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Articles 31 - 37 of 37
Full-Text Articles in Engineering
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
Data
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 …
The Effect Of Plasma Treatment On The Cure Behavior Of Out-Of-Life Prepregs And An Investigation Of The Mechanical Properties Of Composite Parts Manufactured From Plasma-Treated Prepregs, Monjur Morshed Rabby, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan
The Effect Of Plasma Treatment On The Cure Behavior Of Out-Of-Life Prepregs And An Investigation Of The Mechanical Properties Of Composite Parts Manufactured From Plasma-Treated Prepregs, Monjur Morshed Rabby, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Many industries, including aircraft, automobiles, and marine, are using prepreg (pre-impregnated fibers and a partially cured polymer matrix) to manufacture composite parts to achieve optimum fiber and resin volume ratio and part repeatability. Since prepregs have a short out oflife (i.e., the maximum storing time allowed at room temperature), they must be stored in refrigerators at low temperatures, which, if not maintained, have an unfavorable influence on the intended quality of the final product. For the present study, glass/epoxy prepregs (expired out-life) were plasmatreated before being used to make the composite part to compensate for the room temperature aging effect. …
Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Susan Mckeever, Ayman Taha, Jane Courtney
Using Satellite Images Datasets For Road Intersection Detection In Route Planning, Fatmaelzahraa Eltaher, Susan Mckeever, Ayman Taha, Jane Courtney
Datasets
Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the …
Moisture Content Prediction In Polymer Composites Using Machine Learning Techniques, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Moisture Content Prediction In Polymer Composites Using Machine Learning Techniques, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
The principal objective of this study is to employ non-destructive broadband dielectric spectroscopy/impedance spectroscopy and machine learning techniques to estimate the moisture content in FRP composites under hygrothermal aging. Here, classification and regression machine learning models that can accurately predict the current moisture saturation state are developed using the frequency domain dielectric response of the composite, in conjunction with the time domain hygrothermal aging effect. First, to categorize the composites based on the present state of the absorbed moisture supervised classification learning models (i.e., quadratic discriminant analysis (QDA), support vector machine (SVM), and artificial neural network-based multilayer perceptron (MLP) classifier) …
Dielectric State Variables As Qualitative Indicators Of Moisture Absorption-Caused Mechanical Property Degradation In Gfrp Composite Structures, Partha Pratim Das, Vamsee Vadlamudi, Rassel Raihan
Dielectric State Variables As Qualitative Indicators Of Moisture Absorption-Caused Mechanical Property Degradation In Gfrp Composite Structures, Partha Pratim Das, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Fiber reinforced polymer (FRP) composites are being used in numerous fields owing to their intrinsic strength to weight ratio and various design benefits. However, these materials are prone to environmental aging, particularly moisture absorption. In essence, absorbed moisture infiltrates the polymer matrix and induces changes in the polymer network through chain scission, plasticization, and other bonding interactions. This causes irreversible damages to the material and significantly decreases mechanical strength. In this study, Broadband Dielectric Spectroscopy (BbDS) has been used to identify the absorption mechanisms in glass fiber reinforced polymer (GFRP) composites by detecting the related polarization mechanisms. Here, results show …
Dielectric Analysis To Predict Moisture Absorption In Structural Composites: A Data-Driven Approach, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Dielectric Analysis To Predict Moisture Absorption In Structural Composites: A Data-Driven Approach, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Due to continual exposure to moist environment, environmental degradation is a major threat to structural composites throughout their service life. Impedance Spectroscopy (IS)/Broadband Dielectric Spectroscopy (BbDS) is a reliable nondestructive method that has been used in polymer industries for dielectric characterization of material. While moisture absorption causes irreversible changes in the polymer matrix composites, it also alters the electrical properties of the system which is detectable using BbDS. Since the physics that drives the change in electrical characteristics is driven by the modifications imposed by water molecules (whether free or bound), both events can be linked. A dielectric spectrum over …
Coupled Effects In Dielectric And Thermal Properties Of Polymer Matrix Composite Structures Due To Moisture Absorption, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Coupled Effects In Dielectric And Thermal Properties Of Polymer Matrix Composite Structures Due To Moisture Absorption, Partha Pratim Das, Monjur Morshed Rabby, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Fiber reinforced polymer (FRP) composites are being used in number of fields including aerospace, marine, sports, medical, power sectors, etc. due to their lightweight nature while retaining high mechanical performance in terms of high specific strength, stiffness, and great fatigue properties. However, the applicability of these materials is restricted by their stability up to a certain temperature (i.e. glass transition temperature) and environmental degradation (i.e. moisture, UV light, etc.). Moisture ingression greatly reduces their mechanical properties altering material structure by causing polymer plasticization, chain scission and fiber-polymer interface deterioration. These changes instantaneously affect the thermal properties of the materials which …