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Full-Text Articles in Engineering
Performance Based Design And Machine Learning In Structural Fire Engineering: A Case For Masonry, Deanna Craig
Performance Based Design And Machine Learning In Structural Fire Engineering: A Case For Masonry, Deanna Craig
All Theses
The volatile and extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense but not geographically or seasonally bound. Simply, fire can break out anywhere, at any time, and for any number of reasons. Despite the apparent need, fire design of structures still relies on expensive fire tests, complex finite element simulations, and outdated procedures with little room for innovation. This thesis will make a case for adopting the principles of performance-based design and machine learning in structural fire engineering to simplify the process and promote the consideration of fire in all …
Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan
Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan
Publications
Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R2 (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …
Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel
Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel
Theses and Dissertations
Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …
Measuring Accessibility To Food Services To Improve Public Health, Efthymia Kostopoulou
Measuring Accessibility To Food Services To Improve Public Health, Efthymia Kostopoulou
Masters Theses
Food accessibility has lately been of primary interest given its impact on public health outcomes. This thesis illustrates the gaps in food access by applying spatial analysis in Massachusetts accounting for a variety of demographic and socioeconomic factors. The number of grocery stores, farmers markets, and convenience stores within 1/4 and 1 mile of the Census tracts’ centroids are the two accessibility metrics used in the spatial analysis. In addition, a regression model is developed using the Gradient Boosting machine learning method to show the relationship between the socioeconomic factors and the number of grocery stores within 1 mile of …
Enhancing Management Of Built And Natural Water And Sanitation Systems With Data Science, Nelson Da Luz
Enhancing Management Of Built And Natural Water And Sanitation Systems With Data Science, Nelson Da Luz
Doctoral Dissertations
In the age of the data revolution, the civil engineer can enhance the management of infrastructure systems using new techniques focused on data. This dissertation present three studies in which data science approaches are used to enhance management of water and sanitation systems in both the built and natural environments. Chapters 1 and 2 focus on improving methods for data collection relating to water quality monitoring. In Chapter 1, the efficacy of different water quality sampling program designs is evaluated as the programs relate to meeting monitoring goals. Considerations include how timing, location, and distribution system operations can affect monitoring …
Project Leanness Score: A Machine Learning Approach, Julia Said
Project Leanness Score: A Machine Learning Approach, Julia Said
Theses and Dissertations
The construction industry is known to have several inadequacies in resource utilization leading to cost and schedule overruns. One of the popular recent methods that attempts to eliminate these inadequacies is lean construction principles, techniques and tools. Lean construction is a philosophy, backed with principles and tools, aiming at maximizing value, eliminating waste, optimizing efficiency, and seeking continuous improvement. Lean construction techniques (such as pull planning, just-in-time delivery, fail safe for quality, etc.) are widely researched and well developed. However, their implementation in construction sites is tricky as their success depends on several other factors such as the level of …
Modeling Crash Severity And Collision Types Using Machine Learning, Amit Kumar, Hari Krishnan Melempat Kalapurayil
Modeling Crash Severity And Collision Types Using Machine Learning, Amit Kumar, Hari Krishnan Melempat Kalapurayil
Publications
Traffic safety analysis is the fundamental step for reducing economic, social, and environmental cost incurred due to traffic accidents. The essence of traffic safety is understanding the factors affecting crash occurrence, injury severity and collision type and their underlying relationships and predict-prevent future crash instances. Crash injury severity studies in past have utilized numerous statistical, econometric and Machine Learning (ML) and Artificial Intelligence (AI) tools to extract the underlying relationship between the crash causal factors and the consequent severity or collision type. The study aims to explore the Multi-Label Classification (MLC) tool from the domain of Artificial Intelligence (AI) for …
Air Passenger Demand Forecast Through The Use Of Artificial Neural Network Algorithms, Juan Gerardo Muros Anguita, Oscar Díaz Olariaga
Air Passenger Demand Forecast Through The Use Of Artificial Neural Network Algorithms, Juan Gerardo Muros Anguita, Oscar Díaz Olariaga
International Journal of Aviation, Aeronautics, and Aerospace
Airport planning depends to a large extent on the levels of activity that are anticipated. In order to plan facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predict the level and distribution of demand. This document presents a short- and medium-term forecast of the demand for air passengers carried out through a specific case study (Colombia), in which the impact of the pandemic period due to COVID-19 on air traffic was taken into account. To make the forecast, an algorithm that implements techniques based on Artificial Neural Networks (ANN) …