Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Faculty Publications

Discipline
Institution
Keyword
Publication Year
File Type

Articles 541 - 570 of 3294

Full-Text Articles in Engineering

Clustering Behavior In Solar Flare Dynamics, Elmer C. Rivera, Jay R. Johnson, Jonathan Homan, Simon Wing Sep 2022

Clustering Behavior In Solar Flare Dynamics, Elmer C. Rivera, Jay R. Johnson, Jonathan Homan, Simon Wing

Faculty Publications

The solar magnetic activity cycle provides energy input that is released in intense bursts of radiation known as solar flares. As such, the dynamics of the activity cycle is embedded in the sequence of times between the flare events. Recent analysis shows that solar flares exhibit memory on different timescales. These previous studies showed that the time ordering of flare events is not random, but rather there is dependence between successive flares. In the present work, the clustering of flares is demonstrated through a straightforward nonparametric method where the cumulative distribution function of successive flares is compared with the cumulative …

Go to article

A Novel Self-Assembled Cobalt-Free Perovskite Composite Cathode With Triple-Conduction For Intermediate Proton-Conducting Solid Oxide Fuel Cells, Hua Tong, Min Fu, Yang Yang, Fanglin Chen, Zetian Tao Sep 2022

A Novel Self-Assembled Cobalt-Free Perovskite Composite Cathode With Triple-Conduction For Intermediate Proton-Conducting Solid Oxide Fuel Cells, Hua Tong, Min Fu, Yang Yang, Fanglin Chen, Zetian Tao

Faculty Publications

A traditional composite cathode for proton-conducting solid oxide fuel cells (H-SOFCs) is typically obtained by mixing cathode materials and proton conducting electrolyte of BaCe0.7Y0.2Zr0.1O3–δ (BZCY), providing chemical and thermal compatibility with the electrolyte. Here, a series of triple-conducing and cobalt-free iron-based perovskites as cathodes for H-SOFCs is reported. Specifically, BaCexFe1–xO3–δ (x = 0.36, 0.43, and 0.50) shows various contents of two single phase perovskites with an in situ heterojunction structure as well as triple conductivity by tailoring the Ce/Fe ratios. The cell performance with the optimized BaCe0.36 …

Go to article

Mathematical Model For Sei Growth Under Open-Circuit Conditions, Shiv Krishna Madi Reddy, Wei Shang, Ralph E. White Sep 2022

Mathematical Model For Sei Growth Under Open-Circuit Conditions, Shiv Krishna Madi Reddy, Wei Shang, Ralph E. White

Faculty Publications

A solid electrolyte interphase (SEI) growth model is developed in a mixed mode that contains solvent diffusion through the SEI layer and corresponding solvent reduction kinetics at the SEI/electrode interface. The governing equations are solved by the Landau transformation, which makes the moving layer fixed to predict the open circuit potential, SEI layer thickness, and capacity loss. The estimated parameters fitted with experimental data from the literature are computed using COMSOL and MATLAB. Results show that the mixed mode model predicts lower capacity loss and thinner SEI layer due to its growth under open circuit conditions than previously reported by …

Go to article

Overview Of Arbitrarily High-Order Adjoint Sensitivity And Uncertainty Quantification Methodology For Large-Scale Systems, Dan Gabriel Cacuci Sep 2022

Overview Of Arbitrarily High-Order Adjoint Sensitivity And Uncertainty Quantification Methodology For Large-Scale Systems, Dan Gabriel Cacuci

Faculty Publications

This work reviews from a unified viewpoint the concepts underlying the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems” (nth-CASAM-L) and the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-CASAM-N) methodologies. The practical application of the nth-CASAM-L methodology is illustrated for an OECD/NEA reactor physics benchmark, while the practical application of the nth-CASAM-N methodology is illustrated for a nonlinear model of reactor dynamics that exhibits periodic and chaotic oscillations. As illustrated both by the general theory and by the examples reviewed in this work, both the nth-CASAM-L and nth-CASAM-N methodologies overcome the curse of dimensionality …

Go to article

Influence Of Nano-Sized Sic On The Laser Powder Bed Fusion Of Molybdenum, Nathan E. Ellsworth, Ryan A. Kemnitz, Cayla C. Eckley, Brianna M. Sexton, Cynthia T. Bowers, Joshua R. Machacek, Larry W. Burggraf Sep 2022

Influence Of Nano-Sized Sic On The Laser Powder Bed Fusion Of Molybdenum, Nathan E. Ellsworth, Ryan A. Kemnitz, Cayla C. Eckley, Brianna M. Sexton, Cynthia T. Bowers, Joshua R. Machacek, Larry W. Burggraf

Faculty Publications

Consolidation of pure molybdenum through laser powder bed fusion and other additive manufacturing techniques is complicated by a high melting temperature, thermal conductivity and ductile-to-brittle transition temperature. Nano-sized SiC particles (0.1 wt%) were homogeneously mixed with molybdenum powder and the printing characteristics, chemical composition, microstructure, mechanical properties were compared to pure molybdenum for scan speeds of 100, 200, 400, and 800 mm/s. The addition of SiC improved the optically determined density and flexural strength at 400 mm/s by 92% and 80%, respectively. The oxygen content was reduced by an average of 52% over the four scan speeds analyzed. Two mechanisms …

Go to article

Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry Sep 2022

Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry

Faculty Publications

Securing distributed device communication is critical because the private industry and the military depend on these resources. One area that adversaries target is the middleware, which is the medium that connects different systems. This paper evaluates a novel security layer, DDS-Cerberus (DDS-C), that protects in-transit data and improves communication efficiency on data-first distribution systems. This research contributes a distributed robotics operating system testbed and designs a multifactorial performance-based experiment to evaluate DDS-C efficiency and security by assessing total packet traffic generated in a robotics network. The performance experiment follows a 2:1 publisher to subscriber node ratio, varying the number of …

Go to article

Advances In High-Order Sensitivity Analysis For Uncertainty Quantification And Reduction In Nuclear Energy Systems, Dan Gabriel Cacuci Sep 2022

Advances In High-Order Sensitivity Analysis For Uncertainty Quantification And Reduction In Nuclear Energy Systems, Dan Gabriel Cacuci

Faculty Publications

No abstract provided.

Go to article

Distribution Of Dds-Cerberus Authenticated Facial Recognition Streams, Andrew T. Park, Nathaniel Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry Sep 2022

Distribution Of Dds-Cerberus Authenticated Facial Recognition Streams, Andrew T. Park, Nathaniel Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry

Faculty Publications

Successful missions in the field often rely upon communication technologies for tactics and coordination. One middleware used in securing these communication channels is Data Distribution Service (DDS) which employs a publish-subscribe model. However, researchers have found several security vulnerabilities in DDS implementations. DDS-Cerberus (DDS-C) is a security layer implemented into DDS to mitigate impersonation attacks using Kerberos authentication and ticketing. Even with the addition of DDS-C, the real-time message sending of DDS also needs to be upheld. This paper extends our previous work to analyze DDS-C’s impact on performance in a use case implementation. The use case covers an artificial …

Go to article

Effects Of Rotor-Airframe Interaction On The Aeromechanics And Wake Of A Quadcopter In Forward Flight, Denis-Gabriel Caprace, Andrew Ning, Philippe Chatelain, Grégoire Winckelmans Sep 2022

Effects Of Rotor-Airframe Interaction On The Aeromechanics And Wake Of A Quadcopter In Forward Flight, Denis-Gabriel Caprace, Andrew Ning, Philippe Chatelain, Grégoire Winckelmans

Faculty Publications

From small drones to large Urban Air Mobility vehicles, the market of vertical take-off and landing (VTOL) aircraft is currently booming. Modern VTOL designs feature a variety of configurations involving rotors, lifting surfaces and bluff bodies. The resulting aerodynamics are highly impacted by the interactions between those components and their wakes. This has consequences on the aircraft performance and on the downstream wake. Studying the effects of those interactions through CFD can inform the development of cheaper numerical models. In this work, we focus on the interaction between rotors and bluff bodies based on the example of a generic quadcopter …

Go to article

Sensitivity Analysis, Uncertainty Quantification And Predictive Modeling Of Nuclear Energy Systems, Dan Gabriel Cacuci Sep 2022

Sensitivity Analysis, Uncertainty Quantification And Predictive Modeling Of Nuclear Energy Systems, Dan Gabriel Cacuci

Faculty Publications

No abstract provided.

Go to article

Impact Of Operational And Restoration Interdependencies On Cost And Disruptive Effect In Multilayered Infrastructure Networks, Brigham A. Moore, Steven J. Schuldt, Ramana V. Grandhi, David R. Jacques Sep 2022

Impact Of Operational And Restoration Interdependencies On Cost And Disruptive Effect In Multilayered Infrastructure Networks, Brigham A. Moore, Steven J. Schuldt, Ramana V. Grandhi, David R. Jacques

Faculty Publications

Network-based modeling and simulation of interdependent infrastructure systems has traditionally modeled 1 to 2 interdependency subtypes within a given model. Typically, different interdependency subtypes are modeled with special sets, variables, and parameters rather than integrated into the model as a standard feature. The most thorough current modeling efforts have modeled only four of the nine interdependency subtypes identified throughout academic literature. This paper presents the first model to incorporate all nine of the identified interdependency subtypes in a multiobjective mixed-integer program. The model is tested using a simulated flood event and a modified interdependent infrastructure dataset representing a medium- to …

Go to article

Li-Ion Electrode Microstructure Evolution During Drying And Calendering, Mojdeh Nikpour, Baichuan Liu, Paul Minson, Zachary Hillman, Brian A. Mazzeo, Dean R. Wheeler Sep 2022

Li-Ion Electrode Microstructure Evolution During Drying And Calendering, Mojdeh Nikpour, Baichuan Liu, Paul Minson, Zachary Hillman, Brian A. Mazzeo, Dean R. Wheeler

Faculty Publications

The drying process of electrodes might seem to be a simple operation, but it has profound effects on the microstructure. Some unexpected changes can happen depending on the drying conditions. In prior work, we developed the multiphase-smoothed-particle (MPSP) model, which predicted a relative increase in the carbon additive and binder adjacent to the current collector during drying. This motivated us to undertake the present experimental investigation of the relationship between the drying rate and microstructure and transport properties for a typical anode and cathode. Specifically, the drying rate was controlled by means of temperature for both an NMC532 cathode and …

Go to article

Optimizing Build Plate Adhesion Of Polymers In Fused Granule Fabrication Processes, Alex Schroeder, Jason Weaver Aug 2022

Optimizing Build Plate Adhesion Of Polymers In Fused Granule Fabrication Processes, Alex Schroeder, Jason Weaver

Faculty Publications

Perhaps the most crucial element of fused granule fabrication (FGF) is material adhesion; in order to achieve a successful product, the material being printed must adhere to the build plate. For optimal products, the material should only adhere to the build plate until the print is complete, then be easily removable. This paper examines the effects of different build plates, environments, and bonding agents on material adhesion during the FGF process in a CNC mill machine. The force to remove polycarbonate (PC) and polypropylene (PP) from build plates was tested with various bonding agents. Except in one case, the adhesive …

Go to article

A Comparison Of Layer Deposition And Open Molding Of Petg By Fused Pellet Fabrication In An Additive Manufacturing System, Alex Gibson, Jason Weaver Aug 2022

A Comparison Of Layer Deposition And Open Molding Of Petg By Fused Pellet Fabrication In An Additive Manufacturing System, Alex Gibson, Jason Weaver

Faculty Publications

Additive manufacturing continues to offer new possibilities in both production and economics. The industry has quickly adopted it to rapidly produce parts that would be difficult or cost preventative otherwise. Recent innovation has expanded its capabilities, however there are still significant limitations. Most AM processes are restricted by materials available, in producing large parts, or by not achieving material deposition speeds to make certain products feasible. In addition, tight tolerances for features and surfaces cannot be produced without substantial post processing. High-speed Fused Pellet Fabrication (FPF) in combination with Hybrid Manufacturing (HM) offers expanded capabilities as additive and subtractive process …

Go to article

Trade-Off Characterization Between Social And Environmental Impacts Using Agent-Based Models And Life-Cycle Assessment, Joseph C. Leichty, Christopher S. Mabey, Christopher A. Mattson, John L. Salmon, Jason Weaver Aug 2022

Trade-Off Characterization Between Social And Environmental Impacts Using Agent-Based Models And Life-Cycle Assessment, Joseph C. Leichty, Christopher S. Mabey, Christopher A. Mattson, John L. Salmon, Jason Weaver

Faculty Publications

Meeting the UN’s sustainable development goals requires designers and engineers to solve multi-objective optimization problems involving trade-offs between social, environmental, and economic impacts. This paper presents an approach for designers and engineers to quantify the social and environmental impacts of a product at a population-level and then perform a trade-off analysis between those impacts. In the approach, designers and engineers define the attributes of the product as well as the materials and processes used in the product’s life cycle. Agent-Based Modeling (ABM) tools that have been developed to model the social impacts of products are combined with Life- Cycle Assessment …

Go to article

Modeling Radiation Belt Electrons With Information Theory Informed Neural Networks, Simon Wing, Drew L. Turner, Aleksandr Y. Ukhorskiy, Jay R. Johnson, Thomas Sotirelis, Romina Nikoukar, Giuseppe Romeo Aug 2022

Modeling Radiation Belt Electrons With Information Theory Informed Neural Networks, Simon Wing, Drew L. Turner, Aleksandr Y. Ukhorskiy, Jay R. Johnson, Thomas Sotirelis, Romina Nikoukar, Giuseppe Romeo

Faculty Publications

An empirical model of radiation belt relativistic electrons (μ = 560–875 MeV G−1 and I = 0.088–0.14 RE G0.5) with average energy ∼1.3 MeV is developed. The model inputs solar wind parameters (velocity, density, interplanetary magnetic field (IMF) |B|, Bz, and By), magnetospheric state parameters (SYM-H and AL), and L*. The model outputs the radiation belt electron phase space density (PSD). The model is operational from L* = 3 to 6.5. The model is constructed with neural networks assisted by information theory. Information theory is used to select the most effective and relevant solar …

Go to article

Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt Aug 2022

Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt

Faculty Publications

Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life, enabling prioritized maintenance, repair, and renovation actions that reduce asset life-cycle costs and achieve organizational objectives. However, these asset condition forecasts are calculated using standardized, self-correcting distribution models that rely on poorly-fit, continuous functions. This research presents four stepwise asset condition forecast models that utilize historical asset inspection data to improve prediction accuracy: (1) Slope, (2) Weighted Slope, (3) Condition-Intelligent Weighted Slope, and (4) …

Go to article

Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley Aug 2022

Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley

Faculty Publications

Waste-to-Energy technologies have the potential to dramatically improve both the natural and human environment. One type of waste-to-energy technology that has been successful is gasification. There are numerous types of gasification processes and in order to drive understanding and the optimization of these systems, traditional approaches like computational fluid dynamics software have been utilized to model these systems. The modern advent of machine learning models has allowed for accurate and computationally efficient predictions for gasification systems that are informed by numerous experimental and numerical solutions. Two types of machine learning models that have been widely used to solve for quantitative …

Go to article

Electron Energization Signatures In Traveling Kinetic Alfvén Waves At Storm Time Injection Fronts, A. J. Hull, P. A. Damiano, C. C. Chaston, J. R. Johnson, G. D. Reeves Aug 2022

Electron Energization Signatures In Traveling Kinetic Alfvén Waves At Storm Time Injection Fronts, A. J. Hull, P. A. Damiano, C. C. Chaston, J. R. Johnson, G. D. Reeves

Faculty Publications

The properties of traveling kinetic Alfvén waves (KAWs) and their role in energizing electrons in the inner magnetosphere during a geomagnetic storm are examined using measurements from the Van Allen Probes and Gyrofluid-Kinetic Electron (GKE) model simulations. Traveling KAWs occur in the vicinity of energetic plasma injection fronts in association with magnetic field dipolarizations. The KAWs coincide with energized field-aligned electrons at energies ≲1 keV. By using observational constraints and incorporating hot and cold electron populations, the GKE simulations are able to reproduce the observed energized electron distribution signatures. The modeling results demonstrate the crucial importance of cold electrons for …

Go to article

Strain And Strain Rate In Friction Extrusion, Xiao Li, Md Reza-E- Rabby, Anthony Guzman, Glenn Grant, Suveen Mathaudhu, Michah Hinton, Anthony P. Reynolds Aug 2022

Strain And Strain Rate In Friction Extrusion, Xiao Li, Md Reza-E- Rabby, Anthony Guzman, Glenn Grant, Suveen Mathaudhu, Michah Hinton, Anthony P. Reynolds

Faculty Publications

Friction extrusion is a metal forming process that generates large plastic strains and deformation-induced heating through friction between a rotating die and the material to be extruded. The final deformation state in friction extruded wire has been visualized in previous studies but the distribution and evolution of strain and strain rate inside the solid material have yet to be elucidated. This paper develops an approach that reveals the deformation during the process by visualizing the shape change of the pre-embedded markers in the remnant billet. For the first time, the distribution of steady-state strain and strain rate in friction extrusion …

Go to article

Analysis Of The Temperature Characteristics Of High-Speed Train Bearings Based On A Dynamics Model And Thermal Network Method, Baosen Wang, Yongqiang Liu, Bin Zhang, Wenqing Huai Aug 2022

Analysis Of The Temperature Characteristics Of High-Speed Train Bearings Based On A Dynamics Model And Thermal Network Method, Baosen Wang, Yongqiang Liu, Bin Zhang, Wenqing Huai

Faculty Publications

High-speed trains often use temperature sensors to monitor the motion state of bearings. However, the temperature of bearings can be affected by factors such as weather and faults. Therefore, it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors. In this study, a dynamics model of the axle box bearing of high-speed trains is established. The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring, inner-ring, and rolling-element faults. Based on the model, a thermal network method is introduced to study the temperature …

Go to article

Liquid-Phase Effects On Adsorption Processes In Heterogeneous Catalysis, Mehdi Zare, Mohammad S. Saleheen, Nirala Singh, Mark J. Uline, Muhammad Faheem, Andreas Heyden Aug 2022

Liquid-Phase Effects On Adsorption Processes In Heterogeneous Catalysis, Mehdi Zare, Mohammad S. Saleheen, Nirala Singh, Mark J. Uline, Muhammad Faheem, Andreas Heyden

Faculty Publications

Aqueous solvation free energies of adsorption have recently been measured for phenol adsorption on Pt(111). Endergonic solvent effects of ∼1 eV suggest solvents dramatically influence a metal catalyst's activity with significant implications for the catalyst design. However, measurements are indirect and involve adsorption isotherm models, which potentially reduces the reliability of the extracted energy values. Computational, implicit solvation models predict exergonic solvation effects for phenol adsorption, failing to agree with measurements even qualitatively. In this study, an explicit, hybrid quantum mechanical/molecular mechanical approach for computing solvation free energies of adsorption is developed, solvation free energies of phenol adsorption are computed, …

Go to article

Generative Design Of Stable Semiconductor Materials Using Deep Learning And Density Functional Theory, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Indika Perera, Jianjun Hu Aug 2022

Generative Design Of Stable Semiconductor Materials Using Deep Learning And Density Functional Theory, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Indika Perera, Jianjun Hu

Faculty Publications

Semiconductor device technology has greatly developed in complexity since discovering the bipolar transistor. In this work, we developed a computational pipeline to discover stable semiconductors by combining generative adversarial networks (GAN), classifiers, and high-throughput first-principles calculations. We used CubicGAN, a GAN-based algorithm for generating cubic materials and developed a classifier to screen the semiconductors and studied their stability using first principles. We found 12 stable AA’ MH6 semiconductors in the F-43m space group including BaNaRhH6, BaSrZnH6, BaCsAlH6, SrTlIrH6, KNaNiH6, NaYRuH6, CsKSiH6, CaScMnH6, YZnMnH …

Go to article

A Primer On The Factories Of The Future, Noble Anumbe, Clint Saidy, Ramy Harik Aug 2022

A Primer On The Factories Of The Future, Noble Anumbe, Clint Saidy, Ramy Harik

Faculty Publications

In a dynamic and rapidly changing world, customers’ often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities …

Go to article

Piezoelectric Point-Of-Care Biosensor For The Detection Of Sars-Cov-2 (Covid-19) Antibodies, Debdyuti Mandal, Mustahseen M. Indaleeb, Alexandra Younan, Sourav Banerjee Aug 2022

Piezoelectric Point-Of-Care Biosensor For The Detection Of Sars-Cov-2 (Covid-19) Antibodies, Debdyuti Mandal, Mustahseen M. Indaleeb, Alexandra Younan, Sourav Banerjee

Faculty Publications

It is always challenging to diagnose a disease using a biosensor reliably, and quickly with high sensitivity and selectivity, simultaneosuly. Recently the world experienced a global pandemic caused by a novel coronavirus (COVID-19). Although the vaccines are available, COVID-19 resulted a huge threat to the entire world with high mortality rates. Irrespective of a specific disease, there is a constant need for a cheaper and faster in-vitro, lab-on-a-chip sensor with high sensitivity and selectivity. Such sensors will not only facilitate the disease detection but will expedite and vaccine development process through detection of its corresponding antibodies when developed. In this …

Go to article

Securing Information On A Web Application System To Facilitate Online Blood Donation Booking, Hrishitva Patel Aug 2022

Securing Information On A Web Application System To Facilitate Online Blood Donation Booking, Hrishitva Patel

Faculty Publications

Blood donation has saved many lives in the past. According to statistics presented by the American Red Cross, a patient is in need of a blood transfusion every two seconds. There are many benefits that arise from blood donation to both the donor and the blood recipients. With blood donation, cancer patients, people involved in accidents, or those battling diseases that require blood donation have access to enough blood to sustain their survival. There is a need to digitize the blood donation booking to facilitate blood donation across the United States, and ensure patients in need of blood, receive their …

Go to article

Optimization Of Solar-Coal Hybridization For Low Solar Augmentation, Aaron T. Bame, Joseph Furner, Ian Hoag, Kasra Mohammadi, Kody Powell, Brian D. Iverson Aug 2022

Optimization Of Solar-Coal Hybridization For Low Solar Augmentation, Aaron T. Bame, Joseph Furner, Ian Hoag, Kasra Mohammadi, Kody Powell, Brian D. Iverson

Faculty Publications

This work presents a process to determine the preliminary optimal configuration of a concentrating solar power-coal hybrid power plant with low solar augmentation, and is demonstrated on a regenerative steam Rankine cycle coal power plant in Castle Dale, UT, USA (average DNI of 542 W m−2). A representative plant model is developed and validated against published data for a coal power plant. The simplifications that lead to the representative model from a coal power plant model include combining multiple feedwater heaters, combining turbines, and using a mass-average calculation for extraction steam properties. Comparing net power generation and boiler …

Go to article

Isogeometric Reconstruction And Crash Analysis Of A 1996 Body-In-White Dodge Neon, Kendrick M. Shepherd Jul 2022

Isogeometric Reconstruction And Crash Analysis Of A 1996 Body-In-White Dodge Neon, Kendrick M. Shepherd

Faculty Publications

Isogeometric analysis (IGA) has attracted attention from academia and industry because of its high-fidelity results, ability to represent geometry exactly, and potential to streamline the engineering design-through-analysis process. However, one of the greatest challenges limiting the scope of IGA is the ability to rapidly convert CAD geometry into a set of splines suitable for engineering analysis¾particularly for a wide set of shapes of industrial relevance. In this presentation, we describe a new, mathematically rigorous, potentially automatable framework using Ricci flow and subsequent metric optimization through which surface geometries can be rebuilt as sets of watertight, analysis-suitable, boundary-conforming semistructured NURBS patches. …

Go to article

Predicting Lattice Vibrational Frequencies Using Deep Graph Neural Networks, Nghia Nguyen, Steph-Yves V. Louis, Lai Wei, Kamal Choudhary, Ming Hu, Jianjun Hu Jul 2022

Predicting Lattice Vibrational Frequencies Using Deep Graph Neural Networks, Nghia Nguyen, Steph-Yves V. Louis, Lai Wei, Kamal Choudhary, Ming Hu, Jianjun Hu

Faculty Publications

Lattice vibrational frequencies are related to many important materials properties such as thermal and electrical conductivity as well as superconductivity. However, computational calculation of vibrational frequencies using density functional theory methods is computationally too demanding for large number of samples in materials screening. Here we propose a deep graph neural network based algorithm for predicting crystal vibrational frequencies from crystal structures. Our algorithm addresses the variable dimension of vibrational frequency spectrum using the zero padding scheme. Benchmark studies on two data sets with 15,000 mixed-structure and 35,552 rhombohedra samples show that the aggregated R2 scores of the prediction reach …

Go to article

High-Throughput Computational Evaluation Of Lattice Thermal Conductivity Using An Optimized Slack Model, Guangzhao Qin, An Huang, Yinqiao Liu, Huimin Wang, Zhenzhen Qin, Xue Jiang, Jijun Zhao, Jianjun Hu, Ming Hu Jul 2022

High-Throughput Computational Evaluation Of Lattice Thermal Conductivity Using An Optimized Slack Model, Guangzhao Qin, An Huang, Yinqiao Liu, Huimin Wang, Zhenzhen Qin, Xue Jiang, Jijun Zhao, Jianjun Hu, Ming Hu

Faculty Publications

High-throughput computational screening of materials with targeted thermal conductivity (κ) plays an important role in promoting the advancement of material design and enormous applications. The Slack model has been widely applied for the fast evaluation of κ with minimal time and resources, showing the potential capability of high-throughput screening of κ. However, after examining the Slack model on a large set of 353 materials, a huge discrepancy is found between the predicted κ and the correspondingly measured κ in experiments for some materials in addition to the generally overestimated κ by the Slack model. Thus, it is …

Go to article

First Prev Next Last