Risk Assessment in Geotechnical Engineering .pptx
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The document provides an introduction to risk assessment in geotechnical engineering, focusing on prediction methods and factors affecting the accuracy of load-bearing capacity predictions for foundations. It discusses various prediction competitions, highlights common errors in predictions, and emphasizes the need for better design methodologies to manage uncertainty in engineering. Additionally, it addresses the concept of tolerable risk in structural design and references several sources for further reading.
Risk Assessment in Geotechnical Engineering .pptx
- 1. Introduction to Risk Assessment in Geotechnical Engineering Prof. Samirsinh P Parmar Mail: samirddu@gmail.com Asst. Professor, Department of Civil Engineering, Faculty of Technology, Dharmsinh Desai University, Nadiad-387001 Gujarat, INDIA
- 2. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 2 Content of the presentation • Prediction from Symposium • In situ field testing layout • Load test set-up • Methods used for prediction • Predicted design load • Why predictions went wrong??? • Design methods, factor of safety, tolerance limit etc. factors. • Reference books for geotechnical investigations.
- 3. 3 Prediction Symposium at TAMU (1994) 5 square footings ranging in size 1-3 m were constructed and loaded to 0.15 m of displacement at Texas A&M University National Geotechnical Experimentation Site (NGES). 150 requests received and 31 participants from 9 countries finally sent their predictions Prediction results were: • Qdesign load=Min(Q25(predicted), Q150(predicted)/3) • Factor of Safety (FS)=Qfailure load (=Q150)/Qdesign load M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India.
- 4. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 4 Footing 1 Footing 3 Footing 1 Footing 4 Footing 5 N orth 1.5 m 1.5 m 3 m 3 m 3 m 3 m 2 m 2 m 1 m 1 m 1 m 1 m 1 m 1 m Drilled shaft Drilled shaft Drilled shaft Drilled shaft Drilled shaft 8.5 m 4.25 m 8.5 m Prediction Symposium at TAMU (1994)
- 6. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 6 In-situ Field Testing Layout with Auger Hole Location
- 8. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 8 Methods Used for Prediction Soil Tests Used
- 9. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 9 Predicted Loads at 25 and 150 mm Settlements
- 12. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 12 Prediction of Loads Producing 25 mm settlement (3 m footing) North footing South footing
- 13. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 13 Prediction of Loads Producing 150 mm settlement (3 m footing) North footing South footing
- 16. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 16 Evaluation of Prediction Methods – For Bearing Capacity
- 17. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 17 Evaluation of Prediction Methods – For Settlements
- 18. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 18 Choosing the Best Prediction Method
- 19. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 19 Prediction Results For 1 m footing: • Predicted/Measured load for 25 mm settlement: Range=0.069-1.294, mean=0.71, Stdev=0.3, measured value=1 • Predicted/Measured load for 150 mm settlement: Range=0.115-2.279, mean=0.65, Stdev=0.45, measured value=1 • Predicted design load: Range=59-1100 kN, Mean=377 kN, Stdev=229, Measured value=580 kN • Range of FS predicted = 2.23-29.49, Mean FS = 6.64, standard deviation of FS=5.23, and measured FS=3 • Settlement under design load: Range of prediction= 0.5-48 mm, Mean=6.1 mm, Stdev=9.5 mm, and measured value=9.5
- 20. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 20 Imperial college prediction competition • Performance of a single driven steel pile • 34-page information on the ground conditions and as- constructed pile operations is provided to all participants • Predictions were judged against extensive field testing results • 16 predictions from 7 countries – 9 consultants & 4 contractors • Entrants were asked to provide the total load capacity of pile, shaft and base capacity components, load-settlement curve • Unsurprisingly wide scatter of results and conforms that the capacity of piles can be predicted reliably only to about plus or minus 60%.
- 21. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 21 Footing Settlement Prediction Competition • School of Civil and Resource Engineering, the University of Western Australia (http://www.civil.uwa.edu.au/about/research/research_areas/foo ting_settlement_prediction_competition) • Industry professionals are invited to provide footing settlement predictions for four instrumented footings that have recently been load tested at a well characterised sand site in Perth, Australia. • Participants are asked to predict: The settlement of each footing under a load of 100 kN and 180 kN. The footings were incrementally loaded to 200kN within approximately two hours, and creep was small during holding periods. The settlement at a depth of B/2 below each footing for the same loads previously mentioned. (where B is the footing width)
- 22. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 22 Footing Number Width,B (m) Thickne ss (m) Embedme nt (m) 1 1.5 1.0 1.0 2 1.0 1.0 1.0 3 1.0 1.0 0.5 4 0.67 1.0 1.0 Footing 1 Footing 2 Footing 3 Footing 4 • Centre-centre spacing between footings =3m • Seismic/standard cone penetration test & dilatometer test performed within 0.5m of the side of each footing Footing geometry & in-situ test locations D M T 1 C P T 1 D M T 2 S C P T 2 D M T 3 C P T 3 D M T 4 S C P T 4
- 24. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 24 Attributed to one or all?? Natural variability Irrelevant soil properties • Errors in field testing Location of drilled shafts, number of drilled shafts, method of testing • Errors in laboratory testing Equipment, instrumentation Collection of samples in disturbed/undisturbed state Simulating field conditions • Statistical errors due to limited sampling Errors with using simplified transformation models, ex. Mohr circles, bearing capacity, settlement, Human errors, ex. lacking the understanding of nature and applying the basic principles of science to solve engineering problems
- 25. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 25 Factor of safety – a better tool to measure safety?? Effect of variability on design of shallow foundations (Lacasse 2001)
- 29. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 29 Need for a better design methodology • High construction costs • Increased costs of consequence • rapid urbanization and • public awareness draw the attention of practicing engineers and researchers to safer, economical and reliable designs
- 31. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 31 Effect of Wrong Predictions (Uncertainty) • Uncertainty in analysis and design Recognized significant and varying degrees of uncertainty inherently involved in the design process Allowance must be made for these uncertainties in the designs Traditional approaches simplify the problem by considering the uncertain parameters to be deterministic use lumped factors of safety (empirical, based on past experience) to account for the uncertainties propagating in the design decisions
- 32. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 32 Ancient way of design Designs by experience worked well because changes in construction methods and materials were at that time very slow (Allen, 1994) Industrial revolution soon changed the approach based on experience because materials and construction methodologies started to change rapidly To accommodate these rapid changes, civil engineers had to develop more rational design procedures
- 33. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 33 The basis of the design is to ensure that throughout the structure, when it is subjected to the ‘working’ or service applied load, the induced stresses are less than the allowable stresses No proper study and implementation of effects of individual sources of uncertainty No proper quantification of safety or risk involved Effect of uncertainties arriving from number of disparate sources on the output is lumped together and a single value of FS is used to account for all the uncertainties, based on judgment of designer, with no distinction made as to whether it is applied to material strength and resistances or to load effects Conventional Analysis
- 34. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 34 FS values selected for design reflect past experience and the consequence of failure The more serious the consequence of failure or the higher the uncertainty, the higher the factor of safety Suggesting the factor of safety without knowing the sources and amount of uncertainty involved in the evaluation of design parameters bears the resemblance such as suggesting the presumptive bearing capacity without having proper knowledge of the soil shear strength parameters. Conventional Analysis
- 35. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 35 Motivation for an alternative design approach Comparable variations in material properties!!
- 39. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 39 Factor of safety?? Probability density function of FS=R/S Practical implications of effect of variability on design of shallow foundations (Lacasse 2001)
- 40. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 40 Does it appropriate to neglect such high degree of soil property variations associated with mean design parameter??? Practical implications of effect of variability on design of shallow foundations (Lacasse 2001) Motivation Probability density function of FS=R/S
- 41. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 41 Identified its importance way back in 1960 Study of individual sources of uncertainty Rational and unified framework for quantitative analysis of uncertainty and assessment of risk Uniform distribution of safety levels among the different components Useful for formulation of trade-off studies for Planning Design , and Decision making, considering the economical aspects of the study Engineers are reluctant due to unavailability of a large set of sample data and mathematical sophistication Probabilistic approach
- 43. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 43 Tolerable Risk ‘Risks that people (or society) are willing to accept in specific situations or from natural and man-made works’ Tolerable risk refers to a willingness to live with a risk so as to secure certain benefits and in the confidence that risk is being properly controlled or managed. Designs must ensure an acceptable risk or a required level of safety.
- 44. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 44 Levels of acceptable risk, MacGregor (1976): Avoidable risks connected with daring people: 10-3 per year Avoidable risks connected with careful people: 10-4 per year Unavoidable risks: 5 x 10-5 per year Structural collapse is an unavoidable risk (so, design pf = 5 x 10-5 per year) This level of risk corresponds to the target reliability index used in the calibration of the National Building Code of Canada (NBCC) for structural design Tolerable Risk
- 47. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 49 Parmar, S. P. (2022). A Comprehensive Analysis of Foundation Design Approaches. Journal of Geotechnical Studies (e-ISSN: 2581-9763), 28-37. https://www.researchgate.net/profile/Samirsinh-Parmar/publication/ 367561355_A_Comprehensive_Analysis_of_Foundation_Design_Approaches/links/63d8ebf664fc8606380031f6/A-Comprehensive- Analysis-of-Foundation-Design-Approaches.pdf
- 48. M.Tech. Sem-1, DoCL, DDU, Nadiad, Gujarat, India. 50 Parmar, S., & Patel, R. M. (2021). Bearing Capacity of Isolated Square Skirted Foundation on Cohesionless Soil: An Experimental and Analytical Study. Journal of Advances in Geotechnical Engineering, 4(2), 1-11.