Academic literature on the topic 'Roughness prediction'
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Journal articles on the topic "Roughness prediction"
Saleh, A., D. W. Fryrear, and J. D. Bilbro. "AERODYNAMIC ROUGHNESS PREDICTION FROM SOIL SURFACE ROUGHNESS MEASUREMENT." Soil Science 162, no. 3 (1997): 205–10. http://dx.doi.org/10.1097/00010694-199703000-00006.
Full textCai, Xiao Jiang, Z. Q. Liu, Q. C. Wang, Shu Han, Qing Long An, and Ming Chen. "Surface Roughness Prediction in Turning of Free Machining Steel 1215 by Artificial Neural Network." Advanced Materials Research 188 (March 2011): 535–41. http://dx.doi.org/10.4028/www.scientific.net/amr.188.535.
Full textAlajmi, Mahdi S., and Abdullah M. Almeshal. "Prediction and Optimization of Surface Roughness in a Turning Process Using the ANFIS-QPSO Method." Materials 13, no. 13 (2020): 2986. http://dx.doi.org/10.3390/ma13132986.
Full textNalbant, Muammer, Hasan Gokkaya, and 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.
Full textZhang, Qi, Yuechao Pei, Yixin Shen, Xiaojun Wang, Jingqi Lai, and Maohui Wang. "A New Perspective on Predicting Roughness of Discontinuity from Fractal Dimension D of Outcrops." Fractal and Fractional 7, no. 7 (2023): 496. http://dx.doi.org/10.3390/fractalfract7070496.
Full textZeng, Shi, and Dechang Pi. "Milling Surface Roughness Prediction Based on Physics-Informed Machine Learning." Sensors 23, no. 10 (2023): 4969. http://dx.doi.org/10.3390/s23104969.
Full textAlam, S., A. K. M. Nurul Amin, Anayet Ullah Patwari, and Mohamed Konneh. "Prediction and Investigation of Surface Response in High Speed End Milling of Ti-6Al-4V and Optimization by Genetic Algorithm." Advanced Materials Research 83-86 (December 2009): 1009–15. http://dx.doi.org/10.4028/www.scientific.net/amr.83-86.1009.
Full textNg, J. J., Z. W. Zhong, and T. I. Liu. "Prediction of Roughness Heights of Milled Surfaces for Product Quality Prediction and Tool Condition Monitoring." Journal of Materials and Applications 8, no. 2 (2019): 97–104. http://dx.doi.org/10.32732/jma.2019.8.2.97.
Full textSun, Hao, Chaochao Zhang, Yikai Li, Tingting Yin, Hanming Zhang, and Jin Pu. "Study on prediction model of surface roughness of SiCp/Al composites based on Neural Network." Journal of Physics: Conference Series 2174, no. 1 (2022): 012091. http://dx.doi.org/10.1088/1742-6596/2174/1/012091.
Full textMirifar, Siamak, Mohammadali Kadivar, and Bahman Azarhoushang. "First Steps through Intelligent Grinding Using Machine Learning via Integrated Acoustic Emission Sensors." Journal of Manufacturing and Materials Processing 4, no. 2 (2020): 35. http://dx.doi.org/10.3390/jmmp4020035.
Full textDissertations / Theses on the topic "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.
Full textShauche, Vishwesh. "Health Assessment based In-process Surface Roughness Prediction System." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1298323430.
Full textStaheli, 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/.
Full textYamaguchi, 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.
Full textSakthi, 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.
Full textSrinivasan, 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.
Full textCelik, 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.
Full textCummings, 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.
Full textMangin, 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.
Full textLevin, 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.
Full textBooks on the topic "Roughness prediction"
Fox, Christopher Gene. Description, analysis and predictions of sea floor roughness using spectral models. Naval Oceanographic Office, 1985.
Find full textKurlanda, Marian Henryk. Predicting roughness progression of asphalt overlays: Joint C-SHRP/Alberta Bayesian application. Canadian Strategic Highway Research Program, Transportation Association of Canada, 1995.
Find full textChan, 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.
Full textChan, 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.
Full textMcAdams, Stephen, and Bruno L. Giordano. The perception of musical timbre. Edited by Susan Hallam, Ian Cross, and Michael Thaut. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199298457.013.0007.
Full textBook chapters on the topic "Roughness prediction"
Trung, Do Duc, Nhu Tung Nguyen, Hoang Tien Dung, et al. "A Study on Prediction of Grinding Surface Roughness." In Advances in Engineering Research and Application. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64719-3_13.
Full textSreekantan, P. G., and G. V. Ramana. "Roughness based prediction of geofoam interfaces with concrete." In Geosynthetics: Leading the Way to a Resilient Planet. CRC Press, 2023. http://dx.doi.org/10.1201/9781003386889-61.
Full textVagdatli, T., and K. Petroutsatou. "A dynamic Bayesian network for pavement roughness prediction." In Bituminous Mixtures and Pavements VIII. CRC Press, 2024. http://dx.doi.org/10.1201/9781003402541-106.
Full textYan, Tingxu, Huiping Zhu, Xudong Liu, et al. "Wetting Behavior of LBE on 316L and T91 Surfaces with Different Roughness." In Springer Proceedings in Physics. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1023-6_41.
Full textSeehausen, Hendrik, and Joerg R. Seume. "Influence of Complex Surface Structures on the Aerodynamic Loss Behaviour of Blades." In Regeneration of Complex Capital Goods. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-51395-4_9.
Full textTrung, Do Duc, Nguyen Nhu Tung, Nguyen Hong Son, et al. "Prediction of Surface Roughness in Turning with Diamond Insert." In Advances in Engineering Research and Application. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37497-6_69.
Full textYang, Jiasheng, Alexander Stroh, and Pourya Forooghi. "Study of Data-Driven Prediction of Roughness Skin Friction." In High Performance Computing in Science and Engineering '22. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46870-4_11.
Full textXu, Jiakuan, Min Chang, and Junqiang Bai. "Transition Prediction Model Considering the Effects of Surface Roughness." In CFD-Compatible RANS/LES Modeling of Transitional and Separated Flows. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-6886-1_4.
Full textChen, Ying, Yanhong Sun, Han Lin, and Bing Zhang. "Prediction Model of Milling Surface Roughness Based on Genetic Algorithms." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15235-2_179.
Full textIbrahim, Musa Alhaji, and Yusuf Şahin. "Surface Roughness Modelling and Prediction Using Artificial Intelligence Based Models." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35249-3_3.
Full textConference papers on the topic "Roughness prediction"
Sundaram, S. Meenakshi, Kassem AL-Attabi, Veena Yadav S, Abdul Lateef Haroon P.S., and Vanitha Potula. "Prediction of Pavement Roughness using a Deep Neural Network Approach." In 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS). IEEE, 2024. https://doi.org/10.1109/iciics63763.2024.10860023.
Full textChen, Jianing. "Prediction of Asphalt Pavement Roughness Index Based on Bayesian Optimization XGBoost Algorithm." In 2025 5th International Symposium on Computer Technology and Information Science (ISCTIS). IEEE, 2025. https://doi.org/10.1109/isctis65944.2025.11065410.
Full textWardhani, Rivai, Hendro Nurhadi, and Harus Laksana Guntur. "Prediction of Surface Roughness and Hardness on Multi 3D Printers with Machine Learning." In 2024 International Automatic Control Conference (CACS). IEEE, 2024. https://doi.org/10.1109/cacs63404.2024.10773263.
Full textLi, Beibei, Xiyue Zhang, Minnan Han, Haoxuan Luan, and Shujie Sun. "End-to-End Surface Roughness Prediction Method Driven by Multi-Source Information Fusion." In 2024 10th International Conference on Computer and Communications (ICCC). IEEE, 2024. https://doi.org/10.1109/iccc62609.2024.10941778.
Full textWu, Dazhong, Yupeng Wei, and Janis Terpenny. "Surface Roughness Prediction in Additive Manufacturing Using Machine Learning." In ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6501.
Full textRami´rez, M. de J., M. Correa, C. Rodri´guez, and J. R. Alique. "Surface Roughness Modeling Based on Surface Roughness Feature Concept for High Speed Machining." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82256.
Full text"Roughness Prediction For FDM Produced Surfaces." In International Conference Recent treads in Engineering & Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0214527.
Full textZhang, Dingtong, and Ning Ding. "Surface Roughness Intelligent Prediction on Grinding." In 3rd International Conference on Material, Mechanical and Manufacturing Engineering (IC3ME 2015). Atlantis Press, 2015. http://dx.doi.org/10.2991/ic3me-15.2015.415.
Full textHanson, David, and Michael Kinzel. "An Improved CFD Approach for Ice-Accretion Prediction Using the Discrete Element Roughness Method." In ASME 2017 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/fedsm2017-69365.
Full textAgarwal, Sanjay, and P. Venkateswara Rao. "Surface Roughness Prediction Model for Ceramic Grinding." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79180.
Full textReports on the topic "Roughness prediction"
Taylor, R. P., and 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), 1992. http://dx.doi.org/10.2172/10154300.
Full textTaylor, R. P., and 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), 1992. http://dx.doi.org/10.2172/5096745.
Full textJames, C. A., B. K. Hodge, and 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), 1993. http://dx.doi.org/10.2172/10192770.
Full textThegeya, Aaron, Thomas Mitterling, Arturo Martinez Jr, Joseph Albert Niño Bulan, Ron Lester Durante, and 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, 2022. http://dx.doi.org/10.22617/wps220587-2.
Full textAl-Qadi, Imad, Jaime Hernandez, Angeli Jayme, et al. The Impact of Wide-Base Tires on Pavement—A National Study. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-035.
Full textMichaels, Michelle, Theodore Letcher, Sandra LeGrand, Nicholas Webb, and 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.), 2021. http://dx.doi.org/10.21079/11681/42782.
Full textLeGrand, Sandra, Theodore Letcher, Gregory Okin, et al. 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.), 2023. http://dx.doi.org/10.21079/11681/47116.
Full textZiegler, Nancy, Nicholas Webb, Adrian Chappell, and Sandra LeGrand. Scale invariance of albedo-based wind friction velocity. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40499.
Full textZiegler, Nancy, Nicholas Webb, John Gillies, et al. Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47680.
Full textAgassi, Menahem, Michael J. Singer, Eyal Ben-Dor, et al. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7586479.bard.
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