New graph products for configuration processing 2 2 For the analysis of structures, the first step consists of configuration processing followed by data generation. This step is the most time consuming part of the analysis for large-scale structures. In this paper new graph products called triangular and circular graph products are developed for the formation of the space structures. The graph products are extensively used in graph theory and combinatorial optimization, however, the triangular and circular products defined in this paper are more suitable for the formation of practical space structural models which can not be generated easily by the previous products. The new products are employed for the configuration processing of space structures that are of triangular or a combination of triangular and rectangular shapes, and also in circular shapes as domes and some other space structural models. Cut out products are other new types of graph products which are defined to eliminate all of the connected elements to the considered node to configure the model or grid with some vacant panels inside of the model. The application of the presented graph products can be extended to the formation of finite element models. 67 76 2012/03/11 1390/12/21 2013/06/10 1392/3/20 A. Kaveh A. Kaveh Iran University of Science and Technology Iran alikaveh@iust.ac.ir S. Beheshti S. Beheshti Iran University of Science and Technology Iran beheshtisepehr@gmail.com Triangular and circular graph products Configuration processing Generators Space structures Nooshin H. Algebraic representation and processing of structural configurations, Computers and Structures, 1975, Vol. 5, pp. 119–130.##Nooshin H. Formex Configuration Processing in Structural Engineering, Elsevier Applied Science Publishers, London, 1984.##Nooshin H, Disney P, Yamamoto C. Formian, U.K.: Multi-Science Publishers. J. Rebielak, 1995.##Nooshin H, and Disney P. Formex configuration Processing I, II, III, International Journal of Space Structures, 2000 Vol. 15, pp. 1–52; 2001, Vol. 16, pp. 1–56; 2002, Vol. 17, pp. 1–50.##Behravesh A, Kaveh A, Nani M, Sabet S. A set theoretical approach to configuration processing, Computers and Structures, 1988, Vol. 30, pp. 1293–1302.##Kaveh A. A graph theoretical approach to configuration processing, Computers and Structures, 1993, Vol. 48, pp. 357–363.##Kaveh A. Structural Mechanics: Graph and Matrix Methods, Research Studies Press, 3rd edition, Somerset, UK, 2004##Kaveh A, Koohestani K. Graph products for configuration processing of space structures, Computers and Structures, 2008, Vol. 86, pp. 1219-1236.##Kaveh A, Nouri M. Weighted graph products for configuration,##Processing of Planar and Space Structures, International Journal of Space Structures, 2009, Vol. 24, pp. 13-26.##Thacker WC. A brief review of techniques for generating irregular computational grids, International Journal for Numerical Methods in Engineering, 1980, Vol. 15, pp. 1335–1341.##Thomson JF, Warsi ZUA, Hastin CW. Numerical Grid Generation, Foundations and Applications, Elsevier, Amsterdam, 1985.##Vladimir D. Liseikin, Grid Generation Methods, Series: Scientific Computation, Springer Verlag, 1999.##Kaveh A, Rahami H. Block diagonalization of adjacency and Laplacian matrices for graph products; Applications in structural mechanics, International Journal for Numerical Methods in Engineering, 2006, Vol. 68, pp. 33–63.##Kaveh A, Rahami H. A unified method for eigen-decomposition of graph products, Communications in Numerical Methods in Engineering, 2005, Vol. 21, pp. 377–388.##Imrich W, Klavzar S. Product Graphs; Structure and Recognition, John Wiley, NY, 2000.##Kaveh A. Optimal Structural Analysis, John Wiley, 2nd edition, Somerset, UK, 2006.##Kaveh A, Beheshti S. Weighted triangular and circular graph products for configuration processing, Periodica Polytechnica-Civil Engineering, 2012, Vol. 56, pp. 63-71.##Kaveh A, Alinejad B. Graph products with specified domains for configuration processing and formation of the adjacency matrices, Engineering Computations, 2010, Vol. 27, pp. 205-224.##Kaveh A. Optimal Analysis of Structures by Concepts of Symmetry and Regularity, Springer Verlag, GmbH, Wien-New York, http://www.springer.com/materials/mechanics/book/978-3-7091-1564-0, to appear in April 2013.## ##

Size optimization of nonlinear scallop domes by an enhanced particle swarm algorithm 2 2 The present paper focuses on size optimization of scallop domes subjected to static loading. As this type of space structures includes a large number of the structural elements, optimum design of such structures results in efficient structural configurations. In this paper, an efficient optimization algorithm is proposed by hybridizing particle swarm optimization (PSO) algorithm and cellular automata (CA) computational strategy, denoted as enhanced particle swarm optimization (EPSO) algorithm. In the EPSO, the particles are distributed on a small dimensioned grid and the artificial evolution is evolved by a new velocity updating equation. In the new equation, the difference between the design variable vector of each site and an average vector of its neighboring sites is added to the basic velocity updating equation. This new term decreases the probability of premature convergence and therefore increases the chance of finding the global optimum or near global optima. The optimization task is achieved by taking into account linear and nonlinear responses of the structure. In the optimization process considering nonlinear behaviour, the geometrical and material nonlinearity effects are included. The numerical results demonstrate that the optimization process considering nonlinear behaviour results in more efficient structures compared with the optimization process considering linear behaviour. . 77 89 2012/03/112012/06/16 1391/3/27 2013/06/102013/06/15 1392/3/25 R. Kamyab Moghadas R. Kamyab Moghadas Shahid Bahonar University of Kerman Iran rkamyab@uk.ac.ir E. Salajegheh E. Salajegheh Shahid Bahonar University of Kerman Iran eysasala@uk.ac.ir Optimization Scallop domes Particle swarm optimization Cellular automata Nonlinear behavior Static loading. [1] Nooshin H, Tomatsuri H, Fujimoto, M. Scallop domes. IASS97 Symposium on Shell & Spatial Structures: Design, Performance & Economics, Singapore, 1997.##[2] Gholizadeh S, Barzegar A. Shape optimization of structures for frequency constraints by sequential harmony search algorithm, Engineering Optimization, 2012, DOI: 10.1080/0305215X.2012.704028.##[3] Gholizadeh S, Salajegheh E, Torkzadeh P. Structural optimization with frequency constraints by genetic algorithm using wavelet radial basis function neural network, Journal of Sound and Vibration, 2008; 312: 316-331.##[4] Kaveh A, Farhmand Azar B, Talatahari S. Ant colony optimization for design of space trusses, International Journal of Space Structures, 2008; 23: 167-181.##[5] Gholizadeh S, Fattahi F. Design optimization of tall steel buildings by a modified particle swarm algorithm, The Structural Design of Tall and Special Buildings, 2012, DOI: 10.1002/tal.1042.##[6] Kaveh A, Talatahari S. Size optimization of space trusses using Big Bang-Big Crunch algorithm, Computers and Structures, 2009; 87: 1129–1140.##[7] Kaveh A, Talatahari S. A charged system search with a fly boundary method for discrete optimum design of truss structures, Asian Journal of Civil Engineering, 2010; 11: 277–293.##[8] Saka MP, Ulker M. Optimum design of geometrically nonlinear space trusses, Computers & Structures, 1991; 41: 1387-1396.##[9] Saka MP, Kameshki ES. Optimum design of nonlinear elastic framed domes, Advances in Engineering Software, 1998; 29: 519-528.##[10] McKenna F, Fenves G. The Opensees Command Language Manual, 1st ed., 2001.##[11] Eberhart RC, Kennedy J. A new optimizer using particle swarm theory, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, pp. 39-43.##[12] Li LJ, Huang ZB, Liu F, Wu QH. A heuristic particle swarm optimizer for optimization of pin connected structures, Computers and Structures, 2007; 85: 340–349.##[13] Kaveh A, Talatahari S. Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures, Computers and Structures, 2009; 87: 267–283.##[14] Gholizadeh S, Salajegheh E. Optimal design of structures for time history loading by swarm intelligence and an advanced metamodel, Computer Methods in Applied Mechanics and Engineering, 2009; 198: 2936–2949.##[15] Erdal F, Doğan E, Saka MP. Optimum design of cellular beams using harmony search and particle swarm optimizers, Journal of Constructional Steel Research, 2011; 67: 237–247.##[16] Gholizadeh S, Seyedpoor SM. Shape optimization of arch dams by metaheuristics and neural networks for frequency constraints, Scientia Iranica, 2011; 18: 1020-1027.##[17] Von Neumann J. Theory of self-reproducing automata, A. W. Burks, (Eds.), University of Illinois Press, Champaign, Ill, 1966.##[18] Gholizadeh S. Optimum design of structures by an improved particle swarm algorithm, Asian Journal of Civil Engineering, 2010; 11: 779–796.##[19] Angeline P. Evolutionary optimization versus particle swarm optimization: philosophy and performance difference. Proceeding of the Evolutionary Programming Conference, San Diego, USA; 1998.##[20] The Language of Technical Computing. MATLAB. Math Works Inc, 2006.##[21] Federal Emergency Management Agency. NEHRP guidelines for the seismic rehabilitation of buildings, Rep. FEMA 273 (Guidelines) and 274 (Commentary), Washinton, DC, 1997.##[22] Crisfield MA. Non-Linear Finite Element Analysis of Solids and Structures, John Wiley & Sons, Volume 1: Essentials, Chichester, 1991.##[23] AISC: American Institute of Steel Construction, Manual of steel construction-allowable stress design, 9th ed. Chicago, IL; 1989.##[24] Biondini F, Bontempi F, Frangopol DM, Malerba PG. Cellular automata approach to durability analysis of concrete structures in aggressive environments, Journal of Structural Engineering, 2004; 130: 1724–1737.##[25] Gholizadeh S, Salajegheh E. Optimal seismic design of steel structures by an efficient soft computing based algorithm, Journal of Constructional Steel Research, 2010; 66: 85–95.##[26] Canyurt OE, Hajela P. A cellular framework for structural analysis and optimization, Computer Methods in Applied Mechanics and Engineering, 2005; 194: 3516–3534.##[27] Rajasekaran S. Optimization of large scale three dimensional reticulated structures using cellular genetics and neural networks, International Journal of Space Structures, 2001; 16: 315–324.##[28] Gholizadeh S, Salajegheh E. A Cellular Genetic Algorithm for Structural Optimisation, In B.H.V. Topping, J.M. Adam, F.J. Pallares, R. Bru, M.L. Romero, (Ed), Proceedings of the Tenth International Conference on Computational Structures Technology, DATE, Stirlingshire: Civil-Comp Press, 1-14, 2010.##[29] Gholizadeh S. Optimum Design of Structures for Earthquake Loading by a Cellular Evolutionary Algorithm and Neural Networks, In V. Plevris, C.C. Mitropoulou, N.D. Lagaros, (Editors), “Structural Seismic Design Optimization and Earthquake Engineering: Formulations and Applications”, IGI Global, USA, Chapter 12, 306-322, 2012.## ##

Optimization of high-performance concrete structures by variable neighborhood search 2 2 This paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. Three strategies have been applied to discrete optimization of reinforced concrete beams: Variable Neighborhood Descent (VND), Reduced Neighborhood Search (RNS) and Basic Variable Neighborhood Search (BVNS). The problem includes 14 variables: two geometrical one material type one mix design and 10 variables for the reinforcement setups. The algorithms are applied to two objective functions: the economic cost and the embedded CO2 emissions. Firstly, this paper presents the application of these three different optimization strategies, which are evaluated by fitting the set of solutions obtained to a three-parameter Weibull distribution function. The Variable Neighborhood Descent with Threshold Accepting acceptance strategy algorithm (VND-TA) results as the most reliable method. Finally, the study presents a parametric study of the span length from 10 to 20 m in which it can be concluded that economic and ecological beams show a good parabolic correlation with the span length. 90 99 2012/03/112012/06/162012/01/11 1390/10/21 2013/06/102013/06/152013/06/17 1392/3/27 C. Torres-Machi C. Torres-Machi Universitat Politecnica de Valencia Spain cristorma@upv.es V. Yepes V. Yepes Universitat Politecnica de Valencia Spain vyepesp@upv.es J. Alcala J. Alcala Universitat Politecnica de Valencia Spain jualgon@upv.es E. Pellicer E. Pellicer Universitat Politecnica de Valencia Spain pellicer@upv.es Structural optimization Reinforced concrete Sustainable construction CO2 emission High-performance concrete Heuristics. [1] Gartner, E.: 2004, Industrially interesting approaches to “low-CO2” cements, Cem. Concr. Res., 34(9), 1489-1498.##[2] Malhotra, V.M.: 2000, Role of supplementary cementing materials in reducing greenhouse gas emissions. In: O.E. Gjorv, K. Sakai (eds.), Concrete technology for a sustainable development in the 21st century, pp. 226–235, E&FN Spon, London.##[3] Juenger, M.C.G., Winnefeld, F., Provis, J.L. and Ideker, J.H.: 2011, Advances in alternative cementitious binders, Cem. Concr. Res., 41(12), 1232-1243.##[4] Hardjito, D., Wallah, S.E., Sumajouw, D.M.J. and Rangan, B.V.: 2004, On the development of fly ash-based geopolymer concrete, ACI Mater. J., 101(6), 467-472.##[5] Meyer, C.: 2009, The greening of the concrete industry, Cem. Concr. Compos., 31(8), 601-605.##[6] Ashour, S.A.: 2000, Effect of compressive strength and tensile reinforcement ratio on ﬂexural behavior of high-strength concrete beams, Eng. Struct., 22(5), 413-423.##[7] Chen, B. and Liu, J.: 2004, Effect of aggregate on the fracture behavior of high strength concrete, Constr. Build. Mater., 18(8), 585-590.##[8] Cheng, A. S., Huang, Y.L., Huang, C.H. and Yen, T.: 2011, Effects of fly ash particle sizes on the compressive strength and fracture toughness of high performance concrete, Adv. Mat. Res., 284-286, 984-988.##[9] Ding, Y., Zhang, Y. and Thomas, A.: 2009, The investigation on strength and flexural toughness of fiber cocktail reinforced self-compacting high performance concrete, Constr. Build. Mater., 23(1), 448-452.##[10] Do, M.T., Chaallal, O. and Aitcin, P.C.: 1993, Fatigue behavior of high-performance concrete. J. Mater. Civ. Eng., 5(1), 96-111.##[11] Donza, H., Cabrera, O. and Irassar, E.F.: 2002, High-strength concrete with different fine aggregate, Cem. Concr. Res., 32 (11), 1755-1761.##[12] Duval, R. and Kadri, E.H.: 1998, Influence of silica fume on the workability and the compressive strength of high-performance concretes, Cem. Concr. Res., 8(4), 533-547.##[13] Hoe, K.W. and Ramli, M.: 2010, Rational mix design approach for high strength concrete using sand with very high fineness modulus, American Journal of Applied Sciences, 7(12), 1562-1568.##[14] Khatri, R.P., Sirivivatnanon, V. and Gross, W.: 1995, Effect of different supplementary cementitious materials on mechanical properties of high performance concrete, Cem. Concr. Res., 25(1), 209-220.##[15] Ko, M.Y., Kim, S.W. and Kim, J.K.: 2001, Experimental study on the plastic rotation capacity of reinforced high strength concrete beams, Materials and Structures, 34(239), 302-311.##[16] Kodur, V.K.R., Cheng, F.P., Wang, T.-C. and Sultan, M.A.: 2003, Effect of strength and fiber reinforcement on fire resistance of high-strength concrete columns, ASCE J. Struct. Eng., 129(2), 253-259.##[17] Kumar, P.S., Mannan, M.A., Kurian, V.J. and Achuytha, H.: 2003, Investigation on the flexural behavior of high-performance reinforced concrete beams using sandstone aggregates, Build. Environ., 42(7), 2622-2629.##[18] Li, J. and Yao, Y.: 2001, A study on creep and drying shrinkage of high performance concrete, Cem. Concr. Res., 31(8), 1203-1206.##[19] Lim, C.-H., Yoon, Y.-S. and Kim, J.-H.: 2004, Genetic algorithm in mix proportioning of high-performance concrete, Cem. Concr. Res., 34(3), 409-420.##[20] Mazloom, M., Ramezanianpour, A.A. and Brooks, J.J.: 2004, Effect of silica fume on mechanical properties of high-strength concrete, Cem. Concr. Compos., 26(4), 347-357.##[21] Meddah, M.S., Suzuki, M. and Sato, R.: 2011, Influence of a combination of expansive and shrinkage-reducing admixture on autogenous deformation and self-stress of silica fume high-performance concrete, Constr. Build. Mater., 25(1), 239-250.##[22] Oztekin, E., Pul, S. and Husem, M.: 2003, Determination of rectangular stress block parameters for high performance concrete, Eng. Struct., 25(3), 371-376.##[23] Özturan, T. and Çecçen, C.: 2003, Effect of coarse aggregate type on mechanical properties of concretes with different strengths, Cem. Concr. Res., 27(2), 165-170.##[24] Persson, B.: 2000, Correlating laboratory and field tests of creep in high-performance concrete, Cem. Concr. Res., 31(3), 389-395.##[25] Song, P.S. and Hwang, S.: 2004, Mechanical properties of high-strength steel fiber-reinforced concrete, Constr. Build. Mater., 18(9), 669-673.##[26] Wu, K.R., Chen, B., Yao, W. and Zhang, D.: 2001, Effect of coarse aggregate type on mechanical properties of high-performance concrete, Cem. Concr. Res., 31(10), 1421-1425.##[27] Zhou, F.P., Lydon, F.D. and Barr, B.I.G.: 1995, Effect of coarse aggregate on elastic modulus and compressive strength of high performance concrete, Cem. Concr. Res., 25(1), 177-186.##[28] Hernández, S. and Fontan, A.: 2002, Practical applications of design optimization, WIT Press, Southampton, U.K.##[29] Fletcher, R.: 2001, Practical methods of optimization, Chichester, Wiley, U.K.##[30] Sarma, K. C. and Adeli, H.: 1998, Cost optimization of concrete structures, J. Struct. Eng., 124(5), 570-578.##[31] Jenkins, W.M.: 1992, Plane frame optimum design environment based on genetic algorithm, ASCE J. Struct. Eng., 118(11), 3103-3112.##[32] Rajeev, S. and Krishnamoorthy, C.S.: 1992, Discrete optimization of structures using genetic algorithms, ASCE J. Struct. Eng., 118(5), 1233-1250.##[33] Coello, C.A., Christiansen, A.D. and Santos, F.: 1997, A simple genetic algorithm for the design of reinforced concrete beams, Eng. Comput., 13(4), 185-196.##[34] Leite, J.P.B. and Topping, B.H.V.: 1998, Improved genetic operators for structural optimization, Adv. Eng. 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An iterative process for pushover analysis of double unsymmetric-plan low- and medium-rise buildings under bi-directional excitation 2 2 Double- unsymmetric-plan medium-rise buildings subjected to bi-directional seismic excitation are complex structures where higher-mode effects in plan and elevation are important in estimating the seismic responses using nonlinear static or pushover analysis. Considering two horizontal components of the ground motions makes the problem more intricate. This paper presents a method for nonlinear static analysis of double unsymmetric-plan low- and medium-rise buildings subjected to the two horizontal components of ground motions. To consider bi-directional seismic excitation in pushover analyses, the proposed method utilizes an iterative process until displacements at a control node (centre of mass at the roof level) progressively reach the predefined target displacements in both horizontal directions. In the case of medium-rise buildings, continuous implementation of modal pushover analyses is used to take higher-mode effects into account. To illustrate the applicability and to appraise the accuracy of the proposed method, it is applied to the 4- and 10-storey torsionally-stiff and torsionally-flexible buildings as representative of low- and medium-rise buildings, respectively. For the purpose of comparison, modal pushover analysis (MPA) is also implemented considering the two horizontal components of the ground motions. The results indicate that the proposed method and the MPA procedure can compute the seismic demands of double unsymmetric-plan low- and medium-rise buildings with reasonable accuracy however, seismic responses resulting from the proposed method deteriorate at the flexible edge of the torsionally-flexible buildings 100 114 2012/03/112012/06/162012/01/112011/06/15 1390/3/25 2013/06/102013/06/152013/06/172013/06/17 1392/3/27 M. Poursha M. Poursha Sahand University of Technology Iran poursha@sut.ac.ir An iterative process Pushover analysis Modal pushover analysis (MPA) Bi-directional excitation Low- and mediumrise buildings Higher-mode effects Double unsymmetric-plan buildings AISC-ASD, 1989. Allowable Stress Design and Plastic Design Specification for Structural Steel Buildings, American Institute of Steel Construction: Chicago, IL.##Applied Technology Council, ATC-40. Seismic evaluation and retrofit of concrete buildings. vol. 1_2. Redwood City (California); 1996.##Aydinoglu, M.N., 2003. An incremental response spectrum analysis procedure on inelastic spectral displacements for multi-mode seismic performance evaluation, Bulletin of Earthquake engineering, 1, pp. 3-36.##Building Seismic Safety Council (BSSC), 1997. NEHRP Guidelines for the Seismic Rehabilitation of Buildings, FEMA-273, Federal Emergency Management Agency: Washington, D.C.##CEN, 2004. Eurocode 8, Design Of Structures for Earthquake Resistance, Part 1: General Rules, Seismic Actions and Rules for Buildings, Ref. No. EN 1998-1 : 2004 (E), November 2004.: Brussels.##Chopra, A.K. and Goel, R.K., 2002. A modal pushover analysis procedures for estimating seismic demands for buildings. Earthquake Engineering and Structural Dynamics, 31, pp. 561-582.##Chopra, A.K. and Goel, R.K., 2004. A modal Pushover analysis procedure to estimate seismic demand for unsymmetric–plan buildings, Earthquake Engineering and Structural Dynamics, 33, pp. 903-927.##Chopra, A.K., 2007. Dynamics of structures. Theory and Applications to Earthquake Engineering, Third Edition, prentice Hall.##Computers & Structures Incorporated (CSI), 2004. SAP 2000 NL: Berkeley, CA, U.S.A.##Fajfar, P., 2000. A nonlinear analysis method for performance based seismic design, Earthquake Spectra, 16(3), pp. 573-592.## Fajfar, P., Marusic, D. and Perus, I., 2005. Torsional effects in the pushover-based seismic analysis of buildings, Journal of Earthquake Engineering, 9(6), pp. 831-854.##Jan, T.S., Liu, M.W. and Kao, Y.C., 2004. An upper-bound pushover analysis procedure for estimating the seismic demands of high-rise buildings, Engineering Structures, Vol. 26, pp. 117-128.##Kalkan, E. and Kunnath SK., 2006. Adaptive modal combination procedure for nonlinear static analysis of building structures. ASCE, Journal of Structural Engineering, 132(11), pp. 1721-1731.##Kreslin M., Fajfar P (2011) The extended N2 method taking into account higher mode effects in elevation. Earthquake Engineering and Structural Dynamics, Vol. 40 (14), pp. 1571–1589.##Kreslin, M. and Fajfar, P., 2012. The extended N2 method considering higher mode effects in both plan and elevation, Bulletin of Earthquake Engineering, Vol. 10(2), pp. 695-715.##Marusic, D. and Fajfar, P. 2005. On the inelastic seismic response of asymmetric buildings under bi-axial excitation, Earthquake Engineering and Structural Dynamics, 34, pp. 943-963.## ##Perus, I. and Fajfar, P., 2005. On the inelastic torsional response of single-storey structures under bi-axial excitation, Earthquake Engineering and Structural Dynamic, 34(8). pp. 931-941.##Poursha, M., Khoshnoudian, F. and Moghadam, A.S. 2009. A Consecutive modal pushover procedure for estimating the seismic demands of tall buildings, Engineering Structures, 31, pp. 591-599.##Poursha, M., Khoshnoudian, F. and Moghadam, A.S. 2011. A Consecutive modal pushover procedure for nonlinear static analysis of one-way unsymmetric-plan tall building structures, journal of Engineering Structures, 33(9), pp. 2417-2434.##Reyes, J.C. and Chopra, A., 2011a. Three-dimensional modal pushover analysis of buildings subjected to two components of ground motion, including its evaluation for tall buildings, Earthquake Engineering and Structural Dynamics, 40, pp.789-806.##Reyes, J.C., Chopra, A., 2011b. Evaluation of three-dimensional modal pushover analysis for unsymmetric-plan buildings subjected to two components of ground motion, Earthquake Engineering & Structural Dynamics, 40(13), pp. 1475–1494.##Sasaki, K.K., Freeman, S.A. and Paret, T.F., 1998. Multi-mode pushover procedure (MMP) –A method to identify the effects of higher modes in a pushover analysis, Proc. 6th U.S. Nat. Conf. on Earthq. Eng.: Seattle, Washington. ##Standard No. 2800-05, 2005. Iranian code of practice for seismic resistant design of buildings, 3rd edition, Building and Housing Research Centre: Iran.##Tso, W.K. and Moghadam, A.S., 1998. Pushover procedure for seismic analysis of buildings, Progress in structural Engineering and Materials; 1(3): pp.337–44.## ##

Effects of higher modes on vertical distribution of isolated structures under near field earthquakes 2 2 It has been pointed out the static lateral response procedure for a base-isolated structure proposed in International Building Code (IBC) somewhat overestimates the seismic story force. That is why in the current paper, vertical distribution of base shear over the height of isolated structures considering higher mode effects under near field earthquakes is investigated. Nonlinear behavior of isolation systems cause variation of frequencies transmitted to the superstructure and consequently higher modes effects should be considered. In this study base shear distribution obtained from nonlinear dynamic analysis is compared with that achieved from IBC for assessment of the international building code. This investigation has been conducted in two parts, in order to have an appropriate base shear distribution formula for isolated structures under near field earthquakes. In the first part using three first mode shapes of isolated structure and introducing coefficient corresponding to each mode, extracted from nonlinear dynamic analysis under near field earthquakes, a new formula has been derived. In the second part, the mode shape coefficients have been obtained theoretically and consequently a new base shear distribution over the height of isolated structures including the isolation system properties under near field ground motions was proposed. 115 124 2012/03/112012/06/162012/01/112011/06/152011/02/15 1389/11/26 2013/06/102013/06/152013/06/172013/06/172013/06/10 1392/3/20 F. Khoshnoudian F. Khoshnoudian Amirkabir University of Technology Iran khoshnud@aut.ac.ir O. Nozadi O. Nozadi Amirkabir University of Technology Iran info@signaleng.com Base-isolated structures Base shear distribution Near field earthquake Higher modes effects [1] Yang, Y.B, Chang, K.C, and Yao, J.D, “ Base Isolation”, Earthquake Engineering Handbook,2003.##[2] Naeim, F., Mayes., R.L., “Design of structures with seismic isolation ”,Seismic Design Handbook,CA,USA,2001.##[3] Wang,Yen-Po., “Fundamentanls of Seismic Base Isolation”,International Training Programs for Seismic Design of Building Structures.##[4] Uniform Building Code “UBC-91”, International Conference of Building Officials,Chapter 23, Whittier, C.A, USA, 1991.##[5] Uniform Building Code “UBC-97”, International Conference of Building Officials,Chapter 23, Whittier, C.A, USA, 1997.##[6] International Buliding Code, 2010.##[7] European Committee for Standardization (CEN), Eurocode 8: Design of Structures for Earthquake Resistance, 2010.##[8] New Zealand Standard, Structural Design Actions,2010.##[9] Lee, D.G., Hong, J.M., and Kim, J., “Vertical distribution of equivalent static loads for base-isolated building structures”, Journal of Engineering Structures,2001, pp1293-1306.##[10] Cardone, D., Dolce, M., and Gesualdi, G., “Lateral force distribution for the linear static analysis of base-isolated buildings”, Bull Earthquake Eng,2009, pp801-834.##[11] Khoshnoudian, F., Esrafili, S., “A new lateral force distribution formula for base-isolated structures”, Institution of Civil Engineering Journals, 2008, pp277-297.##[12] Khoshnoudian, F., Mehrparvar B., “Evaluation of IBC equivalent lateral response procedure for base shear distribution of seismic isolated-structures”, Journal of Earthquake Engineering, Vol12, 2008,pp681-703.##[13] American Institute of Steel Construction (AISC).##[14] Park, Y.J., Wen, Y.K. and Ang, A.H, “Random vibration of hysteretic systems under bi-directional ground motions”, Earthquake Engineering and Structural Dynamics, Vol 14,1986,pp.34-53.##[15] Ghobarah, A., “Response of structure to near-fault ground motion”, World Conference on Earthquake Engineering, Vancouver, Canada, 2004.##[16] Elsheikh, A., Ghobarah, A., “ Response of RC structures to near-fault records”, Emirates journal for Engineering research,2004,pp45-51.##[17] PEER (Pacific Earthquake Engineering Research Center) Strong Motion Database, University of California, Berkeley, http://peer.berkeley.edu/.##[18] Nagarajaiha, S., Reinhorn, A.M. & Constantinou, M.C. (1993). 3D-BASIS : Computer program for nonlinear dynamic analysis of three dimensional base isolated structures. NCEER-93-0011, National Center for Earthquake Engineering Research, Buffalo, N.Y.##[19] Wen, Y.K. (1979). Method of random vibration of hysteretic systems. Journal of Engineering Mechanics, ASCE, No. 102, 249-263. ## ##

Presenting asphalt mixtures flow number prediction model using gyratory curves 2 2 Pavement permanent deformations due to lack of shear strength in mixture are a major reason of rutting. Any simple test to determine mixtures resistance to permanent deformation isn’t distinguished in the 1st level of SUPERPAVE mix design method and prevalent methods for evaluating mixture rut resistance are expensive and time-consuming. Two aggregate types, gradations, asphalt cements and filler types were used in this research to present a prediction model for rutting based on flow number. A mathematical model to estimate flow number of dynamic creep test was developed using model parameters and gyratory compaction slope. The model is validated using Neural Network and Genetic Algorithm and makes it possible to evaluate mixtures shear strength while optimum asphalt content is being determined in laboratory. So not only there is no need to expensive test instruments of rutting or dynamic creep but a remarkable time saving in mix design procedure is achievable. 125 133 2012/03/112012/06/162012/01/112011/06/152011/02/152012/07/24 1391/5/3 2013/06/102013/06/152013/06/172013/06/172013/06/102013/06/10 1392/3/20 H. Ziari H. Ziari Iran University of Science and Technology Iran h.ziari@iust.ac.ir H. Divandari H. Divandari Islamic Azad University, Nowshahr Branch, Iran divandari@iauns.ac.ir Rutting Gyratory Dynamic creep Flow number Shear stress curve. [1] Ameri, M., Moghadas Nejad, F., & Mirzahoseini, R. (2010). Presenting a Predicting Model for Asphalt Mixture Rutting Using Marshall Mix Design Method Paramteres and Studing These Parameters Effect on Flow Number.6th National Congress on Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran, 2010.##[2] Wen, Y., Yong He, W., & Rui, Z. (2010). Study on Rutting of Asphalt Pavements. Advanced Materials Research , 1096-1099.##[3] Drakos, C. (2003). Identification of A physical Model to Evaluate Rutting Performance of Asphalt Mixture. Florida: A dissertation presented to graduate school of the University of Florida in partial Fulfillment of the requirements for the degree of Doctor of Philosophy University of Florida .##[4] Transportation Research Institute, (2010). Experimental Study of Gradation Type and VoidsEffect on Bleeding and Rutting in Asphalt Concrete in Iran. Tehran, Iran: Transportation Research Institute.##[5] Santucci, L. (2000). Rut Resistant Asphalt Pavements, LTAP Field Engineer, Tech Transfer Program and Pavement Specialist, Pavement Research Center, UC Berkeley, Institute of Transportation Studies, 2000, pp. 1-8.##[6] Hafeez, I., & Kamal, M. (2011). Repeated Load Permanent Deformation Behavior of Mixes. Journal of Engineering and Technology, 15-22.##[7] Fujie , Z., Scullion, T., & Lijun, S. (2004). Verification and Modeling of Three-Stage Permanent Deformation Behavior of Asphalt Mixes. Journal of Transportation Engineering , 486-494.##[8] Horak E, Emery S and Mihaljevic, I (2011) Balancing asphalt rut resistance with durability and safety requirements on runway rehabilitations.Airfield Pavements Seminar, XXIVth World Road Congress, Mexico City, 28-29 Sept##[9] Hai Fan, S., & Ling, L. (2011). Investigation on Countermeasures Analysis of Rutting in Highway Asphalt Concrete Pavement . Advanced Materials Research, Advances in Civil Engineering, 3263-3267.##[10] Ameri, M., Moghadasnejad, F., & Mirzahoseini, R. (2009). The Effect of Gradation and VMA On Rutting Potential and Presenting Rutting Prediction Model. Jaddeh Scientific Journal, 5.##[11] Mohammadzadeh, M., Latifi, M., & Mohammadzadeh, H. (2008). A Comparision Between Gyratory and Marshall Compaction Methods to Prepare Asphalt Mixtures for Evaluating Asphalt Behavior. 4th National Congress on Civil Engineering . Tehran, Iran: University of Tehran.##[12] McGarvey, K., Panko, M., Hurt, C., Mehta, Y., & Sukunaran, B. (2010). Use of Superpave Gyratory Compactor as a Predictor of Field Performance. FAA Worldwide Airport Technology Transfer Conferece . Atlantic City, NewJersey, USA.##[13] Corte, J., & Serfass, J. (2000). The French Approach to Asphalt Mixture Design: A Performance Related System of Specification . Association of Asphalt Paving Technologists.##[14] Anderson, R., Christensen, W., & Bonaquist, R. (2003). Estimating the Rutting Potential of Asphalt Mixtures Using Superpave Gyratory Compaction Properties and Indirect Tensile Strength. Association of Asphalt Paving Technologists-Proceeding of the Technical Sessions.##[15] Roque, R., Birgisson, B., Darku, D., & Darkos, C. (2004). Evaluation of Laboratory Testing System for Asphalt Mixture Design and Evaluation.##[16] Archilla, A. (2006). Use of Superpave Gyratory Compaction Data for Rutting Prediction . Journal of Transportation Engineering.##[17] You, Z., & Barak, J. (2009). Development of Specification for the Superpave Simple Performance Tests (SPT). Michigan: Department of Civil and Environmental Engineering Michigan Technological University .##[18] Lubind Walubita, F., Umashankar, V., Hu, X., Jamison, B., Zhou, F., Scullion, T., Martin, A.E., & Dessouky, S. (2010). New Generation on Mix-Designs: Laboratory Testing and Construction of The APT Test Sections, Texas Department of Transportation and the Federal Highway Administration, Project No.: FHWA/TX-10/0-6132-1, March 2010.##[19] Office of Deputy for Strategic Supervision, The Ministry of Roads and Urban Development, (2011), Iran Highway Asphalt Paving Code No.234##[20] Dessouky, S., Walubita, L., Urnashankar, V., Hu, X., Jamison, B., Zhou, F., et al. (2010). New Generation Mix-Designs: Laboratory Testing and Construction of the APT Test Sections. Texas: Texas Transportation Institute-Project 0-6132.##[21] Standard, A. (2009). Methods of Sampling and Testing Asphalt, Method 12-: Determination of the Permanent Compressive Strain Characteristics of Asphalt-Dynamic Creep Test.##[22] Hua Hu, C. (2011). Prediction of Resilient Modulus for Hot Mix Asphalt Based on Artificial Neural Network. Advanced Materials Research, 18-23.##[23] Sakhaeifar, M., Underwood, S., Kim, R., Puccinelli, J., & Jackson, N. (2010). Development of Artificial Neural Network Models for Populating Dynamic Module of Long-Term Pavement Performance Section. Transportation Research Record, 88-97.##[24] Morova, S. S., Terzi, N., & Sargin, S. (2011). Amount of Bituminous Effects on Asphalt Concrete Strength with Artificial Intelligence and Statistical Analysis Method. International Symposium on Innovations in Intelligent Systems and Applications , (pp. 329-334).##[25] Beainy, F., Commuri, S., & Zaman, M. (2010). Asphalt Compaction Quality Control Using Artificial Neural Network . 49th IEEE Conference on Decision and Control (CDC), (pp. 4643-4648).## ##

Geomatics applied to dam safety DGPS real time monitoring 2 2 New advances in geomatics and communications technologies are enabling the development of Automated Auscultation System for structure monitoring. In particular, Differential GPS (DGPS) technique allows real-time monitoring of structures with millimetre accuracy after an appropriate mathematical treatment. The results of real-time DGPS monitoring of a pilot dam over 15 months are presented and compared with the results of pendulums and angular collimation. DGPS monitoring was established to control two points at the top of the dam with reference to an external and stable station. Communications were critical, evolving from initial GPRS connections to more reliable ASDL line in the last months. Real-time DGPS positions were filtered to reach millimetric accuracy through Kalman filter. Two configurations of the filter were tested, one more adapted to predictable and uniform velocity deformations (low frequency) and another more suitable for sudden and large movements (high frequency). Root mean square errors were calculated taking pendulums as a reference. Results show that both DGPS and angular collimation allow monitoring with millimetric accuracy. In the last period, where communications with processing server were stable, a global accuracy of 1.44 and 1.86 mm was reached for real-time DGPS monitoring. RINEX post-processing yielded millimetric results, validating real-time observations. We can affirm that the DGPS system is very useful for dam auscultation and safety as it detects adequately absolute deformations, being a complement to existing methods which should be considered in new safety plans. 134 141 2012/03/112012/06/162012/01/112011/06/152011/02/152012/07/242012/02/29 1390/12/10 2013/06/102013/06/152013/06/172013/06/172013/06/102013/06/102013/06/10 1392/3/20 D. GALAN D. GALAN TECHNICAL UNIVERSITY OF MADRID/Dam Safety Division. Canal de Isabel II SPAIN dgalanmartin@cyii.es M. MARCHAMALO M. MARCHAMALO TECHNICAL UNIVERSITY OF MADRID SPAIN miguel.marchamalo@upm.es R. MARTINEZ-MARIN R. MARTINEZ-MARIN TECHNICAL UNIVERSITY OF MADRID SPAIN ruben.martinez@upm.es J. A. SANCHEZ-SOBRINO J. A. SANCHEZ-SOBRINO TECHNICAL UNIVERSITY OF MADRID/Geodetic Observation Center. IGN SPAIN jassobrino@fomento.es Dam monitoring Geomatics DGPS Structures Real time. [1] Behr J.A., Hudnut K. W. and King N.E., Monitoring Structural Deformation at Pacoima Dam, California Using Continuous GPS, Southern California Earthquake Center, SCIGN-USGS, United States Geological Survey, California, USA (2000).##[2] Rutledge, D. R. and Meyerholtz S. Z., Performance monitoring of Libby Dam with a differential global positioning system, UNITED STATES SOCIETY OF DAMS, U.S. Army Corps of Engineers, USA (2005).##[3] GOCA, GOCA-Project-Examples, “Monitoring of Kops Dam”, GPS-based online Control and Alarm System, http://www.goca.info/beispiel_e.html, Illwerke Vorarlberg, Austria (2002)##[4] Blázquez F. and Galán D., Informe anual de auscultación Presa de La Aceña-Año 2008, División Seguridad de Presas, Canal de Isabel II, Madrid, Spain (2009).##[5] Kalman, R. E., A New Approach to Linear Filtering and Prediction Problems, Transaction of the ASME—Journal of Basic Engineering, pp. 35-45, (1960).##[6] Hofmann-Wellenhof, B., Lichtenegger, H. and Collins J., “GPS Theory and Practice”. Springer-Verlag Wien NewYork, 382 pp., (2001)##[7] Welch, G and Bishop G., An Introduction to the Kalman Filter, TR 95-041, Department of Computer Science, University of North Carolina, USA, 16 pp., (2002)## ##