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i-manager's Journal on Structural Engineering (JSTE)

Current Issue Vol. 12 Issue 4

Most Cited

Volume 7 Issue 1 March - May 2018

Research Paper

Analysis of Structures Subject to Uncertain Displacements Using Interval Methods

Mehdi Modares*

Associate Professor, Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, USA.

Modares, M.(2018). Analysis of Structures Subject to Uncertain Displacements Using Interval Methods. i-manager’s Journal on Structural Engineering, 7(1), 1-5. https://doi.org/10.26634/jste.7.1.14277

Abstract

This paper presents a new framework for analysis of structures subjected to imprecise or uncertain displacements through application of interval methods. This pertains to quantification of uncertainty existing in the induced displacements using unknown-but-bounded or interval variables. In deterministic conventional displacement-based structural methods, the unknown displacements are obtained followed by determination of internal forces. In order to attain sharp results, using this method, the two main steps of conventional static analysis is combined which leads to determination of bounds of internal forces/moments as well as internal stresses directly. Using this method, the functional dependencies of uncertain interval parameters are considered in the calculations leading to obtaining sharp results. An example illustrating the behavior of the method developed is presented and the results are compared with Monte-Carlo simulations results.

References

[1]. Impollonia, N., & Muscolino, G. (2011). Interval analysis of structures with uncertain-but-bounded axial stiffness. Computer Methods in Applied Mechanics and Engineering, 200(21-22), 1945-1962.

[2]. Modares, M., Mullen, R. L., & Muhanna, R. L. (2006). Natural frequencies of a structure with bounded uncertainty. Journal of Engineering Mechanics, 132(12), 1363-1371.

[3]. Modares, M., & Mullen, R. L. (2009). Static analysis of uncertain structures using inter val eigenvalue decomposition. International Journal of Reliability and Safety, 3(1-3), 246-257.

[4]. Modares, M., & Mullen, R. L. (2013). Dynamic analysis of structures with interval uncertainty. Journal of Engineering Mechanics, 140(5), 04013011.

[5]. Moore, R. E. (1966). Introduction to Interval Analysis. Prentice Hall.

[6]. Muhanna, R. L., & Mullen, R. L. (2001). Uncertainty in mechanics problems-Interval-based approach. Journal of Engineering Mechanics, 127(6), 557-566.

[7]. Rokne, J. G. (2012). Interval Arithmetic and Interval Analysis: An Introduction. In Pedrycz, W. (Eds.), Granular Computing. Studies in Fuzziness and Soft Computing (Vol. 70). Physica, Heidelberg.

[8]. Rao, S. S., & Berke, L. (1997). Analysis of uncertain structural systems using interval analysis. AIAA Journal, 35(4), 727-735.

[9]. Xia, B., & Yu, D. (2014). Modified interval and subinterval perturbation methods for the static response analysis of structures with interval parameters. Journal of Structural Engineering, 140(5), 04013113.

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Research Paper

Lateral - Torsional Buckling of Various Steel Trusses

K.S.Vivek* , C. Ravi Kumar Reddy, K. S. Sai Ram*

* Assistant Professor, Department of Civil Engineering, VVIT, Andhra Pradesh, India.

Professor, Department of Civil Engineering, KHIT, Andhra Pradesh, India.

* Professor, Department of Civil Engineering, RVR & JC CE, Andhra Pradesh, India.

Vivek, K.S., Reddy, C.R.K., and Ram , K.S.S. (2018). Lateral - Torsional Buckling of Various Steel Trusses. i-manager’s Journal on Structural Engineering, 7(1), 6-12. https://doi.org/10.26634/jste.7.1.14280

Abstract

Lateral-torsional buckling behavior of various types of steel trusses without and with intermediate lateral rigid supports is investigated by performing finite element analysis. Commonly used parallel chord trusses, such as Pratt, Howe, Warren (with verticals), K and Diamond trusses of span 8 m and rise 0.8 m are considered. Two different types of intermediate lateral rigid support systems are considered. Elastic critical buckling joint loads of the trusses are found by modeling and performing finite element analysis using ANSYS - commercial software. From the obtained results it can be understood that critical buckling load, the magnitude and shape out of plane deflection depends upon whether the intermediate lateral support is provided or not and if provided, the type of lateral supports and spacing between them. The pattern and inclination of the web lacing also affect the stability of the truss. It is found that the Diamond and K trusses resulted in better stability and hence suggested for use in place of large spans and heavy loading.

References

[1]. Chan, S. L., & Cho, S. H. (2005). Second-order P-?-? analysis and design of angle trusses allowing for imperfections and semi-rigid connections. International Journal of Advanced Steel Construction, 1(1), 157-172.

[2]. Chan, S. L., & Cho, S. H. (2008). Second-order analysis and design of angle trusses Part I: Elastic analysis and design. Engineering Structures, 30(3), 616-625.

[3]. Cho, S. H., & Chan, S. L. (2005). Practical second-order analysis and design of single angle trusses by an equivalent imperfection approach. Steel and Composite Structures, 5(6), 443-458.

[4]. Galambos, T. V. (Ed.). (1998). Guide to Stability Design Criteria for Metal Structures. John Wiley & Sons.

[5]. Jankowska-Sandberg, J., & Ko?odziej, J. (2013). Experimental study of steel truss lateral-torsional buckling. Engineering Structures, 46, 165-172.

[6]. Timoshenko, S. P., & Gere, J. M. (1961). Theory of Elastic nd Stability, 2 Edition. McGraw-Hill, New York.

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Research Paper

A Step by Step Procedure to Perform Isogeometric Analysis of Beam and Bar Problems in Civil Engineering Including Sizing Optimisation of a Beam

K. N. V. Chandrasekhar* , N. S. S. Sahithi**

* Assistant Professor, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India.

** PG Scholar, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India.

Chandrasekhar, K.N.V., and Sahithi, N.S.S. (2018). A Step By Step Procedure to Perform Isogeometric Analysis of Beam and Bar Problems In Civil Engineering Including Sizing Optimisation of a Beam. i-manager’s Journal on Structural Engineering, 7(1), 13-27. https://doi.org/10.26634/jste.7.1.14283

Abstract

The integration of CAD geometry and analysis is really a big advantage of using Isogeometric analysis. The Galerkin weak formulation is used to solve the governing differential equations using the B-splines and NURBS functions. The main focus of this paper is to present a detailed step by step procedure to solve beam and bar problems in Civil Engineering. The beam is analysed for static and dynamic loading, and the bar problem is analysed to find the natural frequency of vibration. The sizing optimization of the beam is also perfomed to determine the optimal cross section dimensions of the beam. The results from the Isogeometric analysis are then compared with the theoretical results. The results from Isogeometric analysis shows a good agreement with those obtained by using the analytical methods. The solution from the Isogeometric analysis has better precision over other standard methods. The structures are designed with a basic set of criteria, which include minimum weight, frequency, compliance, and volume. In this paper, the problems related to the weight and frequency are presented, and this paper provides a few basic examples to discuss in a classroom.

References

[1]. Clough, R. W., & Penzien, J. (1993). Dynamics of Structures, McGraw Hill.

[2]. De Lorenzis, L. (2012). Some recent results and open issues on interface modeling in civil engineering structures. Materials and Structures, 45(4), 477-503.

[3]. Espath, L. F. R., Braun, A. L., & Awruch, A. M. (2011). An introduction to isogeometric analysis applied to solid mechanics. Mecánica Computacional, 30, 1955-1975.

[4]. Gondegaon, S., Ahmada,R., & Voruganti, H. K. (2014). Geometric Modeling for Isogeometric analysis. Proceedings of ICTACEM 2014 International Conference On Theoretical, Applied, Computational And Experimental Mechanics.

[5]. Gondegaon, S., & Voruganti, H. K. (2016). Static structural and modal analysis using Isogeometric analysis. Journal of Theoretical and Applied Mechanics, 46(4), 36- 75.

[6]. Hartmann, S., Benson, D. J., & Lorenz, D. (2011). About Isogeometric analysis and the new NURBS-based Finite th Elements in LS-DYNA. In 8 European LS-DYNA Users Conference, Strasbourg, France.

[7]. Hassani, B., Khanzadi, M., & Tavakkoli, S. M. (2012). An isogeometrical approach to structural topology optimization by optimality criteria. Structural and Multidisciplinary Optimization, 45(2), 223-233.

[8]. Hughes, T. J., Cottrell, J. A., & Bazilevs, Y. (2005). Isogeometric analysis: CAD, finite elements, NURBS, exact geometry and mesh refinement. Computer Methods in Applied Mechanics and Engineering, 194(39-41), 4135- 4195.

[9]. Jockovic, M. (2016, April). Free vibration analysis of t h beam element using Isogeometric analysis. 4 I n t e r n a t i o n a l C o n f e r e n c e o n C o n t e m p o r a r y Achievements in Civil Engineering.

[10]. Lee, J. S., An, Y. N., & Chang, K. (2010). Optimum structural design based on isogeometric analysis method. In Strategic Technology (IFOST), 2010 International Forum on (pp. 377-381). IEEE.

[11]. Nagy, A. P., Abdalla, M. M., & Gürdal, Z. (2010). On the variational formulation of stress constraints in isogeometric design. Computer Methods in Applied Mechanics and Engineering, 199(41-44), 2687-2696.

[12]. Nguyen, V. P., Anitescu, C., Bordas, S. P., & Rabczuk, T. (2015). Isogeometric analysis: An overview and computer implementation aspects. Mathematics and Computers in Simulation, 117, 89-116.

[13]. Rauen, M., Machado, R. D., & Arndt, M. (2013, November). Isogeometric Analysis of Free Vibration of Bars. nd 22 International Congress of Mechanical Engineering.

[14]. Shah, M., & Katukam, R. (2015a). Stress Analysis without Meshing Iso-Geometric Analysis Finite Element Method (IGAFEM). Boeing Summer Internship Project.

[15]. Shah, M., & Katukam, R. (2015b). Stress Analysis without Meshing Isogeometric Analysis Finite Element Method. International Conference on Innovations in Computer Science and Technology, ICICSIT.

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Research Paper

Effect of Suspension to Main Span Ratio on the Behaviour of Cable-Stayed Suspension Hybrid Bridge

G.M. Savaliya* , A. K. Desai**

* Assistant Professor, Department of Civil Engineering, Government Engineering College, Palanpur, Gujarat, India.

** Professor, Department of Applied Mechanics, Sardar Vallabhbhai Patel National Institute of Technology (SVNIT), Surat, Gujarat, India.

Savaliya, G.M., and Desai, A.K.(2018). Effect of Suspension to Main Span Ratio on the Behaviour of Cable-Stayed Suspension Hybrid Bridge. i-manager’s Journal on Structural Engineering, 7(1), 28-34. https://doi.org/10.26634/jste.7.1.14279

Abstract

To accomplish utmost central span in bridges is a fascinating rational challenge. The idea of modified cable-supported bridges has been projected in the past that promise to go beyond the traditional cable-supported bridges in terms of central span length. There are different ways through which long span bridges could be achieved like structural system with innovative form, use of high strength materials, and latest method of analysis and design. The cable supported bridge systems, such as cable-stayed bridge and suspension bridge are used to achieve longer span bridges. The suspension bridge has the ability to offer longer span and cable-stayed bridge has better structural stiffness. Advantages of above system could combine in a system known as long span cable-stayed suspension hybrid bridge. To discriminate behaviour and check the feasibility of this modern form of bridge, 1400 m central span and 700 m side span cablestayed suspension hybrid bridge is selected for analysis. The span of bridge supported by suspenders also influence the behaviour of suspension bridge. Here, the influence of suspension portion is presented in the form of suspension portion to main span ratio. The analysis like modal analysis and nonlinear static analysis is carried out using SAP2000 v14.0.0. The effects of suspension portion to main span ratio on nonlinear static performance of bridge are presented in form of axial forces and bending moment in deck of cable-stayed suspension hybrid bridge.

References

[1]. Gimsing, N. J. (1988). Cable-stayed bridges with ultra long spans. Rep., Dept. of Struct. Engg., Tech. Univ. of Denmark, Lyngby, Denmark.

[2]. Gimsing, N. J., & Georgakis, C. T. (2011). Cable Supported Bridges: Concept and Design. Third Edition. John Wiley & Sons.

[3]. Muller, J. M. (1992). Precast segmental construction. Proc., FIPSymp., FlP, Paris, France.

[4]. Rucheng, X., Lijun, J., Erle, X., Xiheng, L., Limin, D., Ledong, Z., & Haifan, X. (2000). Research on the Design of Cable stayed Suspension Bridges. China Civil Engineering Journal, 33(5), 46-51.

[5]. Schlaich. (1988). Design competition Williamsburg Bridge New York. (Design by Schlaich, Bergermann und Partner, Stuttgart, and Walther & Mori, Basel.) Stahlbau, Berlin, Germany, 57(12), 374-377.

[6]. Starossek, U. (1996). Cable-stayed bridge concept for longer spans. Journal of Bridge Engineering, 1(3), 99-103.

[7]. Walter R. (1988). Cable-stayed Bridges. Thomas Telford, London.

[8]. Zhang, X. J. (2007). Investigation on mechanics performance of cable-stayed-suspension hybrid bridges. Wind and Structures, 10(6), 533-542.

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Research Paper

Influence of VSI Aggregates on Properties of Pervious Concrete

Tejas Joshi* , K. Vaisakh**

* Research Scholar, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

** Professor, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

Joshi, T. and Dave, U.(2018). Influence of VSI Aggregates on Properties of Pervious Concrete. i-manager’s Journal on Structural Engineering, 7(1), 35-40. https://doi.org/10.26634/jste.7.1.14281

Abstract

This paper investigates the effect of replacement in Vertical Shaft Impactor (VSI) aggregates with Natural coarse aggregates on pervious concrete properties. Pervious concrete is a special type concrete prepared without use of fine sand. Pervious concrete is produced with different size of coarse aggregates. For the present investigation comparison has been made between VSI aggregates and Natural aggregates used in pervious concrete. The physical properties of Natural aggregate and VSI aggregate are compared. For the pervious concrete mix design, cement content, 375 3 -10 kg/m is used with 4.75 mm size of coarse aggregate. Three w/c ratios are used, such as 0.4, 0.425, and 0.45. The main properties were studied, such as void ratio, compressive strength permeability, and density. Comparison of results in Natural aggregate and VSI aggregate for making pervious concrete are included in this paper. Test results reveal considerable enhancement in the compressive strength of pervious concrete and other properties are found in similar range. VSI aggregate is a special type of aggregate having rounded edges. It has been found that VSI aggregates is more suitable to use in pervious concrete as compared to Natural coarse aggregates.

References

[1]. Bureau of Indian Standards. (1959). Methods of Tests for Strength of Concrete (IS:516-1959). New Delhi, India.

[2]. Bureau of Indian Standards. (1970). Specification for Coarse and fine aggregate from natural sources for concrete (IS: 383-1970), New Delhi, India.

[3]. Bureau of Indian Standards. (1987). Specifications for 53 grade Portland Cement (IS: 12269-1987). New Delhi, India.

[4]. Deo, O., Sumanasooriya, M., & Neithalath, N. (2010). Permeability reduction in pervious concretes due to clogging: Experiments and modeling. Journal of Materials in Civil Engineering, 22(7), 741-751.

[5]. Ghafoori, N., & Dutta, S. (1995). Laboratory investigation of compacted no-fines concrete for paving materials. Journal of Materials in Civil Engineering, 7(3), 183-191.

[6]. Joshi, T., & Dave, U. (2017). Parametric study of pervious concrete with changing cement content and w/c ratio. Indian Concrete Journal, 91(6), 19-25.

[7]. McCain, G., & Dewoolkar, M. (2010). Porous concrete pavements: Mechanical and hydraulic properties. Transportation Research Record: Journal of the Transportation Research Board, (2164), 66-75.

[8]. Meininger, R. C. (1988). No-fines pervious concrete for paving. Concrete International, 10(8), 20-27.

[9]. National Ready Mixed Concrete Association (NRMCA). (2004). What, Why, and How? Pervious Concrete, Concrete in Practice, CIP 38. Silver Spring, Maryland.

[10]. Sriravindrarajah, R., Wang, N. D. H., & Ervin, L. J. W. (2012). Mix design for pervious recycled aggregate concrete. International Journal of Concrete Structures and Materials, 6(4), 239-246.

[11]. Suleiman, M. T., Ni, L., & Raich, A. (2014). Development of pervious concrete pile groundimprovement alternative and behavior under vertical loading. Journal of Geotechnical and Geoenvironmental Engineering, 140(7), 04014035.

[12]. Tennis, P. D., Leming, M. L., & Akers, D. J. (2004). Pervious concrete pavements (No. PCA Serial No. 2828). Skokie, IL: Portland Cement Association.

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Research Paper

Structural System Prediction Model Based On Cost – Time – Quality Analysis

shashank* , Pratul N. Nema, P. Sathishkumar, B. S. Shashank, B. L. Shivakumar

- Department of Civil Engineering, Visvesvaraya Technological University, Belgaum, Karnataka, India.

Assistant Professor, Department of Civil Engineering, R.V. College of Engineering, Bengaluru, India.

*** Professor and Former Dean, R.V. College of Engineering, Bengaluru, India.

Shreenidhi, R., Nema, P.N., Sathishkumar, P., Shashank. B.S., and Shivakumar, B.L. (2018). Structural System Prediction Model Based on Cost - Time - Quality Analysis. i-manager’s Journal on Structural Engineering, 7(1), 41-47. https://doi.org/10.26634/jste.7.1.14282

Abstract

In present scenario, most building systems are decided on the basis of experience and preferences of Architects and Structural consultants, but seldom are the Project Management aspects considered. Even when they are considered, it is not done in a systematic manner. Because of this it quite often happens that in the middle of the project there are drastic changes in the building systems adopted, which have implications with time, cost, quality, or all of them. There is a general lack of awareness in industries about the different structural systems available and the knowledge about their reliability in the industry. In this work, the construction management methodologies of various building systems, such as Column beam slab, Post Tensioned slab, Reinforced Concrete Wall, and Flat slab were studied. The authors compared the different systems with respect to parameters like suitability, cost, duration, and quality. The authors have generated a prediction model to identify the suitable building system considering the constraints given by the client. From the overall study, Resource-Cost- Duration analysis of a project is carried out and other parameters are optimized when one parameter becomes a constraint, for efficient construction management.

References

[1]. Ahn, Y. H. (2010). The development of models to identify relationships between first costs of green building strategies and technologies and life cycle costs for public green facilities (Doctoral Dissertation, Virginia Tech).

[2]. Aibinu, A. A., Dassanayake, D., Chan, T. K., & Thangaraj, R. (2015). Cost estimation for electric light and power elements during building design: A neural network approach. Engineering, Construction and Architectural Management, 22(2), 190-213.

[3]. An, S. H., Kim, G. H., & Kang, K. I. (2007). A case-based reasoning cost estimating model using experience by analytic hierarchy process. Building and Environment, 42(7), 2573-2579.

[4]. Bala, K., Ahmad Bustani, S., & Shehu Waziri, B. (2014). A computer-based cost prediction model for institutional building projects in Nigeria: An Artificial Neural Network approach. Journal of Engineering, Design and Technology, 12(4), 519-530.

[5]. Cheng, M. Y., Tsai, H. C., & Hsieh, W. S. (2009). Webbased conceptual cost estimates for construction projects using Evolutionary Fuzzy Neural Inference Model. Automation in Construction, 18(2), 164-172.

[6]. Cheng, M. Y., Tsai, H. C., & Sudjono, E. (2010). Conceptual cost estimates using evolutionary fuzzy hybrid neural network for projects in construction industry. Expert Systems with Applications, 37(6), 4224-4231.

[7]. Eashwar, S., and Geetha, G. (2016). Trade-off Between Time, Cost, Quality, Safety, Environment - Star Optimization Model. International Journal of Computer Technology and Applications, 9(11), 5467-5486.

[8]. Fu, F., & Zhang, T. (2016). A New Model for Solving Time- Cost-Quality Trade-Off Problems in Construction. PloS one, 11(12), e0167142.

[9]. Günayd?n, H. M., & Do?an, S. Z. (2004). A neural network approach for early cost estimation of structural systems of buildings. International Journal of Project Management, 22(7), 595-602.

[10]. Hong, T., Hyun, C., & Moon, H. (2011). CBR-based cost prediction model-II of the design phase for multi-family housing projects. Expert Systems with Applications, 38(3), 2797-2808.

[11]. Ji, S. H., Park, M., & Lee, H. S. (2011). Cost estimation model for building projects using case-based reasoning. Canadian Journal of Civil Engineering, 38(5), 570-581.

[12]. Juszczyk, M. (2013). The use of artificial neural networks for residential buildings conceptual cost estimation. In AIP Conference Proceedings (Vol. 1558, No. 1, pp. 1302-1306). AIP.

[13]. Khang, D. B., & Myint, Y. M. (1999). Time, cost and quality trade-off in project management: A case study. International Journal of Project Management, 17(4), 249- 256.

[14]. Kim, G. H., An, S. H., & Kang, K. I. (2004a). Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning. Building and Environment, 39(10), 1235-1242.

[15]. Kim, G. H., Yoon, J. E., An, S. H., Cho, H. H., & Kang, K. I. (2004b). Neural network model incorporating a genetic algorithm in estimating construction costs. Building and Environment, 39(11), 1333-1340.

[16]. Kim, S. (2013). Hybrid forecasting system based on case-based reasoning and analytic hierarchy process for cost estimation. Journal of Civil Engineering and Management, 19(1), 86-96.

[17]. Koo, C. W., Hong, T., Hyun, C. T., Park, S. H., & Seo, J. O. (2010). A study on the development of a cost model based on the owner's decision making at the early stages of a construction project. International Journal of Strategic Property Management, 14(2), 121-137.

[18]. Koo, C., Hong, T., & Hyun, C. (2011). The development of a construction cost prediction model with improved prediction capacity using the advanced CBR approach. Expert Systems with Applications, 38(7), 8597-8606.

[19]. Kutner, M., Nachtsheim, C. J., Li. N.W. (2004). Applied th Linear Statistical Models (5 Ed.), McGraw-Hill/Irwin.

[20]. Lai, C. C., & Lee, W. L. (2006). A WICE approach to real-time construction cost estimation. Automation in Construction, 15(1), 12-19.

[21]. Li, H., Shen, Q. P., & Love, P. E. (2005). Cost modelling of office buildings in Hong Kong: An exploratory study. Facilities, 23(9/10), 438-452.

[22]. Lowe, D. J., Emsley, M. W., & Harding, A. (2006). Predicting construction cost using multiple regression techniques. Journal of Construction Engineering and Management, 132(7), 750-758.

[23]. Moon, S. W., Kim, J. S., & Kwon, K. N. (2007). Effectiveness of OLAP-based cost data management in construction cost estimate. Automation in Construction, 16(3), 336-344.

[24]. Saputra, Y. A., & Latiffianti, E. (2015). Project reliability model considering time–cost–resource relationship under uncertainty. Procedia Computer Science, 72, 561-568.

[25]. Shankar, N. R., Raju, M. M. K., Srikanth, G., & Bindu, P. H. (2011). Time, cost and quality trade-off analysis in construction of projects. Contemporary Engineering Sciences, 4(6), 289-299.

[26]. Siqueira, I. (1999). Neural network-based cost estimating (Doctoral Dissertation, Concordia University).

[27]. Sonmez, R. (2004). Conceptual cost estimation of building projects with regression analysis and neural networks. Canadian Journal of Civil Engineering, 31(4), 677-683.

[28]. Sonmez, R. (2005). Review of conceptual cost modeling techniques. AACE International Transactions, ES71.

[29]. Sonmez, R. (2008). Parametric range estimating of building costs using regression models and bootstrap. Journal of Construction Engineering and Management, 134(12), 1011-1016.

[30]. Trost, S. M., & Oberlender, G. D. (2003). Predicting accuracy of early cost estimates using factor analysis and multivariate regression. Journal of Construction Engineering and Management, 129(2), 198-204.

[31]. Yu, W. D. (2006). PIREM: a new model for conceptual cost estimation. Construction Management and Economics, 24(3), 259-270.

[32]. Zayed, T. M., & Halpin, D. W. (2005). Productivity and cost regression models for pile construction. Journal of Construction Engineering and Management, 131(7), 779- 789.

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Case Study

Analysis of Stability of Finite Slopes by Using Visual Slope

K. Ramya Chitra* , D. Kiranmaye**

* M.Tech Scholar, Department of Structural Engineering, Ashoka Institute of Engineering and Technology, Telangana, India.

** Assistant Professor, Department of Civil Engineering, Mahatma Gandhi Institute of Technology, Telangana, India.

Chitra, K.S., and Kiranmaye, D. (2018). Analysis of Stability of Finite Slopes by Using Visual Slope. i-manager’s Journal on Structural Engineering, 7(1), 48-57. https://doi.org/10.26634/jste.7.1.14278

Abstract

Slopes are either man-made (cuttings, embankments for highways, railroads, etc.) or natural (hillside, valleys). Slopes are of two types, viz., finite and infinite. Forces due to instability are force of gravity, force of seepage, earthquake forces, etc. (Ranjan and Rao, 2007). Slope failures are of two types, viz., translational and rotational. Slopes can be analysed by many methods, such as Total stress analysis, Swedish circle method or Method of slices, Bishop's method, Friction circle method, Stability number method, etc. Other than these, different types of software are available for analysis in stability of slopes, for eg: Geoslope, Visual Slope, Geo- Techpidia, C programming, etc. The present work is to analyse the stability of slopes using Visual Slope. Visual Slope is a user-friendly software used for analysis in stability of slopes. By calculating the different input parameters for different trials, least Factor of Safety (F.O.S) could be obtained so that slope can be analysed and stabilised. By using this software, large amount of arithmetic operations can be done within in a few seconds and hence very useful to engineers in the analysis of slope stability.

References

[1]. China Knowledge Network. (n.d.). Retrieved from www.cnki.com.cn

[2]. Geotechpedia. (n.d.). Software by (Visual Slope). Retrieved from http://geotechpedia.com/software/ publisher/87/visual-slope

[3]. Oasys. (2018). Retrieved from www.oasyssoftware. com

[4]. Punmia, B. C., & Jain, A. K. (2005). Soil Mechanics and Foundations. Firewall Media.

[5]. Ranjan, G., & Rao, A. S. R. (2007). Basic and Applied Soil Mechanics. New Age International.

[6]. Slope Stability Analysis. (n.d). In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/slope_stability_analysis

[7]. Visual Slope User's Guide Version 6. (2016). Retrieved from http://www.visualslope.com/Library/Users-Manual- V6.pdf

[8]. Visual Slope. (n.d.). Tutorial. Retrieved from www.visualslope.com/Tutorial6.html

i-manager's Journal on Structural Engineering (JSTE)

Current Issue Vol. 12 Issue 4

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Volume 7 Issue 1 March - May 2018

Analysis of Structures Subject to Uncertain Displacements Using Interval Methods

Mehdi Modares*

Associate Professor, Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, USA.

Modares, M.(2018). Analysis of Structures Subject to Uncertain Displacements Using Interval Methods. i-manager’s Journal on Structural Engineering, 7(1), 1-5. https://doi.org/10.26634/jste.7.1.14277

Abstract

References

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Lateral - Torsional Buckling of Various Steel Trusses

K.S.Vivek* , C. Ravi Kumar Reddy**, K. S. Sai Ram***

* Assistant Professor, Department of Civil Engineering, VVIT, Andhra Pradesh, India. ** Professor, Department of Civil Engineering, KHIT, Andhra Pradesh, India. *** Professor, Department of Civil Engineering, RVR & JC CE, Andhra Pradesh, India.

Vivek, K.S., Reddy, C.R.K., and Ram , K.S.S. (2018). Lateral - Torsional Buckling of Various Steel Trusses. i-manager’s Journal on Structural Engineering, 7(1), 6-12. https://doi.org/10.26634/jste.7.1.14280

Abstract

References

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A Step by Step Procedure to Perform Isogeometric Analysis of Beam and Bar Problems in Civil Engineering Including Sizing Optimisation of a Beam

K. N. V. Chandrasekhar* , N. S. S. Sahithi**

* Assistant Professor, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India. ** PG Scholar, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India.

Chandrasekhar, K.N.V., and Sahithi, N.S.S. (2018). A Step By Step Procedure to Perform Isogeometric Analysis of Beam and Bar Problems In Civil Engineering Including Sizing Optimisation of a Beam. i-manager’s Journal on Structural Engineering, 7(1), 13-27. https://doi.org/10.26634/jste.7.1.14283

Abstract

References

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Effect of Suspension to Main Span Ratio on the Behaviour of Cable-Stayed Suspension Hybrid Bridge

G.M. Savaliya* , A. K. Desai**

* Assistant Professor, Department of Civil Engineering, Government Engineering College, Palanpur, Gujarat, India. ** Professor, Department of Applied Mechanics, Sardar Vallabhbhai Patel National Institute of Technology (SVNIT), Surat, Gujarat, India.

Savaliya, G.M., and Desai, A.K.(2018). Effect of Suspension to Main Span Ratio on the Behaviour of Cable-Stayed Suspension Hybrid Bridge. i-manager’s Journal on Structural Engineering, 7(1), 28-34. https://doi.org/10.26634/jste.7.1.14279

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Influence of VSI Aggregates on Properties of Pervious Concrete

Tejas Joshi* , K. Vaisakh**

* Research Scholar, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India. ** Professor, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

Joshi, T. and Dave, U.(2018). Influence of VSI Aggregates on Properties of Pervious Concrete. i-manager’s Journal on Structural Engineering, 7(1), 35-40. https://doi.org/10.26634/jste.7.1.14281

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Structural System Prediction Model Based On Cost – Time – Quality Analysis

shashank* , Pratul N. Nema**, P. Sathishkumar***, B. S. Shashank****, B. L. Shivakumar*****

*-*** Department of Civil Engineering, Visvesvaraya Technological University, Belgaum, Karnataka, India. **** Assistant Professor, Department of Civil Engineering, R.V. College of Engineering, Bengaluru, India. ***** Professor and Former Dean, R.V. College of Engineering, Bengaluru, India.

Shreenidhi, R., Nema, P.N., Sathishkumar, P., Shashank. B.S., and Shivakumar, B.L. (2018). Structural System Prediction Model Based on Cost - Time - Quality Analysis. i-manager’s Journal on Structural Engineering, 7(1), 41-47. https://doi.org/10.26634/jste.7.1.14282

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Analysis of Stability of Finite Slopes by Using Visual Slope

K. Ramya Chitra* , D. Kiranmaye**

* M.Tech Scholar, Department of Structural Engineering, Ashoka Institute of Engineering and Technology, Telangana, India. ** Assistant Professor, Department of Civil Engineering, Mahatma Gandhi Institute of Technology, Telangana, India.

Chitra, K.S., and Kiranmaye, D. (2018). Analysis of Stability of Finite Slopes by Using Visual Slope. i-manager’s Journal on Structural Engineering, 7(1), 48-57. https://doi.org/10.26634/jste.7.1.14278

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K.S.Vivek* , C. Ravi Kumar Reddy, K. S. Sai Ram*

* Assistant Professor, Department of Civil Engineering, VVIT, Andhra Pradesh, India.

Professor, Department of Civil Engineering, KHIT, Andhra Pradesh, India.

* Professor, Department of Civil Engineering, RVR & JC CE, Andhra Pradesh, India.

* Assistant Professor, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India.

** PG Scholar, Department of Civil Engineering, CVR College of Engineering, Hyderabad, India.

* Assistant Professor, Department of Civil Engineering, Government Engineering College, Palanpur, Gujarat, India.

** Professor, Department of Applied Mechanics, Sardar Vallabhbhai Patel National Institute of Technology (SVNIT), Surat, Gujarat, India.

* Research Scholar, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

** Professor, Department of Civil Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

shashank* , Pratul N. Nema, P. Sathishkumar, B. S. Shashank, B. L. Shivakumar

- Department of Civil Engineering, Visvesvaraya Technological University, Belgaum, Karnataka, India.

Assistant Professor, Department of Civil Engineering, R.V. College of Engineering, Bengaluru, India.

*** Professor and Former Dean, R.V. College of Engineering, Bengaluru, India.

* M.Tech Scholar, Department of Structural Engineering, Ashoka Institute of Engineering and Technology, Telangana, India.

** Assistant Professor, Department of Civil Engineering, Mahatma Gandhi Institute of Technology, Telangana, India.