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روش تلفیقی سطح پاسخ و فراکاوشی در بروزرسانی مدل عددی جریان غیردائمی در شبکه رودخانهای (مطالعه موردی: رودخانه گرمابدر- زیقان) | ||
| تحقیقات مهندسی سازه های آبیاری و زهکشی | ||
| دوره 24، شماره 91، آبان 1402، صفحه 109-129 اصل مقاله (2.5 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/idser.2024.363104.1550 | ||
| نویسندگان | ||
| فرهود کلاته* 1؛ احسان امین وش2 | ||
| 1دانشیار، دانشکده مهندسی عمران، دانشگاه تبریز، تبریز، ایران. | ||
| 2دانشجوی دکتری، دانشکده مهندسی عمران، دانشگاه تبریز، تبریز، ایران. | ||
| چکیده | ||
| در تحقیق حاضر روشی برای به روزرسانی مدلهای عددی پیشبینی جریان غیردائم در شبکه های رودخانه ای با استفاده از ترکیب روش سطح پاسخ و روشهای فراکاوشی توسعه داده شده است. در این راستا، شاخهای از رود گرمابدر (زیقون) برای مطالعۀ موردی انتخاب شد. از نرم افزار Hec-Ras به منظور تهیۀ مدل عددی جریان غیر دائم در شبکۀ رودخانهای استفاده شده است. شبکۀ عصبی نیز برای شبه سازی روش عددی انتخاب شد تا در روند استفاده از روش الگوریتم ژنتیک بتوان پارامترهای مورد نظر را بهینه سازی کرد. پس از مدلسازی جریان غیردائم در نرم افزار Hec-Ras برای به روز رسانی مدل عددی، ضریب مانینگ به عنوان پارامتر تاثیرگذار در نتایج حاصل از نرم افزار Hec-Ras انتخاب گردید. برای بررسی تاثیر این پارامتر و تعیین مقدار بهینه برای به روز رسانی مدل عددی مورد نظر، به تعداد 100 بار نرم افزار Hec-Ras بهازای ضریب های مانینگ متفاوت مدل سازی و آنالیز گردید و شبکۀ عصبی با تعداد 1000 لایۀ درونی آموزش داده شد. نتایج به دست آمده نشان داد که بهینه سازی پارامتری موثر در رفتار جریان شبیه سازی شده و روندی است فرسایشی و زمانبر اما استفاده از شبکۀ عصبی این سرعت همگرایی را بالا می برد و در نتیجه این روند بسیار سریع تر و قابل اعتمادتر می شود. از طرف دیگر، نتایج نشان می دهد که ضرایب مانینگ از پارامترهای بسیار مهم و تاثیرگذار در رفتار جریان شبیه سازی شده است که با تغییری اندک در آن، نتایج مدل شبیه سازی شده دستخوش پراکندگی قابل توجهی می شود که در روند آنالیز باید در نظر گرفته شود تا نتایج حاصل با واقعیت تفاوت قابل توجهی نداشته باشند. | ||
| کلیدواژهها | ||
| الگوریتم ژنتیک؛ بهینهسازی؛ بروزرسانی مدلهای عددی؛ شبیه سازی؛ نرم افزار Hec-Ras | ||
| عنوان مقاله [English] | ||
| Combined Method of Response Surface and Meta-Exploration in Updating the Numerical Model of Unsteady Flow in River Network, Case Study: Garmabadr-Ziqan River | ||
| نویسندگان [English] | ||
| Farhoud Kalateh1؛ Ehsan Aminvash2 | ||
| 1Associate professor, Faculty of civil engineering, University of Tabriz, Tabriz, Iran. | ||
| 2Ph.D. candidate, Faculty of civil engineering, University of Tabriz, Tabriz, Iran | ||
| چکیده [English] | ||
| Extended Abstract Introduction Nowadays, numerical modeling is known as a powerful method and tool in investigating practical phenomena. So that this method is used in many fields of engineering. Although the numerical model of an engineering problem is usually prepared based on several simplifying assumptions, it is possible that this numerical model does not reflect all aspects of the real problem and is not able to show the real behavior in reality. Direct updating methods use the analytical solution of the problem for this purpose, although these methods specify the necessary corrections without the need to repeat calculations and in one step, but in most cases such corrections do not have a physical meaning in reality but iteration-based updating methods require sensitivity analysis of the effective parameters in the problem in order to find the impact of each of them. One of the solutions to deal with the time-consuming problem of multiple re-analyses in numerical models prepared by commercial software during model updating based on sensitivity analysis is to replace the numerical model with an approximate representative model known as meta-models. The response surface method is one of the common methods for building such meta-models. The response surface technique is actually a test design method to select the design parameters in the experiment with the aim of optimizing some system response functions. From this point of view, the research regarding the response of the network of open channels to the arrival of the flood wave and predicting the characteristics of the flow in the branches of the network can be the solution to minimize the damages caused by it. Methodology In this research, in order to update the numerical model of unsteady flow in the network of open channels by using the combined method of response surface and meta-exploration methods, a branch of the Garmabadr River (Ziquon) has been selected, and the desired data has been prepared and sorted. have been Hec-Ras software has been used as a numerical method. Neural network is also chosen for simulating the numerical method so that the desired parameters can be optimized in the process of using the genetic algorithm method. This area is located in the northern part of Iran and in the northeast of Tehran province. The geographical coordinates include longitude 51 degrees 32 minutes to 51 degrees 38 minutes and latitude 35 degrees 51 minutes to 35 degrees 58 minutes. MATLAB software has been used to build a meta-model or an alternative model. MATLAB is a software that can be called the language of mathematics and modern engineering sciences. Results and Discussion As it is clear from the results of the Hec-Ras program, the discharge of stations number 13 and 22 is equal to 308.03 and 27.89 cubic meters per second, respectively. The estimation error is equal to the difference between the estimated flow rate and the observed flow rate, which is 18.03 and 2.11 cubic meters per second, respectively. The percentage of the estimation error is equal to the ratio of the estimation error to the observed value is equal to 6.2% and 7%, respectively, which is an acceptable value for this research, and this result shows the appropriate performance of the genetic algorithm for optimizing the flow simulated by It shows the neural network, on the other hand, the low percentage of error also determines the accuracy of the intended program. As a result, the error of the genetic program is at an optimal level. As it is known, Manning's coefficients are very important and influential parameters in the behavior of the flow, the change in which causes significant changes in the simulation results. The effect of this uncertainty on the performance of numerical methods was clearly identified in this research. As a result, examining inputs that have inherent uncertainty and determining their appropriate values is a suitable solution for improving numerical methods. Conclusions Genetic algorithm is a powerful method to determine the values of effective parameters in simulated flow performance, and its combination with neural network is a powerful tool for engineering purposes, including the analysis of the behavior of open channels, whose fast convergence is a strong point to choose in these problems. in similar cases. Manning's coefficients are very important and influential parameters in the simulated flow behavior, with a small change in it, the simulated model undergoes significant dispersion, which should be considered in the analysis process so that the results are not significantly different from reality. Optimizing an effective parameter in simulated flow behavior is an erosive and time-consuming process, and the use of neural network becomes much faster and more reliable due to the high convergence speed of this process. | ||
| کلیدواژهها [English] | ||
| Genetic algorithm, optimization, update of numerical models, simulation, Hec-Ras software | ||
| مراجع | ||
|
Abbasi, A. and Malek Nejad Yazdi, M. (2012). Investigation of Effective Parameters on Manning Coefficient in Rivers and Obtain the New Relation for Estimate it (Case Study: Ferizi River). Water and Soil, 26(5), 1308-1317 (In Persian).
Abdi, R. Endreny, T. & Nowak, D. (2020). i-Tree cool river: An open source, freeware tool to simulate river water temperature coupled with HEC-RAS. MethodsX, 7, 100808.
Bush, S. T. Dresback, K. M. Szpilka, C. M. & Kolar, R. L. (2022). Use of 1D Unsteady HEC-RAS in a Coupled System for Compound Flood Modeling: North Carolina Case Study. Journal of Marine Science and Engineering. 10(3), 306.
Chang, T. J. Kao, H. M. Chang, K. H. & Hsu, M. H. (2011). Numerical simulation of shallow-water dam break flows in open channels using smoothed particle hydrodynamics. Journal of Hydrology. 408(1), 78-90.
Chapokpour, J. and Daneshfaraz, R. (2013). Sedimentary study of Qarranqu river using Hec-Ras. International Research Journal of Applied and Basic Sciences, 4(11), 3582-3591.
Daneshfaraz, R. Dasineh, M. and Ghaderi, A. (2019). Evaluation of scour depth around bridge piers with HEC-RAS (case study: Bridge of Simineh Rood, Miandoab, Iran). Environment and Water Engineering, 5(2), 91-102 (In Persian).
Emami, H. Emami, S. and Heydari, S. (2019). Prediction Suspended Sediment Load of River Using Meta-heuristic Algorithms. Iranian Journal of Irrigation & Drainage. 13(5), 1426-1438 (In Persian).
Ghezelsouflu, A.A. and Jaafrzadeh, M.R. (2008). Numerical modeling of shallow water flow with static and dynamic sharp waves. Technical Engineering Journal of Islamic Azad University of Mashhad. 2(2): 27-40 (In Persian).
Guideline for determination of the hydraulic roughness coefficient of rivers, Management and planning organization, Islamic Republic of Iran, No. 688 (In Persian).
He, Z. Wu, T. Weng, H. Hu, P. & Wu, G. (2015). Numerical simulation of dam-break flow and bed change considering the vegetation effects. International Journal of Sediment Research. 32(1), 102-120.
Hsu, C.T. & Yeh, K.C. (2002). Iterative explicit simulation of 1D surges and dam-break flows. International Journal for Numerical Methods in Fluids. 38 (7), 647–675.
Joshi, M. M., and Shahapure, S. S. 2020. Flood susceptibility mapping for part of Bhima River basin using two-dimensional HEC-RAS model. In Techno-Societal 2018: Proceedings of the 2nd International Conference on Advanced Technologies for Societal Applications-Volume 1 (pp. 595-605). Springer International Publishing.
kamakoly, S. Esmaeili varaki, M. and Navabian, M. (2022). Experimental investigation of effect of the efficiency block ramp on increasing the dissolved oxygen in semi-uniform regime. Irrigation and Drainage Structures Engineering Research. 23(86), 19-50 (In Persian).
Karimi, R. Minatoor, Y and Akhtari, A.A. (2013). Application of Finite Element Method in Simulation of One-Dimensional Unsteady Flow. First National Conference of Civil Development, Rasht (In Persian).
Khabaz Tamimi, M.R. Kolahdozan, M. and Majdzadeh Tabatabai, H. (2014). two-dimensional modeling of flow in rivers using curvilinear networks. 5th Iran Hydraulics Conference, Kerman (In Persian).
LaRocque, L. A. Imran, J. & Chaudhry, M. H. (2012). Experimental and numerical investigations of two-dimensional dam-break flows. Journal of Hydraulic Engineering. 139(6), 569-579.
Larocque, L. A. Imran, J. & Chaudhry, M. H. (2013). 3D numerical simulation of partial breach dam-break flow using the LES and k–ϵ turbulence models. Journal of Hydraulic Research. 51(2), 145-157.
Mahjoub, A. Ghayashi, R. Gwashiri, Z. (2009). Numerical modeling of flow in the location of river bridges and investigation of the effect of water guide wall on horizontal vortices. 5th National Congress of Civil Engineering, Mashhad (In Persian).
Mousavi, F. and Daneshfaraz, R. (2013). Evaluating various factors in calculation of scour depth around bridge piers using HEC-RAS Software, CSU2001 and Froehlich equations. Journal of Civil Engineering and Urbanism, 3(6), 398-402.
Pirozzoli, S. (2011). Numerical methods for high-speed flows. Annual review of fluid mechanics. 43, 163-194.
Pořízková, P. Kozel, K. & Horáček, J. (2012). Numerical simulation of unsteady compressible flow in convergent channel: pressure spectral analysis. Journal of Applied Mathematics.
Uca, U. Lamada, M. Arfan, A. & Haris, N. A. (2023). Flood Modelling Using Integration of Multi-data Analysis and HEC-RAS Model in Mata Allo River, Sulawesi. In E3S Web of Conferences. 400: 01004.
Zarei ghorkhodi, A. Shahnazari, A. and Mohammadi, F. (2022). Evaluation of the effect of dams on runoff and sediment parameters using SWAT model (Case study: Tajan River watershed, Mazandaran). Iranian Journal of Irrigation & Drainage. 16(2), 294-307 (In Persian).
Zehtab, R. Akbari, M.H and Alishahi, M.M. (2016). Numerical modeling of flow in an ultrasonic shock turbine. 10th Fluid Dynamics Conference, Yazd (In Persian). | ||
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