Digital Commons Network^™

Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova

Chemical Technology, Control and Management

The issues of constructing an adaptive joint estimation of the state and parameters of dynamic control objects using the Maine estimator are considered. There are various variants of the extended filter, and a variant based on iterations between parameter and state estimates was used in the work. In this version of the extended Kalman filter, the problem of joint parameter and state estimation is solved in such a way that parameter estimation is performed before state estimation. Then, the parameter values are used to assess the state. In this case, further iterations between the state vector estimation and the parameter …

Determination Of Chemical And X-Ray Phase Analysis Of Carbon-Containing Material, Sh.T. Juraev, B.F. Muxiddinov, U.T. Tailakov

Chemical Technology, Control and Management

This paper presents a chemical and X-ray diffraction study of the solid fraction obtained from the thermal-oxidative pyrolysis of waste tires. The study covers the analysis of the composition of rubber products before and after pyrolysis at a temperature of 750-850 °C. A chemical analysis of the gaseous, liquid and solid phases of pyrolysis products was also carried out. The ignition temperatures of gaseous products, their percentage content, as well as the optimal boiling temperatures of the resulting condensates were determined. X-ray analysis showed that the solid carbon residue consists of calcite (7.50%), amorphous carbon (87.24%), ankerite (Ca(Mg, Fe)[CO_{3 …}

Dеvеlоpmеnt Аnd Simulаtiоn Оf Аutоmаtiс Tеmpеrаturе Соntrоl Sуstеms Fоr Sоlаr Drуеrs, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Komil Usmanov

Chemical Technology, Control and Management

Thе utilizаtiоn оf sоlаr еnеrgу in thе drуing оf аgriсulturаl prоduсts is соnsidеrеd signifiсаnt duе tо its еnеrgу еffiсiеnсу аnd еnvirоnmеntаl friеndlinеss. Hоwеvеr, trаditiоnаl drуing mеthоds fасе сhаllеngеs in mаintаining stаblе tеmpеrаturе аnd humiditу lеvеls, whiсh саn lеаd tо rеduсеd prоduсt quаlitу аnd dесrеаsеd prосеss еffiсiеnсу. Tо аddrеss thеsе issuеs, thе implеmеntаtiоn оf аutоmаtiс соntrоl sуstеms is еssеntiаl. In dеvеlоping аn аutоmаtiс tеmpеrаturе соntrоl sуstеm fоr sоlаr drуеrs, thе hеаt аnd mаss trаnsfеr prосеssеs wеrе prесisеlу mоdеlеd. Thе primаrу pаrаmеtеrs оf thе drуing prосеss, suсh аs prоduсt tеmpеrаturе аnd mоisturе соntеnt dуnаmiсs, wеrе еxprеssеd thrоugh mаthеmаtiсаl еquаtiоns. PID аnd Fuzzу …

Investigation Of Dynamic Characteristics Of New Magneto-Elastic Transducers Of Mechanical Quantities, Sulton Amirov, Kamila Jurayeva

Chemical Technology, Control and Management

In the article examines the dynamic characteristics of new magnetically elastic converters of mechanical quantities by the method of parametric structural circuits. It is shown that the developed differential transformer magneto–elastic converters of power parameters in automatic monitoring and control systems act as a real differentiating link without statics, and magneto-elastic converters of motion parameters act as a whole in the form of sequentially connected oscillatory and real differentiating links. It has been established that the duration of the transient process in magnetoelastic converters of power parameters is determined by the parameters (magnetic capacitance and active magnetic resistance) of the …

Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov

Chemical Technology, Control and Management

This article is devoted to the study of the modeling process of analog-to-digital converters (ADCs) that process signals, one of the main parts of control system elements and devices. As we know, ADCs are an important part of modern control systems. During the research, the main stages of analog signal conversion were analyzed, i.e. discretization, quantization, coding. A classification of analog-to-digital conversion methods was made and the advantages and disadvantages of each were identified. Also, the characteristics and parameters of ADC were studied, their impact on ADCs performance was evaluated, and it was determined that certain characteristics should be taken …

Principles And Models Of Construction Of Linear Motion Actuators With Holonomic Structure For Intelligent Robot Movement, Matyokubov Nurbek Rustamovich, Temurbek Omonboevich Rakhimov, Yusupov Bekmurod Bayotovich

Chemical Technology, Control and Management

This article is devoted to the principles and models of building linear motion actuators with holonomic structure for the movement of intelligent robots. Also, the classification of the elements of the linear movement performance according to their interconnections and technical characteristics, taking into account their physical characteristics, was seen. A morphological matrix of the construction of holonomic structured linear motion performance elements based on the classification according to the considered technical specifications is presented. The given morphological matrix of linear motion actuators serves to develop new actuators for intelligent mechatronic and robotic systems. Based on the morphological matrix of the …

Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza

Chemical Technology, Control and Management

This study explores the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling wastewater treatment processes using ion-exchange resins. It addresses the critical challenges of water scarcity and pollution by enhancing the regulation of water hardness (H) and Total Dissolved Solids (TDS). Using a pilot laboratory device and experimental data from the mixed wastewater of the Kungrad Soda Plant in Uzbekistan, an ANFIS model was developed in MATLAB to automate process control. The model leverages water hardness and TDS as input parameters to regulate the water flow rate by servo valve opening degree, ensuring precise and efficient treatment. Compared …

Methods For Detecting Anomalies In Network Traffic Based On One-Class Svm Technology, Komil Kerimov, Sardor Kurbanov, Zarina Azizova

Chemical Technology, Control and Management

This article is dedicated to the research and application of the One-Class Support Vector Machines method for detecting anomalies in network traffic. It examines the problems of detecting anomalies in network traffic and proposes a methodology for using One-Class SVM, including an overview of the main concepts and formulas of the algorithm. A discussion of the results of One-Class SVM is presented, including interpretation, advantages, limitations and possible directions for development of the proposed technique, as well as the practical significance of using the proposed method for detecting anomalies in network traffic.

A Multi-Model And Multi-Agency Approach To Expand The Flood Inundation Mapping Capacity Of The Us National Water Center, Samuel Jay Oldham

Theses and Dissertations

The most accurate numerical model for simulating flood extents of rivers has long been a subject of debate. While specialized models exist for specific hydraulic features, we advocate for the principle that the best model is the one the user is familiar with, has adequate data to support input requirements and limitations, and will consistently employ. To support this approach, we have developed a database schema optimized to store riverine flood inundation model output files. This schema is designed to assist U.S. cities, counties, states, and other flood management agencies in leveraging their existing model-generated flood maps, regardless of the …

Two-Key Dependent Permutation (Tkdp) And Its Applications In Information Security, Arulmani K

Theses and Dissertations

Two-Key Dependent Permutation (TKDP) algorithm for generating permutation sequences of fixed sizes, TKDP based Symmetric Block Cipher (TKDPSBC) and TKDP Audio encryption are being proposed in this thesis. TKDP algorithm is capable of generating different sequences for different key pairs. This makes it suitable for constructing dynamic S-boxes and P-boxes that have more degree of randomness and non-linearity to resist cryptanalytic attacks. Rigorous statistical tests validate the efficacy of the generated permutation sequences, affirming their suitability for cryptographic applications in conjunction with Fiestel network-based block ciphers. TKDPSBC encrypts a plaintext block into a ciphertext block of the same size. TKDP …

Compliant Parallel-Guiding Mechanisms Scaling Data, Jared Hunter, Larry L. Howell Dr.

ScholarsArchive Data

Force/displacement and strain data is captured for various geometric scales of compliant parallel-guided mechanisms.

Processing Parameter-Performance Nexus In 3d Printing Of Nanostructured Chiral Photonics, Kyle George, Nader Taheri-Qazvini, Peter D. Olmsted, Monirosadat Sadati

Faculty Publications

Precisely crafted hierarchical architectures found in naturally derived biomaterials underpin the exceptional performance and functionality showcased by the host organism. In particular, layered helical assemblies composed of cellulose, chitin, or collagen serve as the foundation for some of the most mechanically robust and visually striking natural materials. By utilizing structured materials in additive manufacturing techniques such as extrusion-based 3D printing, the intrinsic deformation process can be used to implement bottom-up design of printed constructs, offering the potential to create intricate macroscale geometries with embedded nanoscale functionality. In this study, comprehensive rheological and rheo-optical characterization of structurally colored, photocurable liquid crystalline …

Immersive Modeling To Communicate And Manage Risks Of Water Shortages, David Rosenberg, Erki Porse

Civil and Environmental Engineering Faculty Publications

Our project goal is to use immersive online collaborative modeling as a tool for active learning to communicate and manage users conflicting risks of water shortages because decisions now to manage risk effect future risk. State-of-the art river basin forecasting tools provide probabilistic estimates of streamflow at hourly to annual scales. Water resource models quantify tradeoffs and risk across hundreds or thousands of scenarios of inflow and demand forecast out decades. Our project objectives are: 1) Formulate extreme scenarios for reservoir inflows without probabilities one to three years out that pose imminent risk of water shortages. 2) Hold immersive model …

Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles

Faculty Publications

Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …

Power System Operations Modeling And Optimization Using Pyomo, Ahmad Heidari, Rui Bo

Graduate Student Research & Creative Works

"The energy sector has witnessed transformative advancements over the past few decades. Power systems, which form the backbone of modern society, have grown increasingly complex with the integration of renewable energy sources, energy storage, and emerging technologies. As these systems evolve, so does the need for efficient operation and optimization strategies to ensure reliability, sustainability, and economic performance.

Optimization plays a central role in solving real-world challenges such as balancing power generation and demand, minimizing operational costs, and managing grid constraints. However, many existing resources tend to focus either on theoretical aspects of optimization or rely on expensive, proprietary software …

Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng

Data Science and Data Mining

This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.

Microfabrication Of Sic Using Femtosecond Lasers, Jared Eldon Payne

Theses and Dissertations

Silicon carbide (SiC) is a desirable material in a wide variety of semiconductor fields. The impressive thermal, chemical, and mechanical properties that make SiC an attractive material also make it very difficult to machine. New fabrication techniques are required to take full advantage of the potential of SiC. First, a new 3-dimensional (3D) non-line-of-sight (NLOS) fabrication technique using two-photon absorption is demonstrated in SiC. NLOS microchannels are shown with aspect ratios higher than 100:1. The process is the only method known, at this time, that can create truly 3D subsurface structures in SiC without direct line of sight to the …

Lab: Developing Explainable Multimodal Ai Models With Hands-On Lab On The Life-Cycle Of Rare Event Prediction In Manufacturing, Chathurangi Shyalika, Ruwan Wickramarachchi, Revathy Venkataramanan, Dhaval Patel, Amit Sheth

Faculty Publications

In the age of Industry 4.0 and smart automation, unplanned downtime is costing industries over $50 billion annually. Even with preventive maintenance, industries like automotive lose more than $2 million per hour due to downtime caused by unexpected or "rare'' events. The extreme rarity of these events makes their detection and prediction a significant challenge for AI practitioners. Factors such as the lack of high-quality data, methodological gaps in the literature, and limited practical experience with multimodal data exacerbate the difficulty of rare event detection and prediction. This lab will provide hands-on experience to learn how to address these challenges …

Research Progress Of Modified Asphalt With Graphene Materials, Zhang Zongwei, He Kai

Journal of China & Foreign Highway

To clarify the research status of mo dified asphalt properties with graphene materials,relevant research literature in China and abroad was consulted to compare the effects of various graphene materials and preparation parameters on asphalt.The results show that graphene,nano graphite sheets,and oxidized graphene can improve the microstructure and road performance of asphalt,increase the service life of asphalt,and reduce the maintenance cost of asphalt.Continuously optimizing the preparation parameters of modified asphalt and exploring the mechanism of modified asphalt with new material not only help the promotion and application of new road asphalt technologies but also reduce energy consumption,pollutants,and carbon emissions,providing new ideas …

A Digital Twin Based Forecasting Framework For Power Flow Management In Dc Microgrids, Kerry Sado, Jarrett Peskar, Austin Downey, Jamil A. Khan, Kristen Booth

Faculty Publications

The ability to forecast system conditions is integral to the definition and functionality of digital twins. While forecasting methods have been explored for use in digital twin systems, the integration of feedback mechanisms for real-time forecasting and in-situ decision-making in DC microgrids has not been extensively investigated. This research develops a modular forecasting framework tailored for digital twins in DC microgrids to enable real-time monitoring, online forecasting, and decision-making. DC microgrids, characterized by dynamic load variations, benefit from advanced predictive capabilities to maintain stability and operational efficiency. The proposed digital twin-based forecasting framework addresses these challenges by providing real-time predictive …

Interfacial Phenomena In Molten Salt Systems And Wetting Transitions In Microcavities, Aaron Essilfie

Theses and Dissertations

Interfacial phenomena are the processes that occur at the interface between two phases of matter: solid-liquid, solid-gas, liquid-liquid, and liquid-gas. Wetting, spreading, adsorption, and capillarity are some features of interfacial phenomena. This research explores two areas of interfacial phenomena: the interfacial tension between a liquid and gas, and wetting transitions in microcavities. Surface tension has been a widely studied topic in surface chemistry. Many techniques have been employed to study the surface tension of liquids in various studies and research areas, but the interfacial tension between a liquid and gas has not been extensively researched. For this reason, part of …

Probing Ion-Blocking Electrode Rigs For Ionic Conductivity In Hybrid Solid Polymer Electrolytes, Kyra Glassey, Gabriela Roman-Martinez, Liliana Delatte, Thomas Burns, Monirosadat Sadati, Paul T. Coman, Ralph E. White

Faculty Publications

Solid electrolytes are critical for structural batteries, combining energy storage with structural strength for applications like electric vehicles and aerospace. However, achieving high ionic conductivity remains challenging, compounded by a lack of standardized testing methodologies. This study examines the impact of experimental setups and data interpretation methods on the measured ionic conductivities of solid polymer electrolytes (SPEs). SPEs were prepared using a polymer-induced phase separation process, resulting in a bi-continuous microstructure for improved ionic transport. Eight experimental rigs were evaluated, including two- and four-electrode setups with materials like stainless steel, copper, and aluminum. Ionic conductivity was assessed using electrochemical impedance …

Performance-Based Full Depth Reclamation Design, Moatasem H. Algburi

Civil Engineering ETDs

The Full-Depth Reclamation (FDR) technique is a cold-mix asphalt (CMA) technology employed in New Mexico to rehabilitate existing pavements. It results in minor disruption to traffic, environmental advantages, and decreased construction period and costs. However, insufficient data on the material properties of FDR mixtures and their characterization limits the use of the mechanical-empirical (M-E) design method of FDR materials. The MEPDG develops performance models using the structural response of pavement layers to predict pavement structure systems based on material properties, climate models, and loading conditions. This study has developed MEPDG models to predict the long-term performance of FDR materials and …

Few-Shot Transfer Learning For Individualized Braking Intent Detection On Neuromorphic Hardware, Nathan A. Lutes, V. Sriram Siddhardth Nedendla, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a Brain Chip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used group-level, models using electroencephalographic data. The efficacy of the method is studied on an advanced driver assist system related task of predicting braking intention. Approach. Data are collected from participants operating an NVIDIA JetBot on a testbed simulating urban streets for three different scenarios. Participants receive a braking indicator in the form of: (1) an audio countdown in a nominal baseline, stress-free environment; (2) an …

Super-Resolution Imaging Reveals Resistance To Mass Transfer In Functionalized Stationary Phases, Ricardo Monge Neria, Muhammad Zeeshan, Aman Kapoor, Tae Kyong John Kim, Nichole Hoven, Jeffrey Pigott, Burcu Gurkan, Christine Duval, Lydia Kisley

Faculty Scholarship

Chemical separations are costly in terms of energy, time, and money. Separation methods are optimized with inefficient trial-and-error approaches that lack insight into the molecular dynamics that lead to the success or failure of a separation and, hence, ways to improve the process. We perform super-resolution imaging of fluorescent analytes in five different commercial liquid chromatography materials. Unexpectedly, we observe that chemical functionalization can block more than 50% of the material’s porous interior, rendering it inaccessible to small-molecule analytes. Only in situ imaging unveils the inaccessibility when compared to the industry-accepted ex situ characterization methods. Selectively removing some of the …

Stochastic Generalization Models Learn To Comprehensively Detect Volatile Organic Compounds Associated With Foodborne Pathogens Via Raman Spectroscopy, Bohong Zhang, Anand K. Nambisan, Abhishek Prakash Hungund, Xavier Jones, Qingbo Yang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Ensuring food safety requires continuous innovation, especially in the detection of foodborne pathogens and chemical contaminants. In this study, we present a system that combines Raman spectroscopy with machine learning (ML) algorithms for the precise detection and analysis of VOCs linked to foodborne pathogens in complex liquid mixtures. A remote fiber-optic Raman probe was developed to collect spectral data from 42 distinct VOC mixtures, representing contamination scenarios with dilution levels ranging from undiluted to highly diluted states. A dataset comprising 1445 Raman spectra was analyzed using classification and regression ML models, including multi-layer perceptron (MLP), random forest, and extreme gradient …

Viscoelastic Protective Armor Liners And Protective Armor, Fatih Dogan, Cody Thomas, Catherine Johnson

Materials Science and Engineering Faculty Research & Creative Works

No abstract provided.

The Efficacy Of Utilizing Artificial Intelligence Techniques In Developing Critical Thinking In Mathematics Among Secondary School Students And Their Attitudes Toward It, Mohammad A. Tashtoush, Aida B. Qasimi, Nawal H. Shirawia, Lubna A. Hussein

Iraqi Journal for Computer Science and Mathematics

The aim of this study is to investigate the efficacy of Artificial Intelligence (AI) techniques and programs in developing Critical Thinking Skills (CTSs) in mathematics among secondary school students, as well as their attitudes towards it. This study employed an experimental methodology, which was applied to a sample of 91 students. A critical thinking test and a scale to measure students' Attitudes Towards Mathematics (ATM) were also utilized. This study revealed significant improvements in the mean scores of critical thinking skills among secondary students who were exposed to Artificial Intelligence Techniques (AITs), particularly in deduction, interpretation, inference, and evaluation. Additionally, …

Microstructural, Oxidation, And Mechanical Behavior Of Nbti-Based Refractory Alloys With 5 To 10 Pct Co, Cr, And Ni Additions, Tae Kyong John Kim, Jennifer Carter

Faculty Scholarship

NbTi-based refractory alloys with additions of Co, Cr, and Ni represent an interesting medium-entropy alloy system with potential for protective oxide film formation, high strength, and ductility. This study investigates the microstructural evolution, oxidation behavior, and mechanical properties of NbTi-based alloys containing 5 to 10 at. pct Co, Cr, and Ni. CALPHAD predictions suggest that this composition range can be heat treated to obtain a predominantly body-centered cubic matrix phase. Mechanical properties, including microhardness, yield strength, maximum strength, and specific strength are evaluated through isothermal compression tests conducted between room temperature and 800 °C. The oxidation kinetics of these alloys …

Experimental Investigation And Operating Characteristics Of Lhr Engine Using Bio-Fuel Blends With Additives, Suresh R

Theses and Dissertations

The huge energy demand and environmental anxiety are the reasons for the focus on the interest in alternative fuels for diesel engines. This has resulted in a worldwide search for renewable, less pollutant and agricultural-based alternate fuels. Also, attention is given to increasing the efficiency of a conventional diesel engine when operating on alternative fuels. The bio-fuel derived from non-edible oil such as Pongamia oil and Neem seed oil are suggested alternative fuels for this LHR engine.

Diesel engine combustion components viz., the piston crown and liner were coated with Aluminium Titanate thermal barrier coating material. The objective of this …