars, as well as severe concrete degradation in the surrounding region. This performance suggests that the minimum web steel content required by ACI 318 may be insufficient. As such, the current minimum web reinforcement requirements were studied using an experimentally-validated, high-resolution finite element modelling approach. The computational parametric study examined the impact of the shear stress demand and web reinforcement ratio on wall deformation and ductility. The study results indicate that increased shear stress demand can significantly reduce wall deformation and ductility; however, designs with excess horizontal reinforcement, beyond what is required by ACI 318-14 to meet shear demand, can improve ductility. The data suggest there are similar performance benefits of reducing the design shear demand-to-capacity ratio. A second stage of the parametric study explored the combined effect of modifying the horizontal reinforcement ratio and increasing boundary element length from the ACI 318-14 minimum to the full neutral axis depth. For walls with low-moderate shear stress demands, this combination results in even greater wall ductility than providing excess horizontal reinforcement alone. The experimental tests provide critical data to developing performance-based design criteria for non-planar walls, since most prior efforts have been related to planar walls. The computational parametric study results are of value in developing new code recommendations for the minimum horizontal web reinforcement ratio which have essentially remained unchanged throughout the history of the ACI 318 building code