The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m

Performance Comparison of NAMI DANCE and FLOW-3D® Models in Tsunami Propagation, Inundation and Currents using NTHMP Benchmark Problems

NTHMP 벤치마크 문제를 사용하여 쓰나미 전파, 침수 및 해류에서 NAMI DANCE 및 FLOW-3D® 모델의 성능 비교

Pure and Applied Geophysics volume 176, pages3115–3153 (2019)Cite this article


Field observations provide valuable data regarding nearshore tsunami impact, yet only in inundation areas where tsunami waves have already flooded. Therefore, tsunami modeling is essential to understand tsunami behavior and prepare for tsunami inundation. It is necessary that all numerical models used in tsunami emergency planning be subject to benchmark tests for validation and verification. This study focuses on two numerical codes, NAMI DANCE and FLOW-3D®, for validation and performance comparison. NAMI DANCE is an in-house tsunami numerical model developed by the Ocean Engineering Research Center of Middle East Technical University, Turkey and Laboratory of Special Research Bureau for Automation of Marine Research, Russia. FLOW-3D® is a general purpose computational fluid dynamics software, which was developed by scientists who pioneered in the design of the Volume-of-Fluid technique. The codes are validated and their performances are compared via analytical, experimental and field benchmark problems, which are documented in the ‘‘Proceedings and Results of the 2011 National Tsunami Hazard Mitigation Program (NTHMP) Model Benchmarking Workshop’’ and the ‘‘Proceedings and Results of the NTHMP 2015 Tsunami Current Modeling Workshop”. The variations between the numerical solutions of these two models are evaluated through statistical error analysis.

현장 관찰은 연안 쓰나미 영향에 관한 귀중한 데이터를 제공하지만 쓰나미 파도가 이미 범람한 침수 지역에서만 가능합니다. 따라서 쓰나미 모델링은 쓰나미 행동을 이해하고 쓰나미 범람에 대비하는 데 필수적입니다.

쓰나미 비상 계획에 사용되는 모든 수치 모델은 검증 및 검증을 위한 벤치마크 테스트를 받아야 합니다. 이 연구는 검증 및 성능 비교를 위해 NAMI DANCE 및 FLOW-3D®의 두 가지 숫자 코드에 중점을 둡니다.

NAMI DANCE는 터키 중동 기술 대학의 해양 공학 연구 센터와 러시아 해양 연구 자동화를 위한 특별 조사국 연구소에서 개발한 사내 쓰나미 수치 모델입니다. FLOW-3D®는 Volume-of-Fluid 기술의 설계를 개척한 과학자들이 개발한 범용 전산 유체 역학 소프트웨어입니다.

코드의 유효성이 검증되고 분석, 실험 및 현장 벤치마크 문제를 통해 코드의 성능이 비교되며, 이는 ‘2011년 NTHMP(National Tsunami Hazard Mitigation Program) 모델 벤치마킹 워크숍의 절차 및 결과’와 ”절차 및 NTHMP 2015 쓰나미 현재 모델링 워크숍 결과”. 이 두 모델의 수치 해 사이의 변동은 통계적 오류 분석을 통해 평가됩니다.

The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m
The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m


  • Allan, J. C., Komar, P. D., Ruggiero, P., & Witter, R. (2012). The March 2011 Tohoku tsunami and its impacts along the U.S. West Coast. Journal of Coastal Research, 28(5), 1142–1153. Google Scholar 
  • Apotsos, A., Buckley, M., Gelfenbaum, G., Jafe, B., & Vatvani, D. (2011). Nearshore tsunami inundation and sediment transport modeling: towards model validation and application. Pure and Applied Geophysics, 168(11), 2097–2119. Google Scholar 
  • Barberopoulou, A., Legg, M. R., & Gica, E. (2015). Time evolution of man-made harbor modifications in San Diego: effects on Tsunamis. Journal of Marine Science and Engineering, 3, 1382–1403.Article Google Scholar 
  • Basu, D., Green, S., Das, K., Janetzke, R. and Stamatakos, J. (2009). Numerical Simulation of Surface Waves Generated by a Subaerial Landslide at Lituya Bay, Alaska. Proceedings of 28th International Conference on Ocean, Offshore and Arctic Engineering. Honolulu, Hawaii, USA.
  • Briggs, M. J., Synolakis, C. E., Harkins, G. S., & Green, D. R. (1995). Laboratory experiments of tsunami run-up on a circular island. Pure and Applied Geophysics, 144(3/4), 569–593.Article Google Scholar 
  • Cheung, K. F., Bai, Y., & Yamazaki, Y. (2013). Surges around the Hawaiian Islands from the 2011 Tohoku Tsunami. Journal of Geophysical Research: Oceans, 118, 5703–5719. Scholar 
  • Choi, B. H., Dong, C. K., Pelinovsky, E., & Woo, S. B. (2007). Three-dimensional Simulation of Tsunami Run-up Around Conical Island. Coastal Engineering, 54, 618–629.Article Google Scholar 
  • Cox, D., T. Tomita, P. Lynett, R.A., Holman. (2008). Tsunami Inundation with Macroroughness in the Constructed Environment. Proceedings of 31st International Conference on Coastal Engineering, ASCE, pp. 1421–1432.
  • Flow Science. (2002). FLOW-3D User’s Manual.
  • Hirt, C. W., & Nichols, B. D. (1981). Volume of fluid (VOF) method for the dynamics of free boundaries. Journal of Computational Physics, 39, 201–225.Article Google Scholar 
  • Horrillo, J., Grilli, S. T., Nicolsky, D., Roeber, V., & Zang, J. (2015). Performance benchmarking Tsunami models for NTHMP’s inundation mapping activities. Pure and Applied Geophysics, 172, 869–884.Article Google Scholar 
  • Kim, K. O., Kim, D. C., Choi, B.-H., Jung, T. K., Yuk, J. H., & Pelinovsky, E. (2015). The role of diffraction effects in extreme run-up inundation at Okushiri Island due to 1993 Tsunami. Natural Hazards and Earth Systems Sciences, 15, 747–755.Article Google Scholar 
  • Liu, P. L.-F. (1994). Model equations for wave propagations from deep to shallow water. (P.-F. Liu, Ed.) Advances in Coastal and Ocean Engineering, 1, 125–158.
  • Liu, P. L.-F., Yeh, H., & Synolakis, C. E. (2008). Advanced numerical models for simulating Tsunami waves and run-up. Advances in Coastal and Ocean Engineering, 10, 344.Google Scholar 
  • Lynett, P. J., Borrero, J., Son, S., Wilson, R., & Miller, K. (2014). Assessment of the tsunami-induced current hazard. Geophysical Research Letters, 41, 2048–2055. Google Scholar 
  • Lynett, P. J., Gately, K., Wilson, R., Montoya, L., Arcas, D., Aytore, B., et al. (2017). Inter-model analysis of Tsunami-induced coastal currents. Ocean Modelling, 114, 14–32.Article Google Scholar 
  • Lynett, P. J., Wu, T.-R., & Liu, P. L.-F. (2002). Modeling wave run-up with depth-integrated equations. Coastal Engineering, 46(2), 89–107.Article Google Scholar 
  • Macias, J., Castro, M. J., Ortega, S., Escalante, C., & Gonzalez-Vida, J. M. (2017). Performance benchmarking of Tsunami-HySEA model for nthmp’s inundation mapping activities. Pure and Applied Geophysics, 174, 3147–3183.Article Google Scholar 
  • Matsuyama, M., & Tanaka, H. (2001). An experimental study of the highest run-up height in the 1993 Hokkaidō Nansei-Oki Earthquake Tsunami. Proceedings of ITS, 2001, 879–889.Google Scholar 
  • National Tsunami Hazard Mitigation Program. 2012. Proceedings and Results of the 2011 NTHMP Model Benchmarking Workshop. Boulder: U.S. Department of Commerce/NOAA/NTHMP; (NOAA Special Report). p. 436.
  • National Tsunami Hazard Mitigation Program. (2017). Proceedings and Results of the National Tsunami Hazard Mitigation Program 2015 Tsunami Current Modeling Workshop, February 9-10, 2015, Portland, Oregon: compiled by Patrick Lynett and Rick Wilson, p 194.
  • Necmioglu, O., & Ozel, N. M. (2014). An earthquake source sensitivity analysis for Tsunami propagation in the Eastern Mediterranean. Oceanography, 27(2), 76–85.Article Google Scholar 
  • Nichols, B.D. and Hirt, C.W. (1975). Methods for Calculating Multi-Dimensional, Transient Free Surface Flows Past Bodies. Proceedings of 1st International Conference Num. Ship Hydrodynamics. Gaithersburg.
  • Nicolsky, D. J., Suleimani, E. N., & Hansen, R. A. (2011). Validation and verification of a numerical model for Tsunami propagation and run-up. Pure and Applied Geophysics, 168(6), 1199–1222.Article Google Scholar 
  • NOAA Center for Tsunami Research: Tsunami Run-up onto a Complex Three-dimensional Beach; Monai Valley. (n.d). Retrieved from:
  • Park, H., Cox, D. T., Lynett, P. J., Wiebe, D. M., & Shin, S. (2013). Tsunami inundation modeling in constructed environments: a physical and numerical comparison of free-surface elevation, velocity, and momentum flux. Coastal Engineering, 79, 9–21.Article Google Scholar 
  • Patel, V. M., Dholakia, M. B., & Singh, A. P. (2016). Emergency preparedness in the case of Makran Tsunami: a case study on Tsunami risk visualization for the Western Parts of Gujarat, India. Geomatics Natural Hazard and Risk, 7(2), 826–842.Article Google Scholar 
  • Pelinovsky, E., Kim, D.-C., Kim, K.-O., & Choi, B.-H. (2013). Three-dimensional simulation of extreme run-up heights during the 2004 Indonesian and 2011 Japanese Tsunamis. Vienna: EGU General Assembly.Google Scholar 
  • Rueben, M., Holman, R., Cox, D., Shin, S., Killian, J., & Stanley, J. (2011). Optical measurements of Tsunami inundation through an urban waterfront modeled in a large-scale laboratory basin. Coastal Engineering, 58, 229–238.Article Google Scholar 
  • Shuto, N. (1991). Numerical simulation of Tsunamis—its present and near future. Natural Hazards, 4, 171–191.Article Google Scholar 
  • Synolakis, C. E. (1986). The run-up of long waves. Ph.D. Thesis. California Institute of Technology, Pasadena, California.
  • Synolakis, C. E., Bernard, E. N., Titov, V. V., Kanoglu, U. & Gonzalez, F. (2007). Standards, criteria, and procedures for NOAA evaluation of Tsunami Numerical Models. 55 p. Seattle, Washington: NOAA OAR Special Report, Contribution No 3053, NOAA/OAR/PMEL.
  • Synolakis, C. E., Bernard, E. N., Titov, V. V., Kanoglu, U., & Gonzalez, F. I. (2008). Validation and verification of Tsunami numerical models. Pure and Applied Geophysics, 165, 2197–2228.Article Google Scholar 
  • Tolkova, E. (2014). Land-water boundary treatment for a tsunami model with dimensional splitting. Pure and Applied Geophysics, 171(9), 2289–2314.Article Google Scholar 
  • Velioglu, D. (2017). Advanced two- and three-dimensional Tsunami models: benchmarking and validation. Ph.D. Thesis. Middle East Technical University, Ankara.
  • Velioglu, D., Kian, R., Yalciner, A.C. and Zaytsev, A. (2016). Performance assessment of NAMI DANCE in Tsunami evolution and currents using a benchmark problem. (R. Signell, Ed.) J. Mar. Sci. Eng., 4(3), 49.
  • Wu, T. (2001). A unified theory for modeling water waves. Advances in Applied Mechanics, 37, 1–88.Article Google Scholar 
  • Wu, N.-J., Hsiao, S.-C., Chen, H.-H., & Yang, R.-Y. (2016). The study on solitary waves generated by a piston-type wave maker. Ocean Engineering, 117, 114–129.Article Google Scholar 
  • Yalciner, A. C., Dogan, P. and Sukru. E. (2005). December 26 2004, Indian Ocean Tsunami Field Survey, North of Sumatra Island. UNESCO.
  • Yalciner, A. C., Gülkan, P., Dilmen, I., Aytore, B., Ayca, A., Insel, I., et al. (2014). Evaluation of Tsunami scenarios For Western Peloponnese, Greece. Bollettino di Geofisica Teorica ed Applicata, 55, 485–500.Google Scholar 
  • Yen, B. C. (1991). Hydraulic resistance in open channels. In B. C. Yen (Ed.), Channel flow resistance: centennial of manning’s formula (pp. 1–135). Highlands Ranch: Water Resource Publications.Google Scholar 
  • Zaitsev, A. I., Kovalev, D. P., Kurkin, A. A., Levin, B. V., Pelinovskii, E. N., Chernov, A. G., et al. (2009). The Tsunami on Sakhalin on August 2, 2007: mareograph evidence and numerical simulation. Tikhookeanskaya Geologiya, 28, 30–35.Google Scholar 

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The authors wish to thank Dr. Andrey Zaytsev due to his undeniable contributions to the development of in-house numerical model, NAMI DANCE. The Turkish branch of Flow Science, Inc. is also acknowledged. Finally, the National Tsunami Hazard Mitigation Program (NTHMP), who provided most of the benchmark data, is appreciated. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Deniz Velioglu SogutPresent address: 1212 Computer Science, Department of Civil Engineering, Stony Brook University, Stony Brook, NY, 11794, USA

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  1. Middle East Technical University, 06800, Ankara, TurkeyDeniz Velioglu Sogut & Ahmet Cevdet Yalciner

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Correspondence to Deniz Velioglu Sogut.

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Velioglu Sogut, D., Yalciner, A.C. Performance Comparison of NAMI DANCE and FLOW-3D® Models in Tsunami Propagation, Inundation and Currents using NTHMP Benchmark Problems. Pure Appl. Geophys. 176, 3115–3153 (2019).

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  • Received22 December 2017
  • Revised16 May 2018
  • Accepted24 May 2018
  • Published07 June 2018
  • Issue Date01 July 2019
  • DOI


  • Tsunami
  • depth-averaged shallow water
  • Reynolds-averaged Navier–Stokes
  • benchmarking
  • FLOW-3D®

냉각 열 응력과 변형 해석

FLOW-3D로 해석한 냉각 열 응력과 변형 시뮬레이션

Temperature contour after cooling

Flow Science, INC 소속의 AHG Isfahani & JM Brethour기 발표한 FLOW-3D로 냉각 열 응력과 변형을 시뮬레이션 한 결과입니다.

주조 업계에서는 고형화 및 냉각 중 열응력을 예측하고 그 결과로 변형되는 현상을 예측하는 것이 여전히 어려운 과제입니다.

플로우 사이언스는 최근 이러한 종류의 예측을 고객에게 제공하기 위해 FSI(Fuid-Structure Interaction)와 TSE(Thermal Stress Evolution) 모델을 개발했습니다. Fuid-cocus 모델링 포트폴리오에 솔리드 메카니즘이 추가됨에 따라 FLOW-3D*(는 이제 하나의 소프트웨어 패키지에서 완전히 결합된 Auid-structure 상호 작용 모델을 제공하는 몇 안 되는 시뮬레이션 툴 중 하나가 되었습니다.

내장된 유한 요소 분석과 FLOW-3D의 입증된 자유 표면 Aows 기록은 주조 업계에 매력적인 선택입니다. 많은 사용자들이 주조 프로세스를 포함한 유체 구조 상호 작용 문제를 시뮬레이션하기 위해 여러 소프트웨어 패키지를 결합해 왔습니다.

모델 제작자는 Auid 역학을 별도로 해결한 다음 표면 경계 조건을 고체 역학적 패키지로 가져와 응력과 변형을 얻은 다음 변형된 형상을 다시 조류 해결기로 공급하고 주기는 계속됩니다.

이 프로세스의 수동 구현은 지루함을 증명하고 스크립트 및 래퍼를 통해 프로세스를 자동화하는 것은 어려운 일입니다. 게다가, 대부분의 경우 이 커플링은 사례별로 수행되어야 합니다.

FLOW-3D는 이 프로세스의 두 측면을 단일 시뮬레이션의 결과로 두 솔루션이 모두 제공되는 하나의 패키지로 원활하게 통합했습니다.

이 기사에서는 시뮬레이션 결과를 실제 주조 부품의 변형과 비교하는 경우를 제시한다. 부품 및 실험 결과는 Littler Diecast Corporation의 Mark Littler에 의해 제공되었습니다.

In the casting industry, the ability to predict thermal stresses and resulting deformations during solidification and cooling continues to be a challenge. Flow Science has recently developed its fuid-structure interaction (FSI) and thermal stress evolution (TSE) models to provide these kinds of predictions to its customers. With the addition of solid mechanics to its existing fuid focused modeling port- folio, FLOW-3D*( is now one of the few simulation tools that provide a fully coupled Auid-structure interaction model within one software package. The built- in finite element analysis along with FLOW-3D’s proven record in free surface Aows makes it an attractive choice to the casting industry. Many users have been coupling multiple software packages in order to simulate fuid-structure interaction problems including casting processes. The modeler solves the Auid mechanics separately, then imports the surface boundary conditions into a solid mechanics package, obtains the stresses and deformations and then feeds the deformed geometry back into the fow solver and the cycle continues. The manual implementation of this process proves tedious and automating it through scripts and wrappers is challeng- ing. Besides, most of the time, this coupling has to be done on a per case basis. FLOW-3D has seamlessly integrated both aspects of this process into one package where both solutions come out as the result of a single simulation. In this article, a case where the simulation results are compared to deformations from an actual cast part is pre- sented. The part and experimental results were provided by Mark Littler of Littler Diecast Corporation.


FLOW-3D는 최근 고체 역학을 컴퓨팅하면서 Auid Aow를 동시에 시뮬레이션하는 기능을 추가했습니다.

업계에서 단일 시뮬레이션 내에서 완전히 결합된 Auid-Structure 상호 작용을 해결할 수 있는 소프트웨어 패키지는 몇 개 되지 않습니다. 이 모델은 선형 후크 모델을 기반으로 하지만 각 시간 단계에서 스트레스가 점진적으로 계산되기 때문에 큰 변형이 가능합니다.

이 방법에서, 각 작은 증가 동안의 응력-변형 관계는 대부분의 경우 선형으로 가정할 수 있다. 또한 다이 및 응고 합금의 온도 의존성 탄성 특성을 지정할 수 있습니다. 이 모델은 열 잔류 응력으로 인해 냉각 중에 부품이 원하는 형상에서 변형되는 주조 업계에 특히 유용합니다.

캐스터는 이러한 변형을 예측하고 다이를 아주 약간만 변화시켜 최종 변형 기하학이 원하는 형태가 되도록 수정합니다.

이 작업은 FLOW-3D 사용자에게 흥미로운 새로운 경로를 제시하며 향후 릴리즈에서 몇 가지 새로운 기능을 제공하는 토대가 됩니다.

그러한 노력에는 플라스틱 변형과 인접한 고체 구성 요소 간, 그리고 고체 구성 요소와 고체화된 Auid 영역 사이의 완전한 결합이 포함됩니다.


FLOW-3D has recently added the capability of simulta- neously simulating the Auid Aow while computing the solid mechanics. There are only a few software packages in the industry that can solve a fully coupled Auid-struc- ture interaction within a single simulation. Although the model is based on a linear Hookean model, large deformations are possible because the stress is computed incrementally during each time step. In this method, the stress-strain relationship during each small incre- ment can be assumed to be linear in most cases. Fur- thermore, temperature-dependent elastic properties of the die and solidified alloy can be specified. This model is particularly beneficial to the casting industry where thermal residual stresses cause the part to deform from the desired geometry during cooling. Casters can predict these deformations and correct for them by changing the die ever so slightly so that in fact the final deformed geometry is the desired shape. This work represents an exciting new path for FLOW- 3D users and serves as a foundation for several new capabilities in future releases. Such efforts will include plastic deformations and full coupling between neigh- boring solid components and between solid components and solidified Auid regions.

Incremental Elastic Stress Model

Elastic stress has been incorporated into FLOW-3D® to emulate viscoplastic materials, which are materials which behave as solids up to a yield stress, beyond which they behave like a viscous liquid.

The incremental elastic stress model recently incorporated into FLOW-3D® computes the elastic stress using linear Hookean theory (Equation 2 above). Although this constitutive equation predicts only a linear response to stress, implementation as an incremental model, in which the stress changes in each time step are accumulated, allows the prediction of highly nonlinear responses. This works because the response within each small time step can be well approximated as linear. Pictorially, with this model, FLOW-3D® predicts the total stress as a summation of the viscous stress and the elastic stress, as shown in Figure 1.