Engineering Commons^™

Buckling Behavior Of Thin Wall Stiffened Cylindrical Shells Through Ml Techniques, Fnu Tabish, Muhammad Hamza Karim, Rajesh Godasu, Iraj H.P Mamaghani

SDSU Data Science Symposium

Stiffened cylindrical shell buckling strength mainly depends on the geometric and stiffness properties. A detailed parametric study was conducted to investigate the influence of these properties on the stiffened aluminium cylindrical shell buckling strength. The proposed framework involves an integration of finite element method and various machine learning techniques. The dataset obtained from the eigenvalue buckling analysis of 350 numerical simulations using ANSYS workbench 2022; however, the FE simulation of ten ring-stiffened cylindrical specimens was initially substantiated by experimental work conducted in the literature. 350 sample specimens were categorized into seven groups based on the no. of stiffeners varying from …

Multimode Point Spectroscopy For Food Authentication, Sayed Asaduzzaman, Nicholas Mackinnon, Hossein Kashani Zadeh

SDSU Data Science Symposium

Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon …

Impulse, Fall 2023, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Students Thank Sung Shin
4 | Norma Nusz Chandler Never Says Never
6 | Gary Anderson Retires
8 | Three New Endowed Positions
9 | Muthu Endowed Department Head
10 | New Faculty and Staff
14 | Concrete Industry Management Program Online
16 | College Hosts Engineering Conference
17 | Viaflex Supports Research
18 | Lunar Exhibit at Children’s Museum
20 | Break the Ice Challenges
22 | Quarter-Scale Tractor Champions
24 | Nasa Contest Success
26 | Student Compete at Nationals
28 | Culver A Model of Consistency
30 | Engineering Gridders Honored
32 | Liam Murray …

Improving Decision Support Systems With Machine Learning: Identifying Barriers To Adoption, Skye Brugler, Maaz Gardezi, Ali Dadkhah, Donna M. Rizzo, Asim Zia, Sharon A. Clay

Agronomy, Horticulture and Plant Science Faculty Publications

Precision agriculture (PA) has been defined as a “management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” This definition suggests that because PA should simultaneously increase food production and reduce the environmental footprint, the barriers to adoption of PA should be explored. These barriers include: 1) the financial constraints associated with adopting DSS, 2) the hesitancy of farmers to change from their trusted advisor to a computer program often behaves …

A Deep-Learning Framework For Spray Pattern Segmentation And Estimation In Agricultural Spraying Systems, Praneel Acharya, Travis Burgers, Kim-Doang Nguyen

Mechanical Engineering Faculty Publications

This work focuses on leveraging deep learning for agricultural applications, especially for spray pattern segmentation and spray cone angle estimation. These two characteristics are important to understanding the sprayer system such as nozzles used in agriculture. The core of this work includes three deep-learning convolution-based models. These models are trained and their performances are compared. After the best model is selected based on its performance, it is used for spray region segmentation and spray cone angle estimation. The output from the selected model provides a binary image representing the spray region. This binary image is further processed using image processing …

Impulse, Spring 2023, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

Page 2| Dewey Rollag Remembered
Page 4| Basu to Develop Testing Platform
Page 5| Faculty News
Page 6| Targeted Donation Comes at Right Time
Page 8| SDSU Robotics Receives $10k Grant
Page 9| SDSU's Lunar Project Catches Eye of NASA Judges
Page 10| Mark Gronowski - The Balancing Act
Page 13| Matt Dentlinger - First Team Academic All American
Page 14| Jocelyn Tanner - Competitive On and Off the Pitch
Page 14| Student Success
Page 16| Electrical Engineering Students Top Peers
Page 18| College of Engineering Statistics
Page 20| Engineering Undergrads from Company
Page 22| Engineering a Family Affair for …

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 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 …

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 …

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, …

Extended Cross-Referenced Analysis Using Data From The Landsat 8 And 9 Underfly Event, Garrison Gross

Electronic Theses and Dissertations

The Landsat 8 and 9 Underfly Event occurred in November 2021, where Landsat 9 flew beneath Landsat 8 in the final stages before settling in its final orbiting path. An analysis was performed on the images taken during this event, which resulted in a cross-referenced with uncertainties estimated to be less than 0.5%. This level of precision was due in part to the near-identical sensors aboard each instrument as well as the underfly event itself, which allowed the sensors to take nearly the exact same image at nearly the exact same time. This initial calibration was applied before the end …

Full Body Harness Design Modifications And Evaluation: A Senior Design Project, Martin Mead, Jordan Von Seggern

The Journal of Undergraduate Research

Full-body harness (FBH) is critical for the safe operation of industrial and recreational activities, from installing and maintaining infrastructure such as wind turbines to ziplining and mountaintop adventures. However, harness design remains in the proprietary information of companies with limited technical information available for improvements or readjustments to specialized applications. As the outcome of the Capstone project, the paper focuses on multiple technical aspects and the engineering processes for designing FBH for ziplining recreational users, from selecting and testing materials for operation in cold weather to improvements in design and manufacturing for user comfort. The project is guided by technical …

The Impact Of Precipitation As An Adverse Weather Condition On Transportation Construction In South Dakota, Akosua Ofosua Okyere-Addo

Civil and Environmental Engineering Graduate Students Plan B Capstone Projects

This research assessed the impact of precipitation as an adverse weather condition on the transportation construction in South Dakota. A statistical survey of the data from the National Oceanic and Atmospheric Administration was conducted on 554 original stations, which was reduced to 433 stations of them were in South Dakota, then reduced to 170 stations with 30-year data coverage higher than 70 %. Eventually, the data were reduced further for pilot study purposes to a final 10 stations used for analysis in this study. The objective of this study is to examine potential precipitation thresholds towards determination of related adverse …

Mechanical Properties Evaluation Of 3d Printed Petg And Pctg Polymers, Kalpesh Krishnarao Bhosale

Electronic Theses and Dissertations

3D printing is also known as additive manufacturing (AM) which has become a popular manufacturing trend over the years. Due to its unique advantages of fast production rate, ability to create complex geometrical features, toolless manufacturing and many more attracts various industries from Aerospace to general cosmetics. Along with the advancement in material science, various polymers including Polylactic Acid (PLA), Polyethylene terephthalate glycol (PETG) and many more are available for 3D printing. Due to the wide range of applications in PLA, it is necessary to improve its toughness to make it more suitable by adding Poly Cyclohexylenedimethylene Terephthalate glycol (PCTG) …

Assessing The Economic Feasibility Of Capturing And Utilizing Carbon Dioxide From Ethanol Production In South Dakota, Makiah Stukel

Electronic Theses and Dissertations

Since the Industrial Revolution, anthropogenic greenhouse gas (GHG) emissions have spiked dramatically, prompting discussions on climate change. Mitigating climate change requires significant reductions in global carbon dioxide (CO2) emissions as CO2 is the most abundant anthropogenic GHG. A process that assists in offsetting the exponential growth in CO2 emissions is carbon capture and storage (CCS). Integrating carbon capture technology into the ethanol industry can provide an economically feasible way to achieve net reductions in CO2 emissions. The proposed work investigates the economic viability of applying CCS technologies to the 16 ethanol facilities in South Dakota (SD) and quantifies the potential …

Validation Of Expanded Trend-To-Trend Cross-Calibration Technique And Its Application To Global Scale, Ramita Shah

Electronic Theses and Dissertations

The expanded Trend-to-Trend (T2T) cross-calibration technique has the potential to calibrate two sensors in much less time and provides trends on daily assessment basis. The trend obtained from the expanded technique aids in evaluating the differences between satellite sensors. Therefore, this technique was validated with several trusted cross-calibration techniques to evaluate its accuracy. Initially, the expanded T2T technique was validated with three independent RadcaTS RRV, DIMITRI-PICS, and APICS models, and results show a 1% average difference with other models over all bands. Further, this technique was validated with other SDSU techniques to calibrate the newly launched satellite Landsat 9 with …

Probing Signal-Based Data-Driven Modeling Of Power Electronics Smart Converter Dynamics Using Power Hardware-In-The-Loop, Nischal Guruwacharya

Electronic Theses and Dissertations

The main objective of this dissertation is to develop a generalized simulation and modeling framework for extracting dynamics of power electronic converters (PECs) with grid support functions (GSFs) and validate model accuracy through experimental comparison with physical measurements. The dynamic models obtained from this modeling framework aim to facilitate accurate dynamic analysis of a highly integrated power system comprising inverter-based resources (IBRs), specifically for stability assessment. These dynamic models helped in reducing simulation time and computational complexity, thereby enhancing efficiency. Moreover, it provides valuable insights for utilities and grid operators involved in effective system planning, operation, and dispatch. The dynamics …

Simulating The Impact Of Emissions Control On Economic Productivity Using Particle Systems And Puff Dispersion Model, Najam Khan

Electronic Theses and Dissertations

A simulation platform is developed for quantifying the change in productivity of an economy under passive and active emission control mechanisms. The program uses object-oriented programming to code a collection of objects resembling typical stakeholders in an economy. These objects include firms, markets, transportation hubs, and boids which are distributed over a 2D surface. Firms are connected using a modified Prim’s Minimum spanning tree algorithm, followed by implementation of an all-pair shortest path Floyd Warshall algorithm for navigation purposes. Firms use a non-linear production function for transformation of land, labor, and capital inputs to finished product. A GA-Vehicle Routing Problem …

Effectiveness Of Atmospheric Cold Plasma In Inactivating Microorganisms, Nadee Shanika Kaluwahandi

Electronic Theses and Dissertations

In the food processing industry, Cold Plasma (CP) is an emerging green process with a number of potential applications. Cold plasma has mostly been used to reduce microbial counts in foodstuffs and biological materials as well as in different levels of packaging, particularly in cases where there is thermal sensitivity. Recent studies have demonstrated that CP technology is being developed for use in the food and agriculture industries. The primary focus is on the interactions between reactive species and food-borne microbes to inactivate them. The literature review discusses both proven and potential applications for cold plasma in food processing, as …

The Development Of Dark Hyperspectral Absolute Calibration Model Using Extended Pseudo Invariant Calibration Sites At A Global Scale: Dark Epics-Global, Padam Bahadur Karki

Electronic Theses and Dissertations

This research aimed to develop a novel dark hyperspectral absolute calibration (DAHAC) model using stable dark targets of "Global Cluster - 36" (GC-36), one of the clusters from "300 Class Global Classification." The stable dark sites were identified from GC-36 called "Dark EPICS-Global" covering the surface types viz; dark rock, volcanic area, and dark sand. The Dark EPICS-Global shows a temporal variation of 0.02 unit reflectance. This work uses the Landsat-8 (L8) Operational Land Imager (OLI) , Sentinel-2A (S2A) Multispectral Instrument (MSI) , and Earth Observing One (EO-1) Hyperion data for the DAHAC model development, where well-calibrated L8 and S2A …

Quantifying The Effects Of Hvac Operation To Mitigate Aerosol Concentration In A Classroom Using Cfd, Scott Deprez

Electronic Theses and Dissertations

Heating, ventilation, and air conditioning (HVAC) is a complex mechanical system for the transition of air between outdoor and indoor areas. These systems are directly responsible for temperature, humidity, and air flow into any given space, thereby providing a level of comfort to those who live indoors. These systems account for 52 percent of U.S. energy consumption. When designing HVAC systems, indoor air quality (IAQ) is the main focus for achieving safe and clean air, such as in the case of airborne diseases. HVAC systems are responsible for the flow of air in indoor spaces and thereby expand the transmissible …

Development Of Corn Kernel-Based Biocomposite Films For Food Packaging Applications, Swastika Bera

Electronic Theses and Dissertations

Most of the current and active food packaging resources and methods are nonbiodegradable and nonrenewable therefore harmful to the environment. Due to this, alternate sources of food packaging materials are in high demand. In this study, a bio-composite film has been developed, with Corn kernel powder as fiber reinforcement which is mixed with gelatin, and lignin two biopolymers as the matrix. The effect of Corn Kernel (CK) reinforcement on the Gelatin/Lignin (G/L) matrix on mechanical and barrier properties has been studied. CK has shown great potential as reinforcement to natural polymer, gelatin, and lignin (G/L) for food packaging applications as …

Multiscale Evaluation Of The Effect Of Deicing Agents And Environmental Conditions On The Performance Of Asphalt Pavements In Cold Regions, Maryam Mihandoust

Electronic Theses and Dissertations

More than 70% of the United States' roadway network is located in regions subjected to severe winters, resulting in icy pavements that pose safety risks. Winter maintenance operations involving chloride-based deicers such as NaCl, CaCl2, and MgCl2 are essential for ensuring the safety, mobility, and functionality of roads. However, these deicers can lead to diminished pavement durability due to moisture-induced damage. This study examined the effects of these deicers on adhesion evolution and moisture-induced damage mechanisms of asphalt binder-aggregate systems at the macro-, centi-, micro-, and nanoscales. Macro-scale performance characteristics of PG 58-34 hot mix asphalt (HMA) specimens, including rutting, …

Evaluating The Impact Of Increased Cycling On Thermal Power Plants Due To Wind Energy Penetration In The Midwest: A Case Study, Joscelyne Larson

Electronic Theses and Dissertations

One of the most significant shifts in the mix of U.S. electricity generation over the past few years has been the rapid expansion of renewable energy resources, especially solar and wind. However, fossil fuels are still necessary to fulfill the world’s energy requirements. Despite efforts to increase the use of renewable energy sources, these sources can be at times unreliable, causing countries around the world to continue to rely on base load units such as coal and natural gas. This decrease in fossil fuels and increase in renewable energy sources presents many complex issues in terms of power system planning, …

An Analysis Of The Effect Of Temperature On Asphalt Paving In South Dakota, S M Rahat Rashedi

Electronic Theses and Dissertations

Temperature is an important parameter to consider for asphalt paving since this work is generally susceptible to weather due to outdoor construction. The South Dakota Department of Transportation (SDDOT) developed working day weather charts in 1998 to address the expected adverse weather days. This thesis investigated the effect of temperature on adverse weather days for asphalt paving and compared them to the value reported in the 1998 SDDOT study. Moreover, the thesis also examined how closely the maximum temperature data from project sites' weekly progress reports (WPR) matched the data from the closest weather stations. When the maximum temperature (TMAX) …

Response Of Bed Shear Stress In Open-Channel Flow To A Sudden Change In Bed Roughness, Muhammad Farrukh Jamil

Electronic Theses and Dissertations

The estimation of bed shear stress plays a pivotal role in understanding the complexities of flow dynamics in both natural and engineered channels. The commonly employed log law formula offers a mechanism to compute the bed shear stress in open channel flows. However, its applicability in flow transition remains relatively unexplored. In this thesis, an in-depth investigation into the behavior of the velocity profiles and bed shear stress during the transition from Rough to Smooth (RTS) and Smooth to Rough (STR) beds is undertaken. Experiments were conducted on smooth-to-rough (STR) and rough-to-smooth (RTS) transitions in an open channel flume under …