Lauren Ronsse – Ph.D. Candidate, Architectural Engineering, University of Nebraska - Lincoln
Lauren M. Ronsse is a Ph.D. candidate in the Architectural Engineering Program at the University of Nebraska – Lincoln. She has conducted research in various areas of acoustics including perceptual impacts of noise on humans, speech intelligibility in rooms, and archeological acoustics. Lauren is chair of the National Acoustical Society of America Student Council and is a recipient of an NSF Graduate Research Fellowship.
- Effects of Classroom Acoustical Environments on Elementary Student Achievement
This research investigates the relationships between unoccupied classroom acoustical conditions and elementary student achievement. Acoustical measurements have been gathered in a range of elementary school classrooms in a Midwestern United States Public School District. Classroom acoustic parameters from these measurements have been correlated to the standardized achievement test scores from students in the surveyed classrooms. The results from this research suggest that elementary student language and reading subject areas may be negatively impacted by higher unoccupied background noise levels. Also, a perception-based acoustics metric was found to be significantly related to the student language achievement test scores.
Hooman Tavallali, Ph.D. Candidate, Department of Architectural Engineering, Pennsylvania State University
- Deformation Capacity of Concrete Beams Reinforced with Ultrahigh Strength Steel
For many years, the seismic design of reinforced concrete structures in the U.S. has been dominated by the use of steel reinforcement with specified yield strength, fy, of 60 ksi. Using steel reinforcement with higher yield strength would introduce several benefits to the architectural, engineering, and construction industry. Not only would it allow for members with reduced cross sectional area, saving on material, shipping, and placement costs, but it would also help to overcome steel congestion, and facilitate concrete placement. This would directly lead to a better quality of construction, improved durability, and shorter construction times. One of the primary obstacles to the use of concrete members reinforced with ultrahigh strength steel (fy greater than 80 ksi) is the paucity of experimental data. A series of seven experiments was carried out to investigate the behavior of concrete beams reinforced with ultrahigh strength steel under load reversals. Each test specimen consisted of two cantilever beams connecting at a central joint. The main experimental variables were the type of longitudinal reinforcement (conventional, Grade 60, or ultrahigh strength steel, Grade 97), the volume fraction of fibers used in the concrete mix (0 or 1.5%), the ratio of compressive to tensile reinforcement, and the spacing of the transverse reinforcement. The applied displacement history included initial cycles of increasing amplitude deflection reversals followed by a monotonic final push to the failure. The applied displacement history was chosen to induce the effect of load reversals caused by earthquake. The applicability of using high performance fiber reinforced concrete with ultrahigh strength steel was also investigated in the current study. Test data from this study show that the use of ultrahigh strength steel is a viable option for earthquake-resistant construction.
Elizabeth Kraft, Ph.D. Candidate, Construction Engineering, University of Colorado - Boulder
Elizabeth Kraft earned a Bachelor’s of Science in Mechanical Engineering from Purdue University and a Master’s of Science in Civil Engineering from Georgia Tech. In her professional career she has worked in manufacturing, excavation, land development, and residential and commercial construction. Currently she is working to complete a Ph.D. in Construction Engineering and Management at the University of Colorado at Boulder. Her research interests include transportation, alternative project delivery, project management and quality management.
- Project Attribute Influence on Highway Construction Quality Management Programs
Delivering highway projects using alternative project delivery methods demands a shift in the traditional agency quality management programs to accommodate the faster pace of design and construction as well as the redistribution of responsibilities among project stakeholders. However, the nation’s current quality management programs procedures were built on decades of design-bid-build project delivery. As a result quality management is practiced in an ad-hoc approach for individual alternative delivery projects. Quality is a bit of an ambiguous topic and the bulk of the research is focused on the more finite elements of quality: specifications, materials testing and inspection. There has been little research on quality management in highway construction and even less for highway construction alternative project delivery. The objective of this research is to begin to close this gap in highway construction quality research by 1) categorizing common alternative quality management models in use by the industry, 2) identifying the project attributes that influence quality management model selection in highway projects and 3) applying these results to select suitable quality management models for individual highway projects.
Ke Xu, Ph.D. Candidate, Architectural Engineering, Pennsylvania State University
Ke Xu is a Ph.D. candidate in the Architectural Engineering department at Penn State University. He received his B. Eng. from Harbin Institute of Technology in China and M.S. from the University of Nebraska-Lincoln. He has worked as a research assistant in the Energy System Laboratory at UNL for three years and was involved in several building Continuous Commissioning projects before he started his Ph.D. in Penn State. He currently conducts research on the building energy simulation calibration based on the building sub-metering data.
- Calibrate Building Energy Simulations By Using The Real-Time Sub-Metering Data
Thebuilding sector in the U.S. consumes about 40 percent primary energy, 70 percent electricity and contributes to 38 percent of the greenhouse gas each year. To stimulate green design and promote the energy-efficient technologies implementation in buildings, the government agencies launched the Energy Star benchmark program for the existing buildings in 1998, and followed by releasing the Leadership in Energy and Environmental Design (LEED) rating system. However, in practice, the actual building energy performance always differs from the prediction of the simulation programs. This could be caused by various reasons, further investigation about this gap, or in another word, calibrating the building energy simulations by using the real energy performance data, could possibly improve the reliability of the building energy saving prediction, accurately evaluate the building energy saving potentials and help diagnose the system fault operation. During this process, adequately sub-metering the building energy system is crucial as it could provide the buildings detailed operation information as feedback to reconcile the initial simulations.
Michael Royer, Ph.D. Candidate, Architectural Engineering, Pennsylvania State University
Michael Royer graduated from Penn State University with a Ph.D. in Architectural Engineering, Illumination Systems in May 2011. Michael has called Penn State home for the past eight years, earning is BAE / MAE in 2008. He has worked as a graduate research assistant and undergraduate research assistant throughout his time in school. Michael has also worked for Haas Building Solutions and Ashland. Michael was recently awarded the Jonas Bellovin Scholar Achievement Award from the Nuckolls Fund for Lighting Education and received an Honorable Mention for the National Science Foundation’s Graduate Research Fellowship. As an undergraduate in the lighting and electrical option, Michael was awarded the Acuity – Lithonia Award for the most outstanding thesis project in his option. He also received awards for Outstanding Performance and Record of Study in Illumination and Outstanding Electronic Portfolio, among other scholarships. Michael has completed research in many areas of illuminating engineering including light loss metrics, sports lighting uniformity, brightness perception, spectral tuning, color rendition, and lighting for nonvisual human needs.
- Tuning Optical Radiation for Visual and Nonvisual Impact
Recent breakthroughs in neurophysiology have led to profound changes in the understanding of the relationship between light and humans. Optical radiation not only allows for vision, but also helps to regulate important body rhythms and can ameliorate conditions such as mood disorders and cognitive decline. Lamp developers and lighting designers must consider both visual and nonvisual impacts simultaneously, utilizing current knowledge of the response of multiple photoreceptors found in the eye. Brightness perception, luminous efficacy, color quality, and circadian effectiveness are all important attributes of lighting systems. All of these elements are influenced by the placement of energy within the visible spectrum, but they cannot be concurrently maximized. Recent research on the psychophysical response to optical radiation will be presented and the direction of future light source development will be discussed.
Catherine Armwood, Ph.D. Candidate, Architectural Engineering, University of Nebraska - Lincoln
Catherine Armwood is originally from Durham, N.C. She received a Bachelor’s of Science degree in Architectural Engineering from Tennessee State University in Nashville, Tennessee. Catherine is currently a Ph.D. Candidate at the University of Nebraska-Lincoln majoring in Architectural Engineering with an emphasis in structures. Her research interests include Fiber Reinforced Mortars (FRM), masonry structures, and finding innovative methods to improve the mechanical properties of structural materials.
- The Effect of Fiber Reinforced Mortars (FRM) for Rehabilitation and Reconstruction of Masonry Structures and Application in New Structures
1) In an extensive experimental program carried out for the National Center for Preservation Technology and Training, the mechanical properties of 80 mortar mixtures were evaluated through a variety of experimental tests after 7 days of curing. This paper discusses the flexural strength of 22 of these mortar mixtures: two control mixtures and 20 fiber reinforced mortar mixtures. Experiments were conducted using two types of binders (Portland cement-lime, type N; and natural hydrated lime 5) and 5 types of fibers: 4 synthetic fibers (nylon or polyvinyl alcohol) and one organic fiber (horse hair). Results indicate that majority of the synthetic fiber mixtures enhanced the performance of the mortar when tested in flexure by a range of 4.62%- 48.50%. The Nano-Nylon and horse hair fibers were the least effective in improving the ductility and the modulus of rupture. Along with the detailed discussions and derived conclusions, suggestions are provided on how to determine the most feasible mortar for different applications. 2) Recycled carbon fibers produced by HADEG recycling GmbH were experimentally tested for their tensile capacity at the Lulea Technological Institute. The tests were performed in partial fulfillment of participation in the University of Nebraska-Lincoln, Sweden Work, Engineering and Design in Advanced Composites (SWEDAC) Program. A small amount of these fibers were also tested in the United States as part of an experimental study on the effects of carbon fiber reinforced (FR) mortar on the shear bond strength of masonry. This paper presents the results of the shear bond tests of the FR mortar. It was discovered that the inclusion of the fibers increased the strain capacity of the mortar by about 177.96%, meaning the fibers increase the ductile capacity of the masonry unit. This increased ductility is valuable to improving masonry strength against in-plane loading. It was also found that the fibers increased the internal friction between the mortar and units by 4.37%, mean while keeping the shear strength capacity generally the same as the masonry units without fibers with a difference of only 0.8%.
Zhenhua Zhu, Ph.D. Candidate, Construction Engineering, Georgia Institute of Technology
Zhenhua Zhu is a doctoral candidate in the construction engineering program at the Georgia Institute of Technology. He holds a B.E. in civil engineering and an M.E. in computer science and technology. He is expected to graduate with his PhD in May 2011. Zhenhua Zhu is an active member in several academic and professional organizations, and officially serves as a reviewer for the Journal of Construction Engineering and Management and the Journal of Computing in Civil Engineering. His research interests include visual pattern recognition of structural members, and machine vision-based damage and defects detection. In 2009, he received the Best Paper Award of the ASCE Construction Research Congress.
- Machine Vision-Based Concrete Column Recognition and Crack Properties Retrieval Emergency responders (ERs) need to enter damaged buildings to save trapped victims within hours after an earthquake. In order to protect the safety of ERs from potential structural collapse, the Federal Emergency Management Agency (FEMA) requires that the damaged buildings must be structurally stable. In a large-scale earthquake where several thousand buildings may be affected, evaluating the safety of all buildings manually by structural specialists requires a significant amount of time. The adverse effect is that the survival rate for trapped victims is significantly reduced. Over 91% of people trapped in collapsed structures can survive if they are rescued within 30 minutes; and this value declines to 36.7% if trapped for two days. In addition, FEMA contends that two or more specialists working together are preferred and ideal. In practice, however, there are not enough qualified specialists. Each urban search and rescue (US&R) task force has at most one expert, and most local emergency response teams, which are responsible for saving more than 75% of disaster victims during initial response, do not have any. As part of solving the problem, this research study proposes an automated method for recognizing concrete columns of reinforced concrete frame structures and retrieving the relative properties of the cracks that are inflicted on the recognized columns. The method involves collecting and transmitting images/video frames through a high-resolution camera and a wireless enabled PDA/Mini-Laptop mounted on an evaluator’s outfit to a more powerful computer outside for analysis. There, concrete columns are first recognized by identifying their long near-vertical lines and the concrete material information on their surfaces. Then, the cracks inflicted on the column surfaces are detected using state-of-the-art crack detection techniques. The detected cracks are superimposed on the detected concrete column to measure their relative properties (e.g. length, width, orientation and position in relation to the column’s dimensions and orientation). The method can reduce the time which the evaluator spent on manual measurements, and help him/her to make a rapid and informed decision about the building safety. The proposed method was implemented into a C++ based prototype, and tested on a database of real images/videos. The performance of concrete column recognition was measured. Crack properties retrieved from the automated method are also compared with the manual measurements. All test results indicate the effectiveness of the method.
Xiaowei Luo, Ph.D. Candidate, University of Texas - Austin
- Although the construction industry has invested heavily on safety, safety performance is still not satisfactory and remains steadily far from the zero-accident goal. In industry practice, many management methods and systems have been deployed on construction jobsites, as workers cannot be fully cognizant of safety conditions all the time. Recently, mobile computing and sensing technologies have been introduced to construction jobsites for material management and productivity studies, making the jobsites increasingly automated and intelligent. These emerging technologies can also be used for safety management and provide room to promote safety performance on jobsites, by providing a background safety monitoring for workers and equipment operators. We envision a next-generation jobsite safety monitoring system and provide the system’s development framework in this research. Using this framework, the system builds from existing infrastructure (e.g., wireless network, mobile computing devices, GPS, RFID and other sensors) developed for intelligent jobsites. In the framework, the system development process is divided into four stages. Stage 1’s goal knowledge elicitation to conceptualize safety in a digital world and analyze the data requirement. Stage 2 aims at developing safety monitoring with perfect data and deploying safety monitoring within distributed computing constrains. Stage 3 investigates data imperfection and its impact on safety decision-making, as well as ways to manage imperfect data. Stage 4 designs and implements a simulation test bed and uses the test bed for simulation and evaluation of a developed safety monitoring application. The research demonstrates the generality of the development framework, as well as the advantage of next-generation jobsite safety monitoring systems.
Cynthia (Cindy) King, Ph.D. Candidate, Construction Management, Arizona State University
Cindy King has worked 28 years in project management with domestic and international experience in all aspects of project development and execution—including design, estimating, cost control, budgeting, planning, procurement, and supervision. Cindy holds a Bachelor of Environmental Design from Texas A&M University, an MBA from the University of St. Thomas, and she is currently working on a CII research project while studying for her PhD in Construction Management at the Arizona State University Del E. Webb School of Construction.
- Project Manager (PM) Skills Of The Future – A Process For Predicting The Future
In 1997, the Strategic Planning Committee of the Construction Industry Institute (CII) led a workshop to stimulate breakthrough “blue-sky” thinking to develop a vision for 2020 that would become the guide for the organization’s long-range planning process. In keeping with the strategic focus on the future success of the engineering and construction industry, CII commissioned in 2010 a research effort with the objective of developing a vision for the skill sets required for the project managers of the future to be successful in a complex and ever-changing global marketplace. For many years, the accepted research in CII was based on industry-wide surveys and their analysis. Often times, when responding to surveys people tend to state the generally expected answers rather than revealing their true actions. This presentation introduces a new approach towards revealing the real behaviors and decision-making processes of the Project Manager through the utilization of games and thought-provoking exercises. The games and exercises are embedded in a one-day seminar organized and facilitated by the participating companies. The seminar serves three purposes: 1) workforce development, 2) feedback about hidden issues in the company, and 3) capturing data about the displayed behavior and thinking of the PMs. The data allows the Research Team to look into the future through the eyes of a large number of experienced Project Managers. A way of validating the findings will also be presented.
Le Zhang, Ph.D. Candidate, Construction and Planning, University of Florida
Le Zhang is a Ph.D. candidate in Rinker School of Building Construction, College of Design, Construction and Planning, University of Florida. He is also pursuing a Master of Science degree in Department of Computer and Information Science and Engineering, College of Engineering. He received his Bachelor and Master’s degree in Construction Management from Tianjin University, Tianjin, China. Le’s current research is focused on Industry Foundation Classes (IFC) and web-based applications of Building Information Modeling (BIM). His translation of partial IFC specification is published in the current release of IFC 2x4.
- Development of IFC-based Construction Industry Ontology for Information Retrieval from an IFC Model
Ontologies are being used in various information-related areas, from knowledge management to Semantic Web. Domain ontologies define concepts, activities, objects and the relationships among elements within a certain domain. As an information-intensive industry, construction industry is seeing more domain ontology research. Several sources have been explored; pilot projects and different ontology building process models have been proposed. Most of current construction ontology research is based on knowledge management, ontologies specifically designed to access building information models is still not available. Accessing the information stored in an Industry Foundation Classes (IFC) model will become easier and more efficient with the help of an ontology. The object-oriented nature of IFC specifications makes it a good ontology candidate. This paper explores the steps and principles on transforming IFC specifications into a formal ontology. A sample working ontology is developed. Best practices are summarized. A Semantic Web Service is also developed to actually make use of the knowledge stored in the ontology and retrieve information from an IFC building model.
JeongWook Son, Ph.D. Candidate, Dept. of Construction Management, University of Washington
JeongWook Son is a Ph.D. candidate in interdisciplinary Ph.D. program in the built environment at the University of Washington. He holds a MS degree in civil engineering from the University of Illinois at Urbana-Champaign and MS degree in architectural engineering from Yonsei University in Korea. His research is focused on intelligent and sustainable project management, reliable project planning and control using computer simulation, and competitive engineering education through series games
- Complexity and dynamics in construction project organizations
As construction projects have been getting larger and more complex, a single individual or organization cannot have complete knowledge or the abilities to handle all matters. Collaborative practices among heterogeneous individuals, which are temporarily congregated to carry out a project, are required in order to accomplish project objectives. These organizational knowledge creation processes of project teams should be understood from the active and dynamic viewpoint of how they create information and knowledge rather than from the passive and static input-process-output sequence. To this end, agent-based modeling and simulation which is built from the ground-up perspective can provide the most appropriate way to systematically investigate them. Agent-based modeling and simulation as a research method and a medium for representing theory is introduced. To illustrate, an agent-based simulation of the evolution of collaboration in large-scale project teams from a game theory and social network perspective is presented.
Mohammed AlQady, Ph.D. Candidate, Civil Engineering, Purdue University
Mohammed AlQady holds a B.Sc. degree in construction engineering from the American University in Cairo in 1999 and a MSc. degree from Iowa State University in 2008. Mr. AlQady has worked in various areas in the construction industry including site supervision, planning and scheduling, quantity surveying, cost control, bid preparation and contract administration. Currently, Mr. AlQady is pursuing his Ph.D. in Civil Engineering at Purdue University’s School of Civil Engineering, the Division of Construction Engineering and Management.
- Automatic classification of project documents using latent semantic analysis
Large amounts of project documents are produced in a construction project. Unlike contract documents which are produced at the same time to finalize the contract, project documents are produced gradually throughout the life of the project. Accordingly, the processing of project documents is a continuous and gradual task performed almost on a daily basis. The majority of project documents are text documents containing unstructured information which from a document management perspective produces several problems such as increasing the difficulty level of information retrieval, creating interoperability issues between different systems and hindering information reuse. Another important aspect that characterizes construction project documents is that the documents are semantically interrelated. Project information on a certain event is recorded, disputed, revised and reiterated in various successive documents producing links between these documents. Ultimately, a knowledge discourse is generated that can only be represented by the aggregation of the information in the relevant documents, not just by the information contained in one document; a discourse that requires the application of cognitive skills by the information seeker to comprehensively deduce. The performance of an automatic text classifier utilizing latent semantic analysis in identifying such relations between project documents is investigated. The results of the evaluation may offer important applications in electronic document management, information retrieval and, in general, for knowledge sharing and reuse.
Ian Bell, Ph.D. Candidate, Mechanical Engineering, Purdue University
Ian Bell graduated from Cornell University with a Bachelors of Science in 2006. Since then he has been a PhD student at the Ray W. Herrick Labs of Purdue University. He will graduate with a PhD in Mechanical Engineering in May 2011.
- Modeling of HVAC&R Systems and their Components
In order to optimize HVAC&R systems and their components it is necessary to have sufficiently detailed models of the performance of each component of the system. To that end, two different classes of models are presented here - a detailed scroll compressor model as well as a moving boundary model used to model residential air conditioning systems. The scroll compressor model is based on the integration of a set of differential equations that are derived from the conservation of mass and energy. This set of differential equations is then integrated over the course of one rotation in order to calculate mass flow rates, electrical power, and other features of merit. The model includes accurate treatments of the scroll compressor geometry and leakage flow rates. The system model is based on a moving-boundary analysis of each of the heat exchangers and a compressor map for the performance of the compressor. With these sub-models, a system solver is then used to link all the components together. When the solver reaches convergence, the system model predicts the cooling capacity, system efficiency, and sensible heat ratio, among other outputs.