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Articles 1 - 30 of 595
Full-Text Articles in Engineering
Impulse, Spring 2024, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering
Impulse, Spring 2024, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering
Impulse (Jerome J. Lohr College of Engineering Publication)
2 | Kurt Cogswell Retirement
4 | Nadim Wehbe Retirement
6 | George Hamer Retirement
8 | Basu Receives Career Award
9 | New Faculty
10 | Celebration of Faculty Excellence
11 | Lohr College of Engineering Awards
12 | Vern Schaefer Distinguished Engineer
14 | Mike Headley Distinguished Engineer
16 | Transportation Center Funding
18 | SDSU Welcomes Papua New Guinea Students
21 | Robotics Team Going to World Competition
22 | Engineering Students in Fine Arts
24 | By the Numbers
26 | Concrete Program’s First Graduate
28 | Noah Nielsen Headed to U.S. Space Force
30 | …
Buckling Behavior Of Thin Wall Stiffened Cylindrical Shells Through Ml Techniques, Fnu Tabish, Muhammad Hamza Karim, Rajesh Godasu, Iraj H.P Mamaghani
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
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 …
Assessing The Performance And Cost Effectiveness Of Rainwater Harvesting For High Tunnel Production Across Climates In The Continental United States, Mustafa Aydogdu
Assessing The Performance And Cost Effectiveness Of Rainwater Harvesting For High Tunnel Production Across Climates In The Continental United States, Mustafa Aydogdu
Electronic Theses and Dissertations
Several factors such as global climate change, population growth, urban and agricultural expansion, rising water demand, unequal water distribution, hydro-political conditions, declining water quality, rainwater scarcity, and temperature-induced drought contribute to water resource degradation. Rainwater harvesting (RWH) emerges as a sustainable solution, involving the collection and storage of rainwater for agriculture, livestock, and domestic use. RWH reduces reliance on municipal water, mitigates climate change impacts, and decreases runoff. Conventional RWH systems in the US vary in effectiveness. Increasing storage and water use enhances RWH effectiveness, improving stormwater runoff and reducing potable water use. High tunnel production of vegetable crops has …
Development Of Innovative Flocculation Technologies For Agricultural Water Treatment, Noor Haleem
Development Of Innovative Flocculation Technologies For Agricultural Water Treatment, Noor Haleem
Electronic Theses and Dissertations
The development of innovative flocculation technologies is essential for addressing the challenges of agricultural water treatment. These technologies play a crucial role in removing contaminants such as suspended solids and nutrients, thereby ensuring safer water for irrigation and livestock consumption. By enhancing water quality and wastewater management, they contribute significantly to environmental sustainability and public health in agricultural communities. This comprehensive thesis extensively explores various dimensions of flocculation, with a focused effort on methodologies and resources aimed at strengthening sustainability and efficiency. A pivotal aspect of the research involves synthesizing cationic starch (CS), a flocculant derived from an underutilized resource, …
Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang
Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang
Electronic Theses and Dissertations
Graphene, a prevalent anode material in commercial lithium-ion batteries, has reached its theoretical capacity limit. The imperative is to develop high-capacity anode materials to meet the growing demand for energy density. Lithium metal, renowned for its exceptionally high theoretical specific capacity density (3680 mAh g-1) and low reduction potential (-3.04 V, relative to the standard hydrogen electrode), is commonly dubbed the "Holy Grail" for negative electrode materials in high-energy-density batteries. However, practical advancements in lithium metal anodes face obstacles like low Coulombic efficiency, limited cycle life, and heightened reactivity to the electrolyte and internal short circuits resulting from lithium dendrite …
Advancing Biological Applications Through Microfluidic-Based Tool Development, K.M. Taufiqur Rahman
Advancing Biological Applications Through Microfluidic-Based Tool Development, K.M. Taufiqur Rahman
Electronic Theses and Dissertations
This research undertook an interdisciplinary approach, integrating bioengineering, microbiology, molecular biology, and systems biology to investigate bacterial dynamics behavior. Specifically, it delved into the development of microfluidic devices for biological applications such as bacterial cell counts, real-time observation of plant roots (here, specialized lectin-coated microbeads are used that mimic root characteristics), and soil microbe interactions. Furthermore, Next-Generation Sequencing and systems biology methodologies were employed to explore the intricate, multifaceted survival mechanisms of Escherichia coli persister population. Studying and quantifying persisters or testing for the existence of VBNC (viable but nonculturable) is challenging. These experiments require precise counts. It has been …
Developing Machine Learning Models For Selection Of Management Zones, Sravanthi Bachina
Developing Machine Learning Models For Selection Of Management Zones, Sravanthi Bachina
Electronic Theses and Dissertations
Soil sampling and analyses play a crucial role in optimizing nutrient management and enhancing crop productivity. However, collecting representative samples across diverse landscapes is challenging due to knowledge gaps about spatial variability of soil properties, large fields, multiple samples, and analysis costs. Collecting soil samples based on the management zones can help farmers gather precise information about soil properties with fewer samples. Recent developments in precision agriculture and machine learning. This study aimed to develop machine learning models that can learn, analyze, and refine landscape and soil properties data for automated selection of soil sampling zones and generating prediction maps. …
Removal Of Phosphorous, Copper And Zinc From Stormwater Using Powdered Activated Carbon (Pac) Based Water Treatment Residuals, Foysol Mahmud
Removal Of Phosphorous, Copper And Zinc From Stormwater Using Powdered Activated Carbon (Pac) Based Water Treatment Residuals, Foysol Mahmud
Electronic Theses and Dissertations
The main aim of this research was to evaluate the efficacy of Powdered Activated Carbon (PAC) based water treatment residual (WTR) in eliminating phosphorus (P), Copper (Cu), and Zinc (Zn) from stormwater. The characteristics of the PAC WTR were analyzed, and a series of batch and column tests were conducted to determine its capacity to remove P, Cu, and Zn from stormwater and synthetic solutions. The PAC WTR conformed to the Langmuir isotherm model, demonstrating P adsorption capacities of 3.51 mg/g at pH 5. Regarding Cu and Zn removal, the PAC WTR also adhered to the Langmuir isotherm model, showing …
Evaluation Of Aashto Seismic Design For Reinforced Concrete Bridge Columns, Andrew Leroy Grismer
Evaluation Of Aashto Seismic Design For Reinforced Concrete Bridge Columns, Andrew Leroy Grismer
Electronic Theses and Dissertations
Bridge failure can be catastrophic resulting in casualties and limiting the accessibility and emergency response efforts. Ensuring a high level of ductility for bridge columns through sufficient design methods and detailing is the most important aspect of the modern seismic codes. Reinforced concrete (RC) bridge columns are widely used in multi-span bridges located in seismic regions of the nation due to their controlled ductility and durability. The objective of this study was to systematically evaluate the AASHTO seismic design requirements for RC bridge columns and to comment on whether current bridge code is sufficient and safe. An extensive literature review …
Impulse, Fall 2023, Jill Fier, Micayla Standish, Jerome J. Lohr College Of Engineering
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
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
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, 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
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
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
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
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
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
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
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
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
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 …
The Impact Of Precipitation As An Adverse Weather Condition On Transportation Construction In South Dakota, Akosua Ofosua Okyere-Addo
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
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) …
Development Of Corn Kernel-Based Biocomposite Films For Food Packaging Applications, Swastika Bera
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 …
Assessing The Economic Feasibility Of Capturing And Utilizing Carbon Dioxide From Ethanol Production In South Dakota, Makiah Stukel
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
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
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 …