Engineering Commons^™

Atomistic Simulation Studies Of Thin Film Growth And Plastic Deformation In Metals And Metal/Ceramic Nanostructures, Reza Namakian

LSU Doctoral Dissertations

Despite the significant improvements in manufacturing and synthesis processes of metals and ceramics in the past decades, there are still areas in which the procedure is still frequently more of an art or skill rather than a science. Therefore, systematic and combined experimental and computational studies are required to facilitate the development of techniques that offer thorough understanding of the events taking place during manufacturing and synthesis processes. With regard to these issues, it is paramount to address microscale characterizations and atomic scale understanding of the events during fabrication processes. One of the focuses of this study is unraveling fundamental …

Deutj: An Imagej Plugin For Improved Automatic Masking And Segmentation Of Images From Confocal Microscopy, Sunny Cui

Independent Student Projects and Publications

Due to advances in microscopic imaging, there are a plethora of biological molecules that can now be tagged and subsequentially imaged from almost any cell, organism, or tissue. However, the ability of software to analyze these images remains to be a challenge. ImageJ is open source software that allows for the processing of these images, but faces challenges when dealing with images that show weak contrast between objects of interest and background. DeutJ is an ImageJ plugin that color corrects and brightness corrects gradients that inhibit segmentation in confocal microscopy images. It can analyze hundreds of images from a given …

Study Of The Graphene Energy Absorbing Layer And The Viscosity Of Sodium Alginate In Laser-Induced- Forward-Transfer (Lift) Bioprinting, Shuqi Zhou, Jianzhi Li, Ben Xu

Manufacturing & Industrial Engineering Faculty Publications

Laser induced forward transfer (LIFT) bioprinting has been viewed as a new and actively developed three-dimensional bioprinting technology due to its high accuracy and good cell viability. The printing quality is highly dependent on the jet formation and its stability in the LIFT bioprinting process. The objective of this study is to investigate the effect of a graphene Energy Absorbing Layer (EAL) and alginate hydrogel (SA) (w.t. 1% and 2%) viscosity on jet generation in the LIFT bioprinting process. Since SA exhibits a shear-thinning behavior, it is a non-Newtonian fluid. The effect of EAL thickness and SA’s viscosity were addressed …

Creatively Making Through Failure, Spencer W. Ashnault

CAFE Symposium 2023

This work of art is a 3D Map of Rome, Italy that uses laser cutting and 3D printing techniques to create. The project and technique is explained by the artist and author Spencer Ashnault.

On The Development And Evaluation Of A Framework For Brain-Computer Interface And Vibrotactile Feedback For Human-Robot-Interaction In Virtual Spaces And Robotic Hardware, Sudip Hazra, Shane Whitaker, Panos S. Shiakolas

Mechanical and Aerospace Student Research - Archive

Research in Brain-Computer Interface (BCI) aims to understand human intent with the goal to enhance Human-Robot Interaction (HRI) especially in the field of assistive robotics. The goal of this research is to develop a behavioral sequence based framework to help persons with upper limb disabilities to maintain self-dependence. The framework aims to operate in stages and links multiple functional components to identify human intent and control a robotic arm. The development, operation, and evaluation of the framework and the linked functional components to acquire, process, evaluate, and map BCI signals generated using facial expressions and head movements to predefined actions …

Graphene-Conductive Polymer-Based Electrochemical Sensor For Dopamine Detection, Dipannita Ghosh, Md Ashiqur Rahman, Ali Ashraf, Nazmul Islam

Electrical and Computer Engineering Faculty Publications

The central nervous system's (CNS) dopaminergic system dysfunction has been linked to neurological illnesses like schizophrenia and Parkinson's disease. As a result, sensitive and selective detection of dopamine is critical for the early diagnosis of illnesses associated with aberrant dopamine levels. In this research, we have investigated the performance of electrochemical screen-printed sensors for different concentrations of dopamine detection using graphene-based conductive PEDOT: PSS(G-PEDOT: PSS) and Polyaniline(GPANI) inks on the working electrode and compared the sensitivity. SEM characterization technique has been performed to visualize the microstructures of the proposed inks. We have investigated cyclic voltammetry (CV) electrochemical techniques with ferri/ferrocyanide …

Formulation Of Encapsulated Nanoparticles Of Leek Extract As Antimicrobial And Anticancer Agent, Rawan Hassan Mohamed Elghanam

Theses and Dissertations

Leek extract (LEK) has broad therapeutic activity. However, plant extract use has many drawbacks, which could be resolved using nanocarriers. The purpose of this research work was to prepare chitosan nanoparticles (CS NPs) encapsulating LEK and investigate their antioxidant, antimicrobial, and anticancer activity. Gas chromatography-mass spectroscopy was used to determine the LEK components. The CS-LEK NPs were produced by tripolyphosphate (TPP) crosslinking with chitosan (CS) the ionic gelation methodology. The particle size was 331 nm, zeta potential (ZP) was 28.9 mv, polydispersity index (PDI) was 0.4, encapsulation efficiency (EE) was 65.6%, and loading capacity (LC) was 28.8 % of the …

Estimation Of The Response, Power Spectra, And Whirling Patterns Generated From Mud Circulating Along The Annulus During Drilling Procedures: An Alternative Mathematical Representation Via Finite Element Modelling, Eleazar Marquez

Mechanical Engineering Faculty Publications

In this study, an alternative mathematical representation of a drill-string is proposed to provide an alternative assessment on BHA dynamic alterations. Lateral vibrations remain the focal point of drill-string breakdowns given their high frequency characterization and ability to deviate perforation trajectories from the subsurface target. In this paper, the proposed model consists of an anisotropic rotor subjected to distinct RPMs, an axial force, and a bidirectional harmonic excitation with specified amplitude and assorted duration to simulate annulus motion generated from the mud fluid. In this regard, Euler-Bernoulli beam theory was adopted to establish a complete MDOF mathematical expression and thus …

Development Of An Improved Mathematical Representation Which Captures The Nonlinear Dynamic Behavior Of A Drill-String Assembly, Eleazar Marquez

Mechanical Engineering Faculty Publications

In this study, an improved mathematical representation of a drill-string assembly is developed to provide an alternative assessment on vibration irregularities proliferating downhole due to bit-rock interference. Lateral vibrations receive particular attention due to their high frequency content which alter the dynamic response of the drill-string, instigate casing damage, and impede optimal penetration rates. The response of the drill-string is captured by synthesizing compatible stationary bit excitations, via an auto-regressive digital filter, and implementing Monte Carlo simulation, while the power spectral density function is approximated to elucidate the dynamic characteristics during drilling. Formulating adequate physical parameters for the equation of …

A Probabilistic Analysis In Vibration-Assisted Drilling To Measure Dynamic Behavior During Drilling And Understand Risk Factors, Eleazar Marquez, Samuel Garcia

Mechanical Engineering Faculty Publications

In this paper, a mathematical representation is proposed to further understand the dynamic behavior and risk factors associated with vibration-assisted drilling (VAD) technology. The proposed Timoshenko beam model, which characterizes VAD technology, consists of two passive, counter-rotating coaxial rotors operating simultaneously, subjected to a stochastic excitation. In this regard, a finite element technique was incorporated to determine the physical parameters of the governing equation of motion, where the shear and rotary effects, as well as the gyroscopic couples generated perpendicular to the axis of rotation, were accounted for. Further, the relative velocity between the coaxial rotors was accounted in the …

Quadcopter Control Using Single Network Adaptive Critics, Alberto Velazquez, Lei Xu, Tohid Sardarmehni

Mechanical Engineering Faculty Publications

In this paper, optimal tracking control is found for an inputaffine nonlinear quadcopter using Single Network Adaptive Critics (SNAC). The quadcopter dynamics consists of twelve states and four controls. The states are defined using two related reference frames: the earth frame, which describes the position and angles, and the body frame, which describes the linear and angular velocities. The quadcopter has six outputs and four controls, so it is an underactuated nonlinear system. The optimal control for the system is derived by solving a discrete-time recursive Hamilton-Jacobi-Bellman equation using a linear in-parameter neural network. The neural network is trained to …

Non-Destructive Infrared Thermographic Curing Analysis Of Polymer Composites, Md Ashiqur Rahman, Javier Becerril, Dipannita Ghosh, Nazmul Islam, Ali Ashraf

Mechanical Engineering Faculty Publications

Infrared (IR) thermography is a non-contact method of measuring temperature that analyzes the infrared radiation emitted by an object. Properties of polymer composites are heavily influenced by the filler material, filler size, and filler dispersion, and thus thermographic analysis can be a useful tool to determine the curing and filler dispersion. In this study, we investigated the curing mechanisms of polymer composites at the microscale by capturing real-time temperature using an IR Thermal Camera. Silicone polymers with fillers of Graphene, Graphite powder, Graphite flake, and Molybdenum disulfide (MoS₂) were subsequently poured into a customized 3D printed mold for …

Sagittal Plane Dynamic Model Using Tibiofemoral Articular Geometric Center And Experimental Tibiofemoral Center Of Rotation To Predict Joint Forces During Knee Extension Exercise, Jose Mario Salinas, Dumitru I. Caruntu

Mechanical Engineering Faculty Publications

A 2-dimensional anatomical dynamic model of the patellofemoral joint was developed for investigating the forces that contribute to patellar motion during the knee extension exercise. Sagittal bone profiles were aligned to kinematic experimental data to simulate bone motion. Kinematic experimental data was collected using VICON motion analysis system. Marker coordinate data was used to set body-fixed coordinate systems on femur and tibia. These body-fixed coordinate systems were used to drive the femur and tibia geometric profiles during the knee extension exercise. Kinematic experimental data was used to calculate the relative instant center of rotation of markers on tibia with respect …

Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, Kc Santosh

SDSU Data Science Symposium

In medical imaging informatics, for any future epidemics (e.g., Covid-19), deep learning (DL) models are of no use as they require a large dataset as they take months and even years to collect enough data (with annotations). In such a context, active learning (or human/expert-in-the-loop) is the must, where a machine can learn from the first day with minimum possible labeled data. In unsupervised learning, we propose to build pre-trained DL models that iteratively learn independently over time, where human/expert intervenes only when it makes mistakes and for only a limited data. In our work, deep features are used to …

Session 12: Analysis Of State And Parameter Estimation Techniques Using Dynamic Perturbation Signals, Timothy M. Hansen

SDSU Data Science Symposium

The trend in electric power systems is the displacement of traditional synchronous generation (e.g., coal, natural gas) with renewable energy resources (e.g., wind, solar photovoltaic) and battery energy storage. These energy resources require power electronic converters (PECs) to interconnect to the grid and have different response characteristics and dynamic stability issues compared to conventional synchronous generators. As a result, there is a need for validated models to study and mitigate PEC-based stability issues, especially for converter dominated power systems (e.g., island power systems, remote microgrids).

This presentation will introduce methods related to dynamic state and parameter estimation via the design …

Session 11: Can Machine Learning Predict Particle Deposition At Specific Intranasal Regions Based On Computational Fluid Dynamics Inputs/Outputs And Nasal Geometry Measurements?, Mohammad Mehedi Hasan Akash, Zachary Silfen, Diane Joseph-Mccarthy, Arijit Chakravarty, Saikat Basu

SDSU Data Science Symposium

Along with machine learning modeling, numerical simulations of respiratory airflow and particle transport can be used to improve targeted deposition at the upper respiratory infection site of numerous airborne diseases. Given the need for more patient data from varied demographics, we propose a machine learning-enabled protocol for determining optimal formulation design parameters that may match nasal spray device settings for successful drug delivery. We measured 11 anatomical parameters (including nasopharyngeal volume, nostril heights, and mid-nasal cavity volume) for 10 CT-based nasal geometries representative of the population for this aim. We also ran 160 computational fluid dynamics simulations of drug delivery …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Application Of Gaussian Mixture Models To Simulated Additive Manufacturing, Jason Hasse, Semhar Michael, Anamika Prasad

SDSU Data Science Symposium

Additive manufacturing (AM) is the process of building components through an iterative process of adding material in specific designs. AM has a wide range of process parameters that influence the quality of the component. This work applies Gaussian mixture models to detect clusters of similar stress values within and across components manufactured with varying process parameters. Further, a mixture of regression models is considered to simultaneously find groups and also fit regression within each group. The results are compared with a previous naive approach.

Spatial Data Analysis For The Development Of Expected Adverse Weather Charts For Transportation Construction Projects, S M Rahat Rashedi, Akosua Ofosua Okyere-Addo

SDSU Data Science Symposium

Problem - Seasonal and daily weather events impact construction projects across the various climate regions of South Dakota in differing fashions. Additionally, the impacts for similar weather events can impact grading, surfacing, and structural construction activities in various ways. Adverse weather conditions can cause major delays which may lead to time extensions and increase project cost.

Purpose – To address these issues, South Dakota Department of Transportation (SDDOT) developed Working Day Weather Charts in 1998. However, advances in construction practices and weather prediction as well as climatic changes have occurred over the interim 25 years. This study is focused on …

Spatial Data Analysis For Traffic Safety Network Screening, Akosua Okyere-Addo, S. M. Rahat Rashedi

SDSU Data Science Symposium

Problem - The roadway system represents a major investment, both public and private, and a valuable resource that enables mobility and accessibility to users. Due to degradation of aging infrastructure and increasing traffic, transportation agencies are seeking to effectively update or improve the system. With rising costs, tight budgets, and limited land resources, agencies are seeking effective techniques for identifying critical mobility and safety concerns. Historically, assignment of crashes to portions of the network, whether segments or intersections, has been the primary manner to link crash and road elements.

Purpose – The primary goal is to explore a potentially more …

Session 2: The Effect Of Boom Leveling On Spray Dispersion, Travis A. Burgers, Miguel Bustamante, Juan F. Vivanco

SDSU Data Science Symposium

Self-propelled sprayers are commonly used in agriculture to disperse agrichemicals. These sprayers commonly have two boom wings with dozens of nozzles that disperse the chemicals. Automatic boom height systems reduce the variability of agricultural sprayer boom height, which is important to reduce uneven spray dispersion if the boom is not at the target height.

A computational model was created to simulate the spray dispersion under the following conditions: a) one stationary nozzle based on the measured spray pattern from one nozzle, b) one stationary model due to an angled boom, c) superposition of multiple stationary nozzles due an angled boom, …

Identification Of Volatile Organic Liquids By Combining An Array Of Fiber-Optic Sensors And Machine Learning, Wassana Naku, Anand K. Nambisan, Muhammad Roman, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Report an Array of Fiber-Optic Sensors based on the Fabry-Perot Interference Principle and Machine Learning-Based Analyses for Identifying Volatile Organic Liquids (VOLs). Three Optical Fiber Tip Sensors with Different Surfaces Were Included in the Array of Sensors to Improve the Accuracy for Identifying Liquids: An Intrinsic (Unmodified) Flat Cleaved Endface, a Hydrophobic-Coated Endface, and a Hydrophilic-Coated Endface. the Time-Transient Responses of Evaporating Droplets from the Optical Fiber Tip Sensors Were Monitored and Collected Following the Controlled Immersion Tests of 11 Different Organic Liquids. a Continuous Wavelet Transform Was Used to Convert the Time-Transient Response Signal into …

Accessible Methods, Novel Arrangement: Developing Self-Centering Composite Structural Frame Systems For Highly Resilient Buildings, Emma Rae Kratz-Bailey

Undergraduate Honors Theses

The benefits of self-centering systems for increasing building resilience are well documented and widely known. These systems are added to buildings to bring them back to “plumb,” or upright, position in the event of an extreme event. Benefits of their use are thus most notably that self-centering systems cut down on the repair, downtime, and/or demolition costs incurred after a structure encounters an extreme event. However, they are sometimes not used due to higher up-front costs incurred by the use of unconventional materials, methods, and construction details. This study developed a self- centering frame system that builds on established methods …

Symmetric Equations For Evaluating Maximum Torsion Stress Of Rectangular Beams In Compliant Mechanisms, Guimin Chen, Larry L. Howell

Faculty Publications

There are several design equations available for calculating the torsional compliance and the maximum torsion stress of a rectangular cross-section beam, but most depend on the relative magnitude of the two dimensions of the cross-section (i.e.,the thickness and the width). After reviewing the available equations, two thickness-to-width ratio independent equations that are symmetric with respect to the two dimensions are obtained for evaluating the maximum torsion stress

of rectangular cross-section beams. Based on the resulting equations, outside lamina emergent torsional joints are analyzed and some useful design insights are obtained. These equations, together with the previous work on symmetric equations …

Membrane-Enhanced Lamina Emergent Torsional Joints For Surrogate Folds, Guimin Chen, Spencer P. Magleby, Larry L. Howell

Faculty Publications

Lamina emergent compliant mechanisms (including origami-adapted compliant mechanisms) are me- chanical devices that can be fabricated from a planar material (a lamina) and have motion that emerges out of the fabrication plane. Lamina emergent compliant mechanisms often exhibit undesirable para- sitic motions due to the planar fabrication constraint. This work introduces a type of lamina emergent torsion (LET) joint that reduces parasitic motions of lamina emergent mechanisms (LEMs), and presents equations for modeling parasitic motion of LET joints. The membrane joint also makes possible one-way joints that can ensure origami-based mechanisms emerge from their flat state (a change point) into …

Impact Of Population Based Indoor Residual Spraying With And Without Mass Drug Administration With Dihydroartemisinin-Piperaquine On Malaria Prevalence In A High Transmission Setting: A Quasi-Experimental Controlled Before-And-After Trial In Northeastern Uganda, Richard C. Elliott

Materials Science and Engineering Faculty Publications and Presentations

Background: Declines in malaria burden in Uganda have slowed. Modelling predicts that indoor residual spraying (IRS) and mass drug administration (MDA), when co-timed, have synergistic impact. This study investigated additional protective impact of population-based MDA on malaria prevalence, if any, when added to IRS, as compared with IRS alone and with standard of care (SOC).

Methods: The 32-month quasi-experimental controlled before-and-after trial enrolled an open cohort of residents (46,765 individuals, 1st enumeration and 52,133, 4th enumeration) of Katakwi District in northeastern Uganda. Consented participants were assigned to three arms based on residential subcounty at study start: MDA+IRS, IRS, SOC. IRS …

Applications Of Underbalanced Fishbone Drilling For Improved Recovery And Reduced Carbon Footprint In Unconventional Plays, Habib Ouadi, Siamak Mishani, Vamegh Rasouli

Petroleum Engineering Student Publications

Fishbone Drilling (FbD) consists of drilling several micro-holes in different directions from the main vertical or deviated wellbore. Similar to multilateral micro-hole drilling, FbD may be used to enhance hydrocarbon production in naturally fractured formations or in refracturing operations by interconnecting the existing natural fractures. When combined with underbalanced drilling using a coiled tubing rig, FbD enhances the production further by easing the natural flow of the hydrocarbon from the reservoir to the wellbore. The design aspects of the Fishbones include determining the number, length, distance between the branches, and the angle of sidetracking of the branches from the main …

Neural Network Flow Optimization Using An Oscillating Cylinder, Meihua Zhang, Zhongquan Charlie Zheng, Yangliu Liu, Xiaoyu Jiang

Mechanical and Aerospace Engineering Student Publications and Presentations

Flow behaviors of a downstream object can be affected significantly by an upstream object in close proximity. Combined with the neural network algorithms, this concept is used for flow control in this study to optimize the aerodynamic performance of a downstream object. Flow with an oscillating cylinder placed upstream is systematically studied because there are multiple control parameters that influence the flow dynamics around the downstream object. These control parameters are used as the input factors of a back-propagation neural network, and then a revised genetic algorithm is applied to find the optimal set of control parameters. In the current …

Therapeutic Options For Covid-19: Drug Repurposing Of Serine Protease Inhibitor Against Tmprss2, Mohammad Wildan Abiyyi, Surya Dwira, Arleni Bustami, Linda Erlina

Indonesian Journal of Medical Chemistry and Bioinformatics

The SARS-Coronavirus 2 (SARS-CoV-2) outbreak is a serious global public health threat. Researchers around the world are conducting mass research to control this epidemic, starting from the discovery of vaccines, to new drugs that have specific activities as antivirals. Drug repurposing is a potential method of using drugs with known activity for reuse as COVID-19 therapy. This method has the advantage that it can reduce costs and also the duration in the development of potential drugs. The initial step in drug repurposing can be done computationally to determine the effectiveness and specificity of the drug on the target protein. Molecular …

Halloysite Reinforced Natural Esters For Energy Applications, Jaime Taha-Tijerina, Karla Aviña, Victoria Padilla-Gainza, Aditya Akundi

Informatics and Engineering Systems Faculty Publications

Recently, environmentally friendly and sustainable materials are being developed, searching for biocompatible and efficient materials which could be incorporated into diverse industries and fields. Natural esters are investigated and have emerged as eco-friendly high-performance alternatives to mineral fluids. This research shows the evaluations on thermal transport and tribological properties of halloysite nanotubular structures (HNS) reinforcing natural ester lubricant at various filler fractions (0.01, 0.05, and 0.10 wt.%). Nanolubricant tribotestings were evaluated under two configurations, block-on-ring, and 4-balls, to obtain the coefficient of friction (COF) and wear scar diameter (WSD), respectively. Results indicated improvements, even at merely 0.01 wt.% HNS concentration, …