ORIGINAL_ARTICLE
Experimental Study of Applying Natural Zeolite as A Partial Alternative for Cement in Self-Compacting Concrete (SCC)
In recent years, with the increasing demand for modern and environmentally friendly materials, natural pozzolan s can be proved to be such a material and several researchers have focused their research efforts in using it as a partial substitute in the manufacture of concrete and mortar. This study concerns the fresh and hardened properties of self-compacted concrete (SCC) with natural zeolite (NZ). SCC mixtures were prepared by inclusion various amounts of NZ (0–20% by weight of cement) at different water/binder ratios. The fresh properties were investigated by slump flow, visual stability index, T50, V-funnel and L-box. The slump flow and compressive strength changes with hauling time were also considered. The hardened properties were tested for compressive strength, splitting tensile strength, ultrasonic pulse velocity (UPV), initial and final absorption. Results showed that with the inclusion of NZ, SCC can be successfully produced with satisfactory performance in flow ability, passing ability and viscosity. For all mixtures, flowability was lost with hauling time, although the rate of slump flow reduction was higher for mixes with higher amount of NZ. Regarding to hardened properties, the effect of NZ on the compressive and splitting tensile strength of SCC mixtures is generally related to its W/B ratio. Moreover, compressive strength enhancement was seen for mixes with slump flow higher than 550 mm at prolonged mixing time. The UPV measurement shows that the effect of NZ on the UPV values at a high compressive strength are negligible. Compared to control SCC, absorption characteristics of SCC containing NZ significantly decrease with increasing ages.
http://www.arce.ir/article_89277_403851cbb1a0f489e00b3c9a56d105ec.pdf
2019-07-01
1
18
10.30469/arce.2019.89277
Self-Compacting Concrete
Zeolite
Durability
Hardened Properties
Saeed
Bozorgmehr Nia
saeed.bozorgmehr@gmail.com
1
Ph.D. of Civil Engineering, Manager of Research and Development at Aptus Research and Production Company
LEAD_AUTHOR
Mehdi
Nemati Chari
nemati@yahoo.com
2
Department of Concrete Technology of Road, Housing and Urban Development Research Center
AUTHOR
Mohammad Reza
Adlparvar
adlparvar_m@yahoo.com
3
Associate Professor, Faculty of Civil Engineering, Qom University
AUTHOR
[1]-Dehwah, H. A. F., 2012, Mechanical properties of self-compacting concrete incorporating quarry dust powder, silica fume or fly ash, Construction and Building Materials, 26, 547-551.
1
[2]-Madandoust, R, Ranjbar, M. M. and Mousavi, S. Y., 2011, An investigation on the fresh properties of self-compacted lightweight concrete containing expanded polystyrene, Construction and Building Materials, 25, 321–331.
2
[3]-Madandoust, R, Mousavi, S. Y., 2012, Fresh and hardened properties of self-compacting concrete containing metakaolin, Construction and Building Materials, 35, 752–760.
3
[4]-Ahmadi, B. and Shekarchi, M., 2010, Use of natural zeolite as a supplementary cementitious material, Cement Concrete Composite, 32, 134-141.
4
[5]- Canpolat, F., Yılmaz, K., Kose, M. M., Sumer, M. and Yurdusev, M. A., 2004, Use of zeolite, coal bottom ash and fly ash as replacement materials in cement production. Cement and Concrete Resistance, 34, 731-735.
5
[6]-Poon, C. S., Lam, L., Kou, S. C. and Lin, Z. S., 1999, A study on the hydration rate of natural zeolite blended cement pastes, Construction and Building Materials, 13(8), 427–432.
6
[7]-Najimi, M., Sobhani, J., Ahmadi, B. and Shekarchi, M., 2012, An experimental study on durability properties of concrete containing zeolite as a highly reactive natural pozzolan, Construction and Building Materials, 35,1023-1033.
7
[8]-Feng, N., Feng, X., Hao, T. and Xing, F., 2002, Effect of ultrafine mineral powder on the charge passed of the concrete. Cement and Concrete Resistance, 32, 623-627.
8
[9]-Feng, N. and Hao, T., 1998, Mechanism of natural zeolite powder in preventing alkali-silica reaction in concrete, Advance Cement Resistance, 10(3), 101–108.
9
[10]-Chan, S. Y. N. and Ji, X., 1999, Comparative study of the initial surface absorption and chloride diffusion of high performance zeolite, silica fume and PFA concretes, Cement Concrete Composite, 21, 293-300.
10
[11]-Feng, N. Q., Li, G. Z. and Zang, X. W., 1990, High-strength and flowing concrete with a zeolite mineral admixture, Cement Concrete Aggregates, 12, 61-69.
11
[12]-Uysal, M. and Tanyildizi, H., 2012, Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network, Construction and Building Materials, 27, 404-414.
12
[13]-Cioffi, R., Colangelo, F., Caputo, D., Ligiori, A., 2006, Influence of high volumes of ultra-fine additions on self-compacting concrete, In: Malhotra VM, editor. Proceedings of the 8th Canmet/ACI international conference on fly ash, silica fume, slag, and natural pozzolans in concrete. Sorrento: Farmington Hills,118-135.
13
[14]-The European guidelines for self-compacting concrete, 2005, specification production and use. EFNARC, May.
14
[15]-Khayat, K. H., Bickley, J. and Lessard, M., 2000, Performance of self-consolidating concrete for casting basement and foundation walls, ACI Material Journal, 97, 374–380.
15
[16]-Ghafoori, N. and Barfield, M., 2010, Effects of hauling time on air-entrained self- consolidating concrete, ACI Material Journal, 107, 275–281.
16
[17]-Barfield, M. and Ghafoori, N., 2012, Air-entrained self-consolidating concrete: A study of admixture sources, Construction and Building Material, 26, 90-96.
17
[18]-Şahmaran, M., Özkan, N., Keskin, S. B., Uzal, B., Yaman, İ. Ö. and Erdem, T. K., 2008, Evaluation of natural zeolite as a viscosity-modifying agent for cement-based grouts. Cement and Concrete Resistance, 38, 930-937.
18
[19]-Felekoglu, B., Turkel, S. and Baradan, B., 2007, Effect of water/cement ratio on the fresh and hardened properties of self-compacting concrete, Building and Environment, 42, 1795–1802.
19
[20]-Bouzoubaa, N. and Lachemi, M., 2001, Self-compacting concrete incorporating high volumes of class F fly ash preliminary results, Cement and Concrete Resistance, 31, 413–420.
20
[21]-Collepardi, M., 1998, Admixtures used to enhance placing characteristics of concrete., Cement Concrete Composite, 20, 103–112.
21
[22]-Lowke, D. and Schiessl, P., 2005, Effect of mixing energy on fresh properties of SCC, In: Proceedings of the fourth international RILEM symposium on self-compacting concrete and second north american conference on the design and use of self-consolidating concrete, Chicago, USA; 2005.
22
[23]-Stieb, M., 1995, Mechanische verfahrenstechnik 1, Berlin: Springer, (second issue).
23
[24]-Sonebi, M., Grünewald, S. and Walraven, J., 2007, Filling ability and passing ability of self-consolidating concrete, ACI Material Journal, 104, 162–170.
24
[25]-Neville, A. M., 1995, Properties of concrete, England: Addison Wesley Longman.
25
[26]-Whitehurst, E. A., 1951, Soniscope tests concrete structures, Journal of American Concrete Institution, 47, 443–440.
26
[27]-Domone, P. L., 2007, A review of the hardened mechanical properties of self-compacting concrete. Cement and Concrete Composite, 29, 1–12.
27
[28]-CEB-FIB model code, 1993, Committee Euro-International du Beton. Thomas Telford, London.
28
[29]-ACI Committee 318, 2005, Building Code Requirements for Reinforced Concrete (ACI 318-05) and Commentary (318R-05), American Concrete Institute, Farmington Hills.
29
[31]-CEB-FIP, 1989, Diagnosis and assessment of concrete structures – ‘‘state of the art report’’. CEB Bull 192, 83–85.
30
[32]-Kosmatka, S. H., Kerkhoff, B., Panares´e, W. C., MacLeod, N. F., McGrath, R. J., 2002, Design and control of concrete mixtures, 7th ed. Ottawa, Ontario, Canada: Cement Association of Canada.
31
ORIGINAL_ARTICLE
Reliability Assessment of Dynamic Soil Properties
Dynamic soil properties are very important topic in geotechnical earthquake engineering due to associated with dynamic loading. Probabilistic analysis of dynamic soil properties is as effective tools to evaluate uncertainty of soil parameters. In this paper, Monte Carlo Simulation (MCS) is used for reliability assessment of dynamic soil properties. For this purpose, a famous model is selected for predicting normalized shear modulus reduction and damping ratio curves. The selected stochastic parameters are internal friction angle, dry and saturated unit weight of soil which is modeled using normal probability distribution functions. To assess the reliability of dynamic soil parameters a computer model is developed for generating input parameter uncertainties. The results show that the shear modulus and damping ratio have more uncertainty for middle range of shear strain. The sensitivity analysis’s results show that saturated unit weight is the most effective parameter in shear modulus and damping ratio.
http://www.arce.ir/article_89278_229ba5e3c9414ba2052611bedbb25ae4.pdf
2019-07-01
19
27
10.30469/arce.2019.89278
Damping Ratio
Shear Modulus
Monte Carlo simulation
Reliability assessment
Ahmad
Heydari
a.heydari@sutech.ac.ir
1
M.Sc. of Geotechnical Engineering, Department of Civil and Environmental Engineering, Shiraz University of Technology
LEAD_AUTHOR
Aslan
Jalilnejad
a1991jalilnejad@gmail.com
2
M.Sc. of Geotechnical Engineering, Department of Civil and Environmental Engineering, Shiraz University of Technology
AUTHOR
Maral
Nonahal
maralnonahal19912@gmail.com
3
B.Sc. of Architectural Engineering, Department of Architectural Engineering, Ardestan Branch, Islamic Azad University, Ardestan, Iran
AUTHOR
[1]- Prakash, S., 1981, Soil Dynamics, Mc. Graw Hill Book Co., New York, NY, Reprint, 1991, S.P. Foundation, Rolla, MO.
1
[2]- Kramer, S. L., 1996, Geotechnical Earthquake Engineering, Prentice Hall; 1996.
2
[3]- Ishibashi, I. and Zhang, X., 1993, Unified dynamic shear moduli and damping ratios of sand and clay, soils and foundations, 33, 1, 182-191.
3
[4]-Whitman, V. W., 1996, Organizing and evaluating uncertainty in geotechnical engineering, in: Uncertainty in Geologic Environment: from Theory to Practice, Proceedings of Uncertainty ’96, Geotechnical Special Publication, ASCE, 58(1), 1-38.
4
[5]-Griffiths, D. V., 2007, Fenton GA. Probabilistic Methods in Geotechnical Engineering, New York: Springer Wien.
5
[6]-Sowers, G. S., 1991, The human factor in failure, Civil Engineering, ASCE, 72–3.
6
[7]-Cornell, C. A., 1968, Engineering seismic risk analysis, Bulletin of the Seismological Society of America, 58, 1583–1606.
7
[8]-Ang, A. H. S., and Tang, W., 1984, Probability Concepts in Engineering Planning and Design, New York, USA: John Wiley and Sons.
8
[9]-Rosenblueth, E., 1975, Point estimates for probability moments, Proceedings, National Academy of Science, 72(10), 3812–3814.
9
[10]- Chameau, J. L., and Clough, G. W., 1983, Probabilistic pore pressure analysis for seismic loading, Journal of Geotechnical Engineering Division, ASCE, 109(GT4), 507–524.
10
[11]-Metropolis, N., and Ulam, S., 1949, The Monte Carlo method, Journal of the American Statistical Association, 44, 335–341.
11
[12]-Harr, M. E., 1987, Reliability-Based Design in Civil Engineering, McGraw-Hill Book Company.
12
ORIGINAL_ARTICLE
Clear-cut, Easy and Safe Air Purifying Technique (Poyrazmatic)
Indoor air quality is inevitably linked to ambient air quality. What controls ambient air quality also affects indoor air quality. The desert belts and their respective dust plumes on a global basis regulate ambient air quality. Each desert has its own exclusive extension zone and during the period of cyclonic depressions millions of tons of dust is injected into the atmosphere. These dust particles having 10- micron size or less can traverse long distances and are composed of clay minerals and embedded bacteria fungus and viruses. It has been shown that when inhaled it may adversely affect the respiratory system as well as triggering genes that are responsible from the production of specific proteins that results with migraine attacks. Basing on this work we have developed simple water based air purifier system that can effectively removes 90 % of particles in an hour and ultimate purification is reached within 120 minutes in one cubic meter experimental chamber. Of course, increase in air flux will inevitably shorten the time necessary for ultimate purification for a given environment. The air purifying system consists of an aquarium pump hose and air stone and simple 5 l water bottle. The basic principle behind the purification system based on the fact that during the rise of air bubble the air bubbles increases the surface area that is in contact with water and friction with water creates a vortex further assisting the transfer of any particles and bacteria fungus and virus to water phase. With this simple purification system the adverse effect of dust particles can effectively be removed from indoor environment. Renewing the water is the only thing required for the continuation of effective purification. The water is not wasted and can be used to irrigate the flowers lawns etc. Such systems also offer an ideal low cost pre-cleaning filtering that can be used to extent the operational life of expensive filtering systems.
http://www.arce.ir/article_89279_bd6b5bf4e8d6f15c257c3f78fa47cc86.pdf
2019-07-01
28
35
10.30469/arce.2019.89279
Air Quality
Bacteria
Dust
water filtration
Hadi
Habibazarfard
hhabibazarfard@gmail.com
1
M.Sc. of Environmental Engineering, Department of Environmental Engineering, Hacettepe University Ankara, Turkey
LEAD_AUTHOR
Ahmed Cemal
Saydan
acsaydam@gmail.com
2
Professor, Department of Environmental Engineering, Hacettepe University Ankara, Turkey
AUTHOR
[1]- Beeldens, A., 2006, An environmentally friendly solution for air purification and self- cleaning effect: theapplication of TiO2 as photocatalyst in concrete, In: Proceedings of transport research arena Europe, TRA, Göteborg, Sweden.
1
[2]- Wang, N., Yang, Y., Al-Deyab, S. S., El-Newehy, M., Yue, J., and Ding, B., 2015, Ultra-light 3D nanofibre-nets binary structured nylon 6-polyacrylonitrile membranes for efficient filtration of fine particulate matter, Journal of Material Chemistry, 3, 47, 23946–23954.
2
[3]- Clausen, G., and Alm, O., 2002, The impact of air pollution from used ventilation filters on human comfort and health, Proceedings of the 9th international conference on indoor air quality and climate, 4. Roterdam: Netherlands in-house publishing, 338-343.
3
[4]- Chapuis, Y., Kivana, D., Guy, C., and Kirchnerova, J., 2002, Photocatalytic oxidation of volatile organic compounds using fluorescent visible light, Journal of Air Waste Management Association, 52, 845-854
4
[5]-Wang, S., Ang, H. M., and Tade, M. O., 2007, Volatile organic compounds in indoor environment and photocatalytic oxidation: state of the art, Environment International, 33, 694-705.
5
[6]- Nath, R. K., Zain, M. F. M., and Jamil, M., 2016, An environment-friendly solution for indoor air purification by using renewable photocatalysts in concrete: A review, Renewer Sustainable Energy Revivion, 62, 1184–1194.
6
[7]- Jung, J. S., and Kim, J. G., 2017, An indoor air purification technology using a non-thermal plasma reactor with multiple-wire-to-wire type electrodes and a fiber air filter, Journal of Electrostatic, 86, 12–17.
7
[8]- Ren, H., Koshy, P., Chen, W. F., Qi, S., and Sorrell, C. C., 2017, Photocatalytic materials and technologies for air purification, Journal of Hazards Materials, 325, 340–366.
8
[9]- Doganay, H., Akcali, D., Goktas, T., Caglar, K., Erbas, D., Saydam, C., and Bolay., H. ,2009, African dust-laden atmospheric conditions activate the trigeminovascular system, Cephalalgia, 29, 10, 1059-1068.
9
ORIGINAL_ARTICLE
Optimum Design of Space Trusses using Water Cycle Algorithm
In this paper the water cycle algorithm (WCA) is utilized for sizing optimization of space trusses. Finding the optimum design of 3-D structures is a difficult task as the great number of design variables and design constraints are present in optimization of these type of structures. The efficiency of the WCA are demonstrated for truss structures subject to multiple loading conditions and constraints on member stresses and nodal displacement. Numerical results are compared with those reported in the literature where the obtained statistical results demonstrate the efficiency and robustness of WCA where it provided faster convergence rate as well as it found better global optimum solution compared to other metaheuristic algorithms.
http://www.arce.ir/article_89280_d7955c8ea66ac939dba07bf6dcb03fcf.pdf
2019-07-01
36
48
10.30469/arce.2019.89280
Water Cycle Algorithm
Weight Optimization
Space trusses
Global optimum
Masoud
Salar
masoud.salar@polimi.it
1
Ph.D. Candidate, Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy
LEAD_AUTHOR
Babak
Dizangian
b.dizangian@velayat.ac.ir
2
Assistant Professor, Department of Civil Engineering, Velayat University, Iran shahr, Iran
AUTHOR
Moterza
Mir
mortezaa.mir1986@gmail.com
3
M.Sc. of Structural Engineering, Department of Civil Engineering, Zahedan Branch, Islamic Azad University, Zahedan, Iran
AUTHOR
[1]- Ling-xi, Q., Wanxie, Z., Yunkang, S., and Jintong, Z., 1982, Efficient optimum design of structures—program DDDU, Computer Methods in Applied Mechanics and Engineering, 30(2), 209-24.
1
[2]- Templeman, A. B., 1988, Discrete optimum structural design, Computers and Structures, 30(3), 511-518.
2
[3]- Hall, S. K., Cameron, G. E., and Grierson, D. E., 1989, Least-weight design of steel frameworks accounting for P-Δ effects, Journal of Structural Engineering, 115(6), 1463-1475.
3
[4]- Adeli, H., and Park, H. S., 1995, A neural dynamics model for structural optimization—theory, Computers and structures, 57(3), 383-390.
4
[5]-Tzan, S. R., and Pantelides, C. P., 1996, Annealing strategy for optimal structural design, Journal of Structural Engineering, 122(7), 815-827.
5
[6]- Deb, K., 2012, Optimization for engineering design: Algorithms and examples, PHI Learning Pvt. Ltd.
6
[7]- Rao, S. S., and Rao, S. S., 2009, Engineering optimization: theory and practice, John Wiley & Sons.
7
[8]-Nanakorn, P., and Meesomklin, K., 2001, An adaptive penalty function in genetic algorithms for structural design optimization, Computers and Structures, 79(29), 2527-2539.
8
[9]- Sivaraj, R., and Ravichandran, T., 2011, A review of selection methods in genetic algorithm, International Journal ofEngineering Science and Technology, 3, 3792-3797.
9
[10]- Salar, M., Ghasemi, M. R. and Dizangian, B. A., 2015, fast GA-based method for solving truss optimization problems, International Journal of Optimization in Civil Engineering, 6(1), 101-114.
10
[11]- Das, S., and Suganthan, P. N., 2011, Differential evolution: A survey of the state-of-the-art, Trans Evol Comput. IEEE, 15, 4-31.
11
[12]- Simon, D., 2008, Biogeography-based optimization, Trans Evol Comput, IEEE, 12, 702-713.
12
[13]- Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P., 1983, Optimization by simulated annealing, Science, 220 (4598), 671-680.
13
[14]- Kaveh, A. and Talatahari, S., 2010, Optimal design of skeletal structures via the charged system search algorithm, Structure Multidisciplinary Optimization, 41(6), 893-911.
14
[15]- Nouhi, B., Talatahari, S., Kheiri, H., and Cattani, C., 2013, Chaotic charged system search with a feasible-based method for constraint optimization problems, Mathematical Problem Engineering, Article ID 391765, 8 pages.
15
[16]- Kaveh, A., and Mahdavai, V. R., 2014, Colliding bodies optimization: A novel meta-heuristic method, Computer Structure, 139, 18-27.
16
[17]- Eberhart, R. C., and Kennedy, J. A., 1995, new optimizer using particle swarm theory, Proceedings ofthe Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan.
17
[18]- Geem, Z. W., 2009, Harmony Search Algorithms for Structural Design, Springer Verlag.
18
[19]- Karaboga, D., Gorkemli, B., Ozturk, C., and Karaboga, N. A., 2014, comprehensive survey: artificial bee colony (ABC) algorithm and applications, Artificial Intelligence Review, 42, 21-57.
19
[20]- Yang, X. S., and Deb, S., 2014, Cuckoo search: recent advances and applications, Neural ComputingApplications, 24, 169-174.
20
[21]- Yang, X. S., 2010, Firefly algorithm, stochastic test functions and design optimization, International Journal ofBio-inspired Computing, 2(2), 78-84.
21
[22]- Gandomi, A. H., and Alavi, A. H., 2012, Krill herd: a new bio-inspired optimization algorithm, Communication Nonlinear Science andNumerical Simulation, 17(12), 4831-4845.
22
[23]- Yang, X. S., 2010, A new metaheuristic bat-inspired algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds JR Gonzalez et al), Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65-74.
23
[24]- Eskandar, H., Sadollah, A., Bahreininejad, A., and Hamdi, M., 2012, Water cycle algorithm -A novel metaheuristic optimization method for solving constrained engineering optimization problems, Computing Structure, 110-111,151-166.
24
[25]- Eskandar, H., Sadollah, A., and Bahreininejad, A., 2013, Weight optimization of truss structures using water cycle algorithm, Iran University of Science and Technology, 3(1), 115-129.
25
[26]- Lee, K. S., and Geem, Z. W., 2004, A new structural optimization method based on the harmony search algorithm, Computing Structure, 82, 781–798.
26
[27]- Sheu, C. Y., and Schmit, L. A., 1972, Minimum weight design of elastic redundant trusses under multiple static loading conditions, AIAA Journal, 10(2), 155-162.
27
[28]- Khan, M. R., Willmert, K. D., and Thornton, W. A., 1979, An optimality criterion method for large-scale structures, AIAA journal, 17(7), 753-761.
28
[29]- Lee, K. S., and Geem, Z. W., 2004, A new structural optimization method based on the harmony search algorithm, Computers and structures, 82(9),781-798.
29
[30]- Rizzi, P., 1976, Optimization of multi-constrained structures based on optimality criteria, InProc. AIAA/ASME/SAE 17th Structures, Structural Dynamics and Materials Conference (pp. 448-462).
30
[31]- Saka, M. P., Optimum design of pin-jointed steel structures with practical applications, Journal of Structural Engineering,116(10), 2599-2620.
31
[32]- Venkayya, V. B., 1971, Design of optimum structures, Computers and Structures, 1;1(1-2), 265-309.
32
[33]- Xicheng, W., and Guixu, M., 1992, A parallel iterative algorithm for structural optimization, Computer Methods in Applied Mechanics and Engineering, 96(1), 25-32.
33
[34]- Chao, N. H., Fenves, S. J., Westerberg, A. W., 1981, Application of a reduced quadratic programming technique to optimal structural design. Carnegie-Mellon University Pittsburgh PA.
34
[35]- Dizangian, B., and Ghasemi, M. R., 2015, Ranked-based sensitivity analysis for size optimization of structures, Journal of Mechanical Design, 137(12), 121-142.
35
[36]-Adeli, H., and Kamal, O., 1986, Efficient optimization of space trusses, Computers and Structures, 24(3), 501-511.
36
ORIGINAL_ARTICLE
The Karkheh River Streamflow Forecast based on the Modelling of Time Series
Autoregressive integrated moving average (ARIMA) models are appropriate for the annual streamflows (annual peak and maximum and also mean discharges) of the Karkheh River at Jelogir Majin station of Karkheh river basin in Khuzestan province in western Iran, through the Box- Jenkins time series modelling approach. In this research among the suggested models interpreted from ACF and PACF, ARIMA(4,1,1) for all annual streamflows satisfied all tests and showed the best performance. The model forecasted streamflow for ten leading years showed the ability of the model to forecast statistical properties of the streamflow in short time in future. The SAS and SPSS softwares were used to implement of the models.
http://www.arce.ir/article_89282_882b7fdcead9e68f6b111c7738cb9185.pdf
2019-07-01
49
57
10.30469/arce.2019.89282
Hydrologic Time Series
Box-Jenkins Approach
Arima Model
Karkheh river
Karim
Hamidi Machekposhti
karim.hamidi@srbiau.ac.ir
1
Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Hossein
Sedghi
h.sedghi1320@gmail.com
2
Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
LEAD_AUTHOR
Abdolrasoul
Telvari
telvari@gmail.com
3
Department of Civil Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
AUTHOR
Hossein
Babazadeh
h_babazadeh@srbiau.ac.ir
4
Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
[1]- Box, G. E. P. and Jenkins, G. M., 1976, Time Series Analysis, Forecasting and Control, Holden Day. San Francisco. California.
1
[2]- Shakeel, A. M., Idrees, A. M., Naeem, H. M., and Sarwar, B. M., 1993, Time Series Modelling of Annual Maximum Flow of River Indus at Sukkur. Pakistan, Journal of Agricultural Sciences, 30(1), 36-38.
2
[3]- Srikanthan, R., McMohan ,T. A. and Irish, J. L., 1983, Time series analysis of annualflows of Australian streams, Journal of Hydrology, 1, 12-21.
3
[4]- Stojković, M., Prohaska, S. and Plavšić, J., 2015, Stochastic Structure of Annual discharges of large European Rivers, Journal of Hydrology and Hydromechanics, 63(1), 63–70.
4
[5]- Nigam, R., Nigam, S., and Mittal, S. K., 2014, The river runoff forecast based on the modeling of time series, Russian Meteorology and Hydrology, 39(11), 750-761.
5
[6]- Tian, P., Zhao, G. J., Li, J., and Tian, K., 2011, Extreme Value Analysis of Stream flow Time Series in Poyang Lake Basin, China, Water Science and Engineering, 4(2), 121-132.
6
[7]- Shahjahan, M. M., and Chowdhury, J. U., 2013, Generation of 10-Day flow of the Brahmaputra River using a time series model, Hydrology Research, 44(6), 1071-1083.
7
[8]- Hamidi machekposhti, K., Sedghi, H., Telvari, A., and Babazadeh, H., 2017, Forecasting by Stochastic Models to Inflow of Karkheh Dam at Iran, Civil Engineering Journal, 3(5): 340-350.
8
[9]- McLeod, A. E., Hipel, K. W. and Lennox, W. C., 1977, Advances in Box- Jenkins modeling: 2- Applications, Water Resources Research, 13(3), 577-586.
9
[10]- Modarres, R., and Eslamian, S. S., 2006, Streamflows time series modeling of Zayandehrud River, Iranian Journal of Science & Technology, Transaction B, Engineering, 30(B4): 567-570.
10
ORIGINAL_ARTICLE
Comparing Semi Active Control of Bridge via Variable Stiffness and Damping Systems and MR Dampers
Semi active devices can be used to control the responses of a continuous bridge during earthquake excitation. They are capable of offering the adaptability of active devices and stability and reliability of passive devices. This study proposes two semi-active control method protection of bridge using variable stiffness and damping systems and MR dampers. The first method is variable stiffness and damping with eight different (on-off) control schemes which is optimized with genetic algorithm. Genetic algorithm is used to define the parameters of this method. In the second method, an intelligent controller using fuzzy control of MR damper is developed. In particular, a fuzzy logic controller is designed to determine the command voltage of MR dampers. In order to evaluate the effectiveness of the proposed method, the performances of the proposed controllers are compared in numerical study. Results reveal that the developed controllers can effectively control both displacement and acceleration responses of the continuous bridge.
http://www.arce.ir/article_89283_83520f7b5f096a8835e12c39cb231423.pdf
2019-07-01
58
71
10.30469/arce.2019.89283
Semi-active devices
MR damper
Variable stiffness
Variable damping
GA algorithm
Fuzzy logic control
Fereydoon
Amini
famini@iust.ac.ir
1
Professor, College of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
LEAD_AUTHOR
Sara
Zalaghi
sarazalaghi2017@gmail.com
2
Research Assistant, College of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
AUTHOR
[1]-Housner, G. W., Bergman, L. A., Caughey, T. K., Chassiakos, A. G., Claus, R. O. and Masri, S. F., 1997, Structural control: past, present, and future, Journal of Engineering Mechanics,123(9), 897-971.
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[2]- Oh, S. K., Yoon, Y. H., Krishna, A. B., 2007, A study on the performance characteristics of variable valve for reverse continuous damper, World Academic Science, Engineering Technology, 32, 123–128.
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[3]- liu, Y., Matsuhisa, H., Utsuno, H., 2008, Semi-active vibration isolation system with variable stiffness and damping control, Journal of sound and vibration, 313, 16-28.
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[4]- Dyke, S. J., Spencer, B. F., Sain, M. K., Carlson, J. D., 1996, Modelling and control of magnetorheogical dampers for seismic response reduction, Smart Material Structure, 5, 565-575.
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[5]- Sodeyama, H., Sunakoda, K., Suzuki, K., Carlson, J. D., Spencer, Jr. B. F., 2001, Development of large capacity semi active vibration control device using magnetorheological fluid, Seismic Engineering ASME PVP, 428(2), 109-114.
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[6]-Yi, F., Dyke, S. J., Caicedo, J. M., Carlson, J. D., 2001, experimental verification of multinput seismic control strategies for smart dampers, Journal of Engineering Mechanics, 127(11), 1152-1164.
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[7]- liu, Y., Matsuhisa, H., Utsuno, H. and Park, J. G., 2005, Vibration isolation by a variable Stiffness and Damping System, International Journal Society of Mechanical Engineering, 48(2), 305-310.
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[8]- Marano, G. C., Quaranta, G., and Monti, G., 2011, Modified genetic algorithm for the dynamic identification of structural systems using incomplete measurements, Computing- Aided Civil Infrastructure Engineering, 26(2), 92-110.
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[9]- Lee, C. C., 1995, Fuzzy logic in control system: fuzzy logic controller part I and part II., IEEE Transaction System Man, and Cybernetics, 20, 404-418.
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[10]- Cronje, J. M, Stephan, P., and Theron, N. J., 2005, Development of a variable stiffness and damping runnable vibration isolator, Journal Vibrate control, 11(3), 381-396.
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[11]- Gonca, V., and Shavab, J., 2010, Design of elastomeric shock absorbers with variable stiffness, Journal Vibroengineering, 12(3), 347-354.
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[12]- Yoshida, O., and Dyke, S. J., Seismic control of a nonlinear benchmark building using smart dampers, Journal of Engineering Mechanics, 130(4), 386-392.
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[13]- Park, K. S., Koh, M. H., and Seo, C. W., 2004, Independent model space fuzzy control of earthquake-excited structures, Engineering Structures, 26, 279-289.
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