Gotowa bibliografia na temat „Roughness prediction”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Roughness prediction”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Roughness prediction"
Nalbant, Muammer, Hasan Gokkaya i İhsan Toktaş. "Comparison of Regression and Artificial Neural Network Models for Surface Roughness Prediction with the Cutting Parameters in CNC Turning". Modelling and Simulation in Engineering 2007 (2007): 1–14. http://dx.doi.org/10.1155/2007/92717.
Pełny tekst źródłaLin, Wan-Ju, Shih-Hsuan Lo, Hong-Tsu Young i Che-Lun Hung. "Evaluation of Deep Learning Neural Networks for Surface Roughness Prediction Using Vibration Signal Analysis". Applied Sciences 9, nr 7 (8.04.2019): 1462. http://dx.doi.org/10.3390/app9071462.
Pełny tekst źródłaSaleh, A., D. W. Fryrear i J. D. Bilbro. "AERODYNAMIC ROUGHNESS PREDICTION FROM SOIL SURFACE ROUGHNESS MEASUREMENT". Soil Science 162, nr 3 (marzec 1997): 205–10. http://dx.doi.org/10.1097/00010694-199703000-00006.
Pełny tekst źródłaCai, Xiao Jiang, Z. Q. Liu, Q. C. Wang, Shu Han, Qing Long An i Ming Chen. "Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network". Advanced Materials Research 188 (marzec 2011): 535–41. http://dx.doi.org/10.4028/www.scientific.net/amr.188.535.
Pełny tekst źródłaLi, Shilong, Xiaolei Yang i Yu Lv. "Predictive capability of the logarithmic law for roughness-modeled large-eddy simulation of turbulent channel flows with rough walls". Physics of Fluids 34, nr 8 (sierpień 2022): 085112. http://dx.doi.org/10.1063/5.0098611.
Pełny tekst źródłaAlajmi, Mahdi S., i Abdullah M. Almeshal. "Prediction and Optimization of Surface Roughness in a Turning Process Using the ANFIS-QPSO Method". Materials 13, nr 13 (4.07.2020): 2986. http://dx.doi.org/10.3390/ma13132986.
Pełny tekst źródłaZeng, Shi, i Dechang Pi. "Milling Surface Roughness Prediction Based on Physics-Informed Machine Learning". Sensors 23, nr 10 (22.05.2023): 4969. http://dx.doi.org/10.3390/s23104969.
Pełny tekst źródłaNg, J. J., Z. W. Zhong i T. I. Liu. "Prediction of Roughness Heights of Milled Surfaces for Product Quality Prediction and Tool Condition Monitoring". Journal of Materials and Applications 8, nr 2 (15.11.2019): 97–104. http://dx.doi.org/10.32732/jma.2019.8.2.97.
Pełny tekst źródłaZhang, Qi, Yuechao Pei, Yixin Shen, Xiaojun Wang, Jingqi Lai i Maohui Wang. "A New Perspective on Predicting Roughness of Discontinuity from Fractal Dimension D of Outcrops". Fractal and Fractional 7, nr 7 (22.06.2023): 496. http://dx.doi.org/10.3390/fractalfract7070496.
Pełny tekst źródłaGu, Jiali, i Pingxiang Cao. "Prediction of straight tooth milling of Scots pine wood by shank cutter based on neural net computations and regression analysis". BioResources 17, nr 2 (4.02.2022): 2003–19. http://dx.doi.org/10.15376/biores.17.2.2003-2019.
Pełny tekst źródłaRozprawy doktorskie na temat "Roughness prediction"
Munoz-Escalona, Patricia. "Surface roughness prediction when milling with square inserts". Thesis, University of Bath, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.519033.
Pełny tekst źródłaShauche, Vishwesh. "Health Assessment based In-process Surface Roughness Prediction System". University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1298323430.
Pełny tekst źródłaStaheli, Kimberlie. "Jacking Force Prediction: An Interface Friction Approach based on Pipe Surface Roughness". Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-07052006-203035/.
Pełny tekst źródłaDr. J. David Frost, Committee Chair ; Dr. G. Wayne Clough, Committee Co-Chair ; Dr. William F. Marcuson III, Committee Member ; Dr. Paul W. Mayne, Committee Member ; Dr. Susan Burns, Committee Member.
Yamaguchi, Keiko. "Improved ice accretion prediction techniques based on experimental observations of surface roughness effects on heat transfer". Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/14148.
Pełny tekst źródłaSakthi, Gireesh. "WIND POWER PREDICTION MODEL BASED ON PUBLICLY AVAILABLE DATA: SENSITIVITY ANALYSIS ON ROUGHNESS AND PRODUCTION TREND". Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-400462.
Pełny tekst źródłaSrinivasan, Sriram. "Development of a Cost Oriented Grinding Strategy and Prediction of Post Grind Roughness using Improved Grinder Models". Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78298.
Pełny tekst źródłaMaster of Science
Celik, Kazim Arda. "Development Of A Methodology For Prediction Of Surface Roughness Of Curved Cavities Manufactured By 5-axes Cnc Milling". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608368/index.pdf.
Pełny tekst źródłaCummings, Patrick. "Modeling the Locked-Wheel Skid Tester to Determine the Effect of Pavement Roughness on the International Friction Index". Scholar Commons, 2010. https://scholarcommons.usf.edu/etd/1604.
Pełny tekst źródłaMangin, Steven F. "Development of an Equation Independent of Manning's Coefficient n for Depth Prediction in Partially-Filled Circular Culverts". Youngstown State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1284488143.
Pełny tekst źródłaLevin, Ori. "Stability analysis and transition prediction of wall-bounded flows". Licentiate thesis, KTH, Mechanics, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1663.
Pełny tekst źródłaDisturbances introduced in wall-bounded .ows can grow andlead to transition from laminar to turbulent .ow. In order toreduce losses or enhance mixing in energy systems, afundamental understanding of the .ow stability is important. Inlow disturbance environments, the typical path to transition isan exponential growth of modal waves. On the other hand, inlarge disturbance environments, such as in the presence of highlevels of free-stream turbulence or surface roughness,algebraic growth of non-modal streaks can lead to transition.In the present work, the stability of wall-bounded .ows isinvestigated by means of linear stability equations valid bothfor the exponential and algebraic growth scenario. Anadjoint-based optimization technique is used to optimize thealgebraic growth of streaks. The exponential growth of waves ismaximized in the sense that the envelope of the most ampli.edeigenmode is calculated. Two wall-bounded .ows areinvestigated, the FalknerSkan boundary layer subject tofavorable, adverse and zero pressure gradients and the Blasiuswall jet. For the FalknerSkan boundary layer, theoptimization is carried out over the initial streamwiselocation as well as the spanwise wave number and the angularfrequency. Furthermore, a uni.ed transition-prediction methodbased on available experimental data is suggested. The Blasiuswall jet is matched to the measured .ow in an experimentalwall-jet facility. Linear stability analysis with respect tothe growth of two-dimensional waves and streamwise streaks areperformed and compared to the experiments. The nonlinearinteraction of introduced waves and streaks and the .owstructures preceding the .ow breakdown are investigated bymeans of direct numerical simulations.
Descriptors: Boundary layer, wall jet, algebraic growth,exponential growth, lift-up e.ect, streamwise streaks,Tollmien-Schlichting waves, free-stream turbulence, roughnesselement, transition prediction, Parabolized StabilityEquations, Direct Numerical Simulation.
Książki na temat "Roughness prediction"
Fox, Christopher Gene. Description, analysis and predictions of sea floor roughness using spectral models. Bay St. Louis, Miss: Naval Oceanographic Office, 1985.
Znajdź pełny tekst źródłaKurlanda, Marian Henryk. Predicting roughness progression of asphalt overlays: Joint C-SHRP/Alberta Bayesian application. Ottawa: Canadian Strategic Highway Research Program, Transportation Association of Canada, 1995.
Znajdź pełny tekst źródłaChan, Johnny C. L. Physical Mechanisms Responsible for Track Changes and Rainfall Distributions Associated with Tropical Cyclone Landfall. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190676889.013.16.
Pełny tekst źródłaChan, Johnny C. L. Physical Mechanisms Responsible for Track Changes and Rainfall Distributions Associated with Tropical Cyclone Landfall. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190699420.013.16.
Pełny tekst źródłaMcAdams, Stephen, i Bruno L. Giordano. The perception of musical timbre. Redaktorzy Susan Hallam, Ian Cross i Michael Thaut. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199298457.013.0007.
Pełny tekst źródłaCzęści książek na temat "Roughness prediction"
Trung, Do Duc, Nhu Tung Nguyen, Hoang Tien Dung, Nguyen Van Thien, Tran Thi Hong, Tran Ngoc Giang, Nguyen Thanh Tu i Le Xuan Hung. "A Study on Prediction of Grinding Surface Roughness". W Advances in Engineering Research and Application, 102–11. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64719-3_13.
Pełny tekst źródłaSreekantan, P. G., i G. V. Ramana. "Roughness based prediction of geofoam interfaces with concrete". W Geosynthetics: Leading the Way to a Resilient Planet, 580–85. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003386889-61.
Pełny tekst źródłaYan, Tingxu, Huiping Zhu, Xudong Liu, Xu Tu, Muran Qi, Yifeng Wang i Xiaobo Li. "Wetting Behavior of LBE on 316L and T91 Surfaces with Different Roughness". W Springer Proceedings in Physics, 468–79. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1023-6_41.
Pełny tekst źródłaTrung, Do Duc, Nguyen Nhu Tung, Nguyen Hong Son, Tran Thi Hong, Nguyen Van Cuong, Vu Nhu Nguyet i Ngoc Pi Vu. "Prediction of Surface Roughness in Turning with Diamond Insert". W Advances in Engineering Research and Application, 607–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37497-6_69.
Pełny tekst źródłaChen, Ying, Yanhong Sun, Han Lin i Bing Zhang. "Prediction Model of Milling Surface Roughness Based on Genetic Algorithms". W Advances in Intelligent Systems and Computing, 1315–20. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15235-2_179.
Pełny tekst źródłaIbrahim, Musa Alhaji, i Yusuf Şahin. "Surface Roughness Modelling and Prediction Using Artificial Intelligence Based Models". W Advances in Intelligent Systems and Computing, 33–40. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35249-3_3.
Pełny tekst źródłaDing, Ning, Long Shan Wang i Guang Fu Li. "Study of Intelligent Prediction Control of Surface Roughness in Grinding". W Advances in Abrasive Technology IX, 93–98. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-416-2.93.
Pełny tekst źródłaOsuri, Krishna K., U. C. Mohanty i A. Routray. "Role of Surface Roughness Length on Simulation of Cyclone Aila". W Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change, 255–62. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7720-0_22.
Pełny tekst źródłaKumar, M. A. Vinod. "Surface Roughness Prediction Using ANFIS and Validation with Advanced Regression Algorithms". W Advances in Intelligent Systems and Computing, 238–45. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51156-2_29.
Pełny tekst źródłaTripathi, Akshay, i Rohit Singla. "Surface Roughness Prediction of 3D Printed Surface Using Artificial Neural Networks". W Lecture Notes in Mechanical Engineering, 109–20. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9956-9_11.
Pełny tekst źródłaStreszczenia konferencji na temat "Roughness prediction"
Wu, Dazhong, Yupeng Wei i Janis Terpenny. "Surface Roughness Prediction in Additive Manufacturing Using Machine Learning". W ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6501.
Pełny tekst źródłaRami´rez, M. de J., M. Correa, C. Rodri´guez i J. R. Alique. "Surface Roughness Modeling Based on Surface Roughness Feature Concept for High Speed Machining". W ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82256.
Pełny tekst źródła"Roughness Prediction For FDM Produced Surfaces". W International Conference Recent treads in Engineering & Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0214527.
Pełny tekst źródłaZhang, Dingtong, i Ning Ding. "Surface Roughness Intelligent Prediction on Grinding". W 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015). Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/ic3me-15.2015.415.
Pełny tekst źródłaAgarwal, Sanjay, i P. Venkateswara Rao. "Surface Roughness Prediction Model for Ceramic Grinding". W ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79180.
Pełny tekst źródłaHanson, David, i Michael Kinzel. "An Improved CFD Approach for Ice-Accretion Prediction Using the Discrete Element Roughness Method". W ASME 2017 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/fedsm2017-69365.
Pełny tekst źródłaWang, Xin, i Emil M. Petriu. "Neural fractal prediction of three dimensional surface roughness". W 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA). IEEE, 2011. http://dx.doi.org/10.1109/cimsa.2011.6059937.
Pełny tekst źródłaBeaugendre, Heloise, i Francois Morency. "FENSAP-ICE: Roughness Effects on Ice Accretion Prediction". W 41st Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2003. http://dx.doi.org/10.2514/6.2003-1222.
Pełny tekst źródłaTezok, Fatih, Fassi Kafyeke i Tuncer Cebeci. "Prediction of airfoil performance with leading edge roughness". W AIAA and SAE, 1998 World Aviation Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1998. http://dx.doi.org/10.2514/6.1998-5544.
Pełny tekst źródłaAlexandrov, Sergei, Ken-ichi Manabe i Tsuyoshi Furushima. "Free Surface Roughness Prediction in Bending Under Tension". W THE 8TH INTERNATIONAL CONFERENCE AND WORKSHOP ON NUMERICAL SIMULATION OF 3D SHEET METAL FORMING PROCESSES (NUMISHEET 2011). AIP, 2011. http://dx.doi.org/10.1063/1.3623735.
Pełny tekst źródłaRaporty organizacyjne na temat "Roughness prediction"
Taylor, R. P., i B. K. Hodge. Validated heat-transfer and pressure-drop prediction methods based on the discrete element method: Phase 1, Three-dimensiional roughness. Office of Scientific and Technical Information (OSTI), luty 1992. http://dx.doi.org/10.2172/10154300.
Pełny tekst źródłaTaylor, R. P., i B. K. Hodge. Validated heat-transfer and pressure-drop prediction methods based on the discrete element method: Phase 1, Three-dimensiional roughness. Office of Scientific and Technical Information (OSTI), luty 1992. http://dx.doi.org/10.2172/5096745.
Pełny tekst źródłaJames, C. A., B. K. Hodge i R. P. Taylor. Validated heat-transfer and pressure-drop prediction methods based on the discrete-element method: Phase 2, two-dimensional rib roughness. Office of Scientific and Technical Information (OSTI), maj 1993. http://dx.doi.org/10.2172/10192770.
Pełny tekst źródłaThegeya, Aaron, Thomas Mitterling, Arturo Martinez Jr, Joseph Albert Niño Bulan, Ron Lester Durante i Jayzon Mag-atas. Application of Machine Learning Algorithms on Satellite Imagery for Road Quality Monitoring: An Alternative Approach to Road Quality Surveys. Asian Development Bank, grudzień 2022. http://dx.doi.org/10.22617/wps220587-2.
Pełny tekst źródłaAl-Qadi, Imad, Jaime Hernandez, Angeli Jayme, Mojtaba Ziyadi, Erman Gungor, Seunggu Kang, John Harvey i in. The Impact of Wide-Base Tires on Pavement—A National Study. Illinois Center for Transportation, październik 2021. http://dx.doi.org/10.36501/0197-9191/21-035.
Pełny tekst źródłaMichaels, Michelle, Theodore Letcher, Sandra LeGrand, Nicholas Webb i Justin Putnam. Implementation of an albedo-based drag partition into the WRF-Chem v4.1 AFWA dust emission module. Engineer Research and Development Center (U.S.), styczeń 2021. http://dx.doi.org/10.21079/11681/42782.
Pełny tekst źródłaLeGrand, Sandra, Theodore Letcher, Gregory Okin, Nicholas Webb, Alex Gallagher, Saroj Dhital, Taylor Hodgdon, Nancy Ziegler i Michelle Michaels. Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1. Engineer Research and Development Center (U.S.), maj 2023. http://dx.doi.org/10.21079/11681/47116.
Pełny tekst źródłaZiegler, Nancy, Nicholas Webb, Adrian Chappell i Sandra LeGrand. Scale invariance of albedo-based wind friction velocity. Engineer Research and Development Center (U.S.), maj 2021. http://dx.doi.org/10.21079/11681/40499.
Pełny tekst źródłaZiegler, Nancy, Nicholas Webb, John Gillies, Brandon Edward, George Nikolich, Justin Van Zee, Brad Cooper, Dawn Browning, Ericha Courtright i Sandra LeGrand. Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland. Engineer Research and Development Center (U.S.), wrzesień 2023. http://dx.doi.org/10.21079/11681/47680.
Pełny tekst źródłaAgassi, Menahem, Michael J. Singer, Eyal Ben-Dor, Naftaly Goldshleger, Donald Rundquist, Dan Blumberg i Yoram Benyamini. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, listopad 2001. http://dx.doi.org/10.32747/2001.7586479.bard.
Pełny tekst źródła