| 1. |
- Chen, Yicheng, et al.
(author)
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Computational fluid-structure interaction analysis of flapping uvula on aerodynamics and pharyngeal vibration in a pediatric airway
- 2023
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 13:1, s. 2013-
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Journal article (peer-reviewed)abstract
- The uvula flapping is one of the most distinctive features of snoring and is critical in affecting airway aerodynamics and vibrations. This study aimed to elucidate the mechanism of pharyngeal vibration and pressure fluctuation due to uvula flapping employing fluid-structure interaction simulations. The followings are the methodology part: we constructed an anatomically accurate pediatric pharynx model and put attention on the oropharynx region where the greatest level of upper airway compliance was reported to occur. The uvula was assumed to be a rigid body with specific flapping frequencies to guarantee proper boundary conditions with as little complexity as possible. The airway tissue was considered to have a uniform thickness. It was found that the flapping frequency had a more significant effect on the airway vibration than the flapping amplitude, as the flapping uvula influenced the pharyngeal aerodynamics by altering the jet flow from the mouth. Breathing only through the mouth could amplify the effect of flapping uvula on aerodynamic changes and result in more significant oropharynx vibration.
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| 2. |
- Chen, Yicheng, et al.
(author)
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Evaluation of computational fluid dynamics models for predicting pediatric upper airway airflow characteristics
- 2023
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In: Medical and Biological Engineering and Computing. - : Springer. - 0140-0118 .- 1741-0444. ; 61:1, s. 259-270
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Journal article (peer-reviewed)abstract
- Computational fluid dynamics (CFD) has the potential for use as a clinical tool to predict the aerodynamics and respiratory function in the upper airway (UA) of children; however, careful selection of validated computational models is necessary. This study constructed a 3D model of the pediatric UA based on cone beam computed tomography (CBCT) imaging. The pediatric UA was 3D printed for pressure and velocity experiments, which were used as reference standards to validate the CFD simulation models. Static wall pressure and velocity distribution inside of the UA under inhale airflow rates from 0 to 266.67 mL/s were studied by CFD simulations based on the large eddy simulation (LES) model and four Reynolds-averaged Navier-Stokes (RANS) models. Our results showed that the LES performed best for pressure prediction; however, it was much more time-consuming than the four RANS models. Among the RANS models, the Low Reynolds number (LRN) SST k-ω model had the best overall performance at a series of airflow rates. Central flow velocity determined by particle image velocimetry was 3.617 m/s, while velocities predicted by the LES, LRN SST k-ω, and k-ω models were 3.681, 3.532, and 3.439 m/s, respectively. All models predicted jet flow in the oropharynx. These results suggest that the above CFD models have acceptable accuracy for predicting pediatric UA aerodynamics and that the LRN SST k-ω model has the most potential for clinical application in pediatric respiratory studies.
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| 3. |
- Chen, Yicheng, et al.
(author)
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Impact of palatopharyngeal sizes changing on pharyngeal airflow fluctuation and airway vibration in a pediatric airway
- 2024
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In: Journal of Biomechanics. - : Elsevier. - 0021-9290 .- 1873-2380. ; 168, s. 112111-112111
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Journal article (peer-reviewed)abstract
- Snoring is common in children and is associated with many adverse consequences. One must study the relationships between pharyngeal morphology and snoring physics to understand snoring progression. Although some model studies have provided fluid–structure interaction dynamic descriptions for the correlation between airway size and snoring physics, the descriptions still need to be further investigated in patient-specific airway models. Fluid-structure interaction studies using patient-specific airway structures complement the above model studies. Based on reported cephalometric measurement methods, this study quantified and preset the size of the palatopharynx airway in a patient-specific airway and investigated how the palatopharynx size affects the pharyngeal airflow fluctuation, soft palate vibration, and glossopharynx vibration with the help of a verified FSI method. The results showed that the stenosis anterior airway of the soft palate increased airway resistance and airway resistance fluctuations, which can lead to increased sleep effort and frequent snoring. Widening of the anterior airway can reduce airflow resistance and avoid obstructing the anterior airway by the soft palate vibration. The pharyngeal airflow resistance, mouth inflow proportion, and soft palate apex displacement have components at the same frequencies in all airway models, and the glossopharynx vibration and instantaneous inflow rate have components at the same frequencies, too. The mechanism of this same frequency fluctuation phenomenon can be explained by the fluid–structure interaction dynamics of an ideal coupled model consisting of a flexible plate model and a collapsible tube model. The results of this study demonstrate the potential of FSI in studying snoring physics and clarify to some degree the mechanism of airway morphology affecting airway vibration physics.
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| 4. |
- Chen, Yicheng, et al.
(author)
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Impact of sleep posture and breathing pattern on soft palate flutter and pharynx vibration in a pediatric airway using fluid-structure interaction
- 2023
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In: Journal of Biomechanics. - : Elsevier. - 0021-9290 .- 1873-2380. ; 152
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Journal article (peer-reviewed)abstract
- Snoring is a common condition in the general population, and the management of snoring requires a better understanding of its mechanism through a fluid-structure interaction (FSI) perspective. Despite the recent popularity of numerical FSI techniques, outstanding challenges are accurately predicting airway deformation and its vibration during snoring due to complex airway morphology. In addition, there still needs to be more un-derstanding of snoring inhibition when lying on the side, and the possible effect of airflow rates, as well as nose or mouth-nose breathing, on snoring remains to be investigated. In this study, an FSI method verified against in vitro models was introduced to predict upper airway deformation and vibration. The technique was applied to predict airway aerodynamics, soft palate flutter, and airway vibration in four sleep postures (supine, left/right lying, and sitting positions) and four breathing patterns (mouth-nose, nose, mouth, and unilateral nose breathing). It was found that, at given elastic properties of soft tissues, the evaluated flutter frequency of 19.8 Hz in inspiration was in good agreement with the reported frequency of snoring sound in literature. Reduction in flutter and vibrations due to the mouth-nose airflow proportion changes were also noticed when having side-lying and sitting positions. Breathing through the mouth results in larger airway deformation than breathing through the nose or mouth-nose. These results collectively demonstrate the potential of FSI for studying the physics of airway vibration and clarify to some degree the reason for snoring inhibition during sleep postures and breathing patterns.
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| 5. |
- Feng, Xin, et al.
(author)
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Aerodynamic characteristics in upper airways among orthodontic patients and its association with adenoid nasopharyngeal ratios in lateral cephalograms
- 2021
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In: BMC Medical Imaging. - : BioMed Central. - 1471-2342. ; 21:1
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Journal article (peer-reviewed)abstract
- Background Adenoid hypertrophy among orthodontic patients may be detected in lateral cephalograms. The study investigates the aerodynamic characteristics within the upper airway (UA) by means of computational fluid dynamics (CFD) simulation. Furthermore, airflow features are compared between subgroups according to the adenoidal nasopharyngeal (AN) ratios. Methods This retrospective study included thirty-five patients aged 9-15 years having both lateral cephalogram and cone beam computed tomography (CBCT) imaging that covered the UA region. The cases were divided into two subgroups according to the AN ratios measured on the lateral cephalograms: Group 1 with an AN ratio < 0.6 and Group 2 with an AN ratio >= 0.6. Based on the CBCT images, segmented UA models were created and the aerodynamic characteristics at inspiration and expiration were simulated by the CFD method for the two groups. The studied aerodynamic parameters were pressure drop (Delta P), maximum midsagittal velocity (V-ms), maximum wall shear stress (P-ws), and minimum wall static pressure (P-w). Results The maximum V-ms exhibits nearly 30% increases in Group 2 at both inspiration (p = 0.013) and expiration (p = 0.045) compared to Group 1. For the other aerodynamic parameters such as Delta P, the maximum P-ws, and minimum P-w, no significant difference is found between the two groups. Conclusions The maximum V-ms seems to be the most sensitive aerodynamic parameter for the groups of cases. An AN ratio of more than 0.6 measured on a lateral cephalogram may associate with a noticeably increased maximum V-ms, which could assist clinicians in estimating the airflow features in the UA.
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| 6. |
- Feng, Xin, et al.
(author)
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The effect of rapid maxillary expansion on the upper airway's aerodynamic characteristics
- 2021
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In: BMC Oral Health. - : BioMed Central. - 1472-6831. ; 21:1
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Journal article (peer-reviewed)abstract
- BackgroundThe effect of rapid maxillary expansion (RME) on the upper airway (UA) has been studied earlier but without a consistent conclusion. This study aims to evaluate the outcome of RME on the UA function in terms of aerodynamic characteristics by applying a computational fluid dynamics (CFD) simulation.MethodsThis retrospective cohort study consists of seventeen cases with two consecutive CBCT scans obtained before (T0) and after (T1) RME. Patients were divided into two groups with respect to patency of the nasopharyngeal airway as expressed in the adenoidal nasopharyngeal ratio (AN): group 1 was comprised of patients with an AN ratio<0.6 and group 2 encompassing those with an AN ratio0.6. CFD simulation at inspiration and expiration were performed based on the three-dimensional (3D) models of the UA segmented from the CBCT images. The aerodynamic characteristics in terms of pressure drop (Delta P), maximum midsagittal velocity (V-ms), and maximum wall shear stress (P-ws) were compared by paired t-test and Wilcoxon test according to the normality test at T0 and T1.ResultsThe aerodynamic characteristics in UA revealed no statistically significant difference after RME. The maximum V-ms (m/s) decreased from 2.79 to 2.28 at expiration after RME (P=0.057).ConclusionThe aerodynamic characteristics were not significantly changed after RME. Further CFD studies with more cases are warranted.
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| 7. |
- Galoppini, Elena, et al.
(author)
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Fast electron transport in metal organic vapor deposition grown dye-sensitized ZnO nanorod solar cells
- 2006
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In: Journal of Physical Chemistry B. - : American Chemical Society (ACS). - 1520-6106 .- 1520-5207. ; 110:33, s. 16159-16161
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Journal article (peer-reviewed)abstract
- The electron transport in dye-sensitized solar cells with a MOCVD (metal organic vapor deposition)-grown ZnO nanorod array (ZnO-N) or a mesoporous film prepared from ZnO colloids (ZnO-C) as the working electrode was compared. The electrodes were of similar thickness (2 Am) and sensitized with zinc(II) mesotetrakis(3-carboxyphenyl) porphyrin, while the electrolyte was I-/I-3-in 3-methoxypropionitrile. Electron transport in the ZnO-C cells was comparable with that found for colloidal TiO2 films (transport time similar to 10 ms) and was light intensity dependent. Electron transport in solar cells with ZnO-N electrodes was about 2 orders of magnitude faster (similar to 30 mu s). Thus, the morphology of the working ZnO electrode plays a key role for the electron transport properties.
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| 8. |
- Li, Cong, et al.
(author)
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Impacts of conservation and human development policy across stakeholders and scales
- 2015
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 112:24, s. 7396-7401
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Journal article (peer-reviewed)abstract
- Ideally, both ecosystem service and human development policies should improve human well-being through the conservation of ecosystems that provide valuable services. However, program costs and benefits to multiple stakeholders, and how they change through time, are rarely carefully analyzed. We examine one of China's new ecosystem service protection and human development policies: the Relocation and Settlement Program of Southern Shaanxi Province (RSP), which pays households who opt voluntarily to resettle from mountainous areas. The RSP aims to reduce disaster risk, restore important ecosystem services, and improve human well-being. We use household surveys and biophysical data in an integrated economic cost-benefit analysis for multiple stakeholders. We project that the RSP will result in positive net benefits to the municipal government, and to cross-region and global beneficiaries over the long run along with environment improvement, including improved water quality, soil erosion control, and carbon sequestration. However, there are significant short-run relocation costs for local residents so that poor households may have difficulty participating because they lack the resources to pay the initial costs of relocation. Greater subsidies and subsequent supports after relocation are necessary to reduce the payback period of resettled households in the long run. Compensation from downstream beneficiaries for improved water and from carbon trades could be channeled into reducing relocation costs for the poor and sharing the burden of RSP implementation. The effectiveness of the RSP could also be greatly strengthened by early investment in developing human capital and environment-friendly jobs and establishing long-term mechanisms for securing program goals. These challenges and potential solutions pervade ecosystem service efforts globally.
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| 9. |
- Li, Yufei, et al.
(author)
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Neural Network Models and Transfer Learning for Impedance Modeling of Grid-Tied Inverters
- 2022
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In: 2022 IEEE 13TH INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG). - : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- The future power grid will be supported by a large number of grid-tied inverters whose dynamics are critical for grid stability and power flow control. The operating conditions of these inverters vary across a wide range, leading to different small-signal impedances and different grid-interface behaviors. Analytical impedance models derived at specific operating points can hardly capture nonlinearities and nonidealities of the physical systems. The applicability of electromagnetic transient (EMT) simulations is often limited by the system complexity and the available computational resources. This paper applies neural network and transfer learning to impedance modeling of gridtied inverters. It is shown that a neural network (NN) trained by data automatically acquired from EMT simulations outperforms the one trained by traditional analytical models when unknown information exist in simulations. Pre-training the NN with analytically calculated data can greatly reduce the amount of simulation data needed to achieve good modeling results.
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| 10. |
- Liao, Yicheng, et al.
(author)
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Neural Network Design for Impedance Modeling of Power Electronic Systems Based on Latent Features
- 2024
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In: IEEE Transactions on Neural Networks and Learning Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2162-237X .- 2162-2388. ; 35:5, s. 5968-5980
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Journal article (peer-reviewed)abstract
- Data-driven approaches are promising to address the modeling issues of modern power electronics-based power systems, due to the black-box feature. Frequency-domain analysis has been applied to address the emerging small-signal oscillation issues caused by converter control interactions. However, the frequency-domain model of a power electronic system is linearized around a specific operating condition. It thus requires measurement or identification of frequency-domain models repeatedly at many operating points (OPs) due to the wide operation range of the power systems, which brings significant computation and data burden. This article addresses this challenge by developing a deep learning approach using multilayer feedforward neural networks (FNNs) to train the frequency-domain impedance model of power electronic systems that is continuous of OP. Distinguished from the prior neural network designs relying on trial-and-error and sufficient data size, this article proposes to design the FNN based on latent features of power electronic systems, i.e., the number of system poles and zeros. To further investigate the impacts of data quantity and quality, learning procedures from a small dataset are developed, and K-medoids clustering based on dynamic time warping is used to reveal insights into multivariable sensitivity, which helps improve the data quality. The proposed approaches for the FNN design and learning have been proven simple, effective, and optimal based on case studies on a power electronic converter, and future prospects in its industrial applications are also discussed.
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