Digital Commons Network^™

Interpretable Battery Soh Prediction: A Comparative Interpretability Framework For Multi-Architecture Ml Models, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

This work introduces a unified interpretability-efficiency framework for lithium-ion battery state of health (SOH) prediction using hybrid deep learning architectures. We comparatively analyze four hybrid models: CNN LSTM MultiHead, CNN Feature Extractor LSTM, DNN LSTM, and DNN BiLSTM to disentangle how network topology, feature composition, and computational design influence both predictive fidelity and physical interpretability. By integrating Monte Carlo Shapley (MC Shapley), background occlusion SHAP (BoSHAP), and ablation analysis, we quantify the contribution and robustness of five electrochemical feature groups: time, capacity, voltage, dQ/dV and peaks of dQ/dV from NASA battery dataset. The results reveal a consistent dominance of differential …

An Explainable Cs-Mitigation Triangular (Ecsmt) Framework To Secure Graph Neural Networks, Sabah Ettahri, Sergio Pallas Enguita, Chung-Hao Chen, Wen-Chao Yang

Electrical & Computer Engineering Faculty Publications

This research addresses cyber risk by defending against backdoor attacks on Graph Neural Networks (GNNs). We propose the Explainable Complex System-Mitigation Triangular (ECSMT) Framework, which integrates Robust Training, Graph Regularization, and Data Sanitization into a lightweight, hardware-efficient defense layer. To evaluate structural generalizability, we conducted empirical evaluations across three distinct benchmark domains (AIDS, MUTAG, and PROTEINS) using a Graph Isomorphism Network (GIN) backbone. Under a baseline 5% backdoor subgraph trigger injection ratio, ECSMT achieves excellent utility retention, securing a Clean Accuracy (CA) of 97.33% (±0.62%) while reducing the Attack Success Rate (ASR) from 97.00% down to 69.45% on the primary …

Generative Ai-Driven Optimization In Flexible And Reconfigurable Manufacturing Systems, Salah Hammedi, Hicham Chaoui, Lotfi Nabli

Electrical & Computer Engineering Faculty Publications

Flexible and Reconfigurable Manufacturing Systems (FRMSs) are essential for coping with variability in modern production environments; however, efficient scheduling and rapid reconfiguration remain challenging. This paper presents a hybrid optimization framework that integrates Colored Petri Net (CPN) modeling with Generative Artificial Intelligence (GenAI) to enhance scheduling performance and system adaptability. The CPN formalism ensures verifiable modeling of system dynamics, while a transformer-based generative model produces candidate scheduling and reconfiguration strategies. Simulation experiments were conducted under static, dynamic, and adaptive scenarios, including machine breakdowns and dynamic job arrivals. Performance was evaluated using makespan, mean flow time, machine utilization, and reconfiguration latency. …

Generalized Inverter Fault Detection Using Normalized Current Features And A Lightweight Bilstm Network, Mohammad Zamani Khaneghah, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on …

Affordable Course Content And Open Education Resources For Undergraduate Courses Teaching Fundamentals Of Wireless Communications And Networking, Dimitrie C. Popescu, Otilia Popescu

Electrical & Computer Engineering Faculty Publications

Wireless communication systems and networks along with the services they provide have become an essential component of the modern 21st century society, fueling job growth in the wireless industry and increasing the need for engineers specialized in wireless communication systems. As a consequence, over the past two decades, undergraduate courses teaching fundamentals of wireless communication systems and networks have become common in electrical and computer engineering and technology programs. At the same time, the number of textbooks dedicated to wireless systems and networks published by mainstream publishers has also grown, with availability in various formats and offerings and a significant …

When Slides Replace Thinking: How Powerpoint Culture Undermines Conceptual Learning In Engineering Education, Shahin Nayyeri Amiri, Hamid Eisazadeh

Civil & Environmental Engineering Faculty Publications

Engineering education has gradually shifted from deep conceptual teaching to a culture dominated by presentation slides. In many universities today, core courses such as Statics, Dynamics, and Mechanics of Materials are taught through PowerPoint files rather than through reasoning, derivation, and problem solving. While slide-based instruction may appear efficient, it encourages passive learning and has severely weakened students’ ability to think independently and make sound engineering judgments. Traditionally, these fundamental courses were taught by seasoned instructors who had mastered the subjects and took genuine pride in explaining complex ideas with clarity and passion. They guided students through the logic behind …

Flood-Season Surface Water-Groundwater Interactions Across Distinct Geomorphic Units In A Yellow River Great Bend Tributary Basin, Yinlong Wang, Ruizhong Gao, Debin Jia, Xixi Wang, Tingxi Liu, Xiaomin Liu, Shiming Bai

Civil & Environmental Engineering Faculty Publications

Surface water-groundwater interactions are complex in the Great Bend region of the Yellow River. Clarifying water exchange and source differences among geomorphic units is important for understanding regional hydrological processes and improving water resources management. In this study, the Wulanmulun River Basin, a typical tributary of the Yellow River, was selected as the study area. A total of 90 water samples were collected, including 25 river water samples, 43 groundwater samples, and 22 precipitation samples. Gibbs diagrams, multivariate statistical analysis, PMF, and MixSIAR models were used to investigate the hydrochemical and isotopic characteristics, source contributions, and transformation relationships of surface …

Parametric Study Of Yields And Properties Of Corn Stover-Derived Hydrothermal Liquefaction Products By Using Statistical Approaches, Isamu Umeda, Meicen Liu, Jiefu Wang, Yi Zheng, Zhiwu Wang, Jaya Shankar Tumuluru, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PCA) and regression modeling to predict AP solution weight, LBO weight and fuel characteristics, and HTL wastewater biodegradability, as well as to improve prediction accuracy for SR and HBO under various operating conditions (temperature: 250–350 °C, residence time: 5–60 min, and the combined solid loading of three batches: 15–45 g). A complementary relationship between SR and AP weights found in PCA enabled the estimation of AP weight based on …

Multi-Isotope Tracing Reveals Nitrate And Sulfate Sources And Fate Across Contrasting Activity Zones In A Semi-Arid Basin Of Northern China, Chang Yue, Ruizhong Gao, Limin Duan, Tianke Su, Xixi Wang, Tingxi Liu, Guoqiang Wang

Civil & Environmental Engineering Faculty Publications

In semi-arid surface water-groundwater systems, nitrate (NO₃^–) and sulfate (SO₄²^–) are jointly influenced by natural processes and anthropogenic activities, yet how their sources, transformations, and export vary across contrasting activity zones remains insufficiently understood. Integrating hydrochemistry, multiple stable isotopes, a Bayesian isotope mixing model, and representative-section flux analysis, this study investigated the source compositions, transformation processes, and export differences of NO₃^– and SO₄²^– in the Dahei River Basin.   New hydrological insights for the region: Results showed greater SO₄²^– enrichment in high-activity zones, whereas NO₃^– exceedance was more prominent in low-activity zones. In …

Resilient Built Environment: An Overview On Design Strategies For Coastal Adaptation To Sea Level Rise, Farzaneh Soflaei, Gelareh Abdolzadeh, Navid Ziaee, Mohammad Amin Jafari, Faeghe Borhani

Civil & Environmental Engineering Faculty Publications

This paper delves into the escalating risks faced by urban coastal communities due to tidal and storm flooding, exacerbated by climate change-induced Sea Level Rise (SLR). Projections indicate a potential increase in sea levels by at least 3 feet by 2100, with historical data revealing an average annual rise of 1.2-1.7 mm since the 1900s. With over 300 million individuals inhabiting coastal areas, low-lying regions emerge as particularly vulnerable to the impacts of SLR. This accelerated rise amplifies the significant challenge of nuisance flooding, a local-scale issue aggravated by high tide and winds, leading to inundation, road closures, infrastructure deterioration, …

Physics-Based Multi-Hazard Fragility Modeling Of Low-Rise Wood-Frame Buildings Under Hurricane-Induced Wind And Surge, Mumtasirun Nahar, Abdullah M. Braik, Mohammad Syed, Maria Koliou, Petros Sideris

Civil & Environmental Engineering Faculty Publications

Coastal buildings are exposed to concurrent hurricane-induced wind and storm surge, yet their vulnerability is commonly assessed using separate single-hazard models that neglect hazard interaction. This study developed a physics-based finite element framework to evaluate the performance of a low-rise light wood-frame building under simultaneous wind and surge-wave loading. A detailed three-dimensional model was constructed using a sub-assembly strategy that explicitly represented framing members, sheathing systems, and critical connections. Structural response was evaluated across a hazard space defined by wind speed, still-water depth, and flow velocity, and component- and system-level fragility functions were derived using Monte Carlo simulation and generalized …

Consensus And Controversies Of International Guidelines For The Diagnosis, Surveillance, And Management Of Fetal Growth Restriction: An Updated Comparison, Daniele Diane Mascio, Suneet P. Chauhan, Tullio Ghi, Asma Khalil, Juliana G. Martins, Sara Sorrenti, Tamara Stampalija, Fabrizio Zullo, Francesc Figueras

Department of Obstetrics & Gynecology Faculty Publications

OBJECTIVE: To compare areas of consensus and disagreements across contemporary international and national guidelines on the diagnosis, surveillance, and management of fetal growth restriction (FGR).

DATA SOURCES: Electronic searches of MEDLINE from database inception up to March 2026 using MeSH terms and keywords related to FGR and guidelines. STUDY ELIGIBILITY CRITERIA: Critical, structured comparison of national or international guidelines on FGR published since 2010. Final inclusion required unanimous agreement from all authors.

STUDY APPRAISAL AND SYNTHESIS METHODS: Pre-specified extraction across domains: definition; prediction/prevention; surveillance tools and frequency; delivery timing and mode; and labor induction methods. Dual data …

H2 Matrix Compression For Fast Magnetic Field Post-Processing, Calvin M. Demps

University of Kentucky Master's Theses

Large-scale computational electromagnetic simulations frequently require the assembly of dense system matrices, whose computation time and memory cost grow rapidly with problem size and can render high-resolution simulations impractical. This thesis presents a benchmark of the H² hierarchical matrix method applied to the construction of a coupling matrix that maps magnetization current in a structure to the magnetic field at observation points external to the structure. The underlying field interaction is derived from Maxwell's equations and discretized using a Nyström approach, producing a dense matrix.

The method is benchmarked across various geometries of increasing complexity and for increasing mesh …

Development Of An Atmospheric Particle Imaging System (Apis), James W. Hebert

University of Kentucky Master's Theses

The study of atmospheric particulates plays a crucial role in both climate change studies and the improvement of hypersonic travel. The current issue at hand is a lack of knowledge of stratospheric particulate content and the high cost that is associated with conducting research at these altitudes. This project focuses on the development of an Atmospheric Particle Imaging System (APIS) to be a low-weight, low-cost optical payload. The goal is to make a device that can be mounted onto an uncrewed aerial system that has the capability of imaging particulates moving at steady flow velocities, and thereby characterize the individual …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

Development Of Thermal Joints For Conduction-Cooling Applications, J. Lewis, G. Ciovati

Mechanical & Aerospace Engineering Faculty Publications

In support of the development of conduction-cooled superconducting radiofrequency (SRF) niobium cavities for use in continuous-wave linear accelerators, an experimental study of thermal contact resistance was performed on bolted joints using high-purity niobium, aluminium, and copper along with Apiezon N grease and indium foil as interfacial materials. The geometry of each joint investigated aims at replicating the design adopted in conduction-cooled SRF cavities currently under development at Jefferson Lab. The materials' thermal conductivity and the joints' thermal resistance were measured in the temperature range of 3.5 - 10 K. The results showed that the low thermal contact resistance of 2-4 …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress-strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Untrained Position-Encoded Multilayer Perceptron Network For Structured Illumination Microscopy Reconstruction, Sahil Sharma, Leonidas Zimianitis, Krishnendu Samanta, Balpreet Singh Ahluwalia, Joby Joseph, Dushan N. Wadduwage

Computer Science Faculty Publications

Structured Illumination Microscopy (SIM) enables super-resolution imaging by encoding high-frequency spatial information through patterned light. While traditional Fourier-based reconstruction methods are prone to artifacts under suboptimal conditions, recent deep learning approaches often require large training datasets and lack adaptability across different imaging setups. In this work, we present Position Encoded Multi-Layer Perceptron (PEM) network that leverages implicit neural representations (INRs) and SIM forward-model-driven modeling to reconstruct super-resolved images without any training data. PEM-SIM represents each spatial coordinate as a combination of sinusoidal functions across multiple frequencies, enabling rich encoding of fine spatial detail. A forward model grounded in SIM image …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Towards Supporting Real-Time Estimation Of Vehicle Fuel Consumption And Co2 Emissions In Smart City Applications, Abrar Alali, Stephan Olariu

Computer Science Faculty Publications

This paper evaluates a simplified physics-based energy demand model designed to estimate vehicle fuel consumption and CO₂ emissions—a critical tool for sustainable transportation planning and smart city applications. Unlike data-driven regression models that lack generalizability for user-defined conditions or complex physics-based approaches that rely on extensive, often proprietary data, the simplified model is distinguished by its minimal parameter requirements, depending primarily on a single, overarching powertrain efficiency value. A key contribution is the comprehensive empirical evaluation of the simplified model against official Environmental Protection Agency (EPA) test data across multiple driving cycles and vehicle types, providing a rigorous validation previously …

Dynamic Modeling Of The Earth's Trapped Proton Environment, Xiaojing Xu, Steve R. Blattnig, Francis F. Badavi, Martha S. Clowdsley, Edward J. Semones

Physics Faculty Publications

Context: Reliable prediction of space radiation exposure is critical for safeguarding spacecraft systems and ensuring astronaut health during missions. Accurate radiation risk assessment for space mission requires advanced models of the Earth’s trapped proton environment. These models must reflect temporal variations driven by geomagnetic field evolution and solar cycle modulation. Existing static models, such as AP8 and IRENE-AP9, are not designed to fully capture these evolving conditions. Aims: This paper presents a dynamic modeling method for the prediction of trapped proton fluxes, which incorporate time-dependent variations due to geomagnetic field evolution and solar cycle fluctuations. Methods: The …

Reaching The Intrinsic Performance Limits Of Superconducting Nanowire Single-Photon Detectors Up To 0.1 Mm Wide, Kristen M. Parzuchowski, Eli Mueller, Bakhrom G. Oripov, Benedikt Hampel, Ravin A. Chowdhury, Sahil R. Patel, Daniel Kuznesof, Emma K. Batson, Ryan Morgenstern, Robert H. Hadfield, Varun B. Verma, Matthew D. Shaw, Jason P. Allmaras, Martina J. Stevens, Alex Gurevich, Adam N. Mccaughan

Physics Faculty Publications

Superconducting nanowire single-photon detectors combine high detection efficiency, low noise, and excellent timing resolution, making them a leading platform for photon-counting applications. However, despite decades of materials and fabrication research, detector performance has never been shown to match theoretical performance expectations. Here, we demonstrate in situ tuning of a detector from its typical, suboptimal operation, to a regime limited only by material quality, allowing the device to reach its intrinsic performance limit. Our approach is based on current-biased superconducting “rails” placed on either side of the detector that redistribute current across its width to achieve peak performance. This technique reduces …

On Distribution Matching For Probabilistic Constellation Shaping, Dimitrie C. Popescu, Cameron Kowski

Electrical & Computer Engineering Faculty Publications

Distribution matching (DM) transforms a stream of equally likely bits into digital symbols that correspond to a specific digital modulation scheme with probabilities of occurrence following a specified statistical distribution. This technique is referred to as probabilistic constellation shaping (PCS), and using the Maxwell–Boltzmann (MB) distribution improves spectral and energy efficiency of digital modulation schemes by enabling more frequent transmissions of lower energy digital symbols. The background behind PCS is presented in the paper and the two main DM methods widely used in practice are discussed, outlining scenarios in which one DM method may be preferable over the other. For …

A Low-Cost Fourier-Based Dual-Pump Mock Circulatory Loop For Arterial Pressure Waveform Reproduction, Victor K. Tsui, Kouhyar Tavakolian, Daniel Ewert

Electrical & Computer Engineering Faculty Publications

Cardiovascular diseases are among the leading causes of death worldwide, creating a need for reliable hemodynamic testing platforms for cardiovascular device evaluation and therapeutic development. Mock circulatory loops (MCLs) provide effective in vitro platforms for reproducing physiological and pathological pressure conditions; however, many existing systems remain limited in programmability, waveform fidelity, standardization, and affordability. This study presents a cost-effective dual-pump hybrid MCL (hMCL) that independently regulates baseline and pulsatile pressure components using Fourier-based harmonic synthesis. Reference arterial pressure waveforms were decomposed into harmonic components, and their amplitudes, frequencies, and phase shifts were converted into pulse-width-modulation signals for dual-pump actuation. Validation …

High Temperature Creep Deformation Mechanism Of Fe28.2ni18.8mn32.9al14.1cr6 High Entropy Alloy And Its Modified Alloys, Edwin S. Jiang, I. Baker

Dartmouth College Ph.D Dissertations

Fe28.2Ni18.8Mn32.9Al14.1Cr6 eutectic high entropy alloy exhibits a good combination of room-temperature and high temperature properties, including tensile strength, ductility, and corrosion resistance, making it a promising candidate for structural applications in extreme environments. However, the creep deformation behavior of this alloy— and high-entropy alloys (HEAs) in general—remains insufficiently understood. This dissertation systematically investigates the high-temperature creep deformation mechanisms of Fe28.2Ni18.8Mn32.9Al14.1Cr6 and its derivatives.

Creep mechanisms and associated microstructural changes were examined across a wide range of strain rates using strain-rate jump and constant-stress tests. Two dominant regimes were identified: dislocation glide/solute-drag at low strain rates, and dislocation climb at high …

Early-Time/High-Frequency Electromagnetic Induction Sensing For Minimal-Metal And None-Metallic Subsurface Targets, Michele Louise Maxson

Dartmouth College Ph.D Dissertations

Conventional electromagnetic induction (EMI) systems operate within the quasi-static regime, where measurements are dominated by conduction currents and are primarily sensitive to highly conductive targets and bulk soil properties. As a result, these systems exhibit limited sensitivity to low-conductivity and layered media, such as permafrost, composite materials, and minimum-metal landmines, where diagnostically relevant information resides in early-time/high-frequency electromagnetic responses, generally above 100 kHz. This limitation reflects a mismatch between conventional EMI system design and the underlying target physics, restricting the ability of standard EMI approaches to resolve fine-scale non-metallic subsurface structure.

In this thesis, I investigate early-time/high-frequency sensitivity as a …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …

Personality Exceptions: Enhancing Character In Narrative Planners With Internal Memory, Elinor Rubin-Mcgregor

University of Kentucky Doctoral Dissertations

Stories and narratives are powerful tools for forging connections between people, as they induce emotions shared through their audience and help build empathy and understanding through sharing unique perspectives. Interactive stories can do all this and more, as they can be used to better educate and engage their audience. But in such stories, the characters must have consistent personality and human-like emotions in order for the audience to relate to them. Current implementations of personality in interactive narratives either portrays characters with static personality that feel less realistic, or else require a great deal of additional work from the author …

Investigation Of Fine-Grain Cu And Cu Alloys For Low-Temperature Hybrid Bonding Applications, Sarabjot Singh

Electronic Theses & Dissertations (2024 - present)

Hybrid bonding has emerged as a key enabler for next-generation three-dimensional (3D) integration, offering fine-pitch interconnects and improved electrical performance. However, conventional Cu–Cu hybrid bonding typically requires elevated temperatures to achieve sufficient diffusion and interface quality, posing challenges for temperature-sensitive device integration and process compatibility. This work investigates materials engineering approaches to enable low-temperature Cu–Cu bonding through both microstructure design and alloying strategies.

This work begins by examining grain refinement in Cu as a pathway to enhance diffusion through increased grain boundary density, providing efficient atomic transport without introducing additional elements. Three Cu-based systems Cu–Co, Cu–Ag, and Cu–Al were systematically …

Improving Modeling Of Corrosion Products In The Primary Circuit Of Light Water Reactors Through The Experimental Determination Of Crud Characteristics, Sri Saravana Konganapuram Narasimma Bharathi

Electronic Theses & Dissertations (2024 - present)

High-temperature water flowing through the coolant circuits in pressurized water reactors (PWRs) creates a harsh environment, deteriorating these materials. This corrosion results in the formation of oxide layer(s) primarily composed of nickel ferrites, iron oxides, nickel oxides, and other nickel-iron-chrome spinel oxides. Being exposed to fluid with high flow rates and pressure, these oxide layers can be eroded, resulting in particulate fouling due to the release of corrosion products (Chalk River Unidentified Deposits, CRUD) into the coolant circuit. When CRUD subsequently deposits on fuel surfaces, it negatively affects the fuel performance (heat transfer and fuel failure); in addition, the particles …