Digital Commons Network^™

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …

Real-Time Multiregional Market-To-Market Congestion Management Through Exchange Of Relief Cost Curve, Haotian Chen, Yonghong Chen, Jose Daniel Lara, Jarrad Wright, Matthew Bossart, Sebastian De Jesus Machado, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a novel method for multiregional market-to-market (M2M) coordinated congestion management. It identifies shortcomings in existing M2M approaches, where Regional Transmission Organizations (RTOs) exchange shadow prices and relief requests to optimize congestion relief allocations across interconnected regions. Two methods are proposed to enhance flow and price convergence. The first method proposes that both Regional Transmission Organizations (RTOs) use state-estimator flows directly to determine relief requirements, eliminating delays and potential oscillations caused by using market flows calculated from the prior period under existing M2M approach. The second method involves exchanging transmission relief cost curves, enabling each RTOs to integrate …

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …

Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The design of package-level power delivery networks (PDNs) has become increasingly challenging as modern high-performance systems demand higher currents. Existing PDN design flows treat ball map assignment, stackup selection, and power plane routing as separate, largely manual steps, leading to long iteration times and limited scalability. This work proposes a unified and automated package PDN design framework based on multi-agent reinforcement learning (MARL). Each power domain is modeled as an agent, with specialized agents responsible for ball map assignment, routing layer selection, and power plane synthesis. A central controller coordinates agent decisions using a global reward that captures electrical and …

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …

Enhancing Explainable Ai For Medical Imaging: Improved Lime Interpretation With Influence Mapping, Abiha Tahsin Chowdhury, Dhanush Bavisetti, Daniel B. Hier, Rahul Dubey, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

The integration of artificial intelligence (AI) into medical imaging is progressing rapidly. It is essential for these AI tools to be transparent, interpretable, and explainable to gain the trust of clinicians and regulators. Current state-of-the-art explainable AI (XAI) techniques in imaging includes Local Interpretable Model-Agnostic Explanations (LIME), Shapley Additive Explanations (SHAP), and Gradient-weighted Class Activation Mapping (Grad-CAM). Recent studies have shown that LIME often suffers from inconsistency and unreliability which limits their utility in sensitive fields like medical imaging. This paper proposes Influence Map based Explanation (IME), an enhanced variant of the original LIME framework, that aggregates multiple runs to …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …

Femtosecond-Laser-Inscribed Cladding Fiber Bragg Gratings: Architectures, Design Trade-Offs And Future Sensing Opportunities, Koustav Dey, Rex E. Gerald, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Femtosecond (fs) laser inscription enables fiber Bragg gratings (FBGs) to be positioned beyond the fiber core, including within the cladding, thereby expanding control over modal interactions and directional sensing. These cladding fiber Bragg gratings (CLFBGs) extend FBG functionality through interactions with core, cladding, and evanescent fields. Their operation does not involve fundamentally different grating physics; rather, core-mode, cladding-mode, and coupled-mode responses depend on power distribution, modal overlap with the laser-inscribed refractive-index modulation (RIM), grating position, fiber geometry, modal excitation, and interrogation configuration. This Perspective reviews advances in CLFBG fabrication, optical characteristics, sensing mechanisms, and applications. Cladding-waveguide-assisted, evanescent-field-coupled, and direct cladding-mode-excitation …

A Large Thermal Vacuum (Tvac) Facility To Simulate Cryogenic Space Environments, Emmanuel Kofi Asuako Wie-Addo, Lucas Alexander Scott, Frank Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work reports the upgrade of a 10-ft (3.0 m) long x 6-ft (1.8 m) diameter vacuum facility as part of ongoing efforts to address some of the technology gaps in NASA's Moon to Mars mission architecture, which include systems to survive and operate through extended periods in extreme environments. Consequently, a removable thermal shroud has been fabricated and installed to facilitate the simulation of extreme cryogenic conditions. The cooling rates of the shroud and a surrogate test article, using liquid nitrogen as the coolant are analyzed and documented under varying vacuum environments during cryogenic testing. The attainable vacuum level …

Upconversion Photoluminescence In Wsse Alloy Monolayer Under Uniaxial Tensile Strain, Shrawan Roy, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The optical responses of monolayer transition metal dichalcogenides (1L-TMDs) can be tuned effectively by using mechanical strain. In this work, the tuning of upconversion photoluminescence (UPL) emission in 1L-WSSe alloy by applying uniaxial tensile strain is investigated. When the uniaxial tensile strain is changed from 0 % to 1.02 %, the peak position of UPL emission has a redshift of around 25.6 nm, and the UPL intensity goes up with an exponential function of the applied strain as the upconversion energy difference is varied from −197 meV to −131 meV. The sublinear power dependence for UPL emission in 1L-WSSe alloy …

Physics-Constrained Generative Adversarial Networks For Dimensionality Reduction In Optimization, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft make a unique form of urban air mobility due to their low noise, zero emission, and precision control. To maximize efficiency, high-fidelity simulation-based multidisciplinary design optimization discovers the optimal balance among subsystems within an eVTOL. However, conventional multidisciplinary design optimization is computationally intensive due to excessive high-fidelity model evaluations. Moreover, complex nonlinear constraints deteriorate optimization efficiency and convergence. While surrogate models enable efficient design optimization, surrogate modeling suffers in large-scale applications and surrogate-based optimization still has to deal with nonlinear constraints. To address these challenges, the authors' previous work proposed physics-constrained generative adversarial …

Optimal Takeoff Trajectory Prediction Of Electric Drones Based On A Fully Automated Optimal Experimental Design Method, Jiachen Wang, Dheeraj Paramkusham, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft is attracting great interest as a viable solution to promote urban aerial mobility with promising flexibility as well as emission reductions. However, the low specific energy of the current battery is still a strong constraint on the range and endurance of eVTOL flights, especially considering the significant power demands during the takeoff process. Engineering design optimization permits promising solutions for the minimum takeoff energy consumption but can be computationally intensive due to iteratively evaluating simulation models. Surrogate-based design optimization is efficient but still relies on optimization iterations which prohibit real-time decision-making. To fill …

Multiphysics Modeling Of Melt Pool Dynamics And Powder Bed Stability In Lpbf Of Inconel 718 For A Circular Cavity, Nayan Pundhir, Oluwapelumi O. Adejumo, Kumbla Chandrashekhara, Joseph W. Newkirk, Heath Misak, Cesar Ortiz Rios

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Laser powder bed fusion (LPBF) is a metal additive manufacturing process in which a concentrated laser beam selectively melts successive powder layers to fabricate components. Final part quality is highly sensitive to process parameters such as hatch spacing, powder bed density, laser power, and scanning speed. In this study, a computational fluid dynamics model employing discrete element method has been developed in FLOW-3D to simulate LPBF of Inconel 718. The modeled powder bed incorporates particle size distribution data obtained from scanning electron microscopy and is evaluated for single-layer, single-track deposition over a circular cavity. The model captured melt pool dynamics …

Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Translating the ultrahigh intrinsic conductivity of conjugated polymers into bulk 3D architectures remains a formidable challenge due to the fundamental dichotomy between rheological printability and electronic purity. Existing strategies necessitate a compromise: solution-processing requires insulating binders that degrade charge transport, while binder-free vapor-phase polymerization (VPP) is kinetically confined to surface-limited thin films by diffusion constraints. Here, we introduce atomized oxidative polymerization (AOP), a manufacturing paradigm that overcomes these kinetic barriers via active, layer-by-layer monomer atomization. This approach ensures stoichiometric reaction conditions throughout the printed volume, driving a structural transition toward highly conductive quinoid-dominant chains with enhanced π-π stacking. The resulting …

Performance Evaluation Of Thick Carbon Fiber-Reinforced Laminates Manufactured Using Six-Magnetron Microwave System, Nayan Pundhir, Sourav Bolar, Kumbla Chandrashekhara, Kristen Donnell, Jim Lua, Kalyan Shrestha, Rui Li

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Microwave curing is a fast, energy-efficient, and a viable alternative to conventional thermal curing processes. It has been widely adopted for processing carbon fiber-reinforced polymer composites because the high electrical conductivity of carbon fibers enables strong microwave coupling. In this study, IM7/Cycom 5320-1 unidirectional prepreg has been used to fabricate 64-layer laminated composites. Symmetric cross-ply ([0°/90°]16S) and a quasi-isotropic ([45°/90°/−45°/0°]8S) layup have been investigated. A custom-built six-magnetron microwave applicator and an autoclave were employed to manufacture the composite panels. Degree of cure of the manufactured laminates was evaluated via differential scanning calorimetry. Interfacial bonding and porosity of the microwave-cured laminates …

Anisotropic Second-Harmonic Ince-Gaussian Beam Generation Using Nbobr2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Ince-Gaussian (IG) modes are a complete and orthogonal set of solutions to the paraxial wave equation in elliptic coordinates representing a continuous transition between Hermite-Gaussian modes and Laguerre-Gaussian modes. Chip-scale platforms to generate IG beams have great significance for various applications, including optical trapping and micromanipulation of particles, optical communication, and quantum optics. On the other hand, materials with high optical anisotropy are crucial for building polarization-sensitive optical devices. In this context, niobium oxide dihalides are a new class of ferroelectric materials exhibiting strong, tailorable, and highly anisotropic second-harmonic generation responses. Here, we report the generation of highly anisotropic second-harmonic …

Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Non-intrusive laser-based diagnostics, such as Two-Point Focused Laser Differential Interfer-ometry (2-FLDI), play a crucial role in modern aerodynamic research by enabling simultaneous measurements of density and velocity in compressible flows. A 2-FLDI system has been developed and implemented for the Missouri S&T Supersonic Wind Tunnel to characterize free stream turbulence fluctuations and free stream convective velocity. Design choices that enabled the 2-FLDI to overcome low turbulence to measure free stream velocity are detailed. The free stream velocity measurements are validated against previous particle image velocimetry data, showing good agreement. Analysis of normalized velocities and density-based turbulence intensities found that the …

2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Turbulence in compressible flows plays a central role in applications such as air-fuel mixing in supersonic combustors and is significantly more complex than incompressible turbulence due to the presence of fluctuating thermodynamic quantities. As such, models like the Strong Reynolds Analogy (SRA) are used to relate these quantities. However, SRA validity has been examined primarily in boundary-layer flows. In this work, a newly developed Two-Point Focused Laser Differential Interferometry (2-FLDI) system is implemented in a two-dimensional parallel supersonic jet. The diagnostic is described in detail, including optical alignment procedures, calibration methods, and data analysis techniques. Measurements acquired at multiple streamwise …

Consumer Responses To Ethical And Privacy Concerns In Ai Chatbots: Evidence From Offensive Language, Gender Bias, And Digital Privacy, Jikhan Jeong

Economics Faculty Research & Creative Works

Due to the rapid innovation of artificial intelligence (AI) and big data, AI chatbots have become increasingly influential computational social systems (CSS) in everyday life. However, the expansion of interactions between AI chatbots and consumers has raised significant ethical and privacy concerns. Using data from an online survey, this study empirically examines how consumer concerns about AI ethics and privacy influence their intention to use AI chatbots. These concerns are categorized into three types: 1) offensive language (generated by AI chatbots or users); 2) gender-biased language (from either source); and 3) digital privacy violations. The findings suggest that prior experience …

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav Bolar, Steven Corns, Nayan Pundhir, Kumbla Chandrashekhara

Engineering Management and Systems Engineering Faculty Research & Creative Works

Producing high-quality fiber-reinforced composites requires precise temperature control during autoclave curing, as even small variations can lead to defects that compromise strength and reliability. At the same time, manufacturers aim to reduce energy use and shorten curing cycles without sacrificing material performance. To address these challenges, this study develops a data-driven Long Short-Term Memory (LSTM) neural network model capable of forecasting temperature evolution inside the autoclave throughout the curing cycle. The model is trained on time-series temperature data collected from multiple sensing locations, enabling it to learn the spatial and temporal trends that govern heat flow during curing. Data augmentation …

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work presents the results of the potential of band linear system solvers for improving the scalability of the Extreme Learning Machine (ELM) method at large model sizes. The model is tested on the standard MNIST dataset with a range of solvers provided by the SciPy Python library. The results are analyzed taking into consideration the overall performance and the performance impact of band solvers across different matrix bandwidths, as well as the performance versus runtime analysis. The findings show potential in applying the proposed method to very large ELM models with narrow band matrices.

Sme Ai Outreach In Finland—A Case Study, Kaj Mikael Björk, Anton Akusok, Amaury Lendasse, Leonardo Espinosa-Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a project (work in progress) where entrepreneurship and higher education in AI (from Master level to postdoc level) are integrated in order to produce a dual effect; helping SMEs to gain insight in how AI can aid in the corporate environment and to expose AI researchers to the real-life situations in the company world. If successful, the companies are made ready for the AI revolution and the researchers more equipped for corporate settings. The project is ongoing, so this paper addresses a work-in-progress project. The paper reflects on the project as well on some aspects that need …

Special Issue: Innovative Numerical Approaches For Problems In Science And Engineering, Xiaoming He, Shuhao Cao, Qiao Zhuang

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

Equilibrium Stability Under Nuclear Confrontation, Martin Bohner, A. A. Martynyuk

Mathematics and Statistics Faculty Research & Creative Works

This article proposes and analyzes mathematical models of confrontation between two and n countries, including countries with nuclear weapons. The proposed models are based on a generalization of Richardson's well-known mathematical model of the arms race. Namely, the factor of hostility is filled with expanded content, including public opinion and the armed forces of the opposing countries. Qualitative analysis of confrontation models is carried out by the method of Lyapunov functions and by applying nonlinear integral inequalities. As a result of the analysis, the conditions for the stability of the equilibrium state of the opposing countries are established, and the …

Threshold Asymmetric Conditional Autoregressive Range (Tacarr) Model, Isuru Ratnayake, V. A. Samaranayake

Mathematics and Statistics Faculty Research & Creative Works

This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed to vary across regimes. A self-adjusting threshold component, determined by past values of the series, is used to identify the prevailing market regime. In this way, the model is able to capture asymmetric and heteroscedastic volatility behavior in financial markets. The TACARR model is designed to address several limitations of existing price range models, including …

Reflections On Linear B, (Part 15): Sign 81 In Linear A And The Egyptian Four-Headed Ram God, Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

This article makes several tentative suggestions, including:

1. Linear A sign 81 (antecedent of Linear B81) may be an abbreviated image (two heads) of the four-headed Egyptian ram god Banebdjedet, with the horizontal line designating his horns shifted downward to the middle of the character.

2. A few other Linear A characters (e.g., sign 305) may represent slight alterations of sign A81.

3. Linear A82 includes two sets of three short horizontal lines. Those might signify brightness, and in the case of Banebdjedet the brightness would be his wisdom.

Orchestrating Bone Healing: Biomaterial-Driven Immunoengineering Of The Bone Microenvironment For Advanced Regenerative Therapies, Ah Joung Rachel Yu, Mohammad Reza Zare, Edikan Ogunnaike, Mostafa Yazdi

Chemical and Biochemical Engineering Faculty Research & Creative Works

Bone regeneration is a multistage and tightly regulated process driven by coordinated interactions between the immune and skeletal systems. While inflammation is essential for initiating repair, its dysregulation contributes to delayed union, nonunion, and impaired healing commonly seen in trauma, chronic disease, and aging. Traditional interventions, including autografts and inert biomaterials, provide structural support but fail to engage or modulate the immune microenvironment that governs successful regeneration. Emerging research in osteoimmunology has revealed the centrality of immune cell populations such as macrophages, T regulatory cells, dendritic cells, and myeloid-derived suppressor cells in directing osteogenesis, angiogenesis, and the resolution of inflammation. …

One Size Doesn’T Fit All: Navigating Gendered Ageism In Older Women’S Entry Into Entrepreneurship, Yanying Chen, Zijie Song, Chevy-Hanqing Fang

Business and Information Technology Faculty Research & Creative Works

Though older women may choose entrepreneurship as a way to escape discrimination in the labor market, they may face other forms of discrimination in the entrepreneurial domain. Drawing on intersectionality theory, we posit that older women encounter amplified discrimination due to the stereotype-consistent implications from gender and age norms, namely gendered ageism. Using 815,428 individual observations pooled across country–year surveys from 56 countries between 2009 and 2018, we found that older women were least likely to enter entrepreneurship. And this intersectional disadvantage could be mitigated by weakening the normative exclusion and possessing resource endowments that signal capability. However, strategies focused …