Engineering Commons^™

A Simulation Way To Investigate The Reason For Congestion In Urban——A Case Study In Hohhot China, Junqing Wang, Hong Yang, Yuan Zhu, Qingwen Pu, Shunlai Cui

College of Engineering & Technology (Batten) Posters

In the case of high density traffic flow, traditional traffic data statistical analysis methods, which not only have certain errors and lead to inaccurate data, but also have many limitations such as labor consumption, can no longer meet the demand for traffic analysis. Drones for traffic data, based on an aerial bird's-eye view, no offset, and error-free complete statistics of urban road shooting section of all data, while greatly reducing cost consumption. A multi-dimensional simulation model is established for the UAV data to the Hohhot central urban area's road simulation platform. This project will test and explore multidimensional data in …

Investigating The Impacts Of Connected Vehicles On Driving Aggressiveness And Situational Awareness In Highway Crash Scenarios: A Driving Simulator Study, Abdalziz Alruwaili

College of Engineering & Technology (Batten) Posters

Psychological factors such as aggressiveness and situational awareness can impact driving performance. Connected vehicles (CV), equipped with advanced sensors and able to communicate safety messages to drivers, have the potential to influence driving performance by altering drivers’ aggressiveness and situational awareness. This paper aims to investigate the impacts of the CVs on driving aggressiveness and situational awareness in highway crash scenarios where a primary crash has already occurred, and a second crash may occur as a result. To achieve this goal, a driving simulator experiment was conducted, and questionnaires focused on driving aggressiveness and CV effectiveness were distributed. Structural equation …

Computer Based Modeling For Tilt-Wing E-Vtol Propeller Performance, Ege Konuk, Drew Landman

College of Engineering & Technology (Batten) Posters

Recent decades have seen a rapid popularization of Urban Air Mobility (UAM) concepts. The new generation of designs presents a wide range of configurations and approaches to exploit the advantages of these vehicles that can be used in civil, commercial, and military applications. One of the more popular concepts is the tandem tilt-wing e-VTOL configuration. However, these types of VTOL configurations bring challenges for performance prediction during crucial parts of flight operations. The flight dynamics during transition regimes where the vehicle transitions from vertical to forward flight and vice versa is not fully understood. In this research, modified blade element …

Production Of Lithium Carbonate From Geothermal Brine By Selective Extraction Of Lithium Using A Novel Ion Sieve Method, Ujjwal Pokharel, Sandeep Kumar

College of Engineering & Technology (Batten) Posters

The project implements a novel approach to extract lithium from a geothermal brine with minimal water loss. Production of high-capacity lithium-ion (Li-ion) batteries for electric vehicles (EV) is believed to be the way to reduce dependence on fossil-fuel based vehicles. Currently, most of the lithium in the world comes from the mining of lithium or the evaporative/concentration of the brine. Mining is not environmentally friendly, and the evaporative process takes 12 months for the completion of the extraction process and results in a large amount of water loss which can lead to scarcity of water. The brines constitute 82% of …

Automatic Generation And Novel Validation Of Patient-Specific, Anatomically Inclusive Scoliosis Models For Biomechanics-Informed Surgical Planning, Austin Tapp, Michel Audette, James Bennett

College of Engineering & Technology (Batten) Posters

Scoliosis is an abnormal spinal curvature of greater than 10 degrees. Severe scoliotic deformities are addressed with highly invasive procedures: anterior or posterior spinal fusion approaches. This invasiveness is due, in part, to the constraints of current surgical planning, which utilizes computed tomography (CT) scans unable to discern spinal ligaments that are dissected to make the spine sufficiently compliant for correction. If localization of ligaments and soft tissues were achieved pre-operatively, corrective procedures could become safer and more efficient by using finite element (FE) biomechanical simulations to determine decreased incidences of ligament releases. This research aims to achieve ligament localization …

Computational Aerodynamics Of A Wing Mounted Propeller, Sarah Agam

College of Engineering & Technology (Batten) Posters

Computational fluid dynamics (CFD) is a vital component in aerospace engineering. A major use of CFD is analyzing the flow properties to determine outputs like aerodynamic lift and drag over an airfoil or compute engine efficiency. It is more practical to conduct a CFD analysis first before doing experimental work as CFD allows for rapid and diverse testing of propeller shapes at a lower cost. CFD also allows for a wider range of testing parameters; for example, an airfoil can be subjected to steady, unsteady, incompressible, or high velocity flows.

Propellers are extensively used in the aircraft industry, especially in …

Musculoskeletal Modeling Of The Pelvis And Lumbar Spine During Running, Ruth Higgins, Maryam Moeini, Hunter Bennett, Stacie Ringleb

College of Engineering & Technology (Batten) Posters

Musculoskeletal modeling provides an alternative to in-vivo characteristics that are difficult to directly measure for movements such as running, especially for trunk muscles and joints. The full-body-lumbar-spine (FBLS) model by Raabe and Chaudhari, 2016 is an OpenSim model created for simulations of jogging. The lifting full-body (LFB) model by Beaucage-Gauvreau et al., 2018 is an adaptation of the FBLS created for estimating spinal loads during lifting. PURPOSE: Determine validity of the FBLS and LFB models in simulating pelvis and lumbar spine kinematics during running. METHODS: Inverse Kinematics were executed using experimental data for the FBLS and LFB models. To …

Data-Limited Domain Adaptation And Transfer Learning For Learning Latent Expression Labels Of Child Facial Expression Images, Megan Witherow, Winston Shields, Manar Samad, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

While state-of-the-art deep learning models have demonstrated success in adult facial expression classification by leveraging large, labeled datasets, labeled data for child facial expression classification is limited. Due to differences in facial morphology and development in child and adult faces, deep learning models trained on adult data do not generalize well to child data. Recent deep domain adaptation approaches have improved the generalizability of models trained on a source domain to a target domain with few labeled samples. We propose that incorporating steps of deep transfer learning, e.g. weights initialization from the pre-trained source model and freezing model layers, may …

3d Lidar Human Skeleton Estimation For Long Range Identification, Alexander Glandon, Lasitha Vidyaratne, Nasrin Sadeghzadehyazdi, Nibir Dhar, Jide Familoni, Scott Acton, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

This research project is the continuation of an effort by the Vision Lab to understand human gait and motion using special-purpose imaging sensors and novel computer vision algorithms. The project began using a Motion Capture (MoCap) system which measures 3D human skeleton information in real-time by attaching markers to a human subject and viewing the human motion with a set of cameras at different angles. We developed an algorithm to determine the gender of a subject wearing these sensors. The current phase of this project extends this work using a state-of-the-art flash Lidar sensor. This sensor scans the surface of …

Unsupervised Multivariate Time Series Clustering, Md Monibor Rahman, Lasitha Vidyaratne, Alex Glandon, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

Clustering is widely used in unsupervised machine learning to partition a given set of data into non-overlapping groups. Many real-world applications require processing more complex multivariate time series data characterized by more than one dependent variables. A few works in literature reported multivariate classification using Shapelet learning. However, the clustering of multivariate time series signals using Shapelet learning has not explored yet. Shapelet learning is a process of discovering those Shapelets which contain the most informative features of the time series signal. Discovering suitable Shapelets from many candidates Shapelet has been broadly studied for classification and clustering of univariate time …

Loading Orientation Dependence On The Compressive Response Of Ice-Templated Ceramic-Polymer Composites, Sashanka Akurati, Justine Marin, Dipankar Ghosh

College of Engineering & Technology (Batten) Posters

Natural materials are made from weak constituents, yet exhibit an excellent synergy of high stiffness, strength, and damage-tolerance. They consist of alternate layers of the hard and soft phases with a complex hierarchical structural organization. The ice-templating technique provides an approach to fabricate multilayered architectures for engineering applications. In this technique, an aqueous ceramic suspension is solidified unidirectionally leading to phase separation into alternating layers of ice-crystals and ceramic particles. Ice-crystals are sublimated by freeze-drying process and resultant ceramic foams are sintered to impart strength. The fabricated sintered ceramic foams contain alternate layers of oriented ceramic lamella walls and pores. …