The document discusses the development of a Python program for designing rectangular indeterminate beams, achieving 99.98% accuracy compared to traditional manual and commercial software methods. It highlights the advantages of using Python in civil engineering, addressing issues with expensive licensing and manual errors, while promoting analytical skills among students. The initiative aims to create an open-source, user-friendly software that contributes to the evolution of a 'civil programming community.'

1. DESIGN OF RECTANGULAR
INDETERMINATE BEAMS
USING PYTHON
PRESENTATION
BY
A. SUNEEL B.Tech
UNDER THE GUIDANCE OF
Mr. M. CHANDRAKANTH M. Tech

2. ABSTRACT
• Now a days, automation/automated softwares becomes as a primary tool in all fields of engineering.
• In civil engineering, design and analysis of structures/structural elements, soil mechanics, Remote sensing activities is
mandatory along with high accuracy followed by proper maintenance over a time with the expanded underlying
setups.
• A numerous commercial programs are available or by using MS-Excel spreadsheet or any other computer programs
in market. But students are not so aware of the applications, subject etc.,
• Through this paper, a program was developed with the support of Python, and the results obtained from this
application shows that 99.98% accuracy, when compared to manually calculated problems and software named
STAAD which analyses structures and structural components.
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3. LITERATURE REVIEW
1. Applicability of Python in Civil Engineering: Review by Mr. Arshad Quraishi, Mr. N. K. Dhapekar.
• Description: Study indicates a review on the application of python programming language in civil
engineering and focused on bringing out advantages of using Python over current practices of
computations for different parameters.
2. Use of Python Programming for interactive design of Reinforced Concrete Structures. Shivaji M. Sarvade1 , Sachin M.
Pore2
• Description: Study indicates an Implementation of Python programming in undergraduate design
course will improve the analytical skills of the students and have significant contribution to make them
design industry ready professionals.
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4. PROBLEM STATEMENT
• Computer applications available in market are having expensive licencing agreement, which are limited
in period and also user count, Making it difficult for renewal of licence each and every time.
• Although MS-Excel is famous but it also has its limitations, i.e., cannot be used for tedious calculations.
• Manual methods give deviations in result, due to errors, miscalculations, etc., and also improper display
of output data.
• Softwares available in market requires prior skills to operate them and also in some cases report
generation takes more time.
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5. SOFTWARE AND HARDWARE
SOFTWARE
• Python, python IDLE
• Staad pro
• Google colab
• Jyupter notebook
• Anaconda navigator
• PyCharm-text editor
HARDWARE
• ANDRIOD MOBILE with android
compatibility 8 or above
• APPLE DEVICES: mobiles IOS-14+, mac-
books MACOS-10+
• Windows 7, 8, 10, 11 compatible
laptops, PCS, etc.
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6. BEAM ANALYSIS AND DESIGN
 Manual - Moment distribution method, slope deflection method.
 Software – STAAD PRO
 Automated by python - math module in python
METHODOLOGY
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7. ALGORITHM AND DATA
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Preliminary data set for deflection criteria design
Curve fitted value for getting dimensions of beam
Source: IS 456 2000

8. OUTPUT:
Design the beam wit U.D.L. over all the
spans i.e., 30 kN/m having 4 supports as
shown in figure and located at a distance
of 4m, 7 m, 11 m from left end. Find end
moments, draw S.F.D, B.M.D
RESULTS
MODEL PROBLEM DESIGN
COMPARISON OF RESULTS
CASES Area of steel ACCURACY
%
manual programming
Singly reinforced
BEAM 1
277.096 276.847 99.91
Singly reinforced
BEAM 2
672.045 671.844 99.97
USER INTERFACE OF BEAM DESIGN CALCULATOR
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Proposed depths by model

9. ADVANTAGES AND APPLICATIONS
ADVANTAGES
• Eliminating most of the manual work by one time investment of time in
programming.
• The final application is an open source, i.e., customizable for
programmers. Predefined report is created, resulting in fast report
preparation.
• As the deflection criteria is the heart of the application; it is achieved by
machine learning concept of curve fitting, resulting in economical
sections.
• Number of repetitions are done in less time. Hence, the entire load is
taken by the system`s processor. No clumsiness in the data allocation
due to predefined and perfect variable declaration.
APPLICATIONS
• We can create a number of applications in every field of civil engineering
like:
• Finite element (FEM) applications in Structural analysis.
• Forecasting of population for urban planning, water supply distribution &
sewerage system.
• Soil simulation and modeling in Geotechnical engineering.
• Construction planning and management.
• Risk evaluation and moderation, for example, expectation of floods,
seismic tremors, cyclones and other natural calamities.
• To anticipate traffic patterns in Highway designing.
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10. DISCUSSIONS AND CONCLUSION
• Design of rectangular beam has done by using manual methods and python programming. The results
obtained from our program(s) shows 99.98% accuracy as compared to manually calculated problems.
• This program just resembles the actual licencing software which is costly, but we made it with free of
cost. This is first step, for which ultimately creates a free licencing, user-friendly software at absolutely
free of cost.
• we can say that implementing software languages in Civil Engineering improves the analytical skills of
the students and have significant contribution in the fields of Structural Engineering, Design of
Reinforced Concrete/Steel Structures, Remote Sensing and GIS and so on.
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11. FUTURE SCOPE
• This is a classical example for the era of data science and AI, where we can make our own applications
which were cost and time effective, while doing any project.
• As it is available at free of cost, ultimately it results in a development of new domain in software zone
i.e., “CIVIL PROGRAMMING COMMUNITY” similar to “python community”, “java community” etc. which
will help to every civil engineer on the globe to solve their problems through programming.
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12. REFRENCES
• Applicability of python in civil engineering: review mr. Arshad quraishi, mr. N. K. Dhapekar e-issn: 2395-0056,
p-issn: 2395-0072.
• IS 456-2000 plain and reinforced concrete – code of practice [ced 2: cement and concrete].
• IS 875 (part 1) (1987, reaffirmed 2008): code of practice for design loads (other than earthquake) for building
and structures. Part 1: dead loads – unit weights of building materials and stored materials (second revision).
Udc 624.042: 006.76
• IS 875 (part 2) (1987, reaffirmed 2008): code of practice for design loads (other than earthquake) for buildings
and structures. Part 2: imposed loads (second revision). Udc 624.042.3:006.76
• Design and Detailing of Reinforced Concrete Structures by M.R Dheerendhra Babu, Falcon publishers
• Webrefrences:
• google colabhttps://colab.research.google.com/notebooks/basic_features_overview.ipynb
• Guido van Rossum, Python Tutorial, http://docs.python.org/
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13. THANK
YOU
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