Engineering Commons^™

Naturally Occurring Van Der Waals Heterostructure Lengenbachite With Strong In-Plane Structural And Optical Anisotropy, Arindam Dasgupta, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Lengenbachite is a naturally occurring layered mineral formed with alternating stacks of two constituent PbS-like and M₂S₃-like two-dimensional (2D) material layers due to the phase segregation process during the formation. Here, we demonstrate to achieve van der Waals (vdW) heterostructures of lengenbachite down to a few layer-pair thickness by mechanical exfoliation of bulk lengenbachite mineral. The incommensurability between the constituent isotropic 2D material layers makes the formed vdW heterostructure exhibit strong in-plane structural anisotropy, which leads to highly anisotropic optical responses in lengenbachite thin flakes, including anisotropic Raman scattering, linear dichroism, and anisotropic third-harmonic generation. Moreover, …

Investigating Anisotropic Blast Wave Parameters Near The Explosive-Air Boundary Using Computer Simulation And Experimental Techniques With Varying Charge Geometry, Kelly Williams, Catherine E. Johnson

Mining Engineering Faculty Research & Creative Works

The prediction of blast wave overpressure using scaled distance calculations use the charge mass and radial distance variables and assumes that the blast wave is isotropic. Simulations and empirical studies demonstrate that altering the charge geometry results in a significant deviation in overpressure vs orientation. While this effect has been measured for cylinders, truncated cones, and cubes, the mechanisms driving geometric blast wave product anisotropy have not been well defined. Velocity vectors plotted from computer simulations in this study show an isotropic radial flow from the cylindrical charges, while the prismatic charges with rectangle, triangle, and five-point star cross sections …

Multimodal Ensemble Deep Learning To Predict Disruptive Behavior Disorders In Children, Sreevalsan S. Menon, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Oppositional defiant disorder and conduct disorder, collectively referred to as disruptive behavior disorders (DBDs), are prevalent psychiatric disorders in children. Early diagnosis of DBDs is crucial because they can increase the risks of other mental health and substance use disorders without appropriate psychosocial interventions and treatment. However, diagnosing DBDs is challenging as they are often comorbid with other disorders, such as attention-deficit/hyperactivity disorder, anxiety, and depression. In this study, a multimodal ensemble three-dimensional convolutional neural network (3D CNN) deep learning model was used to classify children with DBDs and typically developing children. The study participants included 419 females and 681 …

Machine Learning Identifies Liquids Employing A Simple Fiber-Optic Tip Sensor, Wassana Naku, Chen Zhu, Anand K. Nambisan, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We proposed an extremely simple fiber-optic tip sensor system to identify liquids by combining their corresponding droplet evaporation events with analyses using machine learning techniques. Pendant liquid droplets were suspended from the cleaved endface of a single-mode fiber during the experiment. The optical fiber-droplet interface and the droplet-air interface served as two partial reflectors of an extrinsic Fabry-Perot interferometer (EFPI) with a liquid droplet cavity. As the liquid pendant droplet evaporated, its length diminished. A light source can be used to observe the effective change in the net reflectivity of the optical fiber sensor system by observing the resulting optical …

Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.

Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and …

Analysis Of Energy Utilization And Losses For Jet-Propelled Vehicles, Mohammad Abbas, David W. Riggins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The global control volume-based energy utilization balance for an aerospace vehicle is extended to allow for the analysis of jet-propelled vehicles. The methodology is first developed for analyzing the energy utilization and entropy generation characteristics of jet engines without airframe considerations. This methodology, when combined with separate energy utilization analysis for an unpowered airframe, allows for the assessment of a powered vehicle. Wake entropy generation for a powered vehicle is shown to be the summation of the wake entropy generation associated with the propulsion system (no airframe) and the unpowered airframe. The fundamental relationship between overall entropy generation and the …

Aiche Virtual Communities Of Practice – Supporting Faculty During The Covid-19 Pandemic, Christi L. Patton (Luks)

Chemical and Biochemical Engineering Faculty Research & Creative Works

In response to the COVID-19 pandemic, chemical engineering departments from around the world shifted their course offerings from in-person to online almost instantaneously. The AIChE Education Division immediately responded to this educational shift by developing five Virtual Communities of Practice (VCPs) that allowed faculty to share experiences and best practices as well as provide a network for emotional support. Community creation, methods and materials shared, and surveys related to the impact of this initiative will be discussed.

Newmark-Type Pseudo-Three-Dimensional Back-Analysis Of Co-Seismic Landslides In Egkremnoi, Lefkada, Greece, Weibing Gong, Dimitrios Zekkos, Marin Clark, Dalia Kirschbaum

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

A pseudo-three-dimensional (pseudo-3D) methodology to back-analyze coseismic landslides was developed and applied to 68 mapped landslides, which occurred over approximately 1 km2area in Egkremnoi, Greece, during the 2015 Mw6.5 Lefkada earthquake. The methodology is based on a one-dimensional (1D) Newmark-type sliding block model to assess instability and a spatial projection in 3D topography to derive landslide geometry. The strength parameters for modeled landslides that best match the landslide location, area, and volume were derived through an iterative scheme that optimizes the match using predefined matching criteria. The range of different-sized landslides produced shear strength estimates from ~10 to 300 kPa …

Human-Human Hand Interactions Aid Balance During Walking By Haptic Communication, Mengnan Wu, Luke Drnach, Sistania M. Bong, Yun Seong Song, Lena H. Ting

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x …

Ulmus Rubra, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Abies Nordmanniana, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Acer Ginnala, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Aesculus Chinensis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Aesculus Hippocastanum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Buxus Sempervirens, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Carpinus Betulus, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Carpinus Caroliniana, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Carya Glabra, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Castanea Dentata, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cercidiphyllum Japonicum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cercis Canadensis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Chamaecyparis Pisifera, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Chionanthus Virginicus, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cinnamomum Camphora, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cinnamomum Japonicum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cladrastis Lutea, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cotoneaster Horizontalis, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Crataegus Laevigata, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Crataegus Phaenopyrum, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.

Cydonia Oblonga, Viraj Kishorkumar Gajjar, Anand Nambisan, Kurt Louis Kosbar

Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images

No abstract provided.