Engineering Commons^™

Self-Relabeling For Noise-Tolerant Retina Vessel Segmentation Through Label Reliability Estimation, Jiacheng Li, Ruirui Li, Ruize Han, Song Wang

Faculty Publications

Background Retinal vessel segmentation benefits significantly from deep learning. Its performance relies on sufficient training images with accurate ground-truth segmentation, which are usually manually annotated in the form of binary pixel-wise label maps. Manually annotated ground-truth label maps, more or less, contain errors for part of the pixels. Due to the thin structure of retina vessels, such errors are more frequent and serious in manual annotations, which negatively affect deep learning performance.

Methods In this paper, we develop a new method to automatically and iteratively identify and correct such noisy segmentation labels in the process of network training. We consider …

Instructional Design Framework For Construction Materials Training, Hazem Jadallah, Carol J. Friedland, Isabelina Nahmens, Charles Pecquet, Charles Berryman, Yimin Zhu

Faculty Publications

The construction industry is suffering, in part, from a lack of training programs offered to the construction workforce. Unfortunately, most construction training and education research focuses on university student education. Integrating education science theory into construction workforce training has the potential to improve industry training but there is a dearth of studies that present details of this integration process. To address this gap, a training framework was developed to educate material stakeholders on material properties, selection, and installation. This framework is based on andragogical and Universal Design for Learning (UDL) principles. An assessment method evaluates training agendas to improve upon …

A Phase Field Model For Dynamic Simulations Of Reactive Blending Of Polymers, Mukul D. Tikekar, Kris T. Delaney, Michael C. Villet, Douglas R. Tree

Faculty Publications

A facile way to generate compatibilized blends of immiscible polymers is through reactive blending of end-functionalized homopolymers. The reaction may be reversible or irreversible depending on the end-groups and is affected by the immiscibility and transport of the reactant homopolymers and the compatibilizing copolymer product. Here we describe a phase-field framework to model the combined dynamics of reaction kinetics, diffusion, and multi-component thermodynamics on the evolution of the microstructure and reaction rate in reactive blending. A density functional with no fitting parameters, which is obtained by adapting a framework of Uneyama and Doi and qualitatively agrees with self-consistent field theory, …

Closed Loop Recycling Of Low Friction Polymers In Fused Granule Fabrication Additive Manufacturing Processes, Neil Thompson, Jason Weaver

Faculty Publications

Plastic waste is a critical worldwide problem that impacts additive manufacturing (AM). Extensive research has explored how plastic waste in AM can be reduced by recycling prints into new filament, with varying success. An alternative to filament-based extrusion is “fused granule fabrication” (FGF), which extrudes from pellets or granules. This method is often used for large area additive manufacturing (LAAM) of polymers. This paper expands upon the knowledge base from previous research on LAAM and examines the extent to which PETG can be recycled and reprinted through the same FGF tool without significant loss to its material properties. The metric …

Durability Of Vacuum Infusion Tooling Produced From Fused Granular Fabrication Additive Manufacturing, Nathan Northrup, Jason Weaver, Andy R. George

Faculty Publications

Large area additive manufacturing (LAAM) has the capability to create tooling that is lower cost than conventionally manufactured tooling and still has sufficient properties for many applications. A vacuum infusion mold was printed from fiberglass-ABS and evaluated for wear and suitability for small vacuum infusion runs. The mold was designed to accentuate high wear as a “worst case” scenario. The mold was able to produce 10 parts successfully before any noticeable change occurred to the surface finish. By 14 parts, the surface finish had roughened sufficiently that demolding was difficult and resulted in damage to the part. Profilometry measurements showed …

Estimating Beam Strength Of Metallic Gear Materials, Edward E. Osakue, Lucky Anetor

Faculty Publications

Expressions for the pulsating or beam strengths of many popular metallic gear materials are derived based on the tensile strength and endurance ratio. The strength values predicted are for a reliability of 99% at load cycles corresponding to that of the endurance strength of the materials. The expressions are based on the consideration of the revised Lewis gear root stress formula by treating the design parameters as random variables associated with the lognormal probability density function and application of the Gerber fatigue failure rule. Pulsating strength predictions are compared with those of AGMA estimates for through-hardened steels and other materials. …

A Contact Stress Capacity Model For Cylindrical Wormsets, Edward E. Osakue, Lucky Anetor

Faculty Publications

A contact stress capacity expression is derived for cylindrical worm sets by considering the worm as a helical rack mating with a helical gear. The concept of the equivalent spur gear for a helical gear defined by the instantaneous radius of curvature in the virtual plane of the helical gear is utilized in the contact stress capacity model formulation. All the basic design parameters of worm and gear are incorporated in the expression which explicitly shows the influence of the base and nominal helix angles on the contact stress. By considering the geometry of the worm and gear in engagement, …

Considering Thickness-Accommodation, Nesting, Grounding And Deployment In Design Of Miura-Ori Based Space Arrays, Terri Bateman, Diana Bolanos, Nathan Brown, Brooklyn Clark, Larry L. Howell, Collin Ynchausti, Hunter Pruett, Jared Hunter, Spencer P. Magleby

Faculty Publications

The Miura-ori pattern exhibits favorable qualities desirable for deployable space arrays – especially achieving a large deployed area from a compact stowed volume. However, implementing the Miura-ori into a finite-thickness, engineered system poses challenges that are not manifest in a zero-thickness model. As such, it is important to understand and address the limitations of the pattern before implementing it into an engineered system. This paper presents the Miura-ori as a favorable, yet challenging, pattern in design of deployable space arrays. Challenges including thickness-accommodation, nesting, grounding and deployment are presented to introduce designers to unapparent complications associated with design of Miura-ori …

Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …

Magneto-Exothermic Catalytic Chemical Reaction Along A Curved Surface, Muhammad Ashraf, Uzma Ahmad, Saqib Zia, Rama S. R. Gorla, Amnah S. Al-Johani, Ilyas Khan, Mulugeta Andualem

Faculty Publications

In the current study, the physical behavior of the boundary layer flows along a curved surface owing exothermic catalytic chemical reaction, and the magnetic field is investigated. The mathematical model comprised of a part of momentum, energy, and mass equations, which are solved using a finite difference method along with primitive variable formulation. Numerical solutions, using the method of quantitative differentiation, are made with the appropriate choice of dimensionless parameters. Analysis of the results obtained shows that the field temperature and flow of fluids are strongly influenced by the combined effects of catalytic chemical reactions and the magnetic field. The …

Incorporating High-Fidelity Aerostructural Analyses In Wind Turbine Rotor Optimization, Denis-Gabriel Caprace, Adam Cardoza, Andrew Ning, Marco Mangano, Sicheng He, Joaquim R. R. A. Martins

Faculty Publications

s demand grows for wind turbines with larger blades, the design of future wind turbines must account for multi-physical interactions and an ever-increasing number of design load conditions. One aspect, aerostructural coupling, calls for design tools that are both accurate and computationally efficient. In this paper, we present a combined-fidelity approach that couples high-fidelity computational fluid dynamics and computational solid mechanics simulations, with a conventional aeroelastic turbine modeling tool based on blade element momentum and beam theories. The approach is integrated into a multidisciplinary optimization framework. It takes advantage of the high-fidelity tightly-coupled aerostructural simulations to evaluate the rotor power …

A General Coupling Methodology For Unsteady Aerostructural Optimization With Analytic Derivatives, Taylor Mcdonnell, Adam Cardoza, Denis-Gabriel Caprace, Andrew Ning

Faculty Publications

Multidisciplinary design optimization offers a comprehensive approach for designing complex aerostructural systems such as wind turbines. Gradient-based multidisciplinary design optimization can be used to optimize complex systems using large numbers of design variables. However, the convergence of gradient-based optimization methods to an optimal solution is highly dependent on the accuracy of the provided derivatives. In this paper, we propose a general method for creating unsteady coupled systems for steady-state, eigenvalue, and time-domain analyses. We then describe how highly accurate derivatives may be obtained from these analyses using a combination of automatic differentiation and analytic methods (including the unsteady adjoint). Finally, …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

Rapid Ac Electrokinetic Micromixer With Electrically Conductive Sidewalls, Fang Yang, Wei Zhao, Cuifang Kuang, Guiren Wang

Faculty Publications

We report a quasi T-channel electrokinetics-based micromixer with electrically conductive sidewalls, where the electric field is in the transverse direction of the flow and parallel to the conductivity gradient at the interface between two fluids to be mixed. Mixing results are first compared with another widely studied micromixer configuration, where electrodes are located at the inlet and outlet of the channel with electric field parallel to bulk flow direction but orthogonal to the conductivity gradient at the interface between the two fluids to be mixed. Faster mixing is achieved in the micromixer with conductive sidewalls. Effects of Re numbers, applied …

Review—Concentration Measurements In Molten Chloride Salts Using Electrochemical Methods, Tyler Williams, Rankin Shum, Devin Rappleye

Faculty Publications

The electrochemical measurement of concentration in molten chloride salts is a valuable tool for the control of existing and potential industrial processes, recycling of precious materials and energy production. The electrochemical techniques commonly used to measure concentration and each techniques’ associated theory are discussed. Practices which improve measurement accuracy and precision are set forth. Exceptionally accurate and precise measurements published in the literature are evaluated based on their performance in specified concentration ranges. The strengths and weaknesses of the most accurate measurements are briefly explored. Chronopotentiometry (CP) and square wave voltammetry (SWV) are accurate and precise with low concentration measurements. …

Machine-Learning Algorithms For Forecast-Informed Reservoir Operation (Firo) To Reduce Flood Damages, Manizhe Zarei, Omid Bozorg-Haddad, Sahar Baghban, Mohammad Delpasand, Erfan Goharian, Hugo A. Loaiciga

Faculty Publications

Water is stored in reservoirs for various purposes, including regular distribution, flood control, hydropower generation, and meeting the environmental demands of downstream habitats and ecosystems. However, these objectives are often in conflict with each other and make the operation of reservoirs a complex task, particularly during flood periods. An accurate forecast of reservoir inflows is required to evaluate water releases from a reservoir seeking to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. This study aims to improve the informed decisions for reservoirs management and water prerelease before a flood occurs by …

On The Synthesis Of Optimal Control Laws, Meir Pachter, Isaac E. Weintraub

Faculty Publications

In this paper we advocate for Isaacs' method for the solution of differential games to be applied to the solution of optimal control problems. To make the argument, the vehicle employed is Pontryagin's canonical optimal control example, which entails a double integrator plant. However, rather than controlling the state to the origin, we correctly require the end state to reach a terminal set that contains the origin in its interior. Indeed, in practice, it is required to control to a prescribed tolerance rather than reach a desired end state; achieving tight tolerances is expensive, and from a theoretical point of …

Sortie-Based Aircraft Component Demand Rate To Predict Requirements, Thomas R. O'Neal, John M. Dickens, Lance Champaign, Aaron V. Glassburner, Jason R. Anderson, Timothy W. Breitbach

Faculty Publications

Purpose — Forecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs. Design/methodology/approach — This study employs a correlation analysis to show that demand for reparable parts on certain aircraft …

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Response-Coupled Forward/Adjoint Linear Systems (NTh-Casam-L): Ii. Illustrative Application, Dan Gabriel Cacuci

Faculty Publications

This work illustrates the application of the n^th-order comprehensive adjoint sensitivity analysis methodology for response-coupled forward/adjoint linear systems (abbreviated as “n^th-CASAM-L”) to a paradigm model that describes the transmission of particles (neutrons and/or photons) through homogenized materials, as encountered in radiation protection and shielding. The first-, second-, and third-order sensitivities of responses that depend on both the forward and adjoint particle fluxes are obtained exactly, in closed-form, underscoring the principles and methodology underlying the n^th-CASAM-L. The results presented in this work underscore the fundamentally important role of the n^th-CASAM-L in the quest …

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Response-Coupled Forward/Adjoint Linear Systems (NTh-Casam-L): I. Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the mathematical framework of the n^th-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “n^th-CASAM-L”), which is conceived for obtaining the exact expressions of arbitrarily-high-order (n^th-order) sensitivities of a generic system response with respect to all of the parameters (including boundary and initial conditions) underlying the respective forward/adjoint systems. Since many of the most important responses for linear systems involve the solutions of both the forward and the adjoint linear models that correspond to the respective physical system, the sensitivity analysis of such responses makes it necessary …

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Response-Coupled Forward/Adjoint Linear Systems (NTh-Casam-L): I. Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the mathematical framework of the n^th-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “n^th-CASAM-L”), which is conceived for obtaining the exact expressions of arbitrarily-high-order (n^th-order) sensitivities of a generic system response with respect to all of the parameters (including boundary and initial conditions) underlying the respective forward/adjoint systems. Since many of the most important responses for linear systems involve the solutions of both the forward and the adjoint linear models that correspond to the respective physical system, the sensitivity analysis of such responses makes it necessary …

Simultaneous Dirac-Like Cones At Two Energy States In Tunable Phononic Crystals: An Analytical And Numerical Study, Mustahseen M. Indaleeb, Sourav Banerjee

Faculty Publications

Simultaneous occurrence of Dirac-like cones at the center of the Brillouin zone (Γ) at two different energy states is termed Dual-Dirac-like cones (DDC) in this article. The occurrence of DDC is a rare phenomenon. Thus, the generation of multiple Dirac-like cones at the center of the Brillouin zone is usually non-manipulative and poses a challenge to achieve through traditional accidental degeneracy. However, if predictively created, DDC will have multiple engineering applications with acoustics and vibration. Thus, the possibilities of creating DDC have been identified herein using a simple square periodic array of tunable square phononic crystals (PnCs) in air media. …

Approaching Disorder-Tolerant Semiconducting Polymers, Xinwen Yan, Miao Xiong, Xin Yu Deng, Kai Kai Liu, Jia Tong Li, Xue Qing Wang, Song Zhang, Nathaniel Prine, Zhuoqiong Zhang, Wanying Huang, Yishan Wang, Jie Yu Wang, Xiaodan Gu, Shu Kong So, Jia Zhu, Ting Lei

Faculty Publications

Doping has been widely used to control the charge carrier concentration in organic semiconductors. However, in conjugated polymers, n-doping is often limited by the tradeoff between doping efficiency and charge carrier mobilities, since dopants often randomly distribute within polymers, leading to significant structural and energetic disorder. Here, we screen a large number of polymer building block combinations and explore the possibility of designing n-type conjugated polymers with good tolerance to dopant-induced disorder. We show that a carefully designed conjugated polymer with a single dominant planar backbone conformation, high torsional barrier at each dihedral angle, and zigzag backbone curvature is highly …

Semiflexible Oligomers Crystallize Via A Cooperative Phase Transition, Pierre Kawak, Dakota S. Banks, Douglas R. Tree

Faculty Publications

Semicrystalline polymers are ubiquitous, yet despite their fundamental and industrial importance, the theory of homogeneous nucleation from a melt remains a subject of debate. A key component of the controversy is that polymer crystallization is a non-equilibrium process, making it difficult to distinguish between effects that are purely kinetic and those that arise from the underlying thermodynamics. Due to computational cost constraints, simulations of polymer crystallization typically employ non-equilibrium molecular dynamics techniques with large degrees of undercooling that further exacerbate the coupling between thermodynamics and kinetics. In a departure from this approach, in this study, we isolate the near-equilibrium nucleation …

Stochastic Modeling Of Surface Scalar-Flux Fluctuations In Turbulent Channel Flow Using One-Dimensional Turbulence, Marten Klein, Heiko Schmidt, David O. Lignell

Faculty Publications

Accurate and economical modeling of near-surface transport processes is a standing challenge for various engineering and atmospheric boundary-layer flows. In this paper, we address this challenge by utilizing an economical stochastic one-dimensional turbulence (ODT) model. ODT aims to resolve all relevant scales of a turbulent flow for a one-dimensional domain. Here ODT is applied to turbulent channel flow as stand-alone tool. The ODT domain is a wall-normal line that is aligned with the mean shear. The free model parameters are calibrated once for the turbulent velocity boundary layer at a fixed Reynolds number. After that, we use ODT to investigate …

Two-Dimensional Steady Boussinesq Convection: Existence, Computation And Scaling, Jeremiah S. Lane, Benjamin F. Akers

Faculty Publications

This research investigates laser-induced convection through a stream function-vorticity formulation. Specifically, this paper considers a solution to the steady Boussinesq Navier–Stokes equations in two dimensions with a slip boundary condition on a finite box. A fixed-point algorithm is introduced in stream function-vorticity variables, followed by a proof of the existence of steady solutions for small laser amplitudes. From this analysis, an asymptotic relationship is demonstrated between the nondimensional fluid parameters and least upper bounds for laser amplitudes that guarantee existence, which accords with numerical results implementing the algorithm in a finite difference scheme. The findings indicate that the upper bound …

Atlantis: A Benchmark For Semantic Segmentation Of Waterbody Images, Mohammad H. Erfani, Zhenyao Wu, Xinyi Wu, Song Wang, Erfan Goharian

Faculty Publications

Vision-based semantic segmentation of waterbodies and nearby related objects provides important information for managing water resources and handling flooding emergency. However, the lack of large-scale labeled training and testing datasets for water-related categories prevents researchers from studying water-related issues in the computer vision field. To tackle this problem, we present ATLANTIS, a new benchmark for semantic segmentation of waterbodies and related objects. ATLANTIS consists of 5,195 images of waterbodies, as well as high quality pixel-level manual annotations of 56 classes of objects, including 17 classes of man-made objects, 18 classes of natural objects and 21 general classes. We analyze ATLANTIS …

Modeling Electrokinetics Of Oxygen Electrodes In Solid Oxide Electrolyzer Cells, Korey Cook, Jacob Wrubel, Zhiwen Ma, Kevin Huang, Xinfang Jin

Faculty Publications

A microscale model is presented in this study to simulate electrode kinetics of the oxygen electrode in a solid oxide electrolyzer cell (SOEC). Two mixed ionic/electronic conducting structures are examined for the oxygen producing electrode in this work: single layer porous lanthanum strontium cobalt ferrite (LSCF), and bilayer LSCF/SCT (strontium cobalt tantalum oxide) structures. A yttrium-stabilized zirconia (YSZ) electrolyte separates the hydrogen and oxygen electrodes, as well as a gadolinium doped-ceria (GDC) buffer layer on the oxygen electrode side. Electrochemical reactions occurring at the two-phase boundaries (2PBs) and three-phase boundaries (3PBs) of single-layer LSCF and bilayer LSCF/SCT oxygen electrodes are …

Large-Scale Reality Modeling Of A University Campus Using Combined Uav And Terrestrial Photogrammetry For Historical Preservation And Practical Use, Bryce Berrett, Cory Vernon, Haley Beckstrand, Madi Pollei, Kaleb Markert, Kevin Franke, John Hedengren

Faculty Publications

Unmanned aerial vehicles (UAV) enable detailed historical preservation of large-scale infrastructure and contribute to cultural heritage preservation, improved maintenance, public relations, and development planning. Aerial and terrestrial photo data coupled with high accuracy GPS create hyper-realistic mesh and texture models, high resolution point clouds, orthophotos, and digital elevation models (DEMs) that preserve a snapshot of history. A case study is presented of the development of a hyper-realistic 3D model that spans the complex 1.7 km2 area of the Brigham Young University campus in Provo, Utah, USA and includes over 75 significant structures. The model leverages photos obtained during the historic …

An Optimized Machine Learning And Big Data Approach To Crime Detection, Ashokkumar Palanivinayagam, Siva Shankar Gopal, Sweta Bhattacharya, Noble Anumbe, Ebuka Ibeke, Cresantus Biamba

Faculty Publications

Crime detection is one of the most important research applications in machine learning. Identifying and reducing crime rates is crucial to developing a healthy society. Big Data techniques are applied to collect and analyse data: determine the required features and prime attributes that cause the emergence of crime hotspots. The traditional crime detection and machine learning-based algorithms lack the ability to generate key prime attributes from the crime dataset, hence most often fail to predict crime patterns successfully. This paper is aimed at extracting the prime attributes such as time zones, crime probability, and crime hotspots and performing vulnerability analysis …