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University of South Carolina

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Full-Text Articles in Engineering

Left Ventricle Function And Post-Transcriptional Events With Exercise Training In Pigs, Stephanie L. Samani, Shayne C. Barlow, Lisa A. Freeburg, Traci L. Jones, Marlee Poole, Mark A. Sarzynski, Michael R. Zile, Tarek Shazly, Francis G. Spinale Feb 2024

Left Ventricle Function And Post-Transcriptional Events With Exercise Training In Pigs, Stephanie L. Samani, Shayne C. Barlow, Lisa A. Freeburg, Traci L. Jones, Marlee Poole, Mark A. Sarzynski, Michael R. Zile, Tarek Shazly, Francis G. Spinale

Faculty Publications

Background

Standardized exercise protocols have been shown to improve overall cardiovascular fitness, but direct effects on left ventricular (LV) function, particularly diastolic function and relation to post-transcriptional molecular pathways (microRNAs (miRs)) are poorly understood. This project tested the central hypothesis that adaptive LV remodeling resulting from a large animal exercise training protocol, would be directly associated with specific miRs responsible for regulating pathways relevant to LV myocardial stiffness and geometry.

Methods and results

Pigs (n = 9; 25 Kg) underwent a 4 week exercise training protocol (10 degrees elevation, 2.5 mph, 10 min, 5 days/week) whereby LV chamber stiffness (KC) …


Investigation Of Electrically Isolated Capacitive Sensing Skins On Concrete To Reduce Structure/Sensor Capacitive Coupling, Emmanuel Ogunniyi, Alexander Vareen, Austin Downey, Simon Laflamme, Jian Li, Caroline Bennett, William Collins, Hongki Jo, Alexander Henderson, Paul Ziehl Feb 2023

Investigation Of Electrically Isolated Capacitive Sensing Skins On Concrete To Reduce Structure/Sensor Capacitive Coupling, Emmanuel Ogunniyi, Alexander Vareen, Austin Downey, Simon Laflamme, Jian Li, Caroline Bennett, William Collins, Hongki Jo, Alexander Henderson, Paul Ziehl

Faculty Publications

Damage to bridges can result in partial or complete structural failures, with fatal consequences. Cracks develop in concrete infrastructure from fatigue loading, vibrations, corrosion, or unforeseen structural displacement. Effective long-term monitoring of civil infrastructure can reduce the risk of structural failures and potentially reduce the cost and frequency of inspections. However, deploying structural health monitoring technologies for crack detection on bridges is expensive, especially long-term, due to the density of sensors required to detect, localize, and quantify cracks. Previous research on soft elastomeric capacitors (SECs) has shown their viability for low-cost monitoring of cracks in transportation infrastructure. However, when deployed …


Uav Rapidly-Deployable Stage Sensor With Electro-Permanent Magnet Docking Mechanism For Flood Monitoring In Undersampled Watersheds, Corinne A, Smith, Joud Satme, Jacob Martin, Austin Downey, Nikolaos Vitzilaios, Jasim Imran Oct 2022

Uav Rapidly-Deployable Stage Sensor With Electro-Permanent Magnet Docking Mechanism For Flood Monitoring In Undersampled Watersheds, Corinne A, Smith, Joud Satme, Jacob Martin, Austin Downey, Nikolaos Vitzilaios, Jasim Imran

Faculty Publications

The availability of historical flood data is vital in recognizing weather-related trends and outlining necessary precautions for at-risk communities. Flood frequency, magnitude, endurance, and volume are traditionally recorded using established streamgages; however, the material and installation costs allow only a few streamgages in a region, which yield a narrow data selection. In particular, stage, the vertical water height in a water body, is an important parameter in determining flood trends. This work investigates a low-cost, compact, rapidly-deployable alternative to traditional stage sensors that will allow for denser sampling within a watershed and a more detailed record of flood events. The …


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 …


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 …


Integrated Socio-Environmental Vulnerability Assessment Of Coastal Hazards Using Data-Driven And Multi-Criteria Analysis Approaches, Ahad Hasan Tanim, Erfan Goharian Jul 2022

Integrated Socio-Environmental Vulnerability Assessment Of Coastal Hazards Using Data-Driven And Multi-Criteria Analysis Approaches, Ahad Hasan Tanim, Erfan Goharian

Faculty Publications

Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coastal Vulnerability Index (CVI), which simultaneously combines information from five vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI (CVI-50 and CVI-90) have been developed based on average and extreme conditions of the factors. Each CVI is then compared to a data-driven CVI, which is formed based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA …


Structural Health Monitoring Of Fatigue Cracks For Steel Bridges With Wireless Large-Area Strain Sensors, Sdiq Anwar Taher, Jian Li, Jong-Hyun Jeong, Simon Laflamme, Hongki Jo, Caroline Bennett, William N. Collins, Austin Downey Jul 2022

Structural Health Monitoring Of Fatigue Cracks For Steel Bridges With Wireless Large-Area Strain Sensors, Sdiq Anwar Taher, Jian Li, Jong-Hyun Jeong, Simon Laflamme, Hongki Jo, Caroline Bennett, William N. Collins, Austin Downey

Faculty Publications

This paper presents a field implementation of the structural health monitoring (SHM) of fatigue cracks for steel bridge structures. Steel bridges experience fatigue cracks under repetitive traffic loading, which pose great threats to their structural integrity and can lead to catastrophic failures. Currently, accurate and reliable fatigue crack monitoring for the safety assessment of bridges is still a difficult task. On the other hand, wireless smart sensors have achieved great success in global SHM by enabling long-term modal identifications of civil structures. However, long-term field monitoring of localized damage such as fatigue cracks has been limited due to the lack …


An Ontology For Cardiothoracic Surgical Education And Clinical Data Analytics, Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S.Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E.Beygui Jul 2022

An Ontology For Cardiothoracic Surgical Education And Clinical Data Analytics, Maryam Panahiazar, Yorick Chern, Ramon Riojas, Omar S.Latif, Usha Lokala, Dexter Hadley, Amit Sheth, Ramin E.Beygui

Faculty Publications

The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in electronic medical records (EMR) with the standard vocabulary.


Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci Jun 2022

Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci

Faculty Publications

The application of the recently developed “nth-order comprehensive sensitivity analysis methodology for nonlinear systems” (abbreviated as “nth-CASAM-N”) has been previously illustrated on paradigm nonlinear space-dependent problems. To complement these illustrative applications, this work illustrates the application of the nth-CASAM-N to a paradigm nonlinear time-dependent model chosen from the field of reactor dynamics/safety, namely the well-known Nordheim–Fuchs model. This phenomenological model describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This model is sufficiently complex to demonstrate all the …


Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci Jun 2022

Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci

Faculty Publications

The application of the recently developed “nth-order comprehensive sensitivity analysis methodology for nonlinear systems” (abbreviated as “nth-CASAM-N”) has been previously illustrated on paradigm nonlinear space-dependent problems. To complement these illustrative applications, this work illustrates the application of the nth-CASAM-N to a paradigm nonlinear time-dependent model chosen from the field of reactor dynamics/safety, namely the well-known Nordheim–Fuchs model. This phenomenological model describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted, either intentionally or by accident. This model is sufficiently complex to demonstrate all the …


The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (Nth-Casam-N): Mathematical Framework, Dan Gabriel Cacuci Jun 2022

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (Nth-Casam-N): Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (nth-CASAM-N), which enables the most efficient computation of exactly determined expressions of arbitrarily high-order sensitivities of generic nonlinear system responses with respect to model parameters, uncertain boundaries, and internal interfaces in the model’s phase space. The mathematical framework underlying the nth-CASAM-N is proven to be correct by using mathematical induction. The nth-CASAM-N is formulated in linearly increasing higher-dimensional Hilbert spaces—as opposed to exponentially increasing parameter-dimensional spaces—thus overcoming the curse of dimensionality in sensitivity analysis of nonlinear systems.


Tropospheric Attenuation Prediction For Future Millimeter Wave Terrestrial Systems: Estimating Statistics And Extremes, Jinwen Liu, David W. Matolak, Ismail Güvenç, Hani Mehrpouyan May 2022

Tropospheric Attenuation Prediction For Future Millimeter Wave Terrestrial Systems: Estimating Statistics And Extremes, Jinwen Liu, David W. Matolak, Ismail Güvenç, Hani Mehrpouyan

Faculty Publications

Tropospheric attenuations can be significant in the millimeter wave (mmWave) frequency bands; hence, accurate prediction modeling of tropospheric attenuation is important for reliable mmWave communication. Several models have been established by the International Telecommunication Union (ITU), yet estimation accuracy is limited due to the large spatial scales used for model input parameters. In this paper, we address this and apply local precipitation data to analyze tropospheric attenuation statistics and compare to results when using ITU regional input rain data. Specifically, tropospheric attenuation is predicted via simulations using the ITU method at 30, 60, and 90 GHz in four distinct geographic …


Scalable Deeper Graph Neural Networks For High-Performance Materials Property Prediction, Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu May 2022

Scalable Deeper Graph Neural Networks For High-Performance Materials Property Prediction, Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu

Faculty Publications

Machine-learning-based materials property prediction models have emerged as a promising approach for new materials discovery, among which the graph neural networks (GNNs) have shown the best performance due to their capability to learn high-level features from crystal structures. However, existing GNN models suffer from their lack of scalability, high hyperparameter tuning complexity, and constrained performance due to over-smoothing. We propose a scalable global graph attention neural network model DeeperGATGNN with differentiable group normalization (DGN) and skip connections for high-performance materials property prediction. Our systematic benchmark studies show that our model achieves the state-of-the-art prediction results on five out of six …


Chiral Liquid Crystal Microdroplets For Sensing Phospholipid Amphiphiles, Sepideh Norouzi, Jose A. Martinez Gonzalez, Monirosadat Sadati May 2022

Chiral Liquid Crystal Microdroplets For Sensing Phospholipid Amphiphiles, Sepideh Norouzi, Jose A. Martinez Gonzalez, Monirosadat Sadati

Faculty Publications

Designing simple, sensitive, fast, and inexpensive readout devices to detect biological molecules and biomarkers is crucial for early diagnosis and treatments. Here, we have studied the interaction of the chiral liquid crystal (CLC) and biomolecules at the liquid crystal (LC)-droplet interface. CLC droplets with high and low chirality were prepared using a microfluidic device. We explored the reconfiguration of the CLC molecules confined in droplets in the presence of 1,2-diauroyl-sn-glycero3-phosphatidylcholine (DLPC) phospholipid. Cross-polarized optical microscopy and spectrometry techniques were employed to monitor the effect of droplet size and DLPC concentration on the structural reorganization of the CLC molecules. Our results …


Chiral Liquid Crystal Microdroplets For Sensing Phospholipid Amphiphiles, Sepideh Norouzi, Jose A. Martinez Gonzalez, Monirosadat (Sanaz) Sadati May 2022

Chiral Liquid Crystal Microdroplets For Sensing Phospholipid Amphiphiles, Sepideh Norouzi, Jose A. Martinez Gonzalez, Monirosadat (Sanaz) Sadati

Faculty Publications

Designing simple, sensitive, fast, and inexpensive readout devices to detect biological molecules and biomarkers is crucial for early diagnosis and treatments. Here, we have studied the interaction of the chiral liquid crystal (CLC) and biomolecules at the liquid crystal (LC)-droplet interface. CLC droplets with high and low chirality were prepared using a microfluidic device. We explored the reconfiguration of the CLC molecules confined in droplets in the presence of 1,2-diauroyl-sn-glycero3-phosphatidylcholine (DLPC) phospholipid. Cross-polarized optical microscopy and spectrometry techniques were employed to monitor the effect of droplet size and DLPC concentration on the structural reorganization of the CLC molecules. Our results …


A Dual-Band Filtering Structure For Highly Selective Reconfigurable Bandpass Filter And Filtering Balun, Jinqun Ge, Guoan Wang May 2022

A Dual-Band Filtering Structure For Highly Selective Reconfigurable Bandpass Filter And Filtering Balun, Jinqun Ge, Guoan Wang

Faculty Publications

This article proposes a filtering structure consisting of two half-wavelength resonators and two open-stub loaded resonators, which generates two third-order passbands. Multiple transmission zeros are introduced by the newly developed coupling scheme, resulting in extremely sharp roll-off desirable for highly selective filters. The proposed structure is applied to design a PIN-diodes switch-controlled reconfigurable dual-band bandpass filter (BPF) with four-state filtering responses: both passbands ON, both passbands OFF, high-frequency passband ON, and low-frequency passband ON. Stepped-impedance open stubs and one-end-grounded coupled lines are studied and employed in the design to suppress unwanted responses. In addition, two filtering structures are placed symmetrically …


Audio-Based Wildfire Detection On Embedded Systems, Hung-Tien Huang, Austin Downey, Jason D. Bakos Apr 2022

Audio-Based Wildfire Detection On Embedded Systems, Hung-Tien Huang, Austin Downey, Jason D. Bakos

Faculty Publications

The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is …


Audio-Based Wildfire Detection On Embedded Systems, Hung-Tien Huang, Austin Downey, Jason D. Bakos Apr 2022

Audio-Based Wildfire Detection On Embedded Systems, Hung-Tien Huang, Austin Downey, Jason D. Bakos

Faculty Publications

The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is …


Editorial For Gels 6th Anniversary Special Issue, Esmaiel Jabbari, Gulden Camci-Unal Apr 2022

Editorial For Gels 6th Anniversary Special Issue, Esmaiel Jabbari, Gulden Camci-Unal

Faculty Publications

No abstract provided.


Editorial For Gels 6th Anniversary Special Issue, Esmaiel Jabbari, Gulden Camci-Unal Apr 2022

Editorial For Gels 6th Anniversary Special Issue, Esmaiel Jabbari, Gulden Camci-Unal

Faculty Publications

Note: In lieu of an abstract, this is an excerpt from the first page.


This Special Issue celebrates many outstanding quality papers published in Gels over the past six years since its first issue was published in 2015 [...]


Antiviral Polymers: A Review, Ali Akbari, Ashkan Bigham, Vahid Rahimkhoei, Sina Sharifi, Esmaiel Jabbari Apr 2022

Antiviral Polymers: A Review, Ali Akbari, Ashkan Bigham, Vahid Rahimkhoei, Sina Sharifi, Esmaiel Jabbari

Faculty Publications

Polymers, due to their high molecular weight, tunable architecture, functionality, and buffering effect for endosomal escape, possess unique properties as a carrier or prophylactic agent in preventing pandemic outbreak of new viruses. Polymers are used as a carrier to reduce the minimum required dose, bioavailability, and therapeutic effectiveness of antiviral agents. Polymers are also used as multifunctional nanomaterials to, directly or indirectly, inhibit viral infections. Multifunctional polymers can interact directly with envelope glycoproteins on the viral surface to block fusion and entry of the virus in the host cell. Polymers can indirectly mobilize the immune system by activating macrophages and …


Beyond Profitable Shifts To Green Energies, Towards Energy Sustainability, Farboud Khatami, Erfan Goharian Apr 2022

Beyond Profitable Shifts To Green Energies, Towards Energy Sustainability, Farboud Khatami, Erfan Goharian

Faculty Publications

The traditional carbon-based approach towards sustainability has long caused the concepts of green and sustainable energies to be used interchangeably. Recent studies have tried to advance this archaic view by considering more aspects of sustainability. However, almost all major studies have been concerned with only the economic and environmental aspects of electricity generation, whereas the concept of sustainability is beyond these two criteria. In this paper, we seek to provide a methodology for a more comprehensive definition of electricity generation sustainability based on the lessons learned from previous studies and additional metrics suggested by them. The main characteristics of select …


Atmospheric Plasma Spraying To Fabricate Metal-Supported Solid Oxide Fuel Cells With Open-Channel Porous Metal Support, Jie Lin, Haixia Li, Wanhua Wang, Peng Qiu, Greg Tao, Kevin Huang, Fanglin Chen Apr 2022

Atmospheric Plasma Spraying To Fabricate Metal-Supported Solid Oxide Fuel Cells With Open-Channel Porous Metal Support, Jie Lin, Haixia Li, Wanhua Wang, Peng Qiu, Greg Tao, Kevin Huang, Fanglin Chen

Faculty Publications

Metal-supported solid oxide fuel cells (MS-SOFCs) have been fabricated by applying phase-inversion tape-casting and atmospheric plasma spraying (APS). The effect of the binder amount of the phase-inversion slurries on the microstructure development of the 430L stainless steel metal support was investigated. The pore structures, the viscosity of the slurry, porosity and permeability of the as-prepared metal supports are significantly influenced by the amount of the binder. NiO–scandia-stabilized zirconia (ScSZ) anode, ScSZ electrolyte and La0.6Sr0.4Co0.2Fe0.8O3−δ (LSCF) cathode layers were consecutively deposited on the metal support with an ideal microstructure by APS process. The effect …


Developing An Optimized Policy Tree-Based Reservoir Operation Model For High Aswan Dam Reservoir, Nile River, Erfan Goharian, Mohamed Shaltout, Mahdi Erfani, Ahmed Eladawy Mar 2022

Developing An Optimized Policy Tree-Based Reservoir Operation Model For High Aswan Dam Reservoir, Nile River, Erfan Goharian, Mohamed Shaltout, Mahdi Erfani, Ahmed Eladawy

Faculty Publications

The impacts of climate change on the Nile River and Grand Ethiopian Renaissance Dam (GERD) along with the increased water demand downstream suggest an urgent need for more efficient management of the reservoir system that is well-informed by accurate modeling and optimization of the reservoir operation. This study provides an updated water balance model for Aswan High Dam Reservoir, which was validated using combined heterogeneous sources of information, including in situ gauge data, bias-corrected reanalyzed data, and remote sensing information. To investigate the future challenges, the spatial distribution of the annual/seasonal Aswan High Dam Reservoir surface air temperature trends over …


Decellularized Articular Cartilage Microgels As Microcarriers For Expansion Of Mesenchymal Stem Cells, Esmaiel Jabbari, Azadeh Sepahvandi Feb 2022

Decellularized Articular Cartilage Microgels As Microcarriers For Expansion Of Mesenchymal Stem Cells, Esmaiel Jabbari, Azadeh Sepahvandi

Faculty Publications

Conventional microcarriers used for expansion of human mesenchymal stem cells (hMSCs) require detachment and separation of the cells from the carrier prior to use in clinical applications for regeneration of articular cartilage, and the carrier can cause undesirable phenotypic changes in the expanded cells. This work describes a novel approach to expand hMSCs on biomimetic carriers based on adult or fetal decellularized bovine articular cartilage that supports tissue regeneration without the need to detach the expanded cells from the carrier. In this approach, the fetal or adult bovine articular cartilage was minced, decellularized, freeze-dried, ground, and sieved to produce articular …


Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (4th-Casam-N): I. Mathematical Framework, Dan Gabriel Cacuci Feb 2022

Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (4th-Casam-N): I. Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the fourth-order comprehensive sensitivity analysis methodology for nonlinear systems (abbreviated as “4th-CASAM-N”) for exactly and efficiently computing the first-, second-, third-, and fourth-order functional derivatives (customarily called “sensitivities”) of physical system responses (i.e., “system performance parameters”) to the system’s (or model) parameters. The qualifier “comprehensive” indicates that the 4th-CASAM-N methodology enables the exact and efficient computation not only of response sensitivities with respect to the customary model parameters (including computational input data, correlations, initial and/or boundary conditions) but also with respect to imprecisely known material boundaries, caused by manufacturing tolerances, of the system under consideration. The 4th-CASAM-N …


Surface Acoustic Wave (Saw) Sensors: Physics, Materials, And Applications, Debdyuti Mandal, Sourav Banerjee Jan 2022

Surface Acoustic Wave (Saw) Sensors: Physics, Materials, And Applications, Debdyuti Mandal, Sourav Banerjee

Faculty Publications

Surface acoustic waves (SAWs) are the guided waves that propagate along the top surface of a material with wave vectors orthogonal to the normal direction to the surface. Based on these waves, SAW sensors are conceptualized by employing piezoelectric crystals where the guided elastodynamic waves are generated through an electromechanical coupling. Electromechanical coupling in both active and passive modes is achieved by integrating interdigitated electrode transducers (IDT) with the piezoelectric crystals. Innovative meta-designs of the periodic IDTs define the functionality and application of SAW sensors. This review article presents the physics of guided surface acoustic waves and the piezoelectric materials …


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 Dec 2021

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 …


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. Loáiciga Dec 2021

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. Loáiciga

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 …


The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Response-Coupled Forward/Adjoint Linear Systems (NTh-Casam-L): I. Mathematical Framework, Dan Gabriel Cacuci Dec 2021

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 nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “nth-CASAM-L”), which is conceived for obtaining the exact expressions of arbitrarily-high-order (nth-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 …