Skip to main content
Erschienen in: Journal of Engineering Thermophysics 1/2024

01.03.2024

On Applicability of IQR Method for Filtering of Experimental Data

verfasst von: B. B. Ilyushin

Erschienen in: Journal of Engineering Thermophysics | Ausgabe 1/2024

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The results of testing the popular IQR (Interquartile Range) method for filtering experimental data are presented. It is shown that if the distributions of measured values differ greatly from the Gaussian distribution, this method gives a large error in the statistical characteristics, especially the higher moments. The earlier-developed statistical filtering method can take into account substantial skewness of distributions of measured values and can greatly reduce the filtering error.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Gupta, M., Gao, J., Aggarwal, C.C., and Han, J., Outlier Detection for Temporal Data: A Survey, IEEE Trans. Knowl. Data Engin., 2014, vol. 26, no. 9, pp. 2250–2267; https://doi.org/10.1109/TKDE.2013.184CrossRef Gupta, M., Gao, J., Aggarwal, C.C., and Han, J., Outlier Detection for Temporal Data: A Survey, IEEE Trans. Knowl. Data Engin., 2014, vol. 26, no. 9, pp. 2250–2267; https://​doi.​org/​10.​1109/​TKDE.​2013.​184CrossRef
2.
Zurück zum Zitat Aggarwal, C.C., An Introduction to Outlier Analysis, in Outlier Analysis, New York: Springer, 2013; https://doi.org/10.1007/978-1-4614-6396-2_1 Aggarwal, C.C., An Introduction to Outlier Analysis, in Outlier Analysis, New York: Springer, 2013; https://​doi.​org/​10.​1007/​978-1-4614-6396-2_​1
3.
Zurück zum Zitat Chandola, V., Banerjee, A., and Kumar, V., Anomaly Detection: A Survey, ACM Comput. Surv., 2009, vol. 41, no. 3, pp. 1–58; https://doi.org/10.1145/1541880.1541882CrossRef Chandola, V., Banerjee, A., and Kumar, V., Anomaly Detection: A Survey, ACM Comput. Surv., 2009, vol. 41, no. 3, pp. 1–58; https://​doi.​org/​10.​1145/​1541880.​1541882CrossRef
4.
Zurück zum Zitat Kumar, V., Parallel and Distributed Computing for Cybersecurity, IEEE Distr. Syst. Online, 2005, vol. 6, no. 10; https://doi.org/10.1109/MDSO.2005.53 Kumar, V., Parallel and Distributed Computing for Cybersecurity, IEEE Distr. Syst. Online, 2005, vol. 6, no. 10; https://​doi.​org/​10.​1109/​MDSO.​2005.​53
5.
Zurück zum Zitat Vinutha, H.P., Poornima, B., and Sagar, B.M., Detection of Outliers Using Interquartile Range Technique from Intrusion Dataset, Inform. Dec. Sci., 2018, vol. 701, pp. 511–518; http://dx.doi.org/ 10.1007/978-981-10-7563-6_53 Vinutha, H.P., Poornima, B., and Sagar, B.M., Detection of Outliers Using Interquartile Range Technique from Intrusion Dataset, Inform. Dec. Sci., 2018, vol. 701, pp. 511–518; http://​dx.​doi.​org/​ 10.1007/978-981-10-7563-6_53
6.
Zurück zum Zitat Spence, C., Parra, L., and Sajda, P., Detection, Synthesis and Compression in Mammographic Image Analysis with a Hierarchical Image Probability Model, in Procs. of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, Washington, DC, USA: IEEE Computer Society, 2001; https://doi.org/10.1109/MMBIA.2001.991693 Spence, C., Parra, L., and Sajda, P., Detection, Synthesis and Compression in Mammographic Image Analysis with a Hierarchical Image Probability Model, in Procs. of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, Washington, DC, USA: IEEE Computer Society, 2001; https://​doi.​org/​10.​1109/​MMBIA.​2001.​991693
7.
Zurück zum Zitat Ijaz, M.F., Attique, M., and Son, Y., Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods, Sensors, 2020, vol. 20, p. 2809; https://doi.org/10.3390/s20102809ADSCrossRef Ijaz, M.F., Attique, M., and Son, Y., Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods, Sensors, 2020, vol. 20, p. 2809; https://​doi.​org/​10.​3390/​s20102809ADSCrossRef
8.
Zurück zum Zitat Baharuddin, M.Y., Salleh, S.H., Zulkifly, A.H., et al., Design Process of Cementless Femoral Stem Using a Nonlinear Three Dimensional Finite Element Analysis, BMC Musculoskelet Disord, 2014, vol. 15, no. 30; https://doi.org/10.1186/1471-2474-15-30CrossRef Baharuddin, M.Y., Salleh, S.H., Zulkifly, A.H., et al., Design Process of Cementless Femoral Stem Using a Nonlinear Three Dimensional Finite Element Analysis, BMC Musculoskelet Disord, 2014, vol. 15, no. 30; https://​doi.​org/​10.​1186/​1471-2474-15-30CrossRef
9.
Zurück zum Zitat Fay, D.S. and Gerow, K., A Biologist’s Guide to Statistical Thinking and Analysis, WormBook, 2013; https://doi.org/10.1895/wormbook.1.159.1 Fay, D.S. and Gerow, K., A Biologist’s Guide to Statistical Thinking and Analysis, WormBook, 2013; https://​doi.​org/​10.​1895/​wormbook.​1.​159.​1
10.
Zurück zum Zitat Aleskerov, E., Freisleben, B., and Rao, B., Cardwatch: A Neural Network Based Database Mining System for Credit Card Fraud Detection, in Procs. of IEEE Computational Intelligence for Financial Engineering, 1997, pp. 220–226; https://doi.org/10.1109/CIFER.1997.618940 Aleskerov, E., Freisleben, B., and Rao, B., Cardwatch: A Neural Network Based Database Mining System for Credit Card Fraud Detection, in Procs. of IEEE Computational Intelligence for Financial Engineering, 1997, pp. 220–226; https://​doi.​org/​10.​1109/​CIFER.​1997.​618940
11.
Zurück zum Zitat Hilal, W., Gadsden, S.A., and Yawney, J., Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances, Expert Syst. Appl., 2022, vol. 193, p. 116429; https://doi.org/ 10.1016/j.eswa.2021.116429CrossRef Hilal, W., Gadsden, S.A., and Yawney, J., Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances, Expert Syst. Appl., 2022, vol. 193, p. 116429; https://​doi.​org/​ 10.1016/j.eswa.2021.116429CrossRef
12.
Zurück zum Zitat Hodge, V.J. and Austin, J., A Survey of Outlier Detection Methodologies, Artif. Intell. Rev., 2004, vol. 22, pp. 85–126; https://doi.org/10.1007/s10462-004-4304-yCrossRef Hodge, V.J. and Austin, J., A Survey of Outlier Detection Methodologies, Artif. Intell. Rev., 2004, vol. 22, pp. 85–126; https://​doi.​org/​10.​1007/​s10462-004-4304-yCrossRef
13.
Zurück zum Zitat Song, Y., Wang, Q., Zhang, X., et al., Interpretable Machine Learning for Maximum Corrosion Depth and Influence Factor Analysis, npj Mater. Degrad., 2023, vol. 7, p. 9; https://doi.org/10.1038/s41529-023-00324-xCrossRef Song, Y., Wang, Q., Zhang, X., et al., Interpretable Machine Learning for Maximum Corrosion Depth and Influence Factor Analysis, npj Mater. Degrad., 2023, vol. 7, p. 9; https://​doi.​org/​10.​1038/​s41529-023-00324-xCrossRef
14.
Zurück zum Zitat Jones, P.R., A Note on Detecting Statistical Outliers in Psychophysical Data, Atten. Percept. Psychophys., 2019, vol. 81, no. 5, pp. 1189–1196; https://doi.org/10.3758/s13414-019-01726-3CrossRef Jones, P.R., A Note on Detecting Statistical Outliers in Psychophysical Data, Atten. Percept. Psychophys., 2019, vol. 81, no. 5, pp. 1189–1196; https://​doi.​org/​10.​3758/​s13414-019-01726-3CrossRef
15.
Zurück zum Zitat Pimentel, M.A.F., Clifton, D.A., Clifton, L., and Tarassenko, L., A Review of Novelty Detection, Signal Proc., 2014, vol. 99, pp. 215–249; https://doi.org/10.1016/j.sigpro.2013.12.026CrossRef Pimentel, M.A.F., Clifton, D.A., Clifton, L., and Tarassenko, L., A Review of Novelty Detection, Signal Proc., 2014, vol. 99, pp. 215–249; https://​doi.​org/​10.​1016/​j.​sigpro.​2013.​12.​026CrossRef
16.
Zurück zum Zitat Munir, M., Siddiqui, S.A., Dengel, A., and Ahmed, S., DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series, IEEE Access, 2019, vol. 7, pp. 1991–2005; doi: http://dx.doi.org/10.1109/ACCESS.2018.2886457CrossRef Munir, M., Siddiqui, S.A., Dengel, A., and Ahmed, S., DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series, IEEE Access, 2019, vol. 7, pp. 1991–2005; doi: http://​dx.​doi.​org/​10.​1109/​ACCESS.​2018.​2886457CrossRef
17.
Zurück zum Zitat Domingues, R., Filippone, M., Michiardi, P., and Zouaoui, J., A Comparative Evaluation of Outlier Detection Algorithms: Experiments and Analyses, Pattern Recogn., 2018, vol. 74, pp. 406–421; https://doi.org/10.1016/j.patcog.2017.09.037ADSCrossRef Domingues, R., Filippone, M., Michiardi, P., and Zouaoui, J., A Comparative Evaluation of Outlier Detection Algorithms: Experiments and Analyses, Pattern Recogn., 2018, vol. 74, pp. 406–421; https://​doi.​org/​10.​1016/​j.​patcog.​2017.​09.​037ADSCrossRef
18.
Zurück zum Zitat Gupta, N., Eswaran, D., Shah, N., Akoglu, L., and Faloutsos, C., Beyond Outlier Detection: LookOut for Pictorial Explanation, in Machine Learning and Knowledge Discovery in Databases, Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N., and Ifrim, G., Eds., Springer, 2018; https://doi.org/10.1007/978-3-030-10925-7_8 Gupta, N., Eswaran, D., Shah, N., Akoglu, L., and Faloutsos, C., Beyond Outlier Detection: LookOut for Pictorial Explanation, in Machine Learning and Knowledge Discovery in Databases, Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N., and Ifrim, G., Eds., Springer, 2018; https://​doi.​org/​10.​1007/​978-3-030-10925-7_​8
19.
Zurück zum Zitat Zimmerman, D.W., A Note on the Influence of Outliers on Parametric and Nonparametric Tests, J. Gen. Psychol., 1994, vol. 121, no. 4, pp. 391–401; https://psycnet.apa.org/doi/10.1080/ 00221309.1994.9921213CrossRef Zimmerman, D.W., A Note on the Influence of Outliers on Parametric and Nonparametric Tests, J. Gen. Psychol., 1994, vol. 121, no. 4, pp. 391–401; https://​psycnet.​apa.​org/​doi/​10.​1080/​ 00221309.1994.9921213CrossRef
20.
Zurück zum Zitat Zimmerman, D.W., Increasing the Power of Nonparametric Tests by Detecting and Downweighting Outliers, J. Exp. Educat., 1995, vol. 64, no. 1, pp. 71–78; https://api.semanticscholar.org/ CorpusID:120621848CrossRef Zimmerman, D.W., Increasing the Power of Nonparametric Tests by Detecting and Downweighting Outliers, J. Exp. Educat., 1995, vol. 64, no. 1, pp. 71–78; https://​api.​semanticscholar.​org/​ CorpusID:120621848CrossRef
21.
Zurück zum Zitat Zimmerman, D.W., Invalidation of Parametric and Nonparametric Statistical Tests by Concurrent Violation of Two Assumptions, J. Exp. Educat., 1998, vol. 67, no. 1, pp. 55–68; https://psycnet.apa.org/doi/10.1080/00220979809598344CrossRef Zimmerman, D.W., Invalidation of Parametric and Nonparametric Statistical Tests by Concurrent Violation of Two Assumptions, J. Exp. Educat., 1998, vol. 67, no. 1, pp. 55–68; https://​psycnet.​apa.​org/​doi/​10.​1080/​0022097980959834​4CrossRef
22.
Zurück zum Zitat Mowbray, F.I., Fox-Wasylyshyn, S.M., and El-Masri, M.M., Univariate Outliers: A Conceptual Overview for the Nurse Researcher, Can. J. Nurs. Res., 2019, vol. 51, no. 1, pp. 31–37; https://doi.org/ 10.1177/0844562118786647CrossRef Mowbray, F.I., Fox-Wasylyshyn, S.M., and El-Masri, M.M., Univariate Outliers: A Conceptual Overview for the Nurse Researcher, Can. J. Nurs. Res., 2019, vol. 51, no. 1, pp. 31–37; https://​doi.​org/​ 10.1177/0844562118786647CrossRef
23.
Zurück zum Zitat Peirce, B.O., Criterion for the Rejection of Doubtful Observations, Astron. J., 1852, vol. 2, pp. 161–163; https://doi.org/10.1086/100259ADSCrossRef Peirce, B.O., Criterion for the Rejection of Doubtful Observations, Astron. J., 1852, vol. 2, pp. 161–163; https://​doi.​org/​10.​1086/​100259ADSCrossRef
24.
Zurück zum Zitat Grubbs, F.E., Procedures for Detecting Outlying Observations in Samples, Technometrics, 1969, vol. 11, pp. 1–21; https://doi.org/10.2307/1266761CrossRef Grubbs, F.E., Procedures for Detecting Outlying Observations in Samples, Technometrics, 1969, vol. 11, pp. 1–21; https://​doi.​org/​10.​2307/​1266761CrossRef
25.
Zurück zum Zitat Garcı́a, S., Luengo, J., and Herrera, F., Data Preprocessing in Data Mining (Intelligent Systems Reference Library), 2015; http://dx.doi.org/10.1007/978-3-319-10247-4 Garcı́a, S., Luengo, J., and Herrera, F., Data Preprocessing in Data Mining (Intelligent Systems Reference Library), 2015; http://​dx.​doi.​org/​10.​1007/​978-3-319-10247-4
26.
Zurück zum Zitat Raffel, M., Willert, C.E., Wereley, S.T., and Kompenhans, J., Particle Image Velocimetry: A Practical Guide, 2nd ed., Berlin: Springer, 2007; https://doi.org/10.1007/978-3-540-72308-0CrossRef Raffel, M., Willert, C.E., Wereley, S.T., and Kompenhans, J., Particle Image Velocimetry: A Practical Guide, 2nd ed., Berlin: Springer, 2007; https://​doi.​org/​10.​1007/​978-3-540-72308-0CrossRef
27.
Zurück zum Zitat Daszykowski, M., Kaczmarek, K., Vander Heyden, Y., and Walczak, B., Robust Statistics in Data Analysis—A Review. Basic Concepts. Chemometrics Intelligent Lab. Syst., 2007, vol. 85, pp. 203–219; http://dx.doi.org/10.1016/j.chemolab.2006.06.016CrossRef Daszykowski, M., Kaczmarek, K., Vander Heyden, Y., and Walczak, B., Robust Statistics in Data Analysis—A Review. Basic Concepts. Chemometrics Intelligent Lab. Syst., 2007, vol. 85, pp. 203–219; http://​dx.​doi.​org/​10.​1016/​j.​chemolab.​2006.​06.​016CrossRef
28.
Zurück zum Zitat Chandola, V., Banerjee, A., and Kumar, V., Anomaly Detection: A Survey, ACM Comput. Surv., 2009, vol. 41, no. 3, pp. 1–58; https://doi.org/10.1145/1541880.1541882 Chandola, V., Banerjee, A., and Kumar, V., Anomaly Detection: A Survey, ACM Comput. Surv., 2009, vol. 41, no. 3, pp. 1–58; https://​doi.​org/​10.​1145/​1541880.​1541882
29.
Zurück zum Zitat Cousineau, D. and Sylvain C., Outliers Detection and Treatment: A Review, Int. J. Psychol. Res., 2010, vol. 3, pp. 58–67; http://dx.doi.org/10.21500/20112084.844CrossRef Cousineau, D. and Sylvain C., Outliers Detection and Treatment: A Review, Int. J. Psychol. Res., 2010, vol. 3, pp. 58–67; http://​dx.​doi.​org/​10.​21500/​20112084.​844CrossRef
30.
Zurück zum Zitat Zimek, A. and Filzmoser, P., There and Back Again: Outlier Detection between Statistical Reasoning and Data Mining Algorithms, Wiley Interdiscip. Rev.: Data Mining Knowledge Discovery, 2018, vol. 8, no. 6; https://doi.org/10.1002/widm.1280CrossRef Zimek, A. and Filzmoser, P., There and Back Again: Outlier Detection between Statistical Reasoning and Data Mining Algorithms, Wiley Interdiscip. Rev.: Data Mining Knowledge Discovery, 2018, vol. 8, no. 6; https://​doi.​org/​10.​1002/​widm.​1280CrossRef
31.
Zurück zum Zitat Rousseeuw, P.J. and Leroy, A.M., Robust Regression and Outlier Detection, New York: Wiley Interscience, 1987; http://dx.doi.org/10.1002/0471725382CrossRef Rousseeuw, P.J. and Leroy, A.M., Robust Regression and Outlier Detection, New York: Wiley Interscience, 1987; http://​dx.​doi.​org/​10.​1002/​0471725382CrossRef
32.
Zurück zum Zitat Pearson, K., X. On the Criterion That a Given System of Deviations from the Probable in the Case of a Correlated System of Variables Is Such that It Can Be Reasonably Supposed to Have Arisen from Random Sampling, London, Edinburgh, Dublin Philos. Mag., 1900, vol. 50, no. 302, pp. 157–175; https://doi.org/10.1080/14786440009463897CrossRef Pearson, K., X. On the Criterion That a Given System of Deviations from the Probable in the Case of a Correlated System of Variables Is Such that It Can Be Reasonably Supposed to Have Arisen from Random Sampling, London, Edinburgh, Dublin Philos. Mag., 1900, vol. 50, no. 302, pp. 157–175; https://​doi.​org/​10.​1080/​1478644000946389​7CrossRef
33.
Zurück zum Zitat Beyer, H. and Tukey, J.W., Exploratory Data Analysis. Addison-Wesley Publishing Company Reading, Mass.—Menlo Park, Cal., London, Amsterdam, Don Mills, Ontario, Sydney, 1977, XVI, Biometrical J., 1981, vol. 34, no. 4, pp. 413/414; https://doi.org/10.1002/bimj.4710230408CrossRef Beyer, H. and Tukey, J.W., Exploratory Data Analysis. Addison-Wesley Publishing Company Reading, Mass.—Menlo Park, Cal., London, Amsterdam, Don Mills, Ontario, Sydney, 1977, XVI, Biometrical J., 1981, vol. 34, no. 4, pp. 413/414; https://​doi.​org/​10.​1002/​bimj.​4710230408CrossRef
34.
Zurück zum Zitat Chockalingam, S., Aluru, M., and Aluru, S., Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories, Microarrays, 2016, vol. 5, no. 3, p. 23; https://doi.org/10.3390/microarrays5030023CrossRef Chockalingam, S., Aluru, M., and Aluru, S., Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories, Microarrays, 2016, vol. 5, no. 3, p. 23; https://​doi.​org/​10.​3390/​microarrays50300​23CrossRef
35.
Zurück zum Zitat Rajendran, L.K, Bhattacharya, S., Bane, S.P.M., and Vlachos, P.P., Meta-Uncertainty for Particle Image Velocimetry, Meas. Sci. Technol., 2021, vol. 32, p. 104002; http://dx.doi.org/10.1088/1361-6501/abf44fADSCrossRef Rajendran, L.K, Bhattacharya, S., Bane, S.P.M., and Vlachos, P.P., Meta-Uncertainty for Particle Image Velocimetry, Meas. Sci. Technol., 2021, vol. 32, p. 104002; http://​dx.​doi.​org/​10.​1088/​1361-6501/​abf44fADSCrossRef
36.
Zurück zum Zitat Grossmann, F., Flueck, J.L., Roelands, B., Meeusen, R., Mason, B., and Perret, C., Characteristics of Official Wheelchair Basketball Games in Hot and Temperate Conditions, Int. J. Environ. Res. Public Health, 2022, vol. 19, no. 3, p. 1250; https://doi.org/10.3390/ijerph19031250CrossRef Grossmann, F., Flueck, J.L., Roelands, B., Meeusen, R., Mason, B., and Perret, C., Characteristics of Official Wheelchair Basketball Games in Hot and Temperate Conditions, Int. J. Environ. Res. Public Health, 2022, vol. 19, no. 3, p. 1250; https://​doi.​org/​10.​3390/​ijerph19031250CrossRef
37.
Zurück zum Zitat Pervunin, K.S., Timoshevskiy, M.V., and Ilyushin, B.B., Distribution of Probability of the Vapor Phase Occurrence in a Cavitating Flow Based on the Concentration of PIV Tracers in Liquid, Exp. Fluids, 2021, vol. 62, p. 247; https://doi.org/10.1007/s00348-021-03344-yADSCrossRef Pervunin, K.S., Timoshevskiy, M.V., and Ilyushin, B.B., Distribution of Probability of the Vapor Phase Occurrence in a Cavitating Flow Based on the Concentration of PIV Tracers in Liquid, Exp. Fluids, 2021, vol. 62, p. 247; https://​doi.​org/​10.​1007/​s00348-021-03344-yADSCrossRef
38.
Zurück zum Zitat Heinz, O., Ilyushin, B., and Markovich, D., Application of a PDF Method for the Statistical Processing of Experimental Data, Int. J. Heat Fluid Flow, 2004, vol. 25, no. 5, pp. 864–874; https://doi.org/10.1016/j.ijheatfluidflow.2004.05.009CrossRef Heinz, O., Ilyushin, B., and Markovich, D., Application of a PDF Method for the Statistical Processing of Experimental Data, Int. J. Heat Fluid Flow, 2004, vol. 25, no. 5, pp. 864–874; https://​doi.​org/​10.​1016/​j.​ijheatfluidflow.​2004.​05.​009CrossRef
39.
Zurück zum Zitat Ilyushin, B.B., Timoshevskiy, M.V., and Pervunin, K.S., Vapor Concentration and Bimodal Distributions of Turbulent Fluctuations in Cavitating Flow around a Hydrofoil, Int. J. Heat Fluid Flow, 2023, vol. 103, p. 109197; https://doi.org/10.1016/j.ijheatfluidflow.2023.109197CrossRef Ilyushin, B.B., Timoshevskiy, M.V., and Pervunin, K.S., Vapor Concentration and Bimodal Distributions of Turbulent Fluctuations in Cavitating Flow around a Hydrofoil, Int. J. Heat Fluid Flow, 2023, vol. 103, p. 109197; https://​doi.​org/​10.​1016/​j.​ijheatfluidflow.​2023.​109197CrossRef
40.
Zurück zum Zitat Alekseenko, S.V., Bilsky, A.V., Dulin, V.M., and Markovich, D.M., Experimental Study of an Impinging Jet with Different Swirl Rates, Int. J. Heat Fluid Flow, 2007, vol. 28, no. 6, pp. 1340–1359; https://doi.org/10.1016/j.ijheatfluidflow.2007.05.011CrossRef Alekseenko, S.V., Bilsky, A.V., Dulin, V.M., and Markovich, D.M., Experimental Study of an Impinging Jet with Different Swirl Rates, Int. J. Heat Fluid Flow, 2007, vol. 28, no. 6, pp. 1340–1359; https://​doi.​org/​10.​1016/​j.​ijheatfluidflow.​2007.​05.​011CrossRef
41.
Zurück zum Zitat Tokarev, M.P., Markovich, D.M., and Bil’sky, A.V., Adaptive Algorithms for Processing Particle Images for Calculating Instantaneous Velocity Fields, Vychisl. Technol., 2007, vol. 12, no. 3, pp. 109–131. Tokarev, M.P., Markovich, D.M., and Bil’sky, A.V., Adaptive Algorithms for Processing Particle Images for Calculating Instantaneous Velocity Fields, Vychisl. Technol., 2007, vol. 12, no. 3, pp. 109–131.
42.
Zurück zum Zitat Severin, M.V., Timoshevskii, M.V., Ilyushin, B.B., and Pervunin, K.S., Turbulent Structure of a Free Bubble Jet: Analysis of the Higher Statistical Moments of Velocity Fluctuations, PMTF, 2023, no. 6, pp. 81–84; DOI: 10.15372/PMTF202315302 Severin, M.V., Timoshevskii, M.V., Ilyushin, B.B., and Pervunin, K.S., Turbulent Structure of a Free Bubble Jet: Analysis of the Higher Statistical Moments of Velocity Fluctuations, PMTF, 2023, no. 6, pp. 81–84; DOI: 10.15372/PMTF202315302
43.
Zurück zum Zitat Ilyushin, B.B., Use of Higher Moments to Construct PDF’s in Stratified Flows, in Closure Strategies for Turbulent and Transitional Flows, Launder, B.E. and Sandham, N., Eds., Cambridge University Press, 2001, pp. 683–699; https://doi.org/10.1017/CBO9780511755385CrossRef Ilyushin, B.B., Use of Higher Moments to Construct PDF’s in Stratified Flows, in Closure Strategies for Turbulent and Transitional Flows, Launder, B.E. and Sandham, N., Eds., Cambridge University Press, 2001, pp. 683–699; https://​doi.​org/​10.​1017/​CBO9780511755385​CrossRef
Metadaten
Titel
On Applicability of IQR Method for Filtering of Experimental Data
verfasst von
B. B. Ilyushin
Publikationsdatum
01.03.2024
Verlag
Pleiades Publishing
Erschienen in
Journal of Engineering Thermophysics / Ausgabe 1/2024
Print ISSN: 1810-2328
Elektronische ISSN: 1990-5432
DOI
https://doi.org/10.1134/S1810232824010016

Weitere Artikel der Ausgabe 1/2024

Journal of Engineering Thermophysics 1/2024 Zur Ausgabe

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.