Digital Commons Network^™

Comparative Fatigue Analysis Of Cf-Pla Metamaterial Bone Plates For Orthopaedic Fixation, Ani Daniel, Hamed Bakhtiari, Barun K. Das, Muhammad Aamir, Majid Tolouei-Rad

Research outputs 2022 to 2026

Bone plates are widely used in orthopaedic surgery to stabilise fractured bones and support healing following traumatic injuries or osteotomies. However, conventional metallic bone plates suffer from stress shielding and stiffness mismatch with bone, which can hinder optimal healing. Additive manufacturing enables the incorporation of novel metamaterial architectures into polymer-based implants to enhance mechanical properties. The fatigue behaviour of these implants during the healing period is critical to ensuring their structural integrity and long-term performance. In this study, the compressive fatigue performance of fused deposition modelling (FDM)-printed carbon fibre-reinforced polylactic acid (CF-PLA) bone plates were investigated. Four metamaterial structures—tetrachiral, re-entrant, …

Thermo-Hydro-Chemical Coupled Numerical Modeling Of Hydrogen-Thermal Co-Development In Hydraulically Fractured Peridotite, Jiacheng Dai, Zhonglin Ma, Yunzhi Yue, Yujie Yuan, Shouceng Tian

Research outputs 2022 to 2026

Hydrogen generation through serpentinization reactions in peridotite formations under high temperature conditions represents a promising avenue for subsurface hydrogen production. However, the thermal energy in the formation environment have not been sufficiently considered. To integrate hydrogen production with thermal energy development, this study develops a thermo-hydro-chemical coupled numerical model, which is used to investigate hydrogen-thermal co-development in hydraulically fractured peridotite. Given that the hydrogen-thermal co-development process involves fluid flow, heat transfer and serpentinization reactions, the governing equations are formulated based on Darcy flow and energy conservation equations, with serpentinization kinetics incorporated through the reactive source terms. To evaluate hydrogen production …

Role Of Directional Conditional Filtering On Droplet Velocity And Size Distribution, Farzad Hossain, Matthew J. Cleary, Yasir M. Al-Abdeli, Mehdi Khiadani

Research outputs 2022 to 2026

This study investigates the role of directional filtering in the analysis of spray behaviour using two full cone nozzles (65° and 75°) emitting aqueous sprays under atmospheric conditions. A hybrid computational–experimental framework was applied, using Large Eddy Simulation (LES) with Discrete Phase Model (DPM) and Rosin-Rammler distribution in ANSYS Fluent, validated against Shadowgraph and Particle Image Velocimetry (PIV) measurements. The sensitivity of directional filtering to the effects of spray angle and flow rate (1.75 and 3.5 L/min), were also done. Upward-filtered droplets consistently exhibited greater breakup than both raw and downward-filtered data due to gravitational opposition and longer air exposure. …

Dynamic Mechanical Insertion Analysis Of Gelatin Methacryloyl Microneedles Under Realistic Insertion Conditions, Moloud Amini Baghbadorani, Masoumeh Zargar, Abdellah Shafieian, Majid Tolouei-Rad

Research outputs 2022 to 2026

Despite the great potential of Gelatin Methacryloyl (GelMA) microneedles (MNs) for minimally invasive drug delivery and interstitial fluid extraction, their performance under realistic insertion conditions and across diverse geometrical and mechanical parameters has remained uncharacterized. In this study, dynamic and static finite-element analyses were conducted for the first time to compare three types of crosslinked GelMA MNs: conical, pyramidal, and tapered-conical with and without base support. Insertion force, von Mises stress, and safety factors were evaluated at insertion velocities of 2-6 m/s under varying crosslinking times and polymer concentrations. The tapered-conical geometry demonstrated the best overall mechanical reliability, combining moderate …

3d-Printed Cf-Pla Bone Plates With Metamaterial Structures: Design, Fabrication, And Mechanical Evaluation, Ani Daniel, Hamed Bakhtiari, Alireza Nouri, Barun K. Das, Muhammad Aamir, Majid Tolouei-Rad

Research outputs 2022 to 2026

This study presents the design, fabrication, and mechanical performance of carbon fiber-reinforced polylactic acid (CF-PLA) bone plates incorporating auxetic and non-auxetic metamaterial architectures. Four lattice-structured bone plates (re-entrant, rotating square, tetrachiral, and hexagonal) were evaluated for their flexural, tensile, and compressive properties. The specimens were fabricated using Fused Deposition Modelling (FDM). The tetrachiral structure demonstrated superior bending capacity, achieving a flexural stress of 17 MPa and a modulus of 1214 MPa. Under both tension and compression, it exhibited the highest strength (24.5 MPa and 40 MPa, respectively) and stiffness (1441 MPa in tension and 2352 MPa in compression), while the …

Dynamic Load Assessment Of Pem Fuel Cell Systems Under Pid-Based Control Strategies For Sustainable Operation, Tarek Abedin, Paw, Normy Norfiza Abdul Razak, Chen Chai Phing, Yaw Chong Tak, Monowar Mahmud, Manzoore Elahi M. Soudagar, T. M. Yunus Khan, Mohammad Tariqul Islam, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Proton exchange membrane fuel cell (PEMFC) systems’ reliable operation under variable load conditions is a significant challenge because of voltage fluctuations, transient variations, and the high computational requirements of sophisticated control techniques like intelligent and model predictive controllers. Even while these state-of-the-art methods provide great precision, complexity and cost often limit their real-time applicability, underscoring the need for a simpler but efficient control solution. To achieve effective voltage regulation in PEMFC systems, this study suggests a DC–DC buck converter in conjunction with a comparator-based proportional–integral–derivative (PID) control technique. In order to provide stable operation under both constant and changing load …

Engineered Uio-66-Nh2 Hybrid Nanocomposites For Antifouling Ultrafiltration Membranes With Dual Resistance To Microplastics And Protein Fouling, Mitra Golgoli, Mohadeseh Najafi, Javad Farahbakhsh, Masoumeh Zargar

Research outputs 2022 to 2026

The growing presence of microplastics (MPs) in water and their impact on ultrafiltration (UF) membranes during the early stages of wastewater treatment highlight the need for effective mitigation strategies. This study explores the innovative modification of UF membranes by incorporating various hybrid metal-organic frameworks (MOFs) nanoparticles, including UiO-66-NH2 hybrids with multi-walled carbon nanotubes (MWCNTs) (UiOM), chitosan (UiOC), and sulfobetaine zwitterions (UiOZ). These nanoparticles were synthesized and integrated into innovative UF membranes to compare their performance on MPs fouling effect in particular. The integration enhanced membrane hydrophilicity and altered surface roughness, creating a hydrophilic functional network that improved water permeability. Water …

Development Of A Metal-Based Catalyst For The Ammonia Dehydrogenation Reaction, Othman Mohammed Abdullah Al-Amodi

Thesis/ Dissertation Defenses

Developing cost-effective and active catalysts that would replace noble metals is desirable for the ammonia decomposition reaction. Hence, this thesis focuses on the development and evaluation of a 10Ni/0.75TiO2-0.25CeO2 catalyst for ammonia decomposition, a promising route to carbon-free hydrogen production. The system parameters investigated include the effect of reaction temperature (550, 650, and 750°C) and the catalyst mass (100, 200, and 300 mg) on the performance of the ammonia decomposition process. The primary objective of this work is to investigate how catalyst composition and metal-support interactions influence activity, hydrogen production, and ammonia conversion. Catalysts were prepared by the incipient wetness …

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.

Cylindrical Versus Spherical Self-Similar Capillary Cavity Collapse, Karl Cardin, Christophe Josserand, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Drop tower experiments have been performed to study the capillary collapse of large high-aspect-ratio cavities. Cavities are formed by momentarily impinging the free surface of a liquid bath with a jet of air in the microgravity environment of a drop tower. The collapse may give rise to a jet and three distinct jetting regimes are identified. Simulations are performed to further investigate the phenomena. The abrupt emergence of a thin high velocity jet is observed experimentally and numerically at a specific initial cavity aspect ratio. Different power laws are identified in different regions of the cavity during the collapse providing …

Implementation Of Kansei Engineering Method In Designing Spreadable Cheese Packaging, Novi Purnama Sari, Mega Analisa, Suci Puji Lestari, Khofifah Nur Amalia

Makara Journal of Technology

Some spreadable cheese packaging uses flexible plastic without additional features and easily damaged boxes. This packaging causes several problems, such as difficulty in re-storage, loss of product information due to damaged box packaging, wasteful use of packaging materials, and making the product less hygienic. The purpose of this study is to develop packaging that focuses on consumer emotions. The packaging was developed using the Kansei Engineering method, supported by Principal Component Analysis (PCA) as a determinant of the design concept, and Quantification Theory Type 1 (QTT1) to identify design elements. This study produced 46 packaging samples and 40 Kansei words. …

Enhanced Parametric Approach For Solving Interval-Valued Trapezoidal Neutrosophic Linear Fractional Programming Problems, Hamiden Abd El- Wahed Khalifa H.A.Khalifa, Moodi Abdulrahman Abdullah Al-Rajeh, Sultan S. Alodhaibi

Neutrosophic Systems with Applications

Neutrosophic sets (NSs) generalize the classical versions, by providing a flexible framework capable of representing incomplete, inconsistent, and unclassified data that frequently arises in practical decision frameworks. In this study, a linear fractional programming (LFP) problem with uncertain parameters is investigated. All coefficients in the objective function (OF) as well as the left- and right-hand sides of the constraints are represented using fully trapezoidal neutrosophic numbers (NNs). By employing a suitable score function, the proposed neutrosophic LFP model is transformed into an equivalent scalar LFP problem. Subsequently, a parametric solution procedure is established to regulate the neutrosophic optimum solution. This …

Gauss Elimination Method For Solving The System Of Neutrosophic Linear Equations, Elsayed Badr, Shokry Nada, Saeed Ali, Aya Rabie

Neutrosophic Systems with Applications

This paper proposes a unified computational framework for solving linear systems under trapezoidal Neutrosophic uncertainty. The system is formulated as A( I )x = b( I ), where both the coefficient matrix and the right-hand side vector incorporate an indeterminacy parameter I, expressed as A( I ) = A₀ + IA₁ and b( I ) = b₀ + Ib₁. A decomposition strategy is developed to separate the model into deterministic and indeterminacy components, yielding a solution of the form x( I ) = x₀ + Ix₁. The deterministic component is obtained via …

Creating Open Educational Resources With Artificial Intelligence, Serena Scalzi

UNLV Best Teaching Practices Expo

The adoption of artificial intelligence is becoming widespread in higher education. AI-driven technology has the ability to support academic and administrative faculty in designing and delivering course content. As a Part-Time Instructor in the College of Education, I used AI to enhance my teaching practice by creating course resources for my class, CIT 647 Creating Online Learning Environments. These open educational resources, developed through a reflective teaching practice facilitated by the UNLV Teaching and Learning Commons, promote equitable, inclusive education.

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …

Picc-Pal: A Support Band For Independent Picc Line Use, Kylie Luker

Honors Theses

This project presents the design and evaluation of PICC-PAL, a wearable assistive device intended to improve independence and usability for patients managing peripherally inserted central catheters (PICC lines) at home. Current at-home PICC line management often requires help due to the fine motor skills needed to connect and secure tubing. This increases reliance on caregivers and introduces potential risks such as infection and dislodgement. Through stakeholder analysis, prior art evaluation, and iterative prototyping, a device was developed to stabilize the PICC line lumen and enable one-handed connection of medical tubing. Throughout the project, multiple design concepts were explored, with the …

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …

Intelligent Manufacturing Of Edible Oil: From Smart Sensing To Big Data Platform, Ru Jiang, Nadirbek Yusupbekov

Chemical Technology, Control and Management

With the rapid advancement of Industry 4.0 technologies, intelligent manufacturing and big data platforms are profoundly transforming the production models of the traditional edible oil industry. The edible oil production process involves multiple complex unit operations such as refining, decolorization, and deodorization, which impose high requirements on process control and product quality monitoring. This paper presents a systematic review of key technological advances in the field of intelligent manufacturing of edible oil, establishing a comprehensive technical framework encompassing four dimensions: smart sensing, artificial intelligence applications, IoT communication, and big data platforms. The review begins by analyzing the global background and …

Reliability Analysis Of Separator Control Systems, D.P. Muxitdinov, O.U. Sattarov, M.Sh. Nematov

Chemical Technology, Control and Management

This article aims to enhance the reliability, efficiency, and diagnostic capabilities of gas-liquid separators operating in hazardous technological processes. In the study, the separator is considered as a critical functional unit of an industrial system and is analyzed through structural and functional decomposition. The main operating parameters of the separator, including pressure drop (ΔP), separation efficiency and operational state are described on the basis of a mathematical model. In addition, a state model is developed for normal operation, foaming, liquid droplet carryover with the gas flow, and failure conditions. Emphasis is placed on diagnostic and monitoring issues, …

Data-Driven Neuro-Fuzzy Modeling And Rule Optimization For Intelligent Prediction Of Bioreactor Dynamics, Kamala Najaf Mammadzada

Chemical Technology, Control and Management

Modeling wastewater bioreactors is a challenging problem in environmental engineering because the processes are constantly changing and the microorganisms do not behave in a linear or predictable way. This makes it difficult to predict and control the system behavior. This research investigates three artificial intelligence approaches for modeling wastewater bioreactors: the Mamdani Fuzzy Inference System (FIS), the Adaptive Neuro-Fuzzy Inference System (ANFIS), and clustering-based fuzzy models. These models help us predict what is happening in the bioreactors. For instance they help us predict how the amount of substances in the water is changing over time like dS₀/dt dSs/dt …

Optimization Of Renewable Energy-Based Alkaline Electrolysis Systems For Sustainable Hydrogen Production, Shokhrukhbek Kozimjon Ugli Bakhramov

Chemical Technology, Control and Management

This paper presents a comprehensive optimization study of hydrogen production systems through alkaline water electrolysis powered by photovoltaic energy sources, with a specific focus on Central Asian applications. The research systematically investigates critical operating parameters including KOH electrolyte concentration (25-30 wt%), temperature effects (25-80°C), current density optimization (100-500 mA/cm²), and electrode material performance using cost-effective 316L stainless steel. Experimental results demonstrate that optimized systems achieve solar-to-hydrogen efficiency of 13-15%, with hydrogen production costs ranging from $2-8/kg depending on system scale. The study reveals that maximum performance occurs at 30 wt% KOH concentration, 60-80°C operating temperature, and 200-400 mA/cm² current density. …

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …

Analysis Of Automatic Control Of The Channels And Ditches Cleaning Mechanism Based On Dynamic Indicators, Nasiba Siraj Amirbayova

Chemical Technology, Control and Management

The article deals with the automated design and experimental investigation of reinforced concrete irrigation channels and ditches, their interrelated channel-cleaning mechanisms, which are complex mechatronic systems integrating hydraulic, mechanical, and electronic components. A thorough methodology is suggested, hydrodynamic modeling, combining parametric analysis, and information-based design support to enhance channel concrete cover thickness, geometry, and cleaning system performance. Main structural parameters—involving channel depth, slope, bottom width, and concrete cover—are systematically defined and shown in matrix form to facilitate automated calculation and decision-making. Experimental prototypes and Solid Edge-based digital models are employed to verify the methodology, revealing vital interdependencies between structural parameters, …

Regular Synthesis Algorithms Of Control Devices In Nonlinear Control Systems, Husan Zakirovich Igamberdiyev, Iskandar Yusupovich Abdurakhmanov, Uktam Farkhodovich Mamirov

Chemical Technology, Control and Management

This paper examines the development of regularized algorithms for synthesizing control devices in control systems for polynomial objects, described by multidimensional Volterra functional series. The synthesis problem is solved using a two-stage procedure. In the first stage, the optimization problem is initially solved for an open-loop system. The second stage involves determining the parameters of the control device, i.e., its impulse response functions, by using the relationship between the characteristics of the open-loop and closed-loop systems. Regular algorithms are presented for finding the impulse response functions of the control device based on methods for regularizing the solution of operator equations …

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov

Chemical Technology, Control and Management

One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.