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Wikimarks: Harvesting Relevance Benchmarks From Wikipedia, Laura Dietz, Shubham Chatterjee, Connor Lennox, Sumanta Kashyapi, Pooja Oza, Ben Gamari Jul 2022

Wikimarks: Harvesting Relevance Benchmarks From Wikipedia, Laura Dietz, Shubham Chatterjee, Connor Lennox, Sumanta Kashyapi, Pooja Oza, Ben Gamari

Computer Science Faculty Research & Creative Works

We provide a resource for automatically harvesting relevance benchmarks from Wikipedia - which we refer to as "Wikimarks"to differentiate them from manually created benchmarks. Unlike simulated benchmarks, they are based on manual annotations of Wikipedia authors. Studies on the TREC Complex Answer Retrieval track demonstrated that leaderboards under Wikimarks and manually annotated benchmarks are very similar. Because of their availability, Wikimarks can fill an important need for Information Retrieval research. We provide a meta-resource to harvest Wikimarks for several information retrieval tasks across different languages: paragraph retrieval, entity ranking, query-specific clustering, outline prediction, and relevant entity linking and many more. …

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Bert-Er: Query-Specific Bert Entity Representations For Entity Ranking, Shubham Chatterjee, Laura Dietz Jul 2022

Bert-Er: Query-Specific Bert Entity Representations For Entity Ranking, Shubham Chatterjee, Laura Dietz

Computer Science Faculty Research & Creative Works

Entity-oriented search systems often learn vector representations of entities via the introductory paragraph from the Wikipedia page of the entity. As such representations are the same for every query, our hypothesis is that the representations are not ideal for IR tasks. In this work, we present BERT Entity Representations (BERT-ER) which are query-specific vector representations of entities obtained from text that describes how an entity is relevant for a query. Using BERT-ER in a downstream entity ranking system, we achieve a performance improvement of 13-42% (Mean Average Precision) over a system that uses the BERT embedding of the introductory paragraph …

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Machine Learning Boosts Performance Of Optical Fiber Sensors: A Case Study For Vector Bending Sensing, Chen Zhu, Jie Huang Jul 2022

Machine Learning Boosts Performance Of Optical Fiber Sensors: A Case Study For Vector Bending Sensing, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

The Spectral Response Produced When a High-Sensitivity Optical Fiber Sensor (OFS) is Subject to an External Perturbation Has Recently Been Shown to Contain Rich Information that Can Be Potentially Exploited for Multi-Dimensional Sensing. in This Article, We Propose the Use of Machine Learning to Directly and Statistically Learn the Relation between the Complex Spectral Response from an OFS and a Measurand of Interest, Without Knowing If There Are Distinct and Tractable Features in the Spectrum. as a Proof-Of-Concept Demonstration, It is Shown that a Simple Heterostructure-Based Device with a Capillary Tube Sandwiched between Two Single-Mode Fibers Without Any Fiber Modification …

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Combination Of High Ph And An Antioxidant Improves Chemical Stability Of Two-Dimensional Transition-Metal Carbides And Carbonitrides (Mxenes) In Aqueous Colloidal Solutions, Shuohan Huang, Vadym Mochalin Jul 2022

Combination Of High Ph And An Antioxidant Improves Chemical Stability Of Two-Dimensional Transition-Metal Carbides And Carbonitrides (Mxenes) In Aqueous Colloidal Solutions, Shuohan Huang, Vadym Mochalin

Chemistry Faculty Research & Creative Works

MXenes, a large family of two-dimensional (2D) transition-metal carbides/nitrides, have attracted increased attention in recent years because of their excellent electronic, mechanical, thermal, and optical properties. Studying chemical properties of MXenes is important to prolong the shelf life of their colloids and provide robust performance of MXenes in devices and applications. While the role of MXene reactivity with the environment, including water and components of air, is becoming more recognized, less is known about the role of parameters influencing the reactivity. In this work, we investigate the individual and combined effects of the pH and antioxidant on chemical stability of …

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Life Cycle Cost Analysis Of High Friction Surface Treatment Applications, Eslam Deef-Allah, Korrenn Broaddus, Magdy Abdelrahman Jul 2022

Life Cycle Cost Analysis Of High Friction Surface Treatment Applications, Eslam Deef-Allah, Korrenn Broaddus, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Life cycle cost analyses for high friction surface treatment (HFST) applications were executed relying on a Microsoft Excel program developed by the researchers. Calcined bauxite (CB), five CB alternatives, and epoxy binder were utilized in the HFST applications. The aggregates' performances were evaluated through the aggregate image measurement system (AIMS) before and after Micro-Deval polishing. The performance of the HFST applications was evaluated by the dynamic friction tester (DFT) and British pendulum (BP). The major purpose of this program was to present a rational method for converting different input data (project and material specifics) to comparable output data (net present …

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Quantification Of The State Of Practice Of Offsite Construction And Related Technologies: Current Trends And Future Prospects, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy Jul 2022

Quantification Of The State Of Practice Of Offsite Construction And Related Technologies: Current Trends And Future Prospects, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Although some researchers and practitioners have perceived that the current reliance on offsite construction methods is high, other studies have hypothesized that the use of offsite construction techniques is still considered to be somehow limited. To this end, this paper aims to quantify the state of practice of offsite construction in terms of current trends and future prospects for the overall industry as well as the following main sectors: industrial, building and commercial, and infrastructure. First, a questionnaire was formed, pilot-tested, distributed, and completed by 100 construction practitioners. Second, the questionnaire's internal and external validity and reliability were examined using …

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The Impact Of Offsite Construction On The Workforce: Required Skillset And Prioritization Of Training Needs, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy Jul 2022

The Impact Of Offsite Construction On The Workforce: Required Skillset And Prioritization Of Training Needs, Rayan H. Assaad, Islam H. El-Adaway, Makarand Hastak, Kim Lascola Needy

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Offsite construction has showed great potential in addressing many of the industry's problems. While multiple research efforts have been directed at examining different offsite construction aspects, few studies investigated the workforce-related aspects. Therefore, this study aims to address this knowledge gap by examining the impact of offsite construction on the workforce, as represented by the following five workforce categories: offsite, onsite, engineering and design, construction and fabrication, and administrative workforce. To this end, this paper (1) determined the impact of offsite construction on the skillset (reskilling or upskilling) and the demand (shrink or growth) for the offsite and onsite construction …

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Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner Jul 2022

Derivation And Analysis Of A Discrete Predator–Prey Model, Sabrina H. Streipert, Gail S.K. Wolkowicz, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We derive a discrete predator–prey model from first principles, assuming that the prey population grows to carrying capacity in the absence of predators and that the predator population requires prey in order to grow. The proposed derivation method exploits a technique known from economics that describes the relationship between continuous and discrete compounding of bonds. We extend standard phase plane analysis by introducing the next iterate root-curve associated with the nontrivial prey nullcline. Using this curve in combination with the nullclines and direction field, we show that the prey-only equilibrium is globally asymptotic stability if the prey consumption-energy rate of …

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Mgard+: Optimizing Multilevel Methods For Error-Bounded Scientific Data Reduction, Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky Jul 2022

Mgard+: Optimizing Multilevel Methods For Error-Bounded Scientific Data Reduction, Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky

Computer Science Faculty Research & Creative Works

Nowadays, data reduction is becoming increasingly important in dealing with the large amounts of scientific data. Existing multilevel compression algorithms offer a promising way to manage scientific data at scale but may suffer from relatively low performance and reduction quality. In this paper, we propose MGARD+, a multilevel data reduction and refactoring framework drawing on previous multilevel methods, to achieve high-performance data decomposition and high-quality error-bounded lossy compression. Our contributions are four-fold: 1) We propose to leverage a level-wise coefficient quantization method, which uses different error tolerances to quantize the multilevel coefficients. 2) We propose an adaptive decomposition method which …

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Metastable Olivine Within Oceanic Lithosphere In The Uppermost Lower Mantle Beneath The Eastern United States, Fansheng Kong, Stephen S. Gao, Kelly H. Liu, Yinxia Fang, Hejun Zhu, Robert J. Stern, Jiabiao Li Jul 2022

Metastable Olivine Within Oceanic Lithosphere In The Uppermost Lower Mantle Beneath The Eastern United States, Fansheng Kong, Stephen S. Gao, Kelly H. Liu, Yinxia Fang, Hejun Zhu, Robert J. Stern, Jiabiao Li

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Approximately two-thirds of Earth's outermost shell is composed of oceanic plates that form at spreading ridges and recycle back to Earth's interior in subduction zones. A series of physical and chemical changes occur in the subducting lithospheric slab as the temperature and pressure increase with depth. In particular, olivine, the most abundant mineral in the upper mantle, progressively transforms to its high-pressure polymorphs near the mantle transition zone, which is bounded by the 410 km and 660 km discontinuities. However, whether olivine still exists in the core of slabs once they penetrate the 660 km discontinuity remains debated. Based on …

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A Proactive Risk Assessment Framework To Maximize Schedule Benefits Of Modularization In Construction Projects, Mohamad Abdul Nabi, Islam H. El-Adaway Jul 2022

A Proactive Risk Assessment Framework To Maximize Schedule Benefits Of Modularization In Construction Projects, Mohamad Abdul Nabi, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Various studies developed models and decision support tools to assess the feasibility and optimize the use of modularization. However, none has explored the schedule benefits of modular construction. This paper fills this knowledge gap. To this end, the authors completed the following: (1) analyzed the criticalities of the various modular risk factors on potential schedule savings using data collected from 48 industry professionals, (2) investigated the schedule savings associated with the use of modularization using data collected from 68 modular construction projects, and (3) developed an interrelated assessment model to calculate the schedule savings of using modularization. The provided model …

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An Explicit Time-Domain Finite-Element Boundary Integral Method For Analysis Of Electromagnetic Scattering, Ming Dong, Liang Chen, Lijun Jiang, Ping Li, Hakan Bagci Jul 2022

An Explicit Time-Domain Finite-Element Boundary Integral Method For Analysis Of Electromagnetic Scattering, Ming Dong, Liang Chen, Lijun Jiang, Ping Li, Hakan Bagci

Electrical and Computer Engineering Faculty Research & Creative Works

A numerical scheme, which hybridizes the element-level dual-field time-domain finite-element domain decomposition method (ELDDM) and the time-domain boundary integral (TDBI) method to accurately and efficiently analyze open-region transient electromagnetic scattering problems, is proposed. Element-level decomposition decouples Maxwell equations on a discretization element from those on its neighboring elements using equivalent currents defined on their faces. For any element inside the computation domain, the equivalent currents are obtained from fields in the neighboring elements. For any element on the boundary of the computation domain, the equivalent currents are obtained using the fields generated by TDBI. To generate these fields, TDBI 'radiates' …

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Experimentation And Correlation Development Of Mass Transfer In A Mimicked Fischer–Tropsch Slurry Bubble Column Reactor, Lu Han, Mahmoud M. Taha, Premkumar Kamalanathan, Nora Y. Selem, Muthanna H. Al-Dahhan Jul 2022

Experimentation And Correlation Development Of Mass Transfer In A Mimicked Fischer–Tropsch Slurry Bubble Column Reactor, Lu Han, Mahmoud M. Taha, Premkumar Kamalanathan, Nora Y. Selem, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Gas–liquid volumetric mass transfer coefficient "kLa " for CH4, CO2, and Ar were experimentally measured at different conditions in a mimicked Fischer–Tropsch (FT) slurry bubble column reactor by using a non-invasive gaseous tracer technique and the axial dispersion model. Results validate the square root relation, between kLa and diffusivity "Dg", that can be used to predict kLa for different species with k La values available in the literature. Additionally, Higbie's penetration theory was adopted along with bubble dynamics parameters estimation to develop a correlation for predicting kL …

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Probing The Extragalactic Mid-Infrared Background With Hawc, A. Albert, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A.Ayala Solares, R. Babu, E. Belmont-Moreno, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, O. Chaparro-Amaro, U. Cotti, J. Cotzomi, S. Coutiño De León, E. De La Fuente, R. Diaz Hernandez, M. A. Duvernois, M. Durocher, J. C. Diaz-Velez, K. Engel, C. Espinoza, K. L. Fan, M. Fernandez Alonso, N. Fraija, J. A. Garcia-Gonzalez, F. Garfias, M. M. Gonzalez, J. A. Goodman, J. P. Harding, S. Hernandez, D. Huang, F. Hueyotl-Zahuantitla, P. Huntemeyer, A. Iriarte, A. Jardin-Blicq, V. Joshi, D. Kieda, W. H. Lee, J. T. Linnemann, A. L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, E. Moreno, M. Mostafa, A. Nayerhoda, L. Nellen, M. Newbold, M. U. Nisa, R. Noriega-Papaqui, N. Omodei, A. Peisker, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, H. Salazar, D. Salazar-Gallegos, F. Salesa Greus, A. Sandoval, J. Serna-Franco, A. J. Smith, Y. Son, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, L. Villasenor, Xiaojie Wang, T. Weisgarber, E. Willox, H. Zhou, C. De Leon Jul 2022

Probing The Extragalactic Mid-Infrared Background With Hawc, A. Albert, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A.Ayala Solares, R. Babu, E. Belmont-Moreno, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, O. Chaparro-Amaro, U. Cotti, J. Cotzomi, S. Coutiño De León, E. De La Fuente, R. Diaz Hernandez, M. A. Duvernois, M. Durocher, J. C. Diaz-Velez, K. Engel, C. Espinoza, K. L. Fan, M. Fernandez Alonso, N. Fraija, J. A. Garcia-Gonzalez, F. Garfias, M. M. Gonzalez, J. A. Goodman, J. P. Harding, S. Hernandez, D. Huang, F. Hueyotl-Zahuantitla, P. Huntemeyer, A. Iriarte, A. Jardin-Blicq, V. Joshi, D. Kieda, W. H. Lee, J. T. Linnemann, A. L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, E. Moreno, M. Mostafa, A. Nayerhoda, L. Nellen, M. Newbold, M. U. Nisa, R. Noriega-Papaqui, N. Omodei, A. Peisker, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, H. Salazar, D. Salazar-Gallegos, F. Salesa Greus, A. Sandoval, J. Serna-Franco, A. J. Smith, Y. Son, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, L. Villasenor, Xiaojie Wang, T. Weisgarber, E. Willox, H. Zhou, C. De Leon

Physics Faculty Research & Creative Works

The extragalactic background light (EBL) contains all the radiation emitted by nuclear and accretion processes in stars and compact objects since the epoch of recombination. Measuring the EBL density directly is challenging, especially in the near-to-far-infrared wave band, mainly due to the zodiacal light foreground. Instead, gamma-ray astronomy offers the possibility to indirectly set limits on the EBL by studying the effects of gamma-ray absorption in the very high energy (VHE: >100 GeV) spectra of distant blazars. The High-Altitude Water Cherenkov Gamma Ray Observatory (HAWC) is one of the few instrument's sensitive to gamma rays with energies above 10 TeV. …

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Quantum Oscillations Of The J=3/2 Fermi Surface In The Topological Semimetal Yptbi, Hyunsoo Kim, Junhyun Lee, Halyna Hodovanets, Kefeng Wang, Jay D. Sau, Johnpierre Paglione Jul 2022

Quantum Oscillations Of The J=3/2 Fermi Surface In The Topological Semimetal Yptbi, Hyunsoo Kim, Junhyun Lee, Halyna Hodovanets, Kefeng Wang, Jay D. Sau, Johnpierre Paglione

Physics Faculty Research & Creative Works

The bismuth-based half-Heusler materials host a nontrivial topological band structure, unconventional superconductivity, and large spin-orbit coupling in a system with very low electron density. In particular, the inversion of p-orbital-derived bands with an effective angular momentum j of up to 3/2 is thought to play a central role in anomalous Cooper pairing in the cubic half-Heusler semimetal YPtBi, which is thought to be the first "high-spin" superconductor. Here, we report an extensive study of the angular dependence of quantum oscillations (QOs) in the electrical conductivity of YPtBi, revealing an anomalous Shubnikov-de Haas effect consistent with the presence of a coherent …

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Structure And Electronic Properties Of Amorphous Strontium Titanate, Julia E. Medvedeva, Bishal Bhattarai, Ivan A. Zhuravlev, Federico Motti, Piero Torelli, Anita Guarino, Andreas Klein, Emiliano Di Gennaro, Fabio Miletto Granozio Jul 2022

Structure And Electronic Properties Of Amorphous Strontium Titanate, Julia E. Medvedeva, Bishal Bhattarai, Ivan A. Zhuravlev, Federico Motti, Piero Torelli, Anita Guarino, Andreas Klein, Emiliano Di Gennaro, Fabio Miletto Granozio

Physics Faculty Research & Creative Works

Understanding the short-range structure of an amorphous material is the first step in predicting its macroscopic properties. Amorphous strontium titanate (a-STO) presents a unique challenge due to contradictory experimental findings regarding the local oxygen environment of titanium, concluded to be either tetrahedral or octahedral. To elucidate the discrepancy, 72 models of a-STO with density ranging from the crystalline value 5.12 to 3.07g/cm3 were prepared using ab initio molecular dynamics liquid-quench simulations and characterized by extended x-ray absorption fine structure (EXAFS) for both Ti and Sr K edge. An excellent agreement between the calculated and two independent experimental EXAFS measurements demonstrates …

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In-Situ Infrared Thermographic Inspection For Local Powder Layer Thickness Measurement In Laser Powder Bed Fusion, Tao Liu, Cody S. Lough, Hossein Sehhat, Yi Ming Ren, Panagiotis D. Christofides, Edward C. Kinzel, Ming-Chuan Leu Jul 2022

In-Situ Infrared Thermographic Inspection For Local Powder Layer Thickness Measurement In Laser Powder Bed Fusion, Tao Liu, Cody S. Lough, Hossein Sehhat, Yi Ming Ren, Panagiotis D. Christofides, Edward C. Kinzel, Ming-Chuan Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The laser powder bed fusion (LPBF) process is strongly influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. This paper investigates in-situ characterization of the powder layer using thermographic inspection. A thermal camera monitors the temperature history of the powder surface immediately after a layer of new powder is deposited by the recoating system. During this process, thermal energy diffuses from the underlying solid part, eventually raising the temperature of the above powder layer. Guided by 1D modeling of this heat-up process, experiments show how the parameterized thermal history can be correlated with powder …

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A Deep Learning Approach To Detect Blood Vessels In Basal Cell Carcinoma, A. Maurya, R. Joe Stanley, N. Lama, Sarangapani Jagannathan, D. Saeed, S. Swinfard, J. R. Hagerty, William V. Stoecker Jul 2022

A Deep Learning Approach To Detect Blood Vessels In Basal Cell Carcinoma, A. Maurya, R. Joe Stanley, N. Lama, Sarangapani Jagannathan, D. Saeed, S. Swinfard, J. R. Hagerty, William V. Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

Purpose: Blood vessels called telangiectasia are visible in skin lesions with the aid of dermoscopy. Telangiectasia are a pivotal identifying feature of basal cell carcinoma. These vessels appear thready, serpiginous, and may also appear arborizing, that is, wide vessels branch into successively thinner vessels. Due to these intricacies, their detection is not an easy task, neither with manual annotation nor with computerized techniques. In this study, we automate the segmentation of telangiectasia in dermoscopic images with a deep learning U-Net approach. Methods: We apply a combination of image processing techniques and a deep learning-based U-Net approach to detect telangiectasia in …

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Adaptive Control Of Robotic Manipulators Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan Jul 2022

Adaptive Control Of Robotic Manipulators Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we present a lifelong deep learning-based control of robotic manipulators with nonstandard adaptive laws using singular value decomposition (SVD) based direct tracking error driven (DTED) approach. Moreover, we incorporate concurrent learning (CL) to relax persistency of excitation condition and elastic weight consolidation (EWC) for lifelong learning on different tasks in the adaptive laws. Simulation results confirm theoretical conclusions.

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The Effect Of Sodium Polymethacrylate On The Rheology Of The Positive Paste And Performance Of The Lead-Acid Battery, Julian Kosacki, Dimitri Feys, Fatih Dogan Jul 2022

The Effect Of Sodium Polymethacrylate On The Rheology Of The Positive Paste And Performance Of The Lead-Acid Battery, Julian Kosacki, Dimitri Feys, Fatih Dogan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Due to its rheological properties, positive lead-acid battery paste can be difficult to spread on lead current collectors accurately and efficiently under industry machinery and setting. Sodium polymethacrylate dispersant was studied as an effective positive paste additive that could lower the yield stress of the paste without affecting paste density and battery performance. Under a four-blade vane rheometer setup, stress growth and oscillatory amplitude strain sweep experiments evaluated the rheological properties of positive paste with the addition of varying amounts of sodium polymethacrylate. Further, the electrochemical effects of sodium polymethacrylate were also evaluated in 2V batteries by testing positive active …

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Internal Energy Balance And Aerodynamic Heating Predictions For Hypersonic Turbulent Boundary Layers, Matthew Barone, Gary L. Nicholson, Lian Duan Jul 2022

Internal Energy Balance And Aerodynamic Heating Predictions For Hypersonic Turbulent Boundary Layers, Matthew Barone, Gary L. Nicholson, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The elemental equation governing heat transfer in aerodynamic flows is the internal energy equation. For a boundary layer flow, a double integration of the Reynolds-averaged form of this equation provides an expression of the wall heat flux in terms of the integrated effects, over the boundary layer, of various physical processes: turbulent dissipation, mean dissipation, turbulent heat flux, etc. Recently available direct numerical simulation data for a Mach 11 cold-wall turbulent boundary layer allows a comparison of the exact contributions of these terms in the energy equation to the wall heat flux with their counterparts modeled in the Reynolds-averaged Navier-Stokes …

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Snow Parameters Inversion From Passive Microwave Remote Sensing Measurements By Deep Convolutional Neural Networks, Heming Yao, Yanming Zhang, Lijun Jiang, Hong Tat Ewe, Michael Ng Jul 2022

Snow Parameters Inversion From Passive Microwave Remote Sensing Measurements By Deep Convolutional Neural Networks, Heming Yao, Yanming Zhang, Lijun Jiang, Hong Tat Ewe, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel inverse method based on the deep convolutional neural network (ConvNet) to extract snow's layer thickness and temperature via passive microwave remote sensing (PMRS). The proposed ConvNet is trained using simulated data obtained through conventional computational electromagnetic methods. Compared with the traditional inverse method, the trained ConvNet can predict the result with higher accuracy. Besides, the proposed method has a strong tolerance for noise. The proposed ConvNet composes three pairs of convolutional and activation layers with one additional fully connected layer to realize regression, i.e., the inversion of snow parameters. The feasibility of the proposed method …

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Improved Current Shunt Characterization Method For Core Loss Measurement, Anfeng Huang, Xu Wang, Hanyu Zhang, Chulsoon Hwang, David Pommerenke, Jun Fan Jul 2022

Improved Current Shunt Characterization Method For Core Loss Measurement, Anfeng Huang, Xu Wang, Hanyu Zhang, Chulsoon Hwang, David Pommerenke, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

With the increasing switching frequencies and power densities in modern power converters, magnetic core losses are becoming more essential for efficiency and thermal optimization. Traditionally, the two-winding method suffers from sensitivity to phase error in practical measurements; this is mainly created by the unknown phase shift of a current-sensing resistor. Several methods have been developed to characterize the phase shift of a current shunt resistor; however, the load effects of oscilloscopes are ignored. As a result, the corresponding phase shift can be significantly underestimated. This article proposes an improved method for phase shift extraction of a current shunt to solve …

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A 3d Non-Stationary Mimo Channel Model For Reconfigurable Intelligent Surface Auxiliary Uav-To-Ground Mmwave Communications, Baiping Xiong, Zaichen Zhang, Hao Jiang, Jiangfan Zhang, Liang Wu, Jian Dang Jul 2022

A 3d Non-Stationary Mimo Channel Model For Reconfigurable Intelligent Surface Auxiliary Uav-To-Ground Mmwave Communications, Baiping Xiong, Zaichen Zhang, Hao Jiang, Jiangfan Zhang, Liang Wu, Jian Dang

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned aerial vehicle (UAV) communications exploiting millimeter wave (mmWave) can satisfy the increasing data rate demands for future wireless networks owing to the line-of-sight (LoS) dominated transmission and flexibility. In reality, the LoS link can be easily and severely blocked due to poor propagation environments such as tall buildings or trees. To this end, we introduce a reconfigurable intelligent surface (RIS), which passively reflects signals with programmable reflection coefficients, between the transceivers to enhance the communication quality. Specifically, in this paper we generalize a three-dimensional (3D) non-stationary wideband end-to-end channel model for RIS auxiliary UAV-to-ground mmWave multiple-input multiple-output (MIMO) communication …

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Effect Of Grain Size On The Irradiation Response Of Grade 91 Steel Subjected To Fe Ion Irradiation At 300 °C, Jiaqi Duan, Haiming Wen, Li He, Kumar Sridharan, Andrew Hoffman, Maalavan Arivu, Xiaoqing He, Rinat Islamgaliev, Ruslan Valiev Jul 2022

Effect Of Grain Size On The Irradiation Response Of Grade 91 Steel Subjected To Fe Ion Irradiation At 300 °C, Jiaqi Duan, Haiming Wen, Li He, Kumar Sridharan, Andrew Hoffman, Maalavan Arivu, Xiaoqing He, Rinat Islamgaliev, Ruslan Valiev

Materials Science and Engineering Faculty Research & Creative Works

Irradiation using Fe ion at 300 °C up to 100 dpa was carried out on three variants of Grade 91 (G91) steel samples with different grain size ranges: fine-grained (FG, with blocky grains of a few micrometers long and a few hundred nanometers wide), ultrafine-grained (UFG, grain size of ~ 400 nm) and nanocrystalline (NC, lath grains of ~ 200 nm long and ~ 80 nm wide). Electron microscopy investigations indicate that NC G91 exhibit higher resistance to irradiation-induced defect formation than FG and UFG G91. In addition, nano-indentation studies reveal that irradiation-induced hardening is significantly lower in NC G91 …

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First-Principles Study Of The Thermal Properties Of Zr2c And Zr2co, Yue Zhou, William Fahrenholtz, Joseph T. Graham, Gregory E. Hilmas Jul 2022

First-Principles Study Of The Thermal Properties Of Zr2c And Zr2co, Yue Zhou, William Fahrenholtz, Joseph T. Graham, Gregory E. Hilmas

Materials Science and Engineering Faculty Research & Creative Works

First-principles calculations of lattice thermal conductivities and thermodynamic properties of Zr2C and Zr2CO were performed using the quasi-harmonic approximation. Oxygen in the lattice gives Zr2CO higher bonding strength than Zr2C. Thus, the mechanical properties of Zr2C are enhanced when the vacancies in its crystal structure are filled with oxygen. Among the critical parameters that determine the lattice thermal conductivity, Zr2C has significantly higher Grüneisen parameters, thus Zr2C has lower lattice thermal conductivity than Zr2CO. In addition, Zr2CO has a higher heat capacity and thermal expansion coefficient than Zr2C at most temperatures. These results indicate that the addition of oxygen has …

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Room-Temperature Mechanical Properties Of A High-Entropy Diboride, Alec C. Murchie, Jeremy Lee Watts, William Fahrenholtz, Gregory E. Hilmas Jul 2022

Room-Temperature Mechanical Properties Of A High-Entropy Diboride, Alec C. Murchie, Jeremy Lee Watts, William Fahrenholtz, Gregory E. Hilmas

Materials Science and Engineering Faculty Research & Creative Works

The mechanical properties of a (Hf,Mo,Nb,Ta,W,Zr)B2 high-entropy ceramic were measured at room temperature. A two-step synthesis process was utilized to produce the (Hf,Mo,Nb,Ta,W,Zr)B2 ceramics. The process consisted of a boro/carbothermal reduction reaction followed by solid solution formation and densification through spark plasma sintering. Nominally, phase pure (Hf,Mo,Nb,Ta,W,Zr)B2 was sintered to near full density (8.98 g/cm3) at 2000°C. The mean grain size was 6 ± 2 µm with a maximum grain size of 17 µm. Flexural strength was 528 ± 53 MPa, Young's modulus was 520 ± 12 GPa, fracture toughness was 3.9 ± 1.2 MPa·m1/2, and hardness (HV0.2) was 33.1 …

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Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang Jul 2022

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …

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Foldy-Wouthuysen Transformation In Strong Magnetic Fields And Relativistic Corrections For Quantum Cyclotron Energy Levels, Albert Wienczek, Christopher Moore, Ulrich D. Jentschura Jul 2022

Foldy-Wouthuysen Transformation In Strong Magnetic Fields And Relativistic Corrections For Quantum Cyclotron Energy Levels, Albert Wienczek, Christopher Moore, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We carry out a direct iterative Foldy-Wouthuysen transformation of a general Dirac Hamiltonian coupled to an electromagnetic field, including the anomalous magnetic moment. The transformation is carried out through an iterative disentangling of the particle and antiparticle Hamiltonians in the expansion for higher orders of the momenta. The time-derivative term from the unitary transformation is found to be crucial in supplementing the transverse component of the electric field in higher orders. Final expressions are obtained for general combined electric and magnetic fields, including strong magnetic fields. The time derivative of the electric field is shown to enter only in the …

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Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang Jun 2022

Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang

Computer Science Faculty Research & Creative Works

Deep models are powerful in capturing the complex and non-linear relationship buried in brain imaging data. However, the huge number of parameters in deep models can easily overfit given limited imaging data samples. In this work, we proposed a cross-domain transfer learning method to solve the insufficient data problem in brain imaging domain by leveraging the knowledge learned in natural image domain. Specifically, we employed ViT as the backbone and firstly pretrained it using ImageNet-21K dataset and then transferred to the brain imaging dataset. A slice-wise convolution embedding method was developed to improve the standard patch operation in vanilla ViT. …

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