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نمایش:

Reliability analysis of corroded pipes using conjugate HL–RF algorithm based on average shear stress yield criterion

behrooz keshtegar
ثبت نشده , ثبت نشده , Year : 2014 , Pages: 104-117, ISSN: Journal Paper

Abstract

Modeling the behavior of FRP-confined concrete using dynamic harmony search algorithm

behrooz keshtegar
ثبت نشده , ثبت نشده , Year : ثبت نشده , Pages: -, ISSN: Journal Paper

Abstract

Relaxed performance measure approach for reliability-based design optimization

behrooz keshtegar,Lee Ikjin
ثبت نشده , ثبت نشده , Year : 2016 , Pages: -, ISSN: Journal Paper

Abstract

Chaotic conjugate stability transformation method for structural reliability analysis

behrooz keshtegar
ثبت نشده , ثبت نشده , Year : 2016 , Pages: -, ISSN: Journal Paper

Abstract

A hybrid self-adjusted mean value method for reliability-based design optimization using sufficient descent condition

behrooz keshtegar,Peng Hao
ثبت نشده , ثبت نشده , Year : 2016 , Pages: -, ISSN: Journal Paper

Abstract

Gaussian global-best harmony search algorithm for optimization problems

behrooz keshtegar
ثبت نشده , ثبت نشده , Year : 2016 , Pages: -, ISSN: Journal Paper

Abstract

مطالعه تولید آنتروپی و ارزیابی خواص آماری انتقال حرارت در جریان مغشوش

بهروز کشته گر,فرهاد وحیدی نیا,سیده محدثه میری
ايران ، علوم کاربردی و محاسباتی در مکانیک ، سال : 2018 ، صفحات : 63-80، شاپا: ۲۴۲۳-۶۵۱۹ مقاله در مجله

چکیده

در این مقاله، اثر قطر نانو ذرات در انتقال حرارت جابجایی اجباری جریان مغشوش سیال نانوی آب/ اکسید آلومینیوم درون یک لوله دایره‌ای شکل تحت شار حرارتی یکنواخت در دیواره با استفاده از مدل مخلوط دوفازی بصورت عددی بررسی و تحلیل آماری شده است. کسر حجمی نانوذرات برابر ۳ درصد، عدد رینولدز برابر ۱۰۴×۵ و تغییرات قطر نانوذرات در محدوده ۲۰ تا ۱۱۰ نانومتر فرض شده است. در تحلیل آماری از توابع توزیع احتمال پیوسته نظیر؛ گاما، نرمال، لوگ نرمال، گامبل، وایبول و فسچر استفاده گردیده است. پس از بررسی نتایج مشخص شد که با افزایش قطر ذرات نانو عدد ناسلت کاهش و این پارامتر با توجه به تغییرات قطر نانوذرات از تابع توزیع احتمال فسچر پیروی نموده است.

تحلیل قابلیت اعتماد مرتبه اول سازه‌ها به کمک روش بهینه‌سازی بهبود یافته جستجوی هارمونی

بهروز کشته گر
ايران ، مدل سازی در مهندسی ، سال : 2018 ، صفحات : 1-12، شاپا: 2008-4854 مقاله در مجله

چکیده

روش اولین مرتبه قابلیت اعتماد استفاده وسیعی در تخمین احتمال خرابی سازه‌ها دارد. برآورد مناسب شاخص قابلیت اعتماد در تخمین احتمال خرابی به کمک رویه اولین مرتبه قابلیت اعتماد حائز اهمیت است. عمدت‍اً، الگوریتم های تکرار ریاضی مانند هاسفر و لیند-رکویتز-فسلر (HL-RF) در تخمین شاخص قابلیت اعتماد مسائل غیرخطی همگرایی ناپایداری نشان داده است. الگوریتم جستجوی هارمونی بدون در نظر گرفتن تقعر یا تحدب مسائل قابلیت اعتماد می تواند تخمین مناسبی از شاخص قابلیت اعتماد ارائه دهد. در این مقاله یک الگوریتم جستجوی هارمونی کلی ترین ذره با تعداد حافظه هارمونی پایین پیشنهاد شده است. در روش پیشنهادی جستجوی هارمونی، یک پهنای باند جهت تنظیم حافظه هارمونی با استفاده از و تولید تصادفی عدد با تابع توزیع احتمال پیشنهاد شده که بر اساس تعداد متغیرهای تصادفی محاسبه می‌گردد. صحت همگرایی و سرعت تحلیل این الگوریتم به کمک چندین تابع شرایط حدی بر گرفته شده از مراجع با روش‌های تکرار ریاضی مانند HL-RF و انتقال پایدار مقایسه شده است. نتایج حاکی از آن است که روش HL-RFدر بعضی از مثال‌ها همگرا نشده و روش بهبود یافته جستجوی هارمونی به نتایجی مشابه با روش انتقال پایدار با تعداد تکرار کمتری همگرا شده است. روش هارمونی پیشنهادی از سرعت همگرایی بالا و صحت نتایج بسیار مناسبی برخودار است.

Enhanced sequential approximate programming using second order reliability method for accurate and efficient structural reliability-based design optimization

behrooz keshtegar,Zeng Meng,Huanlin Zhou,Hao Hu
USA , Applied Mathematical Modelling , Year : 2018 , Pages: 562-579, ISSN:0307-904X Journal Paper

Abstract

Second-order reliability method (SORM) can provide sufficient accuracy for evaluating the probabilistic constraints in reliability-based design optimization (RBDO). However, the application of SORM in RBDO significantly increases the computational burden, as it is necessary to calculate the second-order sensitivities of the performance function. In order to achieve equal efficiency to that of the first-order reliability method-based RBDO approach, enhanced sequential approximate programming (ESAP) is proposed by implementing the SORM-based RBDO method. Based on the diagonal quadratic approximation method, the Hessian matrix is calculated without generating additional computational costs for providing the design sensitivity analysis of probabilistic constraints within the same iterations. Furthermore, ESAP is applied to the reliability-based topology optimization domain, and five numerical benchmark RBDO problems with two complex engineering examples are studied. The proposed ESAP is compared with other RBDO methods, including the reliability index approach, performance measure approach, sequential optimization and reliability assessment method, and SAP, and the results demonstrate the superiority of the proposed ESAP.

تحلیل قابلیت اعتماد فازی سازهها با استفاده از روش دینامیکی انتقال پایدار امتدادی

بهروز کشته گر,منصور باقری
ايران ، روش های عددی در مهندسی ، سال : 2018 ، صفحات : 133-148، شاپا: 2228-7698 مقاله در مجله

چکیده

در این مقاله یک روش کارا و توانمند بهمنظور ارزیابی قابلیت اعتماد فازی سازهها تحت عدم قطعیتهای آماری متغیرهای تصادفی ارائه شده است. این روش، تحت عنوان روش فازی- دینامیکی انتقال پایدار امتدادی نامگذاری شده که متشکل از دو حلقه داخلی و خارجی است. در حلقه داخلی روش تحلیل قابلیت اعتماد مرتبه اول بهصورت دینامیکی بر اساس روش انتقال پایدار، بهبودیافته است. تحلیل فازی در حلقه خارجی با استفاده از رویکرد بهینهسازی مجموعههای آلفا برش بر پایه الگوریتم ژنتیک پایهگذاری شده است. عملکرد الگوریتم ارائه شده برای سه مثال غیرخطی ارزیابی شده که نتایج بیانگر بهبود کارایی و توانمندی روش دینامیکی انتقال پایدار در در مقایسه با روش معمول تحلیل قابلیت اعتماد مرتبه اول است.

برازش توابع غیرخطی برای توصیف منحنی تولید کوتاه مدت تخم در بلدرچین ژاپنی

هادی فرجی آروق,راضیه رحیم زاده,محمد رکوعی,علی مقصودی,بهروز کشته گر
ايران ، تولیدات دامی ، سال : 2017 ، صفحات : 299-310، شاپا: 2009-6776 مقاله در مجله

چکیده

هدف از این تحقیق، برازش بهترین تابع برای منحنی تولید تخم طی 13 هفته بلدرچین ژاپنی بود. بدین منظور، رکوردهای هفتگی و انفرادی تولید تخم 314 بلدرچین ژاپنی برای برازش توابع استفاده شد. توابع لجستیک غیرخطی، گامای ناقص، گامای تصحیح شده، لخورست، ناروشین تاکما دو، جزء به جزء و لجستیک نلدر با نرم­افزار R برازش شد. برای انتخاب بهترین تابع از معیارهای میانگین مربعات خطا، معیار آکائیک و معیار اطلاعات بیزی استفاده شد. نتایج نشان داد که تابع ناروشین تاکما دو (کمترین میانگین مربعات خطا، معیار آکائیک و معیار اطلاعات بیزی) و تابع جزء به جزء (بیشترین میانگین مربعات خطا، معیار آکائیک، معیار اطلاعات بیزی) به ترتیب مناسب­ترین و نامناسب­ترین تابع برای توصیف منحنی تولید تخم بلدرچین­ها بودند. بیشترین همبستگی (953/0) بین مقادیر پیش­بینی شده تعداد تخم با استفاده از توابع برازش شده و مقدار واقعی مربوط به تابع ناروشین تاکما دو بود. نتایج حاصل از مقایسات توابع و همبستگی­های حاصل نشان می­دهد که تابع ناروشین تاکما دو بهتر از سایر توابع مورد مطالعه در این تحقیق، تولید کوتاه مدت تخم بلدرچین ژاپنی را توصیف می­کند و از این تابع می­توان برای پیش­بینی توان تولید کوتاه مدت بلدرچین ژاپنی استفاده نمود.

Adaptive conjugate single-loop method for efficient reliability-based design and topology optimization

behrooz keshtegar,Zeng Meng
Swiss , Computer Methods in Applied Mechanics and Engineering , Year : 2019 , Pages: 95-119, ISSN:0045-7825 Journal Paper

Abstract

The single-loop approach (SLA) for reliability-based design optimization (RBDO) is one of the most efficient schemes for optimization problems with linear and weak nonlinear probabilistic constraints. However, it may produce unstable results or increase computational efforts when using the ordinary search direction to determine the optimum design in RBDO problems with highly nonlinear probabilistic constraints. The conjugate gradient (CG) is a promising sensitivity vector for locating the most probable point (MPP) of highly nonlinear concave performance functions. However, the MPP computation using the CG may require a high computational burden for convex constraints To overcome the drawbacks of the SLA the adaptive conjugate singleloop approach (AC-SLA) is proposed for RBDO problems with a large variety of nonlinear constraints. The sensitivity vector of the probabilistic constraints is adaptively computed using the CG vector with a dynamical conjugate scalar factor (DCF). The DCF is adjusted within the range from 0 to 2 using two adaptive coefficients, which are adapted based on the new and previous points. Moreover, the Lyapunov exponents are developed as a general tool for detecting the robustness of different MPP approximation algorithms. The method is also applied to solve a reliability-based topology optimization (RBTO) problem. The ability of the AC-SLA in six RBDO benchmark problems, one applicable to an RBDO aircraft engineering problem and one for RBTO problem, is compared in terms of both robustness and efficiency using the SLA, performance measure approach (PMA), reliability index approach (RIA), and sequential optimization and reliability assessment (SORA).

Reliability analysis of low, mid and high-grade strength corroded pipes based on plastic flow theory using adaptive nonlinear conjugate map

behrooz keshtegar,M. A. Ben Saghier,B. Elahmoune
Netherlands , Engineering Failure Analysis , Year : 2018 , Pages: 145-161, ISSN:1350-6307 Journal Paper

Abstract

Generally, the safety levels of corroded pipes are evaluated using the nonlinear probabilistic model thus, an accurate probabilistic model is the important step in the structural reliability analysis of corroded pipelines. In this paper, three novel probabilistic models are developed for describing the burst pressure in low, mid and high-strength grades steels. The developed probabilistic models for corroded pipelines include three terms as 1) model errors, 2) burst pressure of intact pipes based on stress criteria improved by the plastic flow theory and 3) different remaining corroded strength factors. The best models for each steel grades category of corroded pipeline are selected using the confidence index based on three burst experimental database tests of pipes. The best distributions of model error for different probabilistic burst corroded models are given based on Anderson-Darling statistic from the Normal, Lognormal, Frechet, Gumbel, and Weibull distribution functions. An adaptive conjugate map-based first order reliability method is developed to assess the structural failure analysis of corroded pipelines. Six corroded pipelines with different grades strength steels are selected to demonstrate the applicability of the proposed probabilistic models in structural reliability analysis. It conducted that the average shear stress yield criterion is the best plastic flow theory for modeling the burst pressure of intact pipes, where the Gumbel, Frechet and Lognormal are respectively the best distributions for model errors of low, mid and high-strength grade steels

Evaluation of the plant pattern of intercropping in chemical soil elements using the nonlinear response surface model

behrooz keshtegar,,,
Bulgaria , Bulgarian Journal of Agricultural Science , Year : 2018 , Pages: 599-610, ISSN:2534-983X Journal Paper

Abstract

The suitable culture to improve soil fertilities based on chemical properties is one of the most important decisions to implement a suitable culture for the stability of income of farmers in arid regions. The effects of vermicompost and the different patterns of intercropping, including corn, peanut and borage are evaluated on optimum conditions of chemical soil elements such as nitrogen, phosphorus, sodium and carbon. The experimental data are extracted form a dry climatic region in southeast Iran, using three levels of vermicompost (0, 2.5, and 5 t/ha) and nine levels for the intercropping (including pure culture of corn, peanut, and borage in the following proportions: replacement and additive design) using split plot design, which is based on RCBD with three replications during 2015-2016. The Nonlinear Modeling-based Response Surface Method is used to predict the chemical soil elements based on vermicompost and intercropping. The effects of the different culture patterns are investigated to illustrate the sensitivity of soil fertilization. The best pattern to improve the soil’s elements is obtained by increasing the proportion of the peanut in intercropping, introducing five t/ha of vermicompost, and establishing an intercropping of 80% peanut + 50% corn + 50% borage for increasing the soil nutrients.

Limited descent-based mean value method for inverse reliability analysis

behrooz keshtegar,Z. Yassen
Germany , Engineering with Computers , Year : 2018 , Pages: 1-13, ISSN:0177-0667 Journal Paper

Abstract

The robustness and efficiency of inverse reliability methods are important issues in reliability-based design optimization (RBDO) using performance measure approach (PMA). The adaptive modified chaos control (ACC), step length adjustment (SA), and relaxed mean value (RMV) methods were recently implemented to improve the robustness and efficiency of PMA. In this paper, a limited descent mean value (LDMV) method is proposed to improve robustness and efficiency of inverse reliability analysis for either convex or concave probabilistic constraints. The LDMV formula is dynamically adjusted by an adaptive step size based on the advanced mean value method (AMV). The robustness and efficiency of the ACC, SA, RMV, and proposed LDMV methods are compared through six nonlinear performance functions. The results illustrated a similar robust performance between LDMV against RMV and FSL methods and superior to the ACC method. The proposed LDMV improves the robustness and efficiency of the inverse first-order reliability method in comparison with existing reliability methods.

Refined first-order reliability method using cross-entropy optimization method

behrooz keshtegar,Hamed Ghohani Arab,Mohsen Rashki,Mehdi Rostamian,Alireza Ghavidel,Hossein Shahraki
Germany , Engineering with Computers , Year : 2018 , Pages: 1-13, ISSN:0177-0667 Journal Paper

Abstract

Generally, the first-order reliability method (FORM) is an efficient and accurate reliability method for problems with linear limit state functions (LSFs). It is showed that the FORM formula may produce inaccurate results when the LSF is defined by mathematical forms introduced as gray function. Thus, the original FORM formula may provide the results with huge errors. In this paper, a probabilistic optimization model as refined FORM (R-FORM) is presented to search most probable failure point (MPP) with the accurate results for gray LSFs. The cross-entropy optimization (CEO) method is utilized to search MPP in proposed R-FORM model. Several reliability problems are applied to illustrate the accuracy of the R-FORM compared to the conventional FORM formula. Results illustrate that the R-FORM provides more accurate results than the FORM for gray performance functions.

Structural Reliability Analysis of Corroded Pipeline made in X60 Steel Based on M5 Model Tree Algorithm and Monte Carlo Simulation

behrooz keshtegar,Mohamed Seghier,José Correia,Abílio De Jesus,G. Lesiuk
Netherlands , Procedia Structural Integrity , Year : 2018 , Pages: 1670-1675, ISSN:2452-3216 Journal Paper

Abstract

Accurate determination of the failure probability of oil and gas pipeline is very important in integrity assessment and work conditions of such structure. In this paper, the failure probability of the corroded pipelines which is made by X60 steel grade is evaluated. The burst corroded performance function is developed using the M5 model tree for this complex real engineering failure problem. The structural reliability of a the pressurized gas pipeline containing external corrosion defects has been evaluated using hybrid reliability method combined by the M5 model tree and Monte Carlo simulation. The results indicated that increasing the defects depth are strongly reduced the safety levels of this problem.

Reliability analysis based on hybrid algorithm of M5 model tree and Monte Carlo simulation for corroded pipelines: Case of study X60 Steel grade pipes

behrooz keshtegar,Bensaghier,José A.F.O. Correia,Grzegorz Lesiuk,Abílio M.P. De Jesus
Netherlands , Engineering Failure Analysis , Year : 2019 , Pages: 793-803, ISSN:1350-6307 Journal Paper

Abstract

In this paper, the failure probability of corroded pipelines made by X60 steel grade is evaluated. For this complex real engineering failure problem, the burst corroded performance function is developed using an M5Tree model based on calibration with real burst test database. In addition statistical analysis of ILI-report data is conducted for best modeling of corrosion defects geometries (i.e. defects length and depth) based on Anderson-Darling statistic where different PDFs (i.e. Normal, Lognormal, Frechet, Gumbel, Weibull) were tested. Moreover, the effect of defects geometries on the failure probability of the case-studies were investigated for various operating regimes. Then the influence of distributions on the reliability analysis were also illustrated. Results indicated that increases in defects depth are strongly reduced the safety levels of this problem, where miss-selection of defects distributions could lead to conservatives results.

Understanding the hidden relations between pro- and anti inflammatory cytokine genes in bovine oviduct epithelium using a multilayer response surface method

behrooz keshtegar,Rasoul Kowsar,Akio Miyamoto
English , Scientific Reports , Year : 2019 , Pages: 1-15, ISSN:2045-2322 Journal Paper

Abstract

An understanding gene-gene interaction helps users to design the next experiments efficiently and (if applicable) to make a better decision of drugs application based on the different biological conditions of the patients. This study aimed to identify changes in the hidden relationships between pro- and antiinflammatory cytokine genes in the bovine oviduct epithelial cells (BOECs) under various experimental conditions using a multilayer response surface method. It was noted that under physiological conditions (BOECs with sperm or sex hormones, such as ovarian sex steroids and LH), the mRNA expressions of IL10, IL1B, TNFA, TLR4, and TNFA were associated with IL1B, TNFA, TLR4, IL4, and IL10, respectively. Under pathophysiological + physiological conditions (BOECs with lipopolysaccharide + hormones, alpha-1-acid glycoprotein + hormones, zearalenone + hormones, or urea + hormones), the relationship among genes was changed. For example, the expression of IL10 and TNFA was associated with (IL1B, TNFA, or IL4) and TLR4 expression, respectively. Furthermore, under physiological conditions, the co-expression of IL10 + TNFA, TLR4 + IL4, TNFA + IL4, TNFA + IL4, or IL10 + IL1B and under pathophysiological + physiological conditions, the co-expression of IL10 + IL4, IL4 + IL10, TNFA + IL10, TNFA + TLR4, or IL10 + IL1B were associated with IL1B, TNFA, TLR4, IL10, or IL4 expression, respectively. Collectively, the relationships between pro- and anti-inflammatory cytokine genes can be changed with respect to the presence/absence of toxins, sex hormones, sperm, and co-expression of other gene pairs in BOECs, suggesting that considerable cautions are needed in interpreting the results obtained from such narrowly focused in vitro studies.

روش وزنی تصادفی شبیهسازی مونتکارلو برای تحلیل قابلیت اطمینان سازه ها

بهروز کشته گر,سحر سراوانی
ايران ، روش های عددی در مهندسی ، سال : 2019 ، صفحات : 41-60، شاپا: 2228-7698 مقاله در مجله

چکیده

‌‌براورد صحیح احتمال خرابی همراه با حجم محاسبات پایین، دغدغه اصلی در قابلیت اعتماد سازه‌ها به‌شمار می‌آید. روش‌ شبیه‌‌سازی مونت‌کارلو، به‌سادگی می‌تواند ‌‌براورد صحیحی از احتمال خرابی ارائه دهد. اما، برای مسائل پیچیده مهندسی با احتمال خرابی پایین زمان‌بر بوده و ممکن است ‌‌براورد ناکارامدی از احتمال خرابی ارائه دهد. در این مقاله، بر اساس یک روش وزنی، کارایی روش شبیه‌سازی ‌‌مونت‌کارلو بهبود بخشیده شده است. بر مبنای یک تابع نمایی، وزن نمونه‌ها به‌صورت تصادفی در فضای طراحی تنظیم شده و داده‌های تنظیم شده تصادفی، برای بهبود روش مونت‌کارلو استفاده شده است. عملکرد همگرایی روش وزنی تصادفی شبیه‌‌سازی مونت‌‌کارلو مانند صحت و میزان ‌‌براورد تابع عملکرد، به‌کمک چندین مثال غیرخطی ریاضی و سازه‌ای با متغیرهای تصادفی نرمال و غیرنرمال با روش شبیه‌‌سازی مونت‌کارلو مقایسه شده است. نتایج حاکی از آن است که روش پیشنهادی، نتایج صحیحی ‌‌براورد کرده و در حدود 100 تا 1000 برابر حجم محاسبات را نسبت به روش ‌‌مونت‌کارلو کاهش داده است.

Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

behrooz keshtegar,Ozgur Kisi,Mohammad Zounemat-Kermani
English , Hydrological Sciences Journal , Year : 2019 , Pages: 1-11, ISSN:0262-6667 Journal Paper

Abstract

The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET0). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET0. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET0. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET0, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four input PCE models for Isparta and Antalya, respectively.

Probabilistic modeling of fatigue life distribution and size effect ofcomponents with random defects

behrooz keshtegar,Y. Ai,S.P. Zhua,D. Liao,J.A.F.O. Correia,C. Souto,A.M.P. De Jesus
English , International Journal of Fatigue , Year : 2019 , Pages: 165-173, ISSN:0142-1123 Journal Paper

Abstract

Engineering components made of ductile cast irons and aluminum alloys, show fatigue lives which are normally dominated by crack initiation from defects raised by manufacturing processes. This study presents a probabilistic model to account for the influence of manufacturing defects on fatigue life, based on size and position of those defects. Specifically, a correction factor considering the influence of defect surface position is developed by modeling the damage mechanism of surface initial cracks with Weibull distribution. Experimental data of three cast irons and aluminum alloys are used for model validation and comparison. Moreover, the statistical size effect influence on fatigue life distribution under constant amplitude loading is explored. Fatigue lives of three materials with different sizes are evaluated respectively, and P–S–N diagrams show that proposed model predictions agree well with the probabilistic scatter bands.

تاثیر الگوی کشت و ورمی کمپوست بر تغییرات عناصر غذایی خاک در کشت مخلوط ذرت (Zea mays L.)، بادام زمینی (Arachis hypogea L. ) و گاو زبان اروپایی (Borag officinalis L.)

عیسی خمری,مهدیه رجایی,مهدی دهمرده ,بهروز کشته گر
ايران ، بوم شناسی کشاورزی ، سال : 2018 ، صفحات : 547-564، شاپا: ۲۰۰۸-۷۷۱۳ مقاله در مجله

چکیده

بهمنظور بررسی و تعیین اثر الگوی کشت و ورمیکمپوست بر تغییرات عناصر غذایی در کشت مخلوط ذرت ). ،(Zea mays Lبـادام زمینـی ). (Arachis hypogaea Lو گاوزبان اروپایی). ،(Borago officinalis Lآزمایشی در پژوهشکده کشاورزی دانشگاه زابل در سال زراعـی -94 1393بهصورت کرتهای شده در قالب طرح بلوکهای کامل تصادفی با سه تکرار اجرا شد. تیمارهای آزمایش شامل ورمیکمپوست بهعنـوان عامـل اصلی در سه سطح؛ عدم کاربرد کود، 2/5و 5تن در هکتار و الگوهای کشت بهعنوان عامل فرعی در نه سطح شامل؛ کشت خالص ذرت، بادام زمینی و گاوزبان اروپایی، 40درصد ذرت + 30درصد بادام زمینی + 30درصد گاوزبان، 50درصد ذرت + 25درصد بادام زمینی + 25درصد گاوزبان، 60درصد ذرت + 20درصد بادام زمینی + 20درصد گاوزبان، 100درصد ذرت + 50درصد بادام زمینی + 50درصد گاوزبان، 100درصد ذرت + 75درصد بادام زمینی + 25درصد گاوزبان و 100درصد ذرت + 25درصد بادام زمینی + 75درصد گاوزبان بود. . نتایج نشان داد بیشترین مقدار کربن خاک در کشت مخلوط در الگوی کاشت 100درصد ذرت + 50درصد بادام زمینی + 50درصد گاوزبان و کاربرد 5تن ورمی کمپوست در هکتار به میزان ) 0/41درصد( و کمترین مقدار کربن خاک در الگوی کشت 60درصد ذرت + 20درصد بادام زمینی + 20درصد گاوزبان و عدم مصرف ورمیکمپوست بهدست آمـد. افزایش نسبت اختلاط گاوزبان در الگوی کشت موجب کاهش مقدار سدیم خاک و افزایش درصد بادام زمینی در کشت مخلوط منجر به افزایش مقـدار فسفر خاک گردید. تأثیر الگوهای کشت مخلوط در افزایش میزان رطوبت حجمی خاک به میزان 20/78درصد و تشعشع فعال فتوسنتزی 77/17درصد قابل توجه بود. بیشترین مقدار عملکرد ذرت ) 17/3تن در هکتار( در الگوی مخلوط 100درصد ذرت + 25درصد بادام زمینی + 75درصد گاوزبـان و بیشترین عملکرد بادام زمینی ) 15/5تن در هکتار( در الگوی مخلوط 100درصد ذرت + 75درصد بادام زمینی + 25درصد گاوزبان بهدست آمد. نسبت برابری زمین در همه الگوهای مخلوط بیشتر از یک بود و بیشترین میزان نسبت برابری زمین در الگوی کشت مخلوط 100درصـد ذرت + 75درصـد بادام زمینی + 25درصد گاوزبان و مصرف 5تن استفاده ورمیکمپوست در هکتار بهدست آمد که نشاندهنده سودمندی کشت مخلوط نسبت به تک- کشتی بو

Probabilistic modelling of notch fatigue and size effect of components using highly stressed volume approach

behrooz keshtegar,Yang Ai,Shun-Peng Zhu,Ding Liao,José A.F.O. Correia,Abílio M.P. De Jesus
English , International Journal of Fatigue , Year : 2019 , Pages: 110-119, ISSN:0142-1123 Journal Paper

Abstract

Modeling of the notch and size effects on fatigue behavior of materials is vital for ensuring structural integrity and reliability of engineering components. This study presents a methodology considering both effects of notch and size to analyze the fatigue life distribution of specimens with different geometries using the highly stressed volume approach. Specifically, a dynamic model coefficient considering the influence of different maximum local stresses is developed by modeling the size effect of highly stressed volumes with Weibull distribution. Experimental data of three aluminum and titanium alloys are utilized for model validation and comparison. Fatigue lives of three materials with different geometries are evaluated respectively, and predicted P-S-N curves indicate that proposed model predictions agree well with the probabilistic scatter band of experimental results

Predicting reinforcing bar development length using polynomial chaos expansions

behrooz keshtegar,Zaher Mundher Yaseen,Hyeon-Jong Hwang,Moncef L. Nehdi
English , Engineering Structures , Year : 2019 , Pages: 525-534, ISSN:0141-0296 Journal Paper

Abstract

The bond stress of a reinforcing bar in a cementitious matrix varies along the bar length and is difficult to quantify. Thus, design code provisions refer to the concept of bar development length and rely on statistical analysis of rebar-pull-out test results. In the present study, a novel data-driven predictive model based on Polynomial Chaos Expansions (PCE) was developed to predict the reinforcing bar development length using 534 experimental results of simple pull-out tests on short unit bar lengths. The predictive capability of PCE was compared to that of other data-driven models, namely the Response Surface Method (RSM) and Artificial Neural Networks (ANN). Moreover, predictions of the PCE, RSM and ANN were further compared with calculations of three commonly used design code formulas (i.e., ACI 318-14, ACI 408R-03, and Eurocode 2) and predictions of two existing empirical models (i.e. Model Code 2010 and Hwang et al. model). A parametric study was conducted to explore the sensitivity of the proposed model to influential input parameters. It was found that the Polynomial Chaos Expansions model offers a powerful predictive tool for reinforcing bar bond strength. The model was able to capture trends that differ from that of existing models that assume unrealistic uniform bond stress along the rebar. This flexible and data intensive model for predicting rebar bond stress and full embedment length could offer an intelligent platform for accommodating new bar materials, new test data, and calibrating existing design provisions to keep design codes relevant.

Three-term conjugate approach for structural reliability analysis

behrooz keshtegar,Shun-Peng Zhu
USA , Applied Mathematical Modelling , Year : 2019 , Pages: 1-35, ISSN:0307-904X Journal Paper

Abstract

In this paper, a nonlinear conjugatestructural first-orderreliability method is proposedusingthree-term conjugate discrete map-based sensitivity analysisto enhanceconvergence properties as stable results and efficient computational burden of nonlinearreliability problems. The concept of finite-step lengthstrategy is incorporated intothis method to enhance the stability of the iterative formula for highly nonlinear limit state function,whilethree-term conjugate search direction combining witha finite-step sizeis utilized to enhance the efficiency of the sensitivity vector inthe proposed iterative reliability formula.The proposedthree-term discrete conjugate search directionis developedbased on the sufficient descent condition to provide the stable results, theoretically.The efficiency and robustnessof the proposed three-term conjugate formulaare investigatedthrough several nonlinear/ complex structural examples and are compared with several modified existing iterativeformulas. Comparativeresults illustrate that the three-term conjugate–based finite steplength formulaprovidessuperior efficiency and robustness thanother studied methods

Dynamical Accelerated Performance Measure Approach for Efficient Reliability-Based Design Optimization with Highly Nonlinear Probabilistic Constraints

behrooz keshtegar,Souvik Chakraborty
Netherlands , Reliability engineering and system safety , Year : 2018 , Pages: 1-17, ISSN:0951-8320 Journal Paper

Abstract

For satisfactory performance of reliability-based design optimization (RBDO) tools, stable and efficient estimation of the nonlinear probabilistic constraints is of utter importance. Unfortunately, popular methods for reliability analysis, such as hybrid chaos control, self-adaptive chaos control and adaptive chaos control, have several drawbacks which include unstable results and slow rate of convergence. To address this issue, a dynamical accelerated chaos control (DCC) –based beta-circle search direction algorithm is proposed. In order to compute the chaos control factor within DCC, a novel merit function is also proposed in this work. The efficiency and robustness of the proposed DCC method have been illustrated with four nonlinear reliability problems and four RBDO examples. Compared to available state-of-the-art methods, the proposed approach is found to be efficient and accurate. This certifies its possible application to realistic RBDO problems.

Nonlinear mathematical modeling and optimum design of tuned mass dampers using adaptive dynamic harmony search algorithm

behrooz keshtegar,Sadegh Etedali
USA , Structural Control and Health Monitoring , Year : 2018 , Pages: 1-20, ISSN:1545-2263 Journal Paper

Abstract

A novel adaptive dynamic harmony search (ADHS) algorithm is proposed based on the dynamical parameters that are adjusted using the previous results of the harmony memory with a simple formulation. The accuracy and efficiency of ADHS algorithm are compared with the several improved versions of harmony search through mathematical benchmark examples. The optimum design database of tuned mass damper (TMD) parameters for a damped main system under white‐noise base excitation is extracted by the ADHS algorithm for applicable engineering problem. Four mathematical models are calibrated using the nonlinear training approach‐based ADHS for approximating the optimum tuning TMD parameters. By considering the root mean square error and confidence index, a best nonlinear model is selected among the proposed models using ADHS training scheme and several existing empirical models. A 10‐story benchmark structural example under earthquake excitation is considered for validation of the proposed nonlinear model. The simulation results demonstrate that the ADHS provides more accurate and efficient results than the improved harmony search algorithms for mathematical benchmark examples. The proposed nonlinear model also performs with the efficient computational burdens compared with the optimization algorithms for optimum tuning of TMD parameters of a 10‐story structure, more accurately.

A novel nonlinear modeling for the prediction of blast-induced airblast using a modified conjugate FR method

behrooz keshtegar,Mahdi Hasanipanah,Iman Bakhshayeshi,Mehdi Esfandi Sarafraz
English , Measurement , Year : 2018 , Pages: 35-41, ISSN:0263-2241 Journal Paper

Abstract

Prediction of the blast-induced is an important issue in Shur river dam, Iran. The nonlinear mathematical models can provide an appropriate flexibility to achieve the accurate predictions of the blast-induced airblast. In this paper, a set of nonlinear mathematical models with eight empirical relations, which are added based on the logarithmic and power basic functions, are selected to calibrate of the mine blasting airblast using two input variables, i.e. maximum charge per delay (MC) and distance from the blast-point (DI). A general regression analysis is proposed to calibrate the nonlinear models using a modified conjugate Fletcher and Reeves (FR) method using a limited scalar factor and dynamic step size to achieve the stabilization in nonlinear modeling. Finally, three simple empirical models are chosen to implement the prediction of the blast-induced airblast. The proposed empirical models were compared with the United States Bureau of Mines (USBM) model using several error statistics. The results indicate that the proposed modified FR model provides an appropriate calibration for the nonlinear regression analysis. Also, it was found that the empirical model proposed in this study, with the root mean square error (RMSE) of 3.79, is more accurate than USBM, with the RMSE of 4.22, and can be applied to other sites for predicting the airblast.

RM5Tree: Radial basis M5 model tree for accurate structural reliability analysis

behrooz keshtegar,Ozgar Kisi
Netherlands , Reliability engineering and system safety , Year : 2018 , Pages: 49-61, ISSN:0951-8320 Journal Paper

Abstract

The surrogate models-based prediction of performance functions is an efficient and accurate methodology in structural reliability analyses. In this paper, the M5 model tree (M5Tree) is improved based on radial basis training data set and it is named as Radial basis M5Tree (RM5Tree). To predict the performance function, the random input variables are transferred from ordinal space to radial space using several effective points for nonlinear calibrated model of RM5Tree. The input datasets are controlled using the radial dataset for high-dimensional reliability problems to reduce computational efforts to evaluate the performance function. The abilities of RM5Tree using Monte Carlo Simulation (MCS) with respect to accuracy and efficiency are investigated through five nonlinear reliability problems. The results indicate that the proposed RM5Tree performs superior manner in accuracy and efficiency compared to the M5Tree, response surface method (RSM) and first order reliability method.

Enriched FR conjugate search directions for robust and efficient structural reliability analysis

behrooz keshtegar
Germany , Engineering with Computers , Year : 2018 , Pages: 117-128, ISSN:0177-0667 Journal Paper

Abstract

This paper proposes three modified conjugate Fletcher- Reeves (FR) algorithms including improved FR (IFR), the spectral-variant FR (SVFR) and modified FR (MFR) for first-order reliability method (FORM) for nonlinear reliability problems. An adaptive finite-step length is proposed to improve the efficiency and robustness of FORM formula using both steepest descent and conjugate search directions. These conjugate nonlinear maps for computing the search direction of FORM are adjusted based on sufficient decent condition to control instabilities of FORM formula. The efficiency and robustness of three proposed conjugate methods are compared with conjugate Hasofer and Lind-Rackwitz and Fiessler (CHL-RF), limited FR (LFR), HL-RF and finite-step length (FSL) through five nonlinear limit state functions. Numerical experiments illustrated that the modified FR versions of conjugate search direction are robust methods for highly nonlinear performance functions and the IFR is more efficient than the other reliability algorithms.

Reliability analysis-based conjugate map of beams reinforced by ZnO nanoparticles using sinusoidal shear deformation theory

behrooz keshtegar,Reza Kolahchi
south korea , Steel and Composite Structures , Year : 2018 , Pages: 195-207, ISSN:1229-9367 Journal Paper

Abstract

First-order reliability method (FORM) is enhanced based on the search direction using relaxed conjugate reliability (RCR) approach for the embedded nanocomposite beam under buckling failure mode. The RCR method is formulated using discrete conjugate map with a limited scalar factor. A dynamical relaxed factor is proposed to control instability of proposed RCR, which is adjusted using sufficient descent condition. The characteristic of equivalent materials for nanocomposite beam are obtained by micro-electro-mechanical model. The probabilistic model of nanocomposite beam is simulated using the sinusoidal shear deformation theory (SSDT). The beam is subjected to external applied voltage in thickness direction and the surrounding elastic medium is modeled by Pasternak foundation. The governing equations are derived in terms of energy method and Hamilton

An efficient-robust structural reliability method by adaptive finite-step length based on Armijo line

behrooz keshtegar,S. Chakraborty
Netherlands , Reliability engineering and system safety , Year : 2018 , Pages: 195-206, ISSN:0951-8320 Journal Paper

Abstract

The robustness of iterative formula as well as its computational efficiency is the essential characteristic of interest for effective reliability analysis of structures by first order reliability method (FORM). A robust and efficient iterative algorithm termed as finite-based Armijo search direction (FAL) method is proposed in the present study for FORM-based structural reliability analysis. A finite-step size is proposed using the Armijo rule and sufficient descent condition to achieve the stabilization of the FORM algorithm. The FAL is adaptively adjusted based on the information obtained from the iterative algorithm at each iteration and Armijo rule. The robustness and efficiency of the proposed FAL method is elucidated using several problems. The results obtained by the proposed method are compared with various existing reliability methods based on steepest descent search direction. The results of the numerical study indicate that the FAL approach is more robust and efficient than the other existing FORM schemes and improves the robustness of FORM formula. Thus, the FAL can be successfully implemented as a robust FORM-based iterative reliability analysis procedure.

Modified response surface method basis harmony search to predict the burst pressure of corroded pipelines

behrooz keshtegar,M .A. Ben Saghier
Netherlands , Engineering Failure Analysis , Year : 2018 , Pages: 177-199, ISSN:1350-6307 Journal Paper

Abstract

suitable design of water, oil, and gas pipes networks. Generally, the empirical burst pressure models for corroded pipelines have the narrow limitation for large-verity of steel grades. In this paper, a modified response surface model is proposed based on the novel learning procedure using harmony search algorithm to predict the burst pressure of corroded pipelines with different steel grades named as HS-MRSM. The nonlinear relation as a power and high-order polynomial functions is calibrated using improved harmony search for large experimental corroded pipes>572 in HS-MRSM model. The performances for both accuracy and agreement predictions of the HS-MRSM are compared with modified response surface method (MRSM) and existing empirical models using comparative statistics as root mean square error (RMSE), mean absolute error (MAE), the Nash-Sutcliffe Efficiency (NSE), and the Willmott index of agreement (d). The results demonstrated that the proposed HS-MRSM is significantly improved The burst pressure predictions of corroded pipelines compared to best empirical model and MRSM. Generally, the empirical models – based PCORRC format are performed the best predictions among other empirical models.

An adaptive response surface method and Gaussian global-best harmony search algorithm for optimization of aircraft stiffened panels

behrooz keshtegar,P. Hao,Y. Wang,Q. Hu
Netherlands , Applied Soft Computing , Year : 2018 , Pages: 196-207, ISSN:1568-4946 Journal Paper

Abstract

tFor the engineering optimization problems characterized by high computational cost and multiple localoptima, the combination use of surrogate model and meta-heuristic algorithm is increasingly popular.In this paper, a bi-loop optimization framework of stiffened panels is proposed to search the globaloptimum, which includes an adaptive response surface method (ARSM) loop and a Gaussian global-bestharmony search (GGHS) loop, aiming to improve the global optimization capacity in an efficient manner.The ARSM loop involves an inner loop to select the data set for training the response surface function,where the spherical data set can provide an accurate prediction of the optimum condition compared tothe original RSM. Typical aircraft stiffened panels in NASA are employed to demonstrate the effectivenessof the proposed framework. Results demonstrate that the proposed ARSM has higher prediction accuracyof weight and buckling load compared to the traditional RSM, and the optimum design of GGHS combinedwith ARSM has the lowest relative error by comparison with different harmony search algorithms. Finally,a fast prediction model of aircraft stiffened panel is developed, which can provide approximated optimumconditions without detailed optimization process

Enriched self-adjusted performance measure approach for reliability-based design optimization of complex engineering problems

behrooz keshtegar,P. Hao
USA , Applied Mathematical Modelling , Year : 2018 , Pages: 37-51, ISSN:0307-904X Journal Paper

Abstract

For reliability-based design optimization (RBDO) of practical structural/mechanical prob- lems under highly nonlinear constraints, it is an important characteristic of the perfor- mance measure approach (PMA) to show robustness and high convergence rate. In this study, self-adjusted mean value is used in the PMA iterative formula to improve the ro- bustness and efficiency of the RBDO-based PMA for nonlinear engineering problems based on dynamic search direction. A novel merit function is applied to adjust the modified search direction in the enriched self-adjusted mean value (ESMV) method, which can con- trol the instability and value of the step size for highly nonlinear probabilistic constraints in RBDO problems. The convergence performance of the enriched self-adjusted PMA is il- lustrated using four nonlinear engineering problems. In particular, a complex engineering example of aircraft stiffened panel is used to compare the RBDO results of different reli- ability methods. The results demonstrate that the proposed self-adjusted steepest descent search direction can improve the computational efficiency and robustness of the PMA com- pared to existing modified reliability methods for nonlinear RBDO problems.

A hybrid descent mean value for accurate and efficient performance measure approach of reliability-based design optimization

behrooz keshtegar,P. Hao
Swiss , Computer Methods in Applied Mechanics and Engineering , Year : 2018 , Pages: 237-259, ISSN:0045-7825 Journal Paper

Abstract

The robustness and efficiency of performance measure approach (PMA) depend on the reliability loop in reliability-based design optimization (RBDO). For the reliability loop in the PMA using the minimum performance target point (MPTP) search, existing approaches can obtain stable results but may converge to inaccurate results, and higher computational efforts are required to achieve the optimum results for highly nonlinear problems. In this paper, a hybrid descent mean value (HDMV) approach is proposed based on a novel merit function, which is applied to combine the MPTP search formulas of the descent mean value (DMV) and advanced mean value (AMV). The merit function is used to adaptively control the numerical instability of the inverse reliability analysis for RBDO-based PMA. The accuracy, robustness and efficiency of the proposed DMV and HDMV methods are compared with existing methods through four nonlinear performance functions, two structural RBDO problems and a complex aircraft panel problem. The results illustrate that the DMV and HDMV methods are more robust, efficient and accurate than existing reliability methods. For the aircraft panel problem, a simultaneous buckling pattern is finally achieved by the proposed methods with better performance in terms of both convergence rate and computational efficiency.

A hybrid self-adaptive conjugate first order reliability method for robust structural reliability analysis

behrooz keshtegar,S. Chakraborty
USA , Applied Mathematical Modelling , Year : 2018 , Pages: 319-332, ISSN:0307-904X Journal Paper

Abstract

The traditional First Order Reliability Method (FORM) using steepest descent search direc- tion may yield unstable solutions due to periodic nature and chaos for reliability analysis problems involving highly nonlinear performance functions. A conjugate search direction approach is attempted in the present study to overcome such problem of the FORM for Most Probable Point (MPP) search. Two iterative FORM schemes are investigated based on conjugate descent direction using self-adaptive conjugate (SAC) and hybrid self- adaptive conjugate (HSAC) search directions for estimating reliability index. The SAC is proposed using Fletcher and Reeves (FR) method and an adaptive conjugate scalar factor to improve the efficiency of the FR method for reliability analysis of highly nonlinear performance function. The HSAC is adaptively computed using FR and SAC methods to improve the ro- bustness and efficiency of the FORM formula. The effectiveness of the proposed SAC and HSAC approaches are studied compare to the traditional FORM algorithms through several numerical examples. The proposed methods based on conjugate search direction are found to be more efficient and robust than the usual FORM algorithms.

Conjugate finite-step length method for efficient and robust structural reliability analysis

behrooz keshtegar
south korea , Structural Engineering and Mechanics , Year : 2018 , Pages: 415-422, ISSN:1225-4568 Journal Paper

Abstract

The Conjugate Finite-Step Length” (CFSL) algorithm is proposed to improve the efficiency and robustness of first order reliability method (FORM) for reliability analysis of highly nonlinear problems. The conjugate FORM-based CFSL is formulated using the adaptive conjugate search direction based on the finite-step size with simple adjusting condition, gradient vector of performance function and previous iterative results including the conjugate gradient vector and converged point. The efficiency and robustness of the CFSL algorithm are compared through several nonlinear mathematical and structural/mechanical examples with the HL-RF and “Finite-Step-Length” (FSL) algorithms. Numerical results illustrated that the CFSL algorithm performs better than the HL-RF for both robust and efficient results while the CFLS is as robust as the FSL for structural reliability analysis but is more efficient.

Enhanced single-loop method for efficient reliability-based design optimization with complex constraints

behrooz keshtegar,P. Hao
Germany , Structural and Multidisciplinary Optimization , Year : 2018 , Pages: 1731-1747, ISSN:1615-147X Journal Paper

Abstract

Reliability-based design optimization (RBDO) has been widely implemented for engineering design optimization when considering the uncertainty. The single loop approaches (SLA) are highly efficient but is prone to converge with inappropriate results for highly nonlinear probabilistic constraints. In this paper, a novel RBDO algorithm is proposed based on single loop approach and the enhanced chaos control method, named as enhanced single-loop method (ESM). The performance of SLA is enhanced using an adaptive inverse reliability method with limited number of iterations. The adaptive step size is computed based on a merit function which is computed using the results of the

Self‑adaptive conjugate method for a robust and efficient performance measure approach for reliability‑based design optimization

behrooz keshtegar,S. Baharom,A. El Shafie
Germany , Engineering with Computers , Year : 2018 , Pages: 178-132, ISSN:0177-0667 Journal Paper

Abstract

The advanced mean value and hybrid mean value methods are commonly used to evaluate the probabilistic constraint of reliability-based design optimization (RBDO) problems. These iterative methods can yield unstable solutions to highly nonlinear performance functions. The conjugate gradient analysis (CGA) and modified chaos control (MCC) algorithms have recently been employed to achieve the stabilization of reliability analysis in RBDO problems. However, the CGA and the MCC methods can be inefficient for convex performance functions. In this paper, a self-adaptive conjugate gradient (SCG) method

Fuzzy relaxed-finite step size method to enhance the instability of the fuzzy first-order reliability method using conjugate discrete map

behrooz keshtegar,M. Bagheri
Germany , Nonlinear Dynamics , Year : 2018 , Pages: 1443-1459, ISSN:0924-090X Journal Paper

Abstract

Fuzzy reliability analysis can be implemented using two discrete optimization maps in the processes of reliability and fuzzy analysis. Actually, the efficiency and robustness of the iterative reliability methods are two main factors in the fuzzy-based reliability analysis due to the huge computational burdens and unstable results. In the structural fuzzy reliability analysis, the first-order reliability method (FORM) using discrete nonlinear map can provide a C membership function. In this paper, a discrete nonlinear conjugate map is proposed using a relaxed-finite step size method for fuzzy structural reliability analysis, namely Fuzzy conjugate relaxed-finite step size method fuzzy CRS. A discrete conjugate map is stabilized using two adaptive factors to compute

regression techniques in solar radiation modeling: Kriging method vs RSM, MARS and M5 model tree

behrooz keshtegar,C. Mert,O. Kisi
USA , Renewable and Sustainable Energy Reviews , Year : 2018 , Pages: 330-341, ISSN:1364-0321 Journal Paper

Abstract

In this study, four different heuristic regression methods including Kriging, response surface method (RSM), multivariate adaptive regression (MARS) and M5 model tree (M5Tree) have been investigated for accurate estimating of solar radiation with different input data. Monthly solar radiation (SR) from Adana and Antakya stations, which are located in Eastern Mediterranean Region of Turkey is estimated based on the input data of maximum temperature (Tmax), minimum temperature (Tmin), sunshine hours (Hs), wind speed (Ws), and relative humidity (RH). In Adana station, the best MARS model provided slightly better accuracy than the Kriging, RSM and M5Tree while the Kriging was found to be the better than the MARS, RSM and M5Tree in Antakya station. The predictions of M5Tree model are shown inaccurate results for both maximum errors and minimum agreement compared to another models. The effect of periodicity input is examined to obtain the accurate predictions of solar radiation for these stations based on the four heuristic –based modeling Kriging, MARS, RSM, M5Tree approaches. Periodicity input data improved the root mean square errors of the best MARS, RSM, M5Tree and Kriging

Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration

بهروز کشته گر,Ozgur Kisi,Hamed Ghohani Arab,Mohammad Zounemat- Kermani
هلند ، Water Resources Management ، سال : 2018 ، صفحات : 1101-1116، شاپا: 0920-4741 مقاله در مجله

چکیده

The study investigates accuracy of a new modeling scheme, subset adaptive neuro fuzzy inference system (subset ANFIS), in estimating the daily reference evapotranspiration (ET0). Daily weather data of relative humidity, solar radiation, air temperature, and wind speed from three stations in Central Anatolian Region of Turkey were utilized as input to the applied models. The input data set for modeling the ET0 was divided to several subsets to calibrate the local data using a local modeling-based ANFIS. The estimates obtained from subset ANFIS models were compared with those of the M5 model tree (M5Tree), ANFIS models and ANN. Mean absolute error (MAE), root mean square error (RMSE), and model efficiency factor criteria were applied for analysis of models. The accuracy of M5Tree (from 15.3% to 32.5% in RMSE, from 14.4% to 24.2% in MAE), ANN (from 24.3% to 65.3% in RMSE, from 34.1% to 47% in MAE) and ANFIS (from 17.4% to 35.4% in RMSE, from 10.8% to 28.3% in MAE) models was significantly increased using subset ANFIS for estimating

Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study

behrooz keshtegar,S. Heddam
English , Neural Computing and Applications , Year : 2018 , Pages: 295-3006, ISSN:0941-0643 Journal Paper

Abstract

In the present study, two nonlinear mathematical modeling approaches, namely modified response surface method (MRSM) and multilayer perceptron neural network (MLPNN) were developed and compared for modeling daily dissolved oxygen (DO) concentration. The DO concentration and water quality variables data for several years, available from four stations operated by the United States Geological Survey, were used for developing the two models. The water quality data selected consisted of daily measured river discharge, water pH, specific conductance, water turbidity, and DO. The response surface methodology is modified based on the two steps for calibrating process. In the first regression step, the normalized input data were calibrated based on a linear function and then transferred by an inverse power function. In the second regression step, the input data from first step were used to calibrate a highly nonlinear third-order polynomial function. The accuracy of the proposed nonlinear MRSM is compared with the standard MLPNN using several error statistics such as root-mean-square error, mean absolute error, mean bias error, the coefficient of correlation, the Nash–Sutcliffe efficiency, and the Willmott index of agreement. The results obtained indicate that MRSM model performed best in comparison with the MLPNN for the all four stations.

A hybrid conjugate finite-step length method for robust and efficient reliability analysis

behrooz keshtegar
USA , Applied Mathematical Modelling , Year : 2017 , Pages: 226-245, ISSN:0307-904X Journal Paper

Abstract

The robustness and efficiency of the first-order reliability method (FORM) are the important issues in the structural reliability analysis. In this paper, a hybrid conjugate search direction with finite-step length is proposed to improve the efficiency and robustness of FORM, namely hybrid conjugate finite-step length (CFSL-H). The conjugate scalar factor in CFSL-H is adaptively updated using two conjugate methods with a dynamic participation factor. The accuracy, efficiency and robustness of the CFSL-H are illustrated through the nonlinear explicit and structural implicit limit state functions with normal and non-normal random variables. The results illustrated that the proposed CFSL-H algorithm is more robust, efficient and accurate than the modified existing FORM algorithms for complex structural problems.

Enriched FR conjugate search directions for robust and efficient structural reliability analysis

behrooz keshtegar
Germany , Engineering with Computers , Year : 2018 , Pages: 117-128, ISSN:0177-0667 Journal Paper

Abstract

This paper proposes three modified conjugate Fletcher- Reeves (FR) algorithms including improved FR (IFR), the spectral-variant FR (SVFR) and modified FR (MFR) for first-order reliability method (FORM) for nonlinear reliability problems. An adaptive finite-step length is proposed to improve the efficiency and robustness of FORM formula using both steepest descent and conjugate search directions. These conjugate nonlinear maps for computing the search direction of FORM are adjusted based on sufficient decent condition to control instabilities of FORM formula. The efficiency and robustness of three proposed conjugate methods are compared with conjugate Hasofer and Lind-Rackwitz and Fiessler (CHL-RF), limited FR (LFR), HL-RF and finite-step length (FSL) through five nonlinear limit state functions. Numerical experiments illustrated that the modified FR versions of conjugate search direction are robust methods for highly nonlinear performance functions and the IFR is more efficient than the other reliability algorithms.

The employment of polynomial chaos expansion approach for modeling dissolved oxygen concentration in river

behrooz keshtegar,Salim Heddam,Hamidreza Hosseinabadi
Germany , Environmental Earth Sciences , Year : 2019 , Pages: 34-78, ISSN:1866-6280 Journal Paper

Abstract

This article proposes a novel methodology based on polynomial chaos expansions (PCE) for predicting dissolved oxygen (DO) concentration in rivers using four water quality variables as predictors: water temperature, turbidity, pH, and specific conductance. The proposed model is compared to the multilayer perceptron neural network (MLPNN), multilayer perceptron neural network optimized particle swarm optimization (MLPNN_PSO) and the standard multiple linear regression (MLR) with respect to their capabilities for predicting DO. The model results were evaluated using coefficient of correlation (R), Nash–Sutcliffe efficiency (NSE), root mean squared error (RMSE), and mean absolute error (MAE). Using data from more than three stations, operated by the United States Geological Survey (USGS), we demonstrated that that PCE model provides better predicting performance among the different models. Using the four water quality variables led to the best performances of PCE model for modelling DO at all three stations with R and NSE ranging from 0.931 to 0.970, and 0.866 to 0.938, respectively. MLPNN_PSO ranked next with R and NSE which ranged between 0.931 and 0.967, and 0.867 to 0.934, respectively. MLPNN ranked in the third place with R and NSE ranged between 0.921 and 0.966, and 0.849 to 0.931, for the three stations respectively. MLR models led to the worst results with R and NSE ranged between 0.907 and 0.961, and 0.822 to 0.922, respectively. According to the obtained results, PCE model is considered to be a good alternative to the direct measurement of DO concentration in river.

Shear strength of steel fiber-unconfined reinforced concrete beam simulation: Application of novel intelligent model

behrooz keshtegar,Mansour Bagheri,Zaher Mundher Yaseen
Netherlands , Composite Structures , Year : 2019 , Pages: 230-242, ISSN:0263-8223 Journal Paper

Abstract

The research promotes a new nonlinear model-based hybridized response surface method (RSM) and support vector regression (RSM-SVR) to predict shear capacity of steel fiber-reinforced concrete beams (SFRCB). Two approaches are integrated using RSM which is calibrated based on two input datasets; whereas, the SVR is calibrated based on all the predicted datasets generated by RSM. The high-cross correlation of the input dataset is provided using two nonlinear steps for modeling the SFRCB shear strength. The capacity of hybrid RSM-SVR model is validated with stand-alone intelligent models RSM, SVR and neural network (NN) in addition to eight empirical formulations. The dataset of 139 laboratory experimental tests of shear failure capacity belongs to SFRCB without stirrups, are obtained from the literature. The effects of fiber volume and the longitudinal steel ratio on the shear predictions of the normal and high-strange concrete reinforced by steel fiber are compared for the intelligent and empirical based approaches. The achieved results indicated the RSM-SVR model performed superior prediction over the comparable models. The improved agreement indexes using the RSM-SVR were improved with (0.35 and 1.9) over the empirical formulations and with (0.8, 1.2 and 3.5) over the three intelligent models of RSM, SVR and NN, respectively.

Modeling spatial distribution of plant species using autoregressive logistic regression method-based conjugate search direction

Hossein Piri Sahragard,behrooz keshtegar,محمد علی زارع چاهوکی,Zaher Yaseen
Netherlands , Plant Ecology , Year : 2019 , Pages: 267-287, ISSN:1385-0237 Journal Paper

Abstract

Modeling plant habitat range distributions is critical for monitoring and restoring species in their natural habitat. The classical logistic regression (LR) model for plant habitat distribution has several drawbacks such as neglecting the effects of the important variables and sensitivity to non-correlation variables. In this paper, an autoregressive logistic regression (ALR)-based conjugate gradient training approach was proposed to improve the drawbacks of LR in predicting the presence and absence of spatial habitat distribution based on input attributes including soil gypsum amount (gyps), lime content, soil available moisture (AM), soil electrical conductivity (EC), clay, and gravel amounts in Poshtkouh rangelands of Yazd Province, Iran. The conjugate gradient approach to calibrate logit model is extended by an iterative formulation using a limited scalar factor and adaptive step size. The predicted results of the classical LR and ALR were validated for nine plant habitats based on several comparative error statistics. The results illustrated that different coefficients were obtained for LR and ALR models but the proposed ALR performed better than the LR in estimating the occurrence probability of plant species.

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  •   پست الکترونیک:bkeshtegar@uoz.ac.ir