Engineering Commons^™

Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Iv. Effects Of Imprecisely Known Source Parameters, Ruixian Fang, Dan Gabriel Cacuci

Faculty Publications

By applying the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to the polyethylene-reflected plutonium (PERP) benchmark, this work presents results for the first- and second-order sensitivities of this benchmark’s leakage response with respect to the spontaneous fission source parameters. The numerical results obtained for these sensitivities indicate that the 1st-order relative sensitivity of the leakage response to the source parameters for the two fissionable isotopes in the benchmark are all positive, signifying that an increase in the source parameters will cause an increase in the total neutron leakage from the PERP sphere. The 1st- and 2nd-order relative sensitivities with respect to …

Advances In High-Resolution Radiation Detection Using 4h-Sic Epitaxial Layer Devices, Krishna C. Mandal, Joshua W. Kleppinger, Sandeep K. Chaudhuri

Faculty Publications

Advances towards achieving the goal of miniature 4H-SiC based radiation detectors for harsh environment application have been studied extensively and reviewed in this article. The miniaturized devices were developed at the University of South Carolina (UofSC) on 8 × 8 mm 4H-SiC epitaxial layer wafers with an active area of ≈11 mm². The thicknesses of the actual epitaxial layers were either 20 or 50 µm. The article reviews the investigation of defect levels in 4H-SiC epilayers and radiation detection properties of Schottky barrier devices (SBDs) fabricated in our laboratories at UofSC. Our studies led to the development of …

Critical Temperature Prediction Of Superconductors Based On Atomic Vectors And Deep Learning, Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu

Faculty Publications

In this paper, a hybrid neural network (HNN) that combines a convolutional neural network (CNN) and long short-term memory neural network (LSTM) is proposed to extract the high-level characteristics of materials for critical temperature (Tc) prediction of superconductors. Firstly, by obtaining 73,452 inorganic compounds from the Materials Project (MP) database and building an atomic environment matrix, we obtained a vector representation (atomic vector) of 87 atoms by singular value decomposition (SVD) of the atomic environment matrix. Then, the obtained atom vector was used to implement the coded representation of the superconductors in the order of the atoms in the chemical …

Multi-Mode Guided Wave Detection Of Various Composite Damage Types, Hanfei Mei, Robin James, Victor Giurgiutiu

Faculty Publications

This paper presents a new methodology for detecting various types of composite damage, such as delamination and impact damage, through the application of multimode guided waves. The basic idea is that various wave modes have different interactions with various types of composite damage. Using this method, selective excitations of pure-mode guided waves were achieved using adjustable angle beam transducers (ABTs). The tuning angles of various wave modes were calculated using Snell’s law applied to the theoretical dispersion curves of composite plates. Pitch–catch experiments were conducted on a 2-mm quasi-isotropic carbon fiber-reinforced polymer (CFRP) composite plate to validate the excitations of …

Catalysts For Polymer Membrane Fuel Cells, William E. Mustain, Bryan Pivovar

Faculty Publications

No abstract provided.

Towards Overcoming The Curse Of Dimensionality In Predictive Modelling And Uncertainty Quantification, Dan Gabriel Cacuci

Faculty Publications

This invited presentation summarizes new methodologies developed by the author for performing high-order sensitivity analysis, uncertainty quantification and predictive modeling. The presentation commences by summarizing the newly developed 3rd-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for linear systems, which overcomes the “curse of dimensionality” for sensitivity analysis and uncertainty quantification of a large variety of model responses of interest in reactor physics systems. The use of the exact expressions of the 2nd-, and 3rd-order sensitivities computed using the 3rd-ASAM is subsequently illustrated by presenting 3rd-order formulas for the first three cumulants of the response distribution, for quantifying response uncertainties (covariance, skewness) …

On The Importance Of Second-Order Response Sensitivities To Nuclear Data In Reactor Physics Uncertainty Analysis, Dan Gabriel Cacuci

Faculty Publications

This invited keynote presentation compares the relative importance of 1st-order versus 2nd-order sensitivities of the leakage response of an OECD/NEA benchmark (polyethylene-reflected plutonium sphere) to the nuclear data characterizing this benchmark. The imprecisely known parameters underlying the neutron transport computational model for this benchmark include 180 group-averaged total microscopic cross sections, 21600 group-averaged scattering microscopic cross sections, 60 parameters describing the fission process, 30 parameters describing the fission spectrum, 10 parameters describing the system's sources, and 6 isotopic number densities. Thus, this benchmark comprises 21886 1st-order sensitivities of the leakage response with respect to the model parameters, and 478,996,996 2nd-order …

Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar

Publications

The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive …

Relational Sequential Decision Making, Kaushik Roy

Publications

Markov Decision Processes(MDPs) are the standard for sequential decision making. Comprehensive theory and methods have been developed to deal with solving MDPs in the propositional setting. Real world domains however are naturally represented using objects and relationships. To this effect, relational adaptations of algorithms to solve MDPs have been proposed in recent years. This paper presents a study of these techniques both in the model based and model free setting.

Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur

Publications

Humans are able to provide symbolic knowledge in structured form for potential use by an AI system in learning human-desirable concepts. In clinical settings, for instance, prediction of patient outcomes by an AI can be guided by knowledge from patient history. This history contains concepts such as treatment information, observational and drug-related information, mental health conditions, and severity of disease/disorder. Additionally, there is also often a certain graphical structure to the knowledge among the concepts, for example, ”patient symptoms cause certain tests to be taken”, which in turn affects the prescription of medication. This type of structure between human interpretable …

Assessing The Severity Of Health States Based On Social Media Posts, Shweta Yadav, Joy Prakash Sain, Amit P. Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

Publications

The unprecedented growth of Internet users has resulted in an abundance of unstructured information on social media including health forums, where patients request healthrelated information or opinions from other users. Previous studies have shown that online peer support has limited effectiveness without expert intervention. Therefore, a system capable of assessing the severity of health state from the patients’ social media posts can help health professionals (HP) in prioritizing the user’s post. In this study, we inspect the efficacy of different aspects of Natural Language Understanding (NLU) to identify the severity of the user’s health state in relation to two perspectives(tasks) …

Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth

Publications

During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …

A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura

Faculty Publications

We have studied P adsorption on Ni(111), a system which shows complex adsorbate structures. We determined the phase diagram of the surface P adsorbed on Ni(111). At low coverage, amorphous P was observed. At temperatures between 373 and 673 K and coverages above 0.1 monolayer, we found a √7×√7 R19.1° structure, but above 673 K, other complex structures were created. These structures seemed to correlate with each other and we reinterpret a √7×√7 R19.1° structure of P adsorbed on Ni(111) based on the similarities of these surface structures. The new rectangular structure for the √7×√7 19.1° is discussed in relation …

A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura

Faculty Publications

We have studied P adsorption on Ni(111), a system which shows complex adsorbate structures. We determined the phase diagram of the surface P adsorbed on Ni(111). At low coverage, amorphous P was observed. At temperatures between 373 and 673 K and coverages above 0.1 monolayer, we found a √7×√7 R19.1° structure, but above 673 K, other complex structures were created. These structures seemed to correlate with each other and we reinterpret a √7×√7 R19.1° structure of P adsorbed on Ni(111) based on the similarities of these surface structures. The new rectangular structure for the √7×√7 19.1° is discussed in relation …

Microwave-Assisted And One-Step Synthesis Of Peg Passivated Fluorescent Carbon Dots From Gelatin As An Efficient Nanocarrier For Methotrexate Delivery, Nasser Arsalani, Parinaz Nezhad-Mokhtari, Esmaiel Jabbari

Faculty Publications

A green and simple process for preparing the polyethylene glycol passivated fluorescent carbon dots (CDs-PEG) have been studied by a microwave pyrolysis method, using gelatin and PEG as starting materials. This method is very effective for development of carbon-based quantum dots from gelatin with high quantum yield (QY). The synthesized CDs-PEG were found to emit blue photoluminescence (PL) with a maximum QY of 34%. At the following research, we investigated the effect of the presence of PEG on PL intensity, and the result showed that CDs-PEG becomes stronger PL properties than pure CDs from gelatin. The synthesized CDs-PEG were characterized …

Towards Overcoming The Curse Of Dimensionality: The Third-Order Adjoint Method For Sensitivity Analysis Of Response-Coupled Linear Forward/Adjoint Systems, Uncertainty Quantification And Predictive Modeling With Applications To Nuclear Energy Systems, Dan Gabriel Cacuci

Faculty Publications

This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-coupled forward and adjoint linear systems. The 3rd-ASAM enables the efficient computation of the exact expressions of the 3rd-order functional derivatives (“sensitivities”) of a general system response, which depends on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward and adjoint systems. Such responses are often encountered when representing mathematically detector responses and reaction rates in reactor physics problems. The 3rd-ASAM extends the 2nd-ASAM in the quest to overcome the “curse of dimensionality” in sensitivity analysis, uncertainty quantification and predictive …

Towards Overcoming The Curse Of Dimensionality: The Third-Order Adjoint Method For Sensitivity Analysis Of Response-Coupled Linear Forward/Adjoint Systems, With Applications To Uncertainty Quantification And Predictive Modeling, Dan Gabriel Cacuci

Faculty Publications

This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-coupled forward and adjoint linear systems. The 3rd-ASAM enables the efficient computation of the exact expressions of the 3rd-order functional derivatives ("sensitivities") of a general system response, which depends on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward and adjoint systems. Such responses are often encountered when representing mathematically detector responses and reaction rates in reactor physics problems. The 3rd-ASAM extends the 2nd-ASAM in the quest to overcome the "curse of dimensionality" in sensitivity analysis, uncertainty quantification and predictive …

Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: I. Effects Of Imprecisely Known Microscopic Total And Capture Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang, Jeffrey A. Favorite

Faculty Publications

The subcritical polyethylene-reflected plutonium (PERP) metal fundamental physics benchmark, which is included in the Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook, has been selected to serve as a paradigm illustrative reactor physics system for the application of the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) that was developed by Cacuci. The 2nd-ASAM enables the exhaustive deterministic computation of the exact values of the 1st-order and 2nd-order sensitivities of a system response to the parameters underlying the respective system. The PERP benchmark is numerically modeled in this work by using the deterministic multigroup neutron transport equation discretized …

Gasification Of Pelletized Corn Residues With Oxygen Enriched Air And Steam, Poramate Sittisun, Nakorn Tippayawong, Sirivatch Shimpalee

Faculty Publications

This work studied generation of producer gas using oxygen-enriched air and steam mixture as gasifying medium. Corn residues consisting of cobs and stover were used as biomass feedstock. Both corn residues were pelletized and gasified separately with normal air, oxygen enriched air and steam mixture in a fixed bed reactor. Effects of oxygen concentration in enriched air (21-50%), equivalence ratio (0.15-0.35), and steam to biomass ratio (0-0.8) on the yield of product gas, the combustible gas composition such as H2, CO, and CH4, the lower heating value (LHV), and the gasification efficiency were investigated. It was found that the decrease …

Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Ii. Effects Of Imprecisely Known Microscopic Scattering Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang

Faculty Publications

This work continues the presentation commenced in Part I of the second-order sensitivity analysis of nuclear data of a polyethylene-reflected plutonium (PERP) benchmark using the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM). This work reports the results of the computations of the first- and second-order sensitivities of this benchmark's computed leakage response with respect to the benchmark's 21,600 parameters underlying the computed group-averaged isotopic scattering cross sections. The numerical results obtained for the 21,600 first-order relative sensitivities indicate that the majority of these were small, the largest having relative values of O (10(-2)). Furthermore, the vast majority of the (21600)(2) second-order …

Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Iii. Effects Of Imprecisely Known Microscopic Fission Cross Sections And Average Number Of Neutrons Per Fission, Dan Gaberiel Cacuci, Ruixian Fang, J. A. Favorite, M. C. Badea, F. Di Rocco

Faculty Publications

The Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) is applied to compute the first-order and second-order sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental system with respect to the following nuclear data: Group-averaged isotopic microscopic fission cross sections, mixed fission/total, fission/scattering cross sections, average number of neutrons per fission (), mixed /total cross sections, /scattering cross sections, and /fission cross sections. The numerical results obtained indicate that the 1st-order relative sensitivities for these nuclear data are smaller than the 1st-order sensitivities of the PERP leakage response with respect to the total cross sections but are larger than those …

First Principles Investigation Of Anomalous Pressure-Dependent Thermal Conductivity Of Chalcopyrites, Loay Flalfy, Denis Music, Ming Hu

Faculty Publications

The effect of compression on the thermal conductivity of CuGaS2, CuInS2, CuInTe2, and AgInTe2 chalcopyrites (space group I-42d) was studied at 300 K using phonon Boltzmann transport equation (BTE) calculations. The thermal conductivity was evaluated by solving the BTE with harmonic and third-order interatomic force constants. The thermal conductivity of CuGaS2 increases with pressure, which is a common behavior. Striking differences occur for the other three compounds. CuInTe2 and AgInTe2 exhibit a drop in the thermal conductivity upon increasing pressure, which is anomalous. AgInTe2 reaches a very low thermal conductivity of 0.2 W·m−1 ·K −1 at 2.6 GPa, being beneficial …

Upcycling Single-Use Polyethylene Into High-Quality Liquid Products, Gokhan Celik, Robert M. Kennedy, Ryan A. Hackler, Magali Ferrandon, Akalanka Tennakoon, Smita Patnaik, Anne M. Lapointe, Salai Ammal, Andreas Heyden, Frédéric A. Perras, Marek Pruski, Susannah L. Scott, Kenneth R. Poeppelmeier, Aaron D. Sadow, Massimiliano Delferro

Faculty Publications

Our civilization relies on synthetic polymers for all aspects of modern life; yet, inefficient recycling and extremely slow environmental degradation of plastics are causing increasing concern about their widespread use. After a single use, many of these materials are currently treated as waste, underutilizing their inherent chemical and energy value. In this study, energy-rich polyethylene (PE) macromolecules are catalytically transformed into value-added products by hydrogenolysis using well-dispersed Pt nanoparticles (NPs) supported on SrTiO3 perovskite nanocuboids by atomic layer deposition. Pt/SrTiO3 completely converts PE (Mn = 8000− 158,000 Da) or a single-use plastic bag (Mn = 31,000 Da) into high-quality liquid …

Ligaos Is A Fast Li-Ion Conductor: A First-Principles Prediction, Xueling Lei, Wenjun Wu, Bo Xu, Chuying Ouyang, Kevin Huang

Faculty Publications

Solid Li-ion conducting electrolytes are highly sought for all solid-state Li-batteries, which are considered the next-generation safe batteries. Here a systematic computational study on the intrinsic transport properties of lithium gallium oxysulfide, LiGaOS (S. G. Pmc21), as a potential solid-state Li-ion electrolyte have been reported. The phonon dispersion spectrum analysis indicates that LiGaOS crystal structure is dynamically stable. The energy band structure and density of states calculations suggest that LiGaOS is an insulator with a wide indirect band gap of ∼5.44 eV. The CI-NEB calculations reveal that the “kick-off” collective migration via Li-interstitials is the dominant conduction mechanism …

Tissue-Specific Roles Of Transforming Growth Factor Beta Ligands In Cardiac Outflow Tract Malformations And Calcific Aortic Valve Disease, Nadia Al-Sammarraie

Theses and Dissertations

Congenital heart defects and adult calcific aortic valve disease are two of the leading causes of morbidity and mortality worldwide. To date, there is no medical cure and surgical intervention is the main option of treatment. The cardiac outflow tract is the major site for these abnormalities, which are triggered by genetic and/or environmental factors that alter development and/or homeostasis. Recently, significant roles of TGFβ signaling in development of cardiovascular disorders have become more evident in humans, however, the specific requirement of individual TGFβ ligands on the pathogenesis of OFT malformations and diseases remains elusive. In the present work, three …

Properties, Learning Algorithms, And Applications Of Chain Graphs And Bayesian Hypergraphs, Mohammad Ali Javidian

Theses and Dissertations

Probabilistic graphical models (PGMs) use graphs, either undirected, directed, or mixed, to represent possible dependencies among the variables of a multivariate probability distri- bution. PGMs, such as Bayesian networks and Markov networks, are now widely accepted as a powerful and mature framework for reasoning and decision making under uncertainty in knowledge-based systems. With the increase of their popularity, the range of graphical models being investigated and used has also expanded. Several types of graphs with dif- ferent conditional independence interpretations - also known as Markov properties - have been proposed and used in graphical models.

The graphical structure of a …

Quantification Of Material Degradation For Material State Awareness Of Composite Materials., Vahid Tavaf

Theses and Dissertations

The objectives of this research are to develop a comprehensive method to quantify the material degradation of composite materials in the presence of distributed damages and predict the failure in the defected composites using the updated effective material properties. Defects can grow in composites at the macro scale caused by the microscale voids, matrix cracks, fiber breakages starting from manufacturing processes to the high and low cycle fatigue loads, high temperature, and high humidity during operation. Hence, to predict a more realistic failure model, it is necessary to consider the repercussions of degraded materials. The proposed research work is divided …

Modeling Neutron Interaction Inside A 2d Reactor Using Monte Carlo Method, A. S. M. Fakhrul Islam

Theses and Dissertations

Scientists and engineers have been working for many years to develop accurate approaches to analyzing nuclear power reactors using computer codes that closely model the behavior of neutrons in a reactor core. The Monte Carlo simulation method is capable of treating complex geometries with a high level of resolution and fidelity to model neutron interactions inside a reactor core. With the requirement of accurate modeling in reactor physics and dynamics and great innovation of computer technology, Monte Carlo method is becoming an ever more powerful tool and receiving rising attention. In this study, Monte Carlo method is used to model …

Characterization And Drying Of Oxyhydroxides On Aluminum Clad Spent Nuclear Fuel, Matthew Shalloo

Theses and Dissertations

Research reactors such as the Advanced Test Reactor (ATR) and the High Flux Isotope Reactor (HFIR) employ aluminum-clad fuel elements made up of many thin plates with uranium dispersed within. In most engineering applications, aluminum is considered to have favorable corrosion characteristics. It forms a thin oxide layer [Al2O3] under atmospheric conditions that is impenetrable to oxygen thus stopping any further corrosion. However, both aluminum metal and Al2O3 react with water to form hydrous oxides which are less protective against further corrosion and form significantly thicker layers than oxidation in dry air. As a result, aluminum-clad spent nuclear fuel (ASNF) …

Experimental Investigation Of Hydraulic Effects On Unsaturated Soils Behaviors, Muwafaq Awad

Theses and Dissertations

Geo-structures are frequently constructed in or on soils with unsaturated conditions and are subjected to variations of moisture contents due to seasonal changes. Even though unsaturated soil mechanics have been established for several decades, it has not been fully implemented in practice today because of a lack of understanding of the interaction between the soil, water, and air phases. Many experimental research studies have been conducted to improve the understanding of unsaturated behavior but these studies are typically limited to small soil elements tested under fully drained conditions. The goal of this research is to evaluate the effect of hydraulics …