Engineering Commons^™

Deep Reinforcement Learning For The Design Of Structural Topologies, Nathan Brown

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Advances in machine learning algorithms and increased computational efficiencies have given engineers new capabilities and tools for engineering design. The presented work investigates using deep reinforcement learning (DRL), a subset of deep machine learning that teaches an agent to complete a task through accumulating experiences in an interactive environment, to design 2D structural topologies. Three unique structural topology design problems are investigated to validate DRL as a practical design automation tool to produce high-performing designs in structural topology domains.

The first design problem attempts to find a gradient-free alternative to solving the compliance minimization topology optimization problem. In the proposed …

Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon

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The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …

Mesoscale Modeling And Machine Learning Studies Of Grain Boundary Segregation In Metallic Alloys, Malek Alkayyali

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Nearly all structural and functional materials are polycrystalline alloys; they are composed of differently oriented crystalline grains that are joined at internal interfaces termed grain boundaries (GBs). It is well accepted that GB dynamics play a critical role in many phenomena during materials processing or under operating environments. Of particular interest are GB migration and grain growth processes, as they influence many crystal-size dependent properties, such as mechanical strength and electrical conductivity.

In metallic alloys, GBs offer a plethora of preferential atomic sites for alloying elements to occupy. Indeed, recent experimental studies employing in-situ microscopy revealed strong GB solute segregation …

Machine Learning-Enabled Model-Based Condition Assessment Of Water Pipelines By Leveraging Hydraulic Monitoring Data, Ahmad Momeni

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Overpopulation and climate change have direly challenged the freshwater resources, specifically potable water supplied by water distribution networks (WDNs). One aggravating issue associated with the WDNs is associated with the pipeline leakage, which accounts for almost 20% of freshwater loss in WDNs throughout the US. Leakage detection and severity measurement are of top
asset management priorities in water utilities to minimize and mitigate complicated risks attributed to background and burst leakage. Accordingly, decline in other pipe condition parameters such as effective hydraulic diameters and roughness coefficients, which are complex and uncertain in nature, abets leakage by worsening the WDN status …

Using Safety Performance Models, Autonomous Vehicle Data, And Machine Learning To Develop Contextual Complexity Criteria To Establish A Standardized Process For On-Road Evaluation Of Medically At-Risk Drivers Considering Static And Dynamic Factors Of The Roadway Environment, Vijay Bendigeri

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The field of transportation engineering has an opportunity to positively impact the medical community, specifically the clinicians who evaluate, train, and rehabilitate at-risk drivers. Driving Rehabilitation Specialists (DRSs) have an essential role in making roads safer for medically-at-risk drivers, their passengers, and other road users. DRSs conduct on-road driving evaluations, which are considered the gold standard to make fitness-to-drive decisions due to their high face validity. Most DRSs use a fixed route, meaning the exact same route is used to evaluate each client. When a DRS develops a fixed route, that clinician identifies characteristics of the roadway they think are …

Digitalization Of Construction Project Requirements Using Natural Language Processing (Nlp) Techniques, Fahad Ul Hassan

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Contract documents are a critical legal component of a construction project that specify all wishes and expectations of the owner toward the design, construction, and handover of a project. A single contract package, especially of a design-build (DB) project, comprises hundreds of documents including thousands of requirements. Precise comprehension and management of the requirements are critical to ensure that all important explicit and implicit requirements of the project scope are captured, managed, and completed. Since requirements are mainly written in a natural human language, the current manual methods impose a significant burden on practitioners to process and restructure them into …