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- All Subjects: Civil Engineering
Description
As construction and building methods advance so should their focus on reconstruction post-natural disasters. For the past 50 years there has been an average of 6.2 hurricanes making landfall, and several recent unfortunate occurrences in the past year that have caused immeasurable damage and taken priceless lives (Chris Landsea 2017). Damages could have been significantly reduced to residential homes and lives saved if proper, hurricane-resistant construction was used. It is important to continue advancement in efficient planning and reconstructive methods to restore individuals into their homes and ensure their safety in the future. Utilizing tested resilient building methods may increase construction costs but has a visible payoff through mitigation of economic losses in the future. This can also help develop response and mitigation plans based on the very specific conditions of each community or affected location. To do so, it is crucial to continue research and test various methods of construction and materials in residential homes. This study was a comparative analysis of the current roof systems implemented in residential homes, the role of hurricane testing facilities in maintaining building codes, and how damage incurred by hurricanes can be significantly reduced through a shift in the approach of homeowner insurance incentive. The purpose of this study was to provide a feasible and practicable solution for increasing implementation of hurricane resistant construction into homes. The results of this analysis concluded that there is a low percentage of homeowners investing in making their homes hurricane resilient. By re-inventing the incentive methods that insurance companies offer, this problem can step into the right direction in making more homes hurricane resilient consequently reducing damages, deaths, and economic loss.
ContributorsVarkalaite, Migle (Author) / Sullivan, Kenneth (Thesis director) / Ayer, Steven (Committee member) / School of International Letters and Cultures (Contributor) / Del E. Webb Construction (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Emerging information and communication technology (ICT) has had an enormous effect on the building architecture, engineering, construction and operation (AECO) fields in recent decades. The effects have resonated in several disciplines, such as project information flow, design representation and communication, and Building Information Modeling (BIM) approaches. However, these effects can potentially impact communication and coordination of the virtual design contents in both design and construction phases. Therefore, and with the great potential for emerging technologies in construction projects, it is essential to understand how these technologies influence virtual design information within the organizations as well as individuals’ behaviors. This research focusses on understanding current emerging technologies and its impacts on projects virtual design information and communication among projects stakeholders within the AECO organizations.
ContributorsAlsafouri, Suleiman (Author) / Ayer, Steven (Thesis advisor) / Tang, Pingbo (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
In this era of high-tech computer advancements and tremendous programmable computer capabilities, construction cost estimation still remains a knowledge-intensive and experience driven task. High reliance on human expertise, and less accuracy in the decision support tools render cost estimation error prone. Arriving at accurate cost estimates is of paramount importance because it forms the basis of most of the financial, design, and executive decisions concerning the project at subsequent stages. As its unique contribution to the body of knowledge, this paper analyzes the deviations and behavior of costs associated with different construction activities involved in commercial office tenant improvement (TI) projects. The aim of this study is to obtain useful micro-level cost information of various construction activities that make up for the total construction cost of projects. Standardization and classification of construction activities have been carried out based on Construction Specifications Institute’s (CSI) MasterFormat® division items. Construction costs from 51 office TI projects completed during 2015 and 2016 are analyzed statistically to understand the trends among various construction activities involved. It was found that the interior finishes activities showed a much higher cost of construction, and a comparatively higher variation than the mechanical, electrical, and plumbing (MEP) trades. The statistical analysis also revealed a huge scope of energy saving measures that could be achieved in such TI projects because of the absence of energy management systems (EMS) found in 66% of the projects.
ContributorsGhosh, Arunabho (Author) / Grau, David (Thesis advisor) / Ayer, Steven (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2016
Description
At least 30 datacenters either broke ground or hit the planning stages around the United States over the past two years. On such technically complex projects, Mechanical, Electrical and Plumbing (MEP) systems make up a huge portion of the construction work which makes data center market very promising for MEP subcontractors in the next years. However, specialized subcontractors such as electrical subcontractors are struggling to keep crews motivated. Due to the hard work involved in the construction industry, it is not appealing for young workers. According to The Center for Construction Research and Training, the percentages of workers aged between 16 to 19 years decreased by 67%, 20 to 24 years decreased by 49% and 25 to 34 age decreased by 32% from 1985 to 2015. Furthermore, the construction industry has been lagging other industries in combatting its decline in productivity. Electrical activities, especially cable pulling, are some of the most physically unsafe, tedious, and labor-intensive electrical process on data center projects. The motivation of this research is the need to take a closer look at how this process is being done and find improvement opportunities. This thesis focuses on one potential restructuring of the cable pulling and termination process; the goal of this restructuring is optimization for automation. Through process mapping, this thesis presents a proposed cable pulling and termination process that utilizes automation to make use of the best abilities of human and robots/machines. It will also provide a methodology for process improvement that is applicable to the electrical scope of work as well as that of other construction trades.
ContributorsHammam, MennatAllah (Author) / Parrish, Kristen (Thesis advisor) / Ayer, Steven (Committee member) / Irish, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2020
Description
Virtual Reality (VR) has been used in the sphere of training and education in the construction field. Research has investigated the different applications of VR in construction-focused simulations to report its benefits and drawbacks in training and education. Although this is significant, they were not albeit explicitly studied through the lens of accreditation at undergraduate educational levels. The American Council for Construction Education (ACCE) established twenty Students Learning Outcomes (SLOs) that equip students with essential knowledge and industry-oriented technical and managerial skills that maintain quality education in undergraduate construction programs. This paper analyzes the trends in VR literature through reported benefits and unexplored learning outcomes of VR in construction training and education and investigates the ways by which these trends do or do not contribute to the learning experience by targeting the content areas associated with the ACCE’s SLOs. To accomplish this, the author reviewed 59 articles from 2014 to 2023 found through a keyword search for “Virtual” AND “Reality” AND “Construction” AND (“Training” OR “Simulation” OR “Education”) AND “Students”. The learning outcomes of the VR training reported in the 59 articles were mapped to their corresponding content areas from ACCE’s SLO(s). The results demonstrate the content areas of SLOs that were addressed in literature (1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 18, 19, and 20) and the SLOs that were not explored (4, 12, 14, and 17) due to lack of studies in some contexts. This study reveals trends and patterns of VR training, some of which exemplify benefits of addressing content areas of SLOs through virtual on-site immersion, manipulation of time, cost efficiency, and ethical measures, while others indicate unexplored learning outcomes of VR training in targeting content areas of SLOs that involve human interaction, complex quantitative calculations or require construction management tools, delivery method and stakeholders’ management, and risk management. While this research does not seek replacement of traditional trainings, it encourages consideration of VR training under the lens of ACCE’s accreditation. This research’s findings propose guidance to educational researchers on how VR training could address content areas from ACCE’s SLOs.
ContributorsElgamal, Sara (Author) / Ayer, Steven (Thesis advisor, Committee member) / Parrish, Kristen (Thesis advisor, Committee member) / Lamanna, Anthony (Committee member) / Arizona State University (Publisher)
Created2023
Description
Imagery data has become important for civil infrastructure operation and
maintenance because imagery data can capture detailed visual information with high
frequencies. Computer vision can be useful for acquiring spatiotemporal details to
support the timely maintenance of critical civil infrastructures that serve society. Some
examples include: irrigation canals need to maintain the leaking sections to avoid water
loss; project engineers need to identify the deviating parts of the workflow to have the
project finished on time and within budget; detecting abnormal behaviors of air traffic
controllers is necessary to reduce operational errors and avoid air traffic accidents.
Identifying the outliers of the civil infrastructure can help engineers focus on targeted
areas. However, large amounts of imagery data bring the difficulty of information
overloading. Anomaly detection combined with contextual knowledge could help address
such information overloading to support the operation and maintenance of civil
infrastructures.
Some challenges make such identification of anomalies difficult. The first challenge is
that diverse large civil infrastructures span among various geospatial environments so
that previous algorithms cannot handle anomaly detection of civil infrastructures in
different environments. The second challenge is that the crowded and rapidly changing
workspaces can cause difficulties for the reliable detection of deviating parts of the
workflow. The third challenge is that limited studies examined how to detect abnormal
behaviors for diverse people in a real-time and non-intrusive manner. Using video andii
relevant data sources (e.g., biometric and communication data) could be promising but
still need a baseline of normal behaviors for outlier detection.
This dissertation presents an anomaly detection framework that uses contextual
knowledge, contextual information, and contextual data for filtering visual information
extracted by computer vision techniques (ADCV) to address the challenges described
above. The framework categorizes the anomaly detection of civil infrastructures into two
categories: with and without a baseline of normal events. The author uses three case
studies to illustrate how the developed approaches can address ADCV challenges in
different categories of anomaly detection. Detailed data collection and experiments
validate the developed ADCV approaches.
maintenance because imagery data can capture detailed visual information with high
frequencies. Computer vision can be useful for acquiring spatiotemporal details to
support the timely maintenance of critical civil infrastructures that serve society. Some
examples include: irrigation canals need to maintain the leaking sections to avoid water
loss; project engineers need to identify the deviating parts of the workflow to have the
project finished on time and within budget; detecting abnormal behaviors of air traffic
controllers is necessary to reduce operational errors and avoid air traffic accidents.
Identifying the outliers of the civil infrastructure can help engineers focus on targeted
areas. However, large amounts of imagery data bring the difficulty of information
overloading. Anomaly detection combined with contextual knowledge could help address
such information overloading to support the operation and maintenance of civil
infrastructures.
Some challenges make such identification of anomalies difficult. The first challenge is
that diverse large civil infrastructures span among various geospatial environments so
that previous algorithms cannot handle anomaly detection of civil infrastructures in
different environments. The second challenge is that the crowded and rapidly changing
workspaces can cause difficulties for the reliable detection of deviating parts of the
workflow. The third challenge is that limited studies examined how to detect abnormal
behaviors for diverse people in a real-time and non-intrusive manner. Using video andii
relevant data sources (e.g., biometric and communication data) could be promising but
still need a baseline of normal behaviors for outlier detection.
This dissertation presents an anomaly detection framework that uses contextual
knowledge, contextual information, and contextual data for filtering visual information
extracted by computer vision techniques (ADCV) to address the challenges described
above. The framework categorizes the anomaly detection of civil infrastructures into two
categories: with and without a baseline of normal events. The author uses three case
studies to illustrate how the developed approaches can address ADCV challenges in
different categories of anomaly detection. Detailed data collection and experiments
validate the developed ADCV approaches.
ContributorsChen, Jiawei (Author) / Tang, Pingbo (Thesis advisor) / Ayer, Steven (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2020
Description
Design is widely accepted as a factor that affects construction work. Although knowledge about this effect will contribute to the improvement of construction practice, this is very limited. No study has been focused on establishing how the effect of design on construction work can be evaluated. The primary objective of this research was to formulate an approach enabling the assessment of the effect of building design on construction work. To achieve this, a quantitative index based on field data, termed the 'index of difficulty,' was established. Given a construction activity, this index relates the effective work effort per unit of output expended in completing a construction part under two distinct designs: one under evaluation and the other designated as the base design for common comparison. The greater the index of difficulty associated with a design, the higher the required work effort, consequently resulting in a greater affect of the design on construction work.
Multiple ways of utilizing the index of difficulty to assess the effect of building design on construction activities are suggested. Additionally, application cases are exhibited to illustrate the implementation of the proposed approach and the required computations.
ContributorsChang, Luis Gerardo (Author) / Wiezel, Avi (Thesis advisor) / Sullivan, Kenneth (Committee member) / Ayer, Steven (Committee member) / Arizona State University (Publisher)
Created2023