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Full-Text Articles in Entire DC Network
Variable-Order Fractional Laplacian And Its Accurate And Efficient Computations With Meshfree Methods, Yixuan Wu, Yanzhi Zhang
Variable-Order Fractional Laplacian And Its Accurate And Efficient Computations With Meshfree Methods, Yixuan Wu, Yanzhi Zhang
Mathematics and Statistics Faculty Research & Creative Works
The variable-order fractional Laplacian plays an important role in the study of heterogeneous systems. In this paper, we propose the first numerical methods for the variable-order Laplacian (-Δ) α (x) / 2 with 0 < α (x) ≤ 2, which will also be referred as the variable-order fractional Laplacian if α(x) is strictly less than 2. We present a class of hypergeometric functions whose variable-order Laplacian can be analytically expressed. Building on these analytical results, we design the meshfree methods based on globally supported radial basis functions (RBFs), including Gaussian, generalized inverse multiquadric, and Bessel-type RBFs, to approximate the variable-order Laplacian (-Δ) α (x) / 2. Our meshfree methods integrate the advantages of both pseudo-differential and hypersingular integral forms of the variable-order fractional Laplacian, and thus avoid numerically approximating the hypersingular integral. Moreover, our methods are simple and flexible of domain geometry, and their computer implementation remains the same for any dimension d ≥ 1. Compared to finite difference methods, our methods can achieve a desired accuracy with much fewer points. This fact makes our method much attractive for problems involving variable-order fractional Laplacian where the number of points required is a critical cost. We then apply our method to study solution behaviors of variable-order fractional PDEs arising in different fields, including transition of waves between classical and fractional media, and coexistence of anomalous and normal diffusion in both diffusion equation and the Allen–Cahn equation. These results would provide insights for further understanding and applications of variable-order fractional derivatives.
Comprehensive Understanding Of Factors Impacting Competitive Construction Bidding, Muaz O. Ahmed, Islam H. El-Adaway, Aubrie Caldwell
Comprehensive Understanding Of Factors Impacting Competitive Construction Bidding, Muaz O. Ahmed, Islam H. El-Adaway, Aubrie Caldwell
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Construction competitive bidding has been studied by many researchers; however, their focus was mainly on certain bidding aspects. Thus, despite their value, existing bidding models have limited applicability for various reasons including the non-inclusion of some real-life factors that impact bidding-related decisions. As such, there is a need for identifying a comprehensive list of bidding factors that impact construction bidding-related decisions, studying their associations, and identifying understudied factors to direct future research efforts. This paper fills this knowledge gap. First, the authors conducted a systematic selection of 124 construction bidding-related articles published within the past 40 years. Second, the authors …
Risk–Reward Share Allocation Under Different Integrated Project Delivery Relational Structures: A Monte-Carlo Simulation And Cooperative Game Theoretic Solutions Approach, Radwa Eissa, Mohamad Abdul Nabi, Islam H. El-Adaway
Risk–Reward Share Allocation Under Different Integrated Project Delivery Relational Structures: A Monte-Carlo Simulation And Cooperative Game Theoretic Solutions Approach, Radwa Eissa, Mohamad Abdul Nabi, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Sharing of risks and rewards is considered to be one of the key benefits and principles of integrated project delivery (IPD). Despite its importance, risk–reward strategies are not implemented widely in IPD construction projects due to the lack of a well-defined basis for establishing adequate allocation plans. This paper fills this knowledge gap. This research followed a multistep methodology. First, the authors calculated the risk control valuations of all potential combinations of coalitions for IPD stakeholders. This was performed using interrelated steps of risk identification and quantification, risk assignment based on associated contractual analysis, establishment of a coordination network, and …
The Dynamics Of The Flavin, Nadph, And Active Site Loops Determine The Mechanism Of Activation Of Class B Flavin-Dependent Monooxygenases, Gustavo Pierdominici-Sottile, Juliana Palma, María Leticia Ferrelli, Pablo Sobrado
The Dynamics Of The Flavin, Nadph, And Active Site Loops Determine The Mechanism Of Activation Of Class B Flavin-Dependent Monooxygenases, Gustavo Pierdominici-Sottile, Juliana Palma, María Leticia Ferrelli, Pablo Sobrado
Chemistry Faculty Research & Creative Works
Flavin-dependent monooxygenases (FMOs) constitute a diverse enzyme family that catalyzes crucial hydroxylation, epoxidation, and Baeyer–Villiger reactions across various metabolic pathways in all domains of life. Due to the intricate nature of this enzyme family's mechanisms, some aspects of their functioning remain unknown. Here, we present the results of molecular dynamics computations, supplemented by a bioinformatics analysis, that clarify the early stages of their catalytic cycle. We have elucidated the intricate binding mechanism of NADPH and L-Orn to a class B monooxygenase, the ornithine hydroxylase from (Formula presented.) (Formula presented.) known as SidA. Our investigation involved a comprehensive characterization of the …
Structure, Dynamics, And Redox Reactivity Of An All-Purpose Flavodoxin, Sharique Khan, Ahmadullah Ansari, Monica Brachi, Debarati Das, Wassim El Housseini, Shelley Minteer, Anne Frances Miller
Structure, Dynamics, And Redox Reactivity Of An All-Purpose Flavodoxin, Sharique Khan, Ahmadullah Ansari, Monica Brachi, Debarati Das, Wassim El Housseini, Shelley Minteer, Anne Frances Miller
Chemistry Faculty Research & Creative Works
The Flavodoxin Of Rhodopseudomonas Palustris CGA009 (Rp9Fld) Supplies Highly Reducing Equivalents To Crucial Enzymes Such As Hydrogenase, Especially When The Organism Is Iron-Restricted. By Acquiring Those Electrons From Photodriven Electron Flow Via The Bifurcating Electron Transfer Flavoprotein, Rp9Fld Provides Solar Power To Vital Metabolic Processes. To Understand Rp9Fld's Ability To Work With Diverse Partners, We Solved Its Crystal Structure. We Observed The Canonical Flavodoxin (Fld) Fold And Features Common To Other Long-Chain Flds But Not All The Surface Loops Thought To Recognize Partner Proteins. Moreover, Some Of The Loops Display Alternative Structures And Dynamics. To Advance Studies Of Protein–protein Associations …
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Computer Science Faculty Research & Creative Works
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …
Physical And Chemical Methods To Assess Performance Of Tpo-Modified Asphalt Binder, Rebecca M. Herndon, Jay Balasubramanian, Klaus Woelk, Magdy Abdelrahman
Physical And Chemical Methods To Assess Performance Of Tpo-Modified Asphalt Binder, Rebecca M. Herndon, Jay Balasubramanian, Klaus Woelk, Magdy Abdelrahman
Chemistry Faculty Research & Creative Works
The Demand for Effective Asphalt Additives is Growing as Road Infrastructure Ages and More Sustainable Pavement Solutions Are Needed. Tire Pyrolysis Oil (TPO) is an Example Material that Has Been Gaining Attention as a Potential Asphalt Additive. While Physical Performance Grade (PG) Temperatures Are the Predominant Performance Requirements for Asphalt Binders, Chemical Properties Are Also Significant in the Evaluation of Asphalt Performance. There is a Need to Chemically Characterize the Aging of Asphalt Binders Modified with TPO and Link Chemical Changes in Binder Components to Binder Performance. This Study Compares 2%, 4%, and 8% TPO and Asphalt Binder Blends Via …
Multifunctional Models In Digital And Physical Twinning Of The Built Environment—A University Campus Case Study, Genda Chen, Ibrahim Alomari, Woubishet Zewdu Taffese, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Tarutal Ghosh Mondal, Son Nguyen
Multifunctional Models In Digital And Physical Twinning Of The Built Environment—A University Campus Case Study, Genda Chen, Ibrahim Alomari, Woubishet Zewdu Taffese, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Tarutal Ghosh Mondal, Son Nguyen
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The Digital Twin (DT) Concept Has Been Developed for a Single Function in Previous Studies. This Study Aims to Empower DTs with a Layered Integration of Multifunctional Models in the Built Environment. It Develops a Framework of DT Modules in Three Hierarchical Tiers: Region, Asset, and System; Defines a New Concept of the Degree of Digital Twinning (DODT) to the Real World by the Number of Models Enabled by a Common DT Platform; and Enables Spatiotemporal Analysis in Multiple Scales to Couple Nonstructural with Structural Building Components and Connect the Built Environment to Planning Constructions. While the Asset and System …
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Computer Science Faculty Research & Creative Works
The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …
Nitrene-Transfer Chemistry To C-H And C═C Bonds Mediated By Triangular Coinage Metal Platforms Supported By Triply Bridging Pnictogen Elements Sb(Iii) And Bi(Iii), Meenakshi Sharma, Reece M. Fritz, Joseph O. Adebanjo, Zhou Lu, Thomas R. Cundari, Mohammad A. Omary, Amitava Choudhury, Pericles Stavropoulos
Nitrene-Transfer Chemistry To C-H And C═C Bonds Mediated By Triangular Coinage Metal Platforms Supported By Triply Bridging Pnictogen Elements Sb(Iii) And Bi(Iii), Meenakshi Sharma, Reece M. Fritz, Joseph O. Adebanjo, Zhou Lu, Thomas R. Cundari, Mohammad A. Omary, Amitava Choudhury, Pericles Stavropoulos
Chemistry Faculty Research & Creative Works
Tripodal Ligands (TMG3trphen-E) That Feature Heavy Pnictogen Elements (E = Sb(III), Bi(III)) And Tetramethylguanidinyl (TMG) Arms Have Been Explored In Stabilizing Cu(I) And Ag(I) Sites And Facilitating Nitrene-Transfer Chemistry. Compounds [(TMG3trphen-E)M3(Μ-X)3] (M = Cu(I), Ag(I); X = Cl, Br, I) Have Been Generated Upon Extraction Of M3(Μ-X)3 Units From MX Sources, Exhibiting Support Of The Crown-Shaped M3(Μ-X)3 Fragment By M-NTMG Bonds And Triply Bridging E → M3 Interactions. Orbital Interactions Between Cu(I) Sites And NTMG Residues Are More Dominant Than Sb/Bi → Cu3 Donor Interactions Between The Sb 5s Or Bi 6s Orbitals And Admixed Cu 4s/3d Orbitals, With Larger …
Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Computer Science Faculty Research & Creative Works
The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient Ascent as an Approximation. However, as Training Progresses, the Non-Linearity of the Loss Landscape Increases, Rendering One-Step Gradient Ascent Less Effective. on the Other Hand, Multi-Step Gradient Ascent Will Incur Higher Training Cost. in This Paper, We Introduce a Normalized Hessian Trace to Accurately Measure the Curvature of Loss Landscape on Both Training and Test Sets. in Particular, to Counter Excessive Non-Linearity of Loss Landscape, …
The Shock Cone Instabilities And Quasi-Periodic Oscillations Around The Hartle–Thorne Black Hole, Orhan Donmez, Fatih Dogan
The Shock Cone Instabilities And Quasi-Periodic Oscillations Around The Hartle–Thorne Black Hole, Orhan Donmez, Fatih Dogan
Materials Science and Engineering Faculty Research & Creative Works
To explain the observed X-ray data in a black hole–accreting matter system and understand the physical mechanisms behind QPOs, we have numerically modeled the dynamical and oscillation properties of the shock cone formed around both slowly and rapidly rotating Hartle–Thorne black holes, resulting from the mechanism of Bondi–Hoyle–Lyttleton (BHL). According to the numerical simulations, an increase in the quadrupole parameter leads to a decrease in the shock cone opening angle around the black hole. A larger quadrupole parameter results in more matter falling into the black hole within the cone. The combination of the quadrupole parameter and black hole rotation …
Second Inflection Point Of Supercooled Water Surface Tension Induced By Hydrogen Bonds: A Molecular-Dynamics Study, Fawaz Hrahsheh, Inshad Jum'h, Gerald Wilemski
Second Inflection Point Of Supercooled Water Surface Tension Induced By Hydrogen Bonds: A Molecular-Dynamics Study, Fawaz Hrahsheh, Inshad Jum'h, Gerald Wilemski
Physics Faculty Research & Creative Works
Surface Tension Of Supercooled Water Is A Fundamental Property In Various Scientific Processes. In This Study, We Perform Molecular Dynamics Simulations With The TIP4P-2005 Model To Investigate The Surface Tension Of Supercooled Water Down To 220 K. Our Results Show A Second Inflection Point (SIP) In The Surface Tension At Temperature TSIP ≈ 267.5 ± 2.3 K. Using An Extended IAPWS-E Functional Fit For The Water Surface Tension, We Calculate The Surface Excess Internal-Energy And Entropy Terms Of The Excess Helmholtz Free Energy. Similar To Prior Studies [Wang Et Al., Phys. Chem. Chem. Phys. 21, 3360 (2019); Gorfer Et Al., …
Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang
Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This study reports for the first time, to the best of our knowledge, a real-time detection of ultralow-concentration chemical gases using fiber-optic technology, combining a miniaturized Fabry-Perot interferometer (FPI) with metal-organic frameworks (MOFs). The sensor consists of a short and thick-walled silica capillary segment spliced to a lead-in single-mode fiber (SMF), housing a tiny single crystal of HKUST-1 MOF, imparting chemo selectivity features. Ethanol and benzene gases were tested, resulting in a shift in the FPI interference signal. The sensor demonstrated high sensitivity, detecting ethanol gas concentrations (EGCs) with a sensitivity of 0.428 nm/ppm between 24.9 and 40.11 ppm and …
Feature Engineering And Supervised Machine Learning To Forecast Biogas Production During Municipal Anaerobic Co-Digestion, Hunter W. Schroer, Craig L. Just
Feature Engineering And Supervised Machine Learning To Forecast Biogas Production During Municipal Anaerobic Co-Digestion, Hunter W. Schroer, Craig L. Just
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Municipalities with excess anaerobic digestion capacity accept offsite wastes for co-digestion to meet sustainability goals and create more biogas. Despite the benefits inherent to co-digestion, the temporal and compositional heterogeneity of external waste streams creates operational challenges that lead to upsets or conservative co-digestion. Given the complex microbial bioprocesses occurring during anaerobic digestion, prediction and modeling of the outcomes can be challenging, and machine learning has the potential to improve understanding and control of co-digestion processes. Biogas flows are a surrogate for process health, and here, we predicted biogas production from historical data collected by a water resource recovery facility …
Highly Efficient Dopamine Sensing With A Carbon Nanotube-Encapsulated Metal Chalcogenide Nanostructure, Harish Singh, Jiandong Wu, Kurt A.L. Lagemann, Manashi Nath
Highly Efficient Dopamine Sensing With A Carbon Nanotube-Encapsulated Metal Chalcogenide Nanostructure, Harish Singh, Jiandong Wu, Kurt A.L. Lagemann, Manashi Nath
Chemical and Biochemical Engineering Faculty Research & Creative Works
Carbon nanotube-encapsulated nickel selenide composite nanostructures were used as nonenzymatic electrochemical sensors for dopamine detection. These composite nanostructures were synthesized through a simple, one-step, and environmentally friendly chemical vapor deposition method, wherein the CNTs were formed in situ from pyrolysis of a carbon-rich metallo-organic precursor. The composition and morphology of these hybrid NiSe2-filled carbon nanostructures were confirmed by powder X-ray diffraction, Raman, X-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy images. Electrochemical tests demonstrated that the as-synthesized hybrid nanostructures exhibited outstanding electrocatalytic performance toward dopamine oxidation, with a high sensitivity of 19.62 μA μM-1 cm-2, low detection limit, broad linear …
Thermal Performance Of Forced Convection Of Water- Nepcm Nanofluid Over A Semi-Cylinder Heat Source, Xiaoming Wang, Rassol H. Rasheed, Babak Keivani, Dheyaa J. Jasim, Abbas J. Sultan, Sajad Hamedi, Hamed Kazemi-Varnamkhasti, Soheil Salahshour, Davood Toghraie
Thermal Performance Of Forced Convection Of Water- Nepcm Nanofluid Over A Semi-Cylinder Heat Source, Xiaoming Wang, Rassol H. Rasheed, Babak Keivani, Dheyaa J. Jasim, Abbas J. Sultan, Sajad Hamedi, Hamed Kazemi-Varnamkhasti, Soheil Salahshour, Davood Toghraie
Mathematics and Statistics Faculty Research & Creative Works
1) Background: Phase change materials (PCMs) have been used statically, which has caused the use of these materials to face challenges. Encapsulating PCMs and combining them with the base fluid can significantly solve the problem of using PCMs in BTM systems. In the present study, based on computational fluid dynamics, forced convection heat transfer of nano-encapsulated phase change materials (NEPCM) in a BTM system are simulated. The main aim of the present research is to reduce the temperature at the surface of the hot cylinder. 2) Methods: In this research, we simulated lithium battery thermal management systems in both steady …
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is, however, challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This article, therefore, proposes a multilayered Mult timescale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. in the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy …
Circular Economy Policies For Decarbonization Of Us Commercial Building Stocks: Data Integration And System Dynamics Coflow Modeling Approach, Radwa Eissa, Islam H. El-Adaway
Circular Economy Policies For Decarbonization Of Us Commercial Building Stocks: Data Integration And System Dynamics Coflow Modeling Approach, Radwa Eissa, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Despite the recognition of the built environment as a sector with high potential for reducing embodied emissions, there is a lack of national-level data on embodied carbon emissions attributed to the US commercial building stocks. Hence, there is a need to benchmark the current state of embodied emissions attributed to the commercial built environment and the impact of circular economy (CE) policies for their decarbonization to facilitate well-informed decision-making. This paper fills this knowledge gap through providing policy makers with a framework that estimates the current and future projections of embodied carbon emissions attributable to the US commercial building stocks …
Ionization Cross Sections Of Hydrogen Molecule By Electron And Positron Impact, Károly Tőkési, Robert D. Dubois
Ionization Cross Sections Of Hydrogen Molecule By Electron And Positron Impact, Károly Tőkési, Robert D. Dubois
Physics Faculty Research & Creative Works
We Present Ionization Cross Sections of Hydrogen Molecules by Electron and Positron Impact for Impact Energies between 20 and 1000 EV. a Three-Body Classical Trajectory Monte Carlo Approximation is Applied to Mimic the Collision System. in This Approach, the H2 Molecule is Modeled by a Hydrogen-Type Atom with One Active Electron Bound to a Central Core of Effective Charge with an Effective Binding Energy. Although This Model is Crude for Describing a Hydrogen Molecule, We Found that the Total Cross Sections for Positron Impact Agree Reasonably Well with the Experimental Data. for the Electron Impact, Our Calculated Cross Sections Are …
Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi
Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi
Physics Faculty Research & Creative Works
Scale Invariance And Self-Similarity In Physics Provide A Unified Framework For Classifying Phases Of Matter And Dynamical Properties Near Equilibrium In Both Classical And Quantum Systems. This Paradigm Has Been Further Extended To Isolated Many-Body Quantum Systems Driven Far From Equilibrium, For Which The Physical Observables Exhibit Dynamical Scaling With Universal Scaling Exponents. Universal Dynamics Appear In A Wide Range Of Scenarios, Including Cosmology, Quark–gluon Matter, Ultracold Atoms And Quantum Spin Magnets. However, How The Universal Dynamics Depend On The Symmetry Of The Underlying Hamiltonian In Non-Equilibrium Systems Remains An Outstanding Challenge. Here We Report On The Classification Of Universal …
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN back-stepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in …
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a high step-up dc-dc converter based on a trans-inverse impedance-source structure, in which the voltage gain of the converter is increased by using a lower number of turns ratio of the coupled inductors (CI) windings. The proposed converter achieves a very high voltage gain and a very low voltage stress on the switches. An active clamp is incorporated into the topology of the proposed converter, helping to absorb the energy of the leakage inductances of the CI, and to recycle that energy to the output of the converter to further increase the voltage gain. Furthermore, the active …
Jet-Driven Mixing Regimes Identified In The Unsteady Isothermal Filling Of Rectangular Municipal Water Storage Tanks, Pramod Narayan Bangalore, K. (Kelly) O. Homan
Jet-Driven Mixing Regimes Identified In The Unsteady Isothermal Filling Of Rectangular Municipal Water Storage Tanks, Pramod Narayan Bangalore, K. (Kelly) O. Homan
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Poor mixing of old and new water in municipal water storage vessels is a well-documented basis for potentially harmful water quality degradation in drinking water distribution systems. This numerical study investigates the effects of inflow and operational variables on mixing in the jet-driven filling process, with a particular focus on the transition from inadequate to sufficient mixing levels. An isothermal unsteady reynolds-averaged-navier-stokes volume-of-fluid (RANS-VOF) simulation is used to model the variable-volume filling process, accounting for the moving free surface following a draw-down in the stored water volume. A low diffusivity tracer is used to mark the old-water volume, and a …
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Chemistry Faculty Research & Creative Works
Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic Mutations To Altered Protein Structures, And Altered Proteins To Changes In Molecular Functions And Biological Processes. It Is Desirable To Gain New Insights From These Data, Especially With Regard To The Uncovering Of Hierarchical Structures Relating Disease Variants. However, Analysis To This End Has Proven Difficult Due To The Complexity Of The Connections Between Multi-Categorical Symbolic Data. This Article Proposes Symbolic Tree Adaptive Resonance Theory (START), With Additional Supervised, Dual-Vigilance (DV-START), And Distributed Dual-Vigilance (DDV-START) Formulations, For The Clustering Of …
Comprehensive Numerical Modeling Of Prestressed Girder Bridges Under Low-Velocity Impact, Mohamed T. Elshazli, Mohanad M. Abdulazeez, Mohamed Elgawady, Ahmed Ibrahim
Comprehensive Numerical Modeling Of Prestressed Girder Bridges Under Low-Velocity Impact, Mohamed T. Elshazli, Mohanad M. Abdulazeez, Mohamed Elgawady, Ahmed Ibrahim
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Accidental Collisions Involving Over-Height Trucks That Exceed Vertical Clearance Limits And Bridge Superstructures Frequently Happen, Resulting In Compromised Girders And Potential Threats To Structural Safety And Performance. The Numerical Simulation Of Large-Scale Prestressed Girder Bridge Collisions Poses Challenges Due To The Associated Nonlinearities, As Well As The Limited Availability Of Large-Scale Experimental Testing Data In The Literature Due To Cost And Complexity Constraints. This Study Introduces A Numerical Modeling Approach To Efficiently Capture The Response Of Prestressed Girder Bridges Under Lateral Impact Loads. A Finite Element (FE) Model Was Developed Using LS-DYNA And Meticulously Validated Against Experimental Data From The …
Natural Gas Induced Vegetation Stress Identification And Discrimination From Hyperspectral Imaging For Pipeline Leakage Detection, Pengfei Ma, Ying Zhuo, Genda Chen, Joel G. Burken
Natural Gas Induced Vegetation Stress Identification And Discrimination From Hyperspectral Imaging For Pipeline Leakage Detection, Pengfei Ma, Ying Zhuo, Genda Chen, Joel G. Burken
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Remote Sensing Detection of Natural Gas Leaks Remains Challenging When using Ground Vegetation Stress to Detect Underground Pipeline Leaks. Other Natural Stressors May Co-Present and Complicate Gas Leak Detection. This Study Explores the Feasibility of Identifying and Distinguishing Gas-Induced Stress from Other Natural Stresses by Analyzing the Hyperspectral Reflectance of Vegetation. the Effectiveness of This Discrimination is Assessed Across Three Distinct Spectral Ranges (VNIR, SWIR, and Full Spectra). Greenhouse Experiments Subjected Three Plant Species to Controlled Environmental Stressors, Including Gas Leakage, Salinity Impact, Heavy-Metal Contamination, and Drought Exposure. Spectral Curves Obtained from the Experiments Underwent Preprocessing Techniques Such as Standard …
Technical Note: Generalizable And Promptable Artificial Intelligence Model To Augment Clinical Delineation In Radiation Oncology, Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, William W. Wong, Sujay A. Vora, Dajiang Zhu, Tianming Liu, Wei Liu
Technical Note: Generalizable And Promptable Artificial Intelligence Model To Augment Clinical Delineation In Radiation Oncology, Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, William W. Wong, Sujay A. Vora, Dajiang Zhu, Tianming Liu, Wei Liu
Computer Science Faculty Research & Creative Works
Background: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for treatment planning and dose evaluation. Deep learning-based auto-segmentation of OARs has shown promising results and is increasingly being used in radiation therapy. However, existing deep learning-based auto-segmentation approaches face two challenges in clinical practice: generalizability and human-AI interaction. A generalizable and prompt able auto-segmentation model, which segments OARs of multiple disease sites simultaneously and supports on-the-fly human-AI interaction, can significantly enhance the efficiency of radiation therapy treatment planning. Purpose: Meta's segment anything model (SAM) was proposed as a generalizable and prompt able model for next-generation …
Inverting Geodetic Strain Rates For Slip Deficit Rate In Complex Deforming Zones: An Application To The New Zealand Plate Boundary, Kaj M. Johnson, Laura M. Wallace, Jeremy Maurer, Ian Hamling, Charles Williams, Chris Rollins, Matt Gerstenberger, Russ Van Dissen
Inverting Geodetic Strain Rates For Slip Deficit Rate In Complex Deforming Zones: An Application To The New Zealand Plate Boundary, Kaj M. Johnson, Laura M. Wallace, Jeremy Maurer, Ian Hamling, Charles Williams, Chris Rollins, Matt Gerstenberger, Russ Van Dissen
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
The potential for future earthquakes on faults is often inferred from inversions of geodetically derived surface velocities for locking on faults using kinematic models such as block models. This can be challenging in complex deforming zones with many closely spaced faults or where deformation is not readily described with block motions. Furthermore, surface strain rates are more directly related to coupling on faults than surface velocities. We present a methodology for estimating slip deficit rate directly from strain rate and apply it to New Zealand for the purpose of incorporating geodetic data in the 2022 revision of the New Zealand …
Acs Measurement Science Au In 2024, Shelley Minteer
Acs Measurement Science Au In 2024, Shelley Minteer
Chemistry Faculty Research & Creative Works
No abstract provided.