Digital Commons Network^™

Review Of Modern Methods For Identification, Forecasting, And Intelligent Control Of Wastewater Biological Treatment Processes, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon O'G'Li Mannobjonov

Chemical Technology, Control and Management

This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors.

Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It …

Analysis Of The Carbonization Process Of Ammoniated Brine In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fotima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of heat and mass transfer, hydrodynamics, carbonation kinetics, and crystallization. The paper considers the potential of using digital twins, neural network models, fuzzy logic devices, and hybrid models to improve forecasting accuracy and the adaptability of process solutions. Modern carbonation process control strategies are also considered. A detailed analysis is provided of predictive control (MPC), neuro-fuzzy controllers, decentralized and multivariate control systems that ensure stable column operation under disturbances, optimize …

Synthesis Of An Adaptive Synergistic Fuzzy Discrete Controller For Nonlinear Systems, Isamidin Xakimovich Sidikov, Gulruxsor Murot Qizi Nashvandova, Feruzakhon Botirxon Qizi Sodiqova

Chemical Technology, Control and Management

The paper considers the issues of synthesizing an adaptive fuzzy synergetic controller with discrete time for nonstationary nonlinear dynamic objects. The proposed approach is based on the integrated use of synergetic control principles and fuzzy logic methods, which ensure the formation of a control law for nonlinear dynamic objects that provides asymptotic stability of the control system. Such a hybrid combination makes it possible to guarantee the asymptotic stability of the closed-loop system and to shape the required dynamic behavior of the object over a wide range of operating modes. In addition, this approach provides the ability to adapt to …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Adaptive-Robust Control Of Dynamic Systems Using Generalized Predictive Methods, Shuxrat Tulyaganov

Chemical Technology, Control and Management

This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient stability to inaccurate selection of delay or model order. A generalized predictive control approach is suggested, with simulation outcomes showing superiority over traditional methods like generalized minimum variance control and pole assignment.This sliding horizon algorithm is based on predicting future system output signals several steps ahead, based on assumptions about subsequent control actions. One effective assumption is the presence of a “control horizon,” beyond which control signal increments are assumed to …

Learning From Experience: A Study Of Q Learning In Reinforcement Learning, Samuel Olusegun

Research Horizons Day Posters

No abstract provided.

Fiber Lasers For High Power Optical Research, Cora L. Prescott, Christapher N. Vincent

Research Horizons Day Posters

No abstract provided.

Predicting Internal Temperature Gradient Of Friction Stir Welding With Pinns, Evelina Gustafsson

Research Horizons Day Posters

No abstract provided.

Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta

Faculty Publications

Introduction: 

Stated aims for digital healthcare transformation frequently cite goals for better coordinated patient-centric systems. However, despite advances in medical science, digital technologies, health policies, and billions of dollars invested over the past 25 years, most healthcare providers are far from fully realizing the demonstrated benefits of today's digital technologies for improving patient care. Sharing information across healthcare systems remains challenging. Problems with fragmentation, quality, inequities, and rising costs of care delivery persist. A recent study of 1,026 U.S. hospital systems found that only 15.8 percent achieved a digital maturity level needed to provide digitally enabled healthcare services to better …

Program Review Report 3-3-26, Angela Brock

Program Review Committee

No abstract provided.

Infrastructural Resiliency Analysis Concerning Extreme Events, Yasaman Norouzi

Theses and Dissertations

Infrastructural resiliency is critical for maintaining functionality during and after extreme events, ensuring minimal service disruptions and supporting rapid recovery. Key resiliency attributes—robustness, redundancy, resourcefulness, and rapidity—enhance infrastructure adaptability and safety. This study investigates significant factors and methods for improving resiliency, with a focus on equity and reliability. A new resiliency metric, incorporating equity as a core element, is developed using probabilistic approaches. This metric integrates structural vulnerability with accessibility, income, cost, and exposure factors to evaluate community impact on infrastructure access. To achieve this, limit state functions are defined to assess how infrastructural vulnerabilities affect diverse communities. Apart From …

Review On Data Privacy And Security For Iot-Based Multifunctional Layers Of Cyber-Physical Systems In Smart Grids, Mohammad Kamrul Hasan, Md Mehedi Hasan, Nabeel Al-Qirim, Siti Norul Huda Sheikh Abdullah, Shayla Islam, Md Abdur Razzaque

All Works

Smart grid cyber-physical systems (SG-CPS) are intelligent platforms that incorporate IoT-enabled multifunctional layers including the physical, perception, communication, cyber, and application layers. It includes supervisory control and data acquisition, wide-area measurement systems, and advanced metering infrastructure for remote data aggregation, monitoring, and control operations. From an environmental perspective, these green technologies support two-way operations, which generate and transmit data over wired and wireless communication systems. However, this critical infrastructure faces data privacy and cybersecurity challenges. Hence, extensive research is required to address data privacy and security gaps to strengthen national grid cybersecurity and reduce economic losses. Therefore, this review highlights …

Ucc Minutes 3-3-26, Angela Brock

UCC Agendas/Minutes

No abstract provided.

Approved Courses 3-3-26, Angela Brock

Individual Course Committee (ICC)

No abstract provided.

Icc Agenda 3-3-26, Angela Brock

Individual Course Committee (ICC)

No abstract provided.

Physical And Chemical Study Of Interaction In The Urea–Valine System For The Creation Of Modified Liquid Nitrogen Fertilizers, Suvonkul Erkhanovich Nurmonov, Saydullo Khamidovich Azimov

Chemical Technology, Control and Management

This study reports the results of a comprehensive physicochemical investigation of the urea–L-valine binary system, conducted to validate its potential as a modified base for liquid nitrogen fertilizers.

By utilizing the methods of isomolar series, visual-polythermal analysis, X-ray phase (XRD) and single-crystal X-ray diffraction (SC-XRD), synchronous thermal analysis (TGA/DTA), and FT-IR spectroscopy, it was determined that the interaction between components in both aqueous solutions and the solid phase results in the formation of molecular associates stabilized by hydrogen bonds, without the formation of new stoichiometric compounds.

The concentration and temperature limits of the system's stability were defined, revealing a reduction …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

Analytical Method For Investigating Nonlinear Magnetic Circuits Of Measuring Transducers With A Standard Parameter Distribution Structure, Javhar Sulton O'G'Li Fayzullayev

Chemical Technology, Control and Management

The article proposes a new analytical method for investigating magnetic circuits with distributed parameters and nonlinear magnetic coupling. The method is based on introducing into the system of nonlinear differential equations of such circuits the condition that the second derivative of the magnetic flux with respect to the circuit length is equal to zero, as well as on assuming that one of the geometric parameters of the studied magnetic circuit – the value of the air gap between ferromagnetic cores, their thickness, width, or the linear value of the number of turns of the distributed excitation winding – is a …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Clinical Validation Of Perfusion Imaging With Pulmonary Function Test Data Using Voronoi-Based Discretization, Jorge Cisneros, Caleb J. Herrera, Yi-Kuan Liu, Lisa V. Du, Yevgeniy Vinogradskiy, Richard Castillo, Girish Nair, Edward Castillo

Department of Medicine Faculty Papers

Objective.Accurate lung function assessment is essential for diagnosing and managing diseases like chronic obstructive pulmonary disorder, pulmonary emboli, and lung cancer. Single-photon emission computed tomography (SPECT) provides valuable 3D functional imaging of ventilation and perfusion, but is limited by low spatial resolution, availability, additional radiation, and cost. Alternative methods, including CT-based perfusion (CT-P) and deep learning models, require large datasets to validate results that are often scarce. Pulmonary function tests (PFTs) offer rapid and noninvasive global lung function measures and are clinically widely used. While ventilation correlates well with PFTs, perfusion imaging presents challenges due to complex blood flow and …

Self-Aware Quantum-Inspired Routing Framework For 6g And Quantum Networks, Haitham M. Abdelghany, Mohamed M. Ashour

Mansoura Engineering Journal

This paper introduces a quantum-hybrid-aware routing framework that incorporates the concepts of quantum computing with meta-cognitive learning to improve adaptability, reliability, and awareness in dynamic quantum networks. The proposed system accommodates a new IoT, edge computing and 6G system, where routing schemes should be flexible and robust and have cross-topology functionality. Conventional methods of quantum reinforcement learning can be characterized by a trade-off between exploration and decision stability. To cope with this, the proposed self-aware hybrid architecture is a combination of quantum-enhanced learning and a meta-cognitive awareness layer to allow autonomous agents to monitor performance and adjust routing strategies on …

Cfd Simulation Of The Influence Of The Inflow Guided Baffles On Photovoltaic Cooling Thermal Performance, Hussein A. Jaffar, Ali A. Ismaeel, Ahlam Luaibi Shuraiji

Terra Joule Journal

This study presents a comprehensive investigation into enhancing the thermal performance of photovoltaic (PV) modules through the integration of inflow-guided cooling baffles, using a validated 3D CFD model developed in ANSYS Fluent 2020 R1. The simulations were performed under a solar heat flux of 850 W/m², an inlet air velocity of 2.5 m/s, and a Reynolds number of 1.2× 10⁴, while four configurations were examined: a baseline PV module without baffles, a vertical-guide model reported in previous studies, and three novel nozzle-type inflow guides positioned at 45°, 30°, and 25°. Experimental validation conducted under controlled environmental …

Intelligent Fault Diagnosis Of Ev Induction Motors Using Multi-Sensor Ann And Explainable Ai For Sustainable Transportation, Royal Madan, Ahmed Ali Farhan Ogaili

Terra Joule Journal

Maintaining the dependability and operational continuity of electric vehicle (EV) drivetrains has become crucial as the world's shift to electrified transportation picks up speed. This is a major obstacle for sustainable mobility. Using a high-capacity Artificial Neural Network (ANN), this study presents a data-driven multi-sensor framework for advanced fault diagnosis of induction motors in EV applications. The publicly available University of Ottawa dataset that encompasses nine distinct fault categories and 180 test samples was utilized to replicate both mechanical failure modes (e.g., broken rotor bars, bearing defects, rotor misalignment) and electrical anomalies (e.g., stator winding faults, voltage imbalance) under constant …

Reducing The Surface Roughness Of Curvature Surfaces By Electrical Discharge Machining With Magnetic Abrasive Finishing, Shahad Taqi, Saad Shather, Wisam Hamdan

Engineering and Technology Journal

This study presents an integrated work that combines unconventional machining and finishing techniques for complex geometric models. A Taguchi design investigated three electrical-discharge parameters—electric current, pulse duration, and gap—each at three levels; a multi-objective optimization matrix was then used to select the optimal conditions. The geometric models were designed using SolidWorks software and machined on a CNC machine to ensure maximum accuracy in the resulting samples. The samples were finished using the magnetic abrasive finishing technique, where the particle mixture was developed as a hybrid blend of two types of abrasive particles, tungsten carbide (WC) and silicon carbide (SiC). Among …

Enhancing The Surface Integrity Of Gas Turbine Compressor Blades Using Alumina Abrasives In Magnetic Finishing: An Experimental Approach, Tahseen Salman, Saad Shather, Baraa Albaghdadi

Engineering and Technology Journal

Magnetic Abrasive Finishing (MAF) is a highly effective technique for enhancing the surface integrity of high-value components with complex geometries, owing to its non-contact, flexible, and precisely controllable nature. This study investigates the use of Al₂O₃ (alumina) powder as an abrasive medium in the MAF process, selected for its high hardness, thermal stability, and chemical inertness. Although Al₂O₃ is only weakly paramagnetic, it was successfully incorporated into the magnetic abrasive brush through mechanical blending with ferromagnetic particles that respond to the magnetic field. This hybrid abrasive system enables effective control of finishing forces, leading to significant improvements in surface quality …

Experimental And Numerical Investigation Of Al2o3-Sio2 Nanopowder For Stainless Steel 304 L, Qasim Sachit, Maan Tawfiq, Muhssn Shamky, Waseem Abbas

Engineering and Technology Journal

Electro-Discharge Machining (EDM) is a unique manufacturing method. Recently developed thermo-electric methods include Nano Powder-Mixed Electric Discharge Machining (NPMEDM), which suspends metallic Nanopowder in a dielectric. This study examines how Al2O3 -SiO2 Nanopowder concentration and mixing ratio affect EDM dielectric fluid surface integrity (outputs) on stainless steel 304L. Material Removal Rate (MRR), Electrode Wear Rate (EWR), and surface roughness (Ra) are used to evaluate machining efficiency. Nanofluid has much better heat conductivity than dielectrics, enhancing material removal. Material Removal Rate rises with discharge current. At Run No. 26, increasing Al2O3 particle proportion with 35 A discharge current, 2 g/l particle …

In-Chip Artificial Intelligence Technology For Generating And Self-Correcting The Topology Of Low-Consumption Rc Filters, Zainab Al-Araji

Engineering and Technology Journal

This study presents an innovative self-tuning system for first-class RC filter circuits, specially designed to achieve a target cut-off frequency of 500 kHz with unprecedented accuracy and high energy efficiency. The proposed model is based on a multivariate adaptive tuning algorithm that synchronously adjusts both the resistance (R) and the capacitance (C). The effectiveness of the model was verified through a three-level methodology that included theoretical modeling using Maxwell's equations, digital simulation using the MATLAB/Simulink environment, and practical testing with an accurate spectrometer. The results demonstrated a standard frequency accuracy of 99.9969% and a relative error of less than 0.0031%, …

A Review Of Smart Actuation Technologies In Modern Mechatronic Systems, Ivan Gorial

Engineering and Technology Journal

Smart actuation has transformed mechatronics over the past six years by harnessing materials that turn heat, electricity, magnetism, or light into finely tuned motion. Our survey of developments from 2019 to 2025 reveals clear trade-offs: electro-active polymers can stretch beyond 200% but operate at roughly 30% efficiency, whereas piezoelectric devices achieve over 95% efficiency with displacements under 0.1%. Ionic polymer–metal composites and magnetorheological actuators strike the best balance for precision work, delivering about 50% stroke at 60% efficiency. Real-world examples show that packing tiny shape-memory alloy bundles into soft exosuits grants sub-millimeter accuracy without sacrificing comfort, and that materials capable …

Experimental Investigation Of Applying Multi-Stage (Pid-Mrac) Controller For Trajectory Tracking Of Four Mecanum Wheeled Mobile Robot, Asaad Abdullsahib, Hassan Alwan

Engineering and Technology Journal

This paper presents a practical investigation into the design and implementation of a multi-stage controller, which integrates a Model Reference Adaptive Controller (MRAC) with a Proportional-Integral-Derivative (PID) controller for trajectory tracking control in a Four Mecanum Wheels Mobile Robot (FMWMR). The MRAC adaptively updates the control parameters based on the difference between the actual and desired behaviors of the mobile robot. In contrast, the PID controller manages the angular velocities of the wheels. The mobile robot has been designed and constructed with two holders to facilitate the transportation of logistical items and constrain the weight to the center of the …

Design And Control Of Wireless Charging System For Electric Vehicle, Basma Abbas, Hosham Anead, Khalid Sultan

Engineering and Technology Journal

This study concentrated on utilizing a neural network controller and inductive power transfer to enhance the electric vehicle charging. Electric vehicles are a key transportation system component since they lower fuel costs, noise levels, and carbon emissions. The charging duration and operational battery efficiency are the primary obstacles to wireless charging in electric vehicles. In the beginning, the system was designed. It included the primary side (grid, rectifier, DC-DC boost converter, and DC-AC high-frequency inverter), mutual inductance (one coil transmitter and six coils receiver), and secondary side (single-phase rectifier and battery pack). A neural network controller has been employed to …