Keyword search (4,163 papers available)

"Models" Keyword-tagged Publications:

Title Authors PubMed ID
1 Assessment of PlanetScope Spectral Data for Estimation of Peanut Leaf Area Index Using Machine Learning and Statistical Methods Ekwe M; Fernando H; James G; Adeluyi O; Verrelst J; Kross A; 41682534
CONCORDIA
2 MedCLIP-SAMv2: Towards universal text-driven medical image segmentation Koleilat T; Asgariandehkordi H; Rivaz H; Xiao Y; 40779830
ENCS
3 Statistical or Embodied? Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors Nadler EO; Guilbeault D; Ringold SM; Williamson TR; Bellemare-Pepin A; Com?a IM; Jerbi K; Narayanan S; Aziz-Zadeh L; 40621800
PSYCHOLOGY
4 Application of machine learning for predicting the incubation period of water droplet erosion in metals AlHammad K; Medraj M; Tembely M; 40612685
ENCS
5 Large language models deconstruct the clinical intuition behind diagnosing autism Stanley J; Rabot E; Reddy S; Belilovsky E; Mottron L; Bzdok D; 40147442
ENCS
6 Utilizing large language models for detecting hospital-acquired conditions: an empirical study on pulmonary embolism Cheligeer C; Southern DA; Yan J; Wu G; Pan J; Lee S; Martin EA; Jafarpour H; Eastwood CA; Zeng Y; Quan H; 40105654
ENCS
7 A synthetic model of bioinspired liposomes to study cancer-cell derived extracellular vesicles and their uptake by recipient cells López RR; Ben El Khyat CZ; Chen Y; Tsering T; Dickinson K; Bustamante P; Erzingatzian A; Bartolomucci A; Ferrier ST; Douanne N; Mounier C; Stiharu I; Nerguizian V; Burnier JV; 40069225
ENCS
8 Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models Gheflati B; Mirzaei M; Rottoo S; Rivaz H; 39953355
ENCS
9 Toward cognitive models of misophonia Savard MA; Coffey EBJ; 39874936
PSYCHOLOGY
10 Face Boundary Formulation for Harmonic Models: Face Image Resembling Huang HT; Li ZC; Wei Y; Suen CY; 39852327
CONCORDIA
11 Beyond the Illusion of Controlled Environments: How to Embrace Ecological Pertinence in Research? Cassandre Vielle 39777969
BIOLOGY
12 Deep clustering analysis via variational autoencoder with Gamma mixture latent embeddings Guo J; Fan W; Amayri M; Bouguila N; 39662201
ENCS
13 Ion channel classification through machine learning and protein language model embeddings Ghazikhani H; Butler G; 39572876
ENCS
14 Predictive heating load management and energy flexibility analysis in residential sector using an archetype gray-box modeling approach: Application to an experimental house in Québec Abtahi M; Athienitis A; Delcroix B; 39507415
ENCS
15 A guide to exploratory structural equation modeling (ESEM) and bifactor-ESEM in body image research Swami V; Maïano C; Morin AJS; 39492241
PSYCHOLOGY
16 How to evaluate local fit (residuals) in large structural equation models Rex B Kline 39359027
PSYCHOLOGY
17 Exploiting protein language models for the precise classification of ion channels and ion transporters Ghazikhani H; Butler G; 38656743
CSFG
18 A longitudinal person-centered investigation of the multidimensional nature of employees' perceptions of challenge and hindrance demands at work Gillet N; Morin AJS; Fernet C; Austin S; Huyghebaert-Zouaghi T; 38425154
CONCORDIA
19 Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency Al-Bazzaz H; Azam M; Amayri M; Bouguila N; 37837127
ENCS
20 A comparative study of black-box and white-box data-driven methods to predict landfill leachate permeability Ghasemi M; Samadi M; Soleimanian E; Chau KW; 37335361
ENCS
21 Water risk modeling: A framework for finance Gramlich D; Walker T; 37224654
CONCORDIA
22 Human Activity Recognition with an HMM-Based Generative Model Manouchehri N; Bouguila N; 36772428
ENCS
23 Modeling hormonal contraception in female rats: a framework for studies in behavioral neurobiology Lacasse JM; Gomez-Perales E; Brake WG; 35952797
PSYCHOLOGY
24 Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review Asif Z; Chen Z; Stranges S; Zhao X; Sadiq R; Olea-Popelka F; Peng C; Haghighat F; Yu T; 35317188
ENCS
25 The effect of past defaunation on ranges, niches, and future biodiversity forecasts Sales LP; Galetti M; Carnaval A; Monsarrat S; Svenning JC; Pires MM; 35246902
BIOLOGY
26 Mechanisms of hypericin incorporation to explain the photooxidation outcomes in phospholipid biomembrane models Pereira LSA; Camacho SA; Almeida AM; Gonçalves RS; Caetano W; DeWolf C; Aoki PHB; 35167859
CNSR
27 Thermoregulatory significance of immobility in the forced swim test Nadeau BG; Marchant EG; Amir S; Mistlberger RE; 35065081
PSYCHOLOGY
28 Comment on the article "Spatially-extended nucleation-aggregation-fragmentation models for the dynamics of prion-like neurodegenerative protein-spreading in the brain and its connectome 486 (2020) 110102" Arsalan Rahimabadi 34843739
PERFORM
29 Complementary variable- and person-centered approaches to the dimensionality of burnout among fire station workers Sandrin E; Morin AJS; Fernet C; Gillet N; 34314264
CONCORDIA
30 Drug discovery and chemical probing in Drosophila. Millet-Boureima C, Selber-Hnatiw S, Gamberi C 32551911
BIOLOGY
31 Water Droplet Erosion of Wind Turbine Blades: Mechanics, Testing, Modeling and Future Perspectives. Elhadi Ibrahim M, Medraj M 31906204
ENCS
32 Cyst Reduction in a Polycystic Kidney Disease Drosophila Model Using Smac Mimics. Millet-Boureima C, Chingle R, Lubell WD, Gamberi C 31635379
BIOLOGY
33 Psychometric Properties of the Body Checking Questionnaire (BCQ) and of the Body Checking Cognitions Scale (BCCS): A Bifactor-Exploratory Structural Equation Modeling Approach. Maïano C, Morin AJS, Aimé A, Lepage G, Bouchard S 31328530
CONCORDIA
34 Distance sonification in image-guided neurosurgery. Plazak J, Drouin S, Collins L, Kersten-Oertel M 29184665
PERFORM

 

Title:Water Droplet Erosion of Wind Turbine Blades: Mechanics, Testing, Modeling and Future Perspectives.
Authors:Elhadi Ibrahim MMedraj M
Link:https://www.ncbi.nlm.nih.gov/pubmed/31906204?dopt=Abstract
DOI:10.3390/ma13010157
Publication:Materials (Basel, Switzerland)
Keywords:damage mechanismserosion prediction modelserosion testingleading edge erosionwater droplet erosionwind turbine blades
PMID:31906204 Category:Materials (Basel) Date Added:2020-01-08
Dept Affiliation: ENCS
1 Department of Mechanical and Industrial Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, QC H3G 1M8, Canada.

Description:

Water Droplet Erosion of Wind Turbine Blades: Mechanics, Testing, Modeling and Future Perspectives.

Materials (Basel). 2019 Dec 31;13(1):

Authors: Elhadi Ibrahim M, Medraj M

Abstract

The problem of erosion due to water droplet impact has been a major concern for several industries for a very long time and it keeps reinventing itself wherever a component rotates or moves at high speed in a hydrometer environment. Recently, and as larger wind turbine blades are used, erosion of the leading edge due to rain droplets impact has become a serious issue. Leading-edge erosion causes a significant loss in aerodynamics efficiency of turbine blades leading to a considerable reduction in annual energy production. This paper reviews the topic of water droplet impact erosion as it emerges in wind turbine blades. A brief background on water droplet erosion and its industrial applications is first presented. Leading-edge erosion of wind turbine is briefly described in terms of materials involved and erosion conditions encountered in the blade. Emphases are then placed on the status quo of understanding the mechanics of water droplet erosion, experimental testing, and erosion prediction models. The main conclusions of this review are as follow. So far, experimental testing efforts have led to establishing a useful but incomplete understanding of the water droplet erosion phenomenon, the effect of different erosion parameters, and a general ranking of materials based on their ability to resist erosion. Techniques for experimentally measuring an objective erosion resistance (or erosion strength) of materials have, however, not yet been developed. In terms of modelling, speculations about the physical processes underlying water droplet erosion and consequently treating the problem from first principles have never reached a state of maturity. Efforts have, therefore, focused on formulating erosion prediction equations depending on a statistical analysis of large erosion tests data and often with a combination of presumed erosion mechanisms such as fatigue. Such prediction models have not reached the stage of generalization. Experimental testing and erosion prediction efforts need to be improved such that a coherent water droplet erosion theory can be established. The need for standardized testing and data representation practices as well as correlations between test data and real in-service erosion also remains urgent.

PMID: 31906204 [PubMed]





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