The upper sub-grade of many countries is manly formed from a clayey soil. This kind of soil presents a weak California Bearing Ratio CBR value when it is soaked. The normal CBR test is done by applying a continuous load after placing surcharge weight ring on the compacted soil. The main purpose of this paper is to study the effect of the vertical confinement caused by the surcharge weight ring on the soaked CBR of soil. For this purpose, five CBR tests are performed to each of the ten different soils collected from Lebanese territories. Each CBR test is performed with different weight ring loading ranging from no ring till four rings. At the same time, identifications tests are performed on these soils in order to identify them. The CBR test results are linked to the soil properties obtained from the identification tests. The analysis shows that the vertical confinement has a positive effect on the soaked CBR of clayey soils. In general, the CBR value increases as the number of ring loadings increases. The synthesis of experimental results shows that the increment ratio of CBR for soil under a given number of rings is related to the liquid limit of the soil.
Keywords: Confinement pressure, CBR, Clay, Liquid limit, increment Ratio, Surcharge weight rings.
 A. N. Abdul Ghani et al., " Road submergence during flooding and its effect on subgrade strength", International Journal of Geomate, vol. 10, no. 21, pp. 1848- 1853, 2016.
 R.S. Rani et al., '"The behavior and performance of Geotextiles with reference to CBR value on clay soil", Applied Mechanics and Materials, vol. 877, pp. 224-229, 2018.
 R. B.C. Mamat, "Engineering properties of Batu Pahat soft claystabilized with lime, cement and bentonite for sub-grade in road construction" M.S. dissertation, Tun Hussein Onn Univ., Malaysia, 2013.
 W. Sas et al., "Determination of the Resilient Modulus MR for the lime stabilized clay obtained from the repeated loading CBR," Annals of Warsaw University of Life Sciences-SGGW, Issue 2, vol. 44, ISSN: 1898-8857, 2012.
 S.R. Phani Kumar and R.S. Sharma, "Effect of fly ash on engineering properties of expansive soils", Journal of Geotechnical and Geoenvironmental Engineering, vol. 7, no. 130, pp. 764-767, 2004.
 A. Senqupt et al., "Improvement of Bearing Ratio of clayey subgrade using compacted fly ash layer," Geotechnical and Geological Engineering, vol. 35, no. 4, pp. 1885-1894, 2017.
 N. K. Sharma and S.K. Swain, "Stabilization of a clayey soil with fly ash and lime: Amicro level investigation, Geotechnical and Geological Engineering", vol. 30, no. 5, pp. 1197-1205, 2012.
 S. S. Razouki and B. M. Salem, "Soaking-drying frequency effect on gypsum rich roadbed sand", International Journal of Pavement Engineering, vol. 15, no. 10, pp. 933-939, 2014.
 S. S. Razouki and B. M. Salem, "Gypsum sand resilient modulus during cyclic soaking and drying," International Journal of Pavement Engineering, vol. 18, no.2, pp. 108-120, 2017.
 ASTM Standard Test Methods for CBR of Laboratory- Compacted Soils, ASTM Standard D1883, 2001.
 ASTM Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Standard Effort, ASTM Standard D698, 2001.
[12 ] ASTM Standard Test Methods for Liquid Limit, Plastic Limit and Plasticity Index of Soils, ASTM Standard D4318, 2001.
 ASTM Standard Test Methods for Particle-Size Analysis of Soils, ASTM Standard D422, 2001.
 ASTM Standard Test Methods for Specific Gravity of Soil Solids by Water Pycnometer, ASTM Standard D854, 2001.
 ASTM Standard Test Methods for Amount of Material in Soils Finer Than the No. 200 Sieve, ASTM Standard D1140, 2001.
In the past decades, there have been a number of theoretical methods developed to calculate the lateral bearing capacity of deep foundations, and especially short and long piles. Most of these methods are based on the soil reaction models such as the coefficient of lateral pressure and soil passive pressure. The associated calculations would also usually follow the allowable strength design by applying appropriate factor of safety in regard to the bearing capacity of the surrounding soil or limited lateral deformation of pile and soil. However, with more applications of pile foundations in the structures in the recent years, and consequently more tests and investigations of the behavior of piles under lateral loads, it has become clearer that the behavior of a pile under lateral loads is more a problem of combined soil and structure reactions, where the deformation of the pile would heavily depend on the reaction of the soil, and vice versa. In the past few years, it was suggested that due to the complicated interaction of soil and pile, both behavior of pile and soil should be modeled simultaneously in a comprehensive analysis to have more realistic results. However, due to these complications, most of the analytical models have generally applied many simplifications to the models, which might sometimes lead to under designing (risky) or over designing (expensive) of the pile systems due to the inaccuracies of the models. Therefore, in this paper, a set of sensitivity analyses have been performed on a number of different short and long piles, using the neural network analyses. As the result, the effects of various parameters on the ultimate lateral bearing capacity of pile foundations were discussed to identify the most important ones. At the end, a new bearing capacity equation has been developed and proposed in the paper that would consider various weighted parameters of combined reactions of soil and pile that provides more realistic results.
Keywords: Lateral bearing capacity; Neural network; Pile foundation; Sensitivity analyses.
 Abu-Kiefa, M. A., (1998), "General Regression Neural Networks
for Driven Piles in Cohesionless Soils," Journal of Geotechnical
and Geoenvironmental Engineering, ASCE,124(12), pp 1177-85.
Basheer, I. A., (2001), "Empirical Modeling of the Compaction Curve of Cohesive Soil," Canadian Geotechnical Journal, 38(1), pp29-45.
Broms, B. B., (1964), "Lateral Resistance of Piles in Cohesive Soils," Journal of Soil Mechanics and Foundation Engineering., ASCE, 90(SM2), pp 27-63.
Chan, C. L. and Low, B. K., (2012), "Probabilistic analysis of laterally loaded piles using response surface and neural network approaches", Computers and Geotechnics, vol. 43, pp. 101-110.
Chan, W. T. and Chow, Y. K. and Liu L. F., (1995), “Neural Network: An Alternative to Pile Driving Formulas,” Journal of Computers and Geotechnics, 17, pp 135-56.
Das, S. K., (2013), "Artificial Neural Networks in Geotechnical Engineering: Modeling and Application Issues", Metaheuristics in Water, Geotechnical and Transport Engineering, pp 231-270.
Das, B. M., Sivakugan, N., (2018), "Principles of Foundation Engineering", 9th Edition, Cengage Learning, ISBN-13: 978- 1337705028.
Farfani, A. H., Behnamfar, F., and Fathollahi, A., (2015), "Dynamic analysis of soil-structure interaction using the neural networks and the support vector machines", Expert Systems with Applications, vol. 42 (22), pp. 8971-8981.
Garson, GD., (1991), "Interpreting Neural-Network Connection Weights," Artificial Intelligence Expert 6(7), pp47-51.
Goh, A. T. C., (1995a), "Empirical Design in Geotechnics Using Neural Networks," Geotechnique, 45(4), pp 709-14.
Goh, A. T. C., (1995b), "Modeling Soil Correlations Using Neural Networks," Journal of Computing in Civil Engineering., ASCE,9(4), pp 275-8.
Goh, A. T. C., (1996), "Pile Driving Records Reanalyzed Using Neural Networks," Journal of Geotechnical Engineering, ASCE,122(6), pp 492-5.
Hansen, B., (1961), "The Ultimate Resistance of Rigid Piles Against Transversal Force," Copenhagen, Danish Geotechnical Institute, 12, pp 5-9.
Haykin, S., 1999. Neural Networks: A Comprehensive Foundation. Prentice Hall, Upper Saddle River, New Jersey.
Ismail, A., and Jeng, D.S. (2011), "Modelling load–settlement behavior of piles using high-order neural network (HON-PILE model)", Engineering Applications of Artificial Intelligence, vol. 24 (5), pp. 813-821.
Jesmani, M., and Kamalzare, M. (2010), "Comparison between numerical and analytical solution of dynamic response of circular shallow footing", Electronic Journal of Geotechnical Engineering, vol. 15, pp. 1737-1750.
Jesmani, M., Nabavi, S. H. and Kamalzare, M. (2014), "Numerical analysis of buckling behavior of concrete piles under axial load embedded in sand", Arabian Journal of Science and Engineering, vol. 39, pp. 2683-2693.
Jesmani, M., Kasrania, A., Kamalzare, M., and Mehdipour, I, (2015), "Undrained vertical bearing capacity of pile located near soft clay slope", Journal of Engineering research, vol. 3 (3), pp. 21-38.
Jesmani, M., Kasrania, A., and Kamalzare, M., (2018), "Finite element modelling of undrained vertical bearing capacity of piles adjacent to different types of clayey slopes", International Journal of Geotechnical Engineering, vol. 12 (2), pp. 147-154.
Lee, I. M. and Lee, J. H., (1996), "Prediction of Pile Bearing Capacity Using Artificial Neural Net- works," Journal of Computers and Geotechnics ,18(3), pp 189-200.
Matlock, H. and Reese, L. C., (1962), "Generalized Solutions for Laterally Loaded Piles," Trans ASCE, 127, pp 1220-48.
Meyerhof, G. G., (1976), "Bearing Capacity and Settlement of Pile Foundations," J Geotech Eng., ASCE, 102(3), pp 196-228.
Nawari, N. O. and Liang, R. and Nusairat, J., (1999), "Artificial Intelligence Techniques for the Design and Analysis of Deep Foundations", Electronic Journal of Geotechnical Engineering, vol. 4-99.
Nejad, F.P., and Jaksa, M. B., (2017), "Load-settlement behavior modeling of single piles using artificial neural networks and CPT data", Journal of Computers and Geotechnics, vol. 89, pp. 9-21.
Portugal, J. C. and Seco e Pinto, P. S., (1993), "Analysis and Design of Pile Under Lateral Loads," In Proceedings of the 11th International Geotechnical Seminar on Deep Foundation on Bored and Auger Piles, Belgium, pp 309-13.
Poulos, H. G. and Davis, E. H., (1980), "Pile Foundation Analysis and Design," New York, Wiley.
Rausche, F. and Moses, F. and Goble, G. G., (1972), "Soil Resistance Predictions from Pile Dynamics," Journal of Soil Mechanics and Foundations, vol. 98, pp 917-37.
Rumelhart, D. E, Hinton, G. E, Williams, R. J., (1986), "Learning internal representation by error propagation", In: Rumelhart, D. E., McClelland, J. L. (Eds.), Parallel Distributed Processing, vol. 1. MIT Press, Cambridge, MA (Chapter 8).
Shahin, M. A. and Maier, H. R. and Jaksa, M. B., (2002), "Predicting Settlement of Shallow Foundations Using Neural Network," Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 128(9), pp785-93.
Tarawneh, B., (2013), "Pipe pile setup: Database and prediction model using artificial neural network", Journal of soils and foundations, vol. 53 (4), pp. 607-615.
Transportation Research Board, (1999), "Use of Artificial Neural Networks in Geomechanical and Pavement Systems, Transportation Research Circular E-C012, Prepared by A2K05(3) Subcommittee on Neural Nets and Other Computational Intelligence-based Modeling Systems", Transportation Research Board, Washington, USA.
Teh, C. I. and Wong, K. S. and Goh, A. T. C. and Jaringam, S., (1997), "Prediction of Pile Capacity Using Neural Networks," Journal of Computing in Civil Engineering, vol. 11 (2), pp 129- 38.
Zeghal, M., Khogali, W., (2005), "Predicting the Resilient Modulus of Unbound Granular Materials by Neural Networks", BCRA, Trondheim, Norway 1-9.
Zhang, W., and Goh, A., (2016), "Multivariate adaptive regression splines and neural network models for prediction of pile drivability", Geoscience Frontiers, vol. 7 (1), pp. 45-52.
This study was to assess the durability characteristics of limewood ash stabilized lateritic soils. This was carried out to establish it as a more environmentally friendly and cheaper alternative to cement addition under moisture condition as is practice in standard stabilization techniques for pavement construction. Field sampling and testing were carried out in accordance to British Standard 1337 of 1992. The soil samples were subsequently stabilized at constant lime contents of 2% and 4%, with variations of wood ash at 2%, 4% 6% and 8% and all percentages used were by the weight of dry soil to determine the influence of the stabilizing agents on the engineering properties of the soils. Durability tests were carried out according to BS 1924: Part 2: 1990. Specific gravity was gotten to be 2.66, while grain size analysis value of 2.56%, 86.06% and 11.38% respectively was obtained for Gravel, Sand and Fine portions. The soils were classified as Fair to Poor, Clayey Soil (A-7-6) using the AASTHO classification system and Clay of High Plasticity (CH) in the Unified Classification System. The lateritic soils were of relatively high plasticity.
Stabilization of the lateritic soil using lime in addition with wood ash was quite effective. Significant increase from 200.5kN/m3 to 532.8kN/m3 and 571.5kN/m3 for 2% and 4% Lime addition at 6% Saw Dust Ash Content were obtained upon stabilization. Durability tests carried out on the samples showed that a resistance to loss in strength within the range of 67.33% to 75.33% with maximum value obtained for samples with 4% Lime and 6% Wood Ash addition. Although, the values fell short of the 80% used as evaluation criterion, the improvement of the soil shows effectiveness under poor moisture conditions, without losing much of their strength.
Keywords: Stabilization, Lateritic Soil, Lime, Wood Ash, Strength, Durability
 G. O. Adeyemi, R.A. Owosanya and F.C. Anokwu, “Some
geotechnical properties of a cement stabilized granite gneissderived
lateritic soils from Ile-Ife, SW Nigeria.” J. Appl. Sci. and
Tech., vol.3, pp. 8-12, 2003.
 Agbede, I.O.; and Joel, M. 2011. Effect of carbide waste on the properties of Makurdi shale and burnt bricks made from the admixtures. American Journal of Scientific and Industrial Research 2(4): 670-3.
 AlRawas A. A. and Goosen M.F.A., 2006. Expansive soils- Recent advances in characterization and treatment.
 American Association of State Highway and Transportation Officials, 1986. AASHTO Guide for Design of Pavement Structures, 1986, Volume 2. American Association of State Highway and Transportation Officials.
 Amu O., & Babajide S., 2011. Effects of Bamboo Leaf Ash on Lime Stabilized Lateritic Soil for Highway Construction. Research Journal of Applied Sciences, Engineering and Technology. 3.
 Amu, O. O., Adeyeri, J. B., Oduma, E. W. and Fayokun, O. A. (2008): Stabilization Characteristics of Lime on Palm Kernel Blended Lateritic Soil. Trends in Applied Sciences Research, 3: 182-188.
 Bell. F.G., 1996. “Lime stabilization of clay minerals and soils”, Engineering Geology, vol. 42, pp 223-237.
 British Standards Institution, 1990. BS 1377-2:1990 Methods of test for soils for civil engineering purposes. Classification tests. Retrieved from http://www.bsi.com/
 British Standards Institution, 1990. BS 1924-2:1990 Stabilized materials for civil engineering purposes. Methods of test for cement-stabilized and lime-stabilized materials. Retrieved from http://www.bsi.com/
 British Standards Institution, 1996. BS 12-1996- Specification for Portland Cement. Retrieved from http://www.bsi.com/
 Consoli, N. C., Lopes, L. S. Jr., and Heineck, K. S., (2009a): Key parameters for the control of lime stabilized soils. Journal of Materials in Civil Engineering; 21(5): 210-216.
 Cristelo N, Glendinning S, and Jalali S. (2009b): Subbases of residual granite soil stabilized with lime. Soils and Rocks; 32(2): 83-88.
 Das D.K., 2000. “Micronutrients: their behavior in soils and plants Kalyani publishers.
 Dash S. K., and Hussain M. (2012): Lime stabilization of soils: reappraisal. Journal of Materials in Civil Engineering; 24(6): 707-714.
 Federal Ministry of Works & Housing, 1997. General Specifications (Soil Testing). Director of Federal Highways, Federal Ministry of Works & Housing Headquarters, Abuja, Nigeria, Government of The Federal Republic of Nigeria Volume II Revised 1997
 Garber J.N. & Lester A. H., 2018. Traffic and highway engineering / Nicholas J. Garber, Lester A. Hoel.. SERBIULA (sistema Librum 2.0).
 Hughes, P.N.; and Glendinning, S. 2004. Deep dry mix ground improvement of a soft peaty clay using blast furnace slag and red gypsum. Quarterly Journal of Engineering Geology and Hydrogeology 37(3): 205-16.
 Iorliam A.Y.; Agbede I.O.; and Joel, M. 2012a. Effect of cement kiln dust (CKD) on some geotechnical properties of black cotton soil (BCS). Electronic Journal of Geotechnical Engineering 17(H): 967-77.
 Locat, J., M.A. Berube and M. Choquette, 1990. Laboratory investigations on the lime stabilization of sensitive clays: Shear strength development. Can. Geotech. J., 27(3): 294-304.
 Medjo Eko, R.; and Riskowski, G.L. 2004. A procedure for processing mixtures of soil, cement, and sugar cane bagasse. Agricultural Engineering International: the CIGR (Commission Internationale du Genie Rural) Journal of Scientific Research and Development 3: 1-5, Manuscript BC 99 001.
 Millogo Y, Morel JC, Traoré K, and Ouedraogo R. (2012): Microstructure, geotechnical and mechanical characteristics of quicklime-lateritic gravels mixtures used in road construction. Construction & Building Materials; 26(1): 663-669
 O'Flaherty, C.A., 1974. Highways Vol. 1 Highways and Traffic. 2nd Edition, Edward Arnold Publishers Ltd., London.
 Okafor, F.O.; and Okonkwo, U.N. 2009. Effects of rice husk ash on some geotechnical properties of lateritic soil. Leonardo Electronic Journal of Practices and Technologies (LEJPT) 8(15): 67-74.
 Okunade E.A., 2008. The Effect of Wood Ash and Sawdust Admixtures on the Engineering Properties of a Burnt Laterite- Clay Brick. Journal of Applied Sciences, 8: 1042-1048.
 Ola, S. A. (1977): The Potentials of Lime Stabilization of Lateritic Soils. Engineering Geology; 11(4): 305-317
 Ola, S. A., 1974. Need for Estimated Cement Requirements for stabilization of Laterite Soils. Journal of Transportation Engineering, Division, ASCE, 100 (2): 379-388.
 Oriola, F.; Moses, G. 2010. Groundnut shell ash stabilization of black cotton soil. Electronic Journal of Geotechnical Engineering 15(E): 415-28. Available:
 Osinubi K.J and Katte, V.Y., 1997. Effect of Elapsed Time after Mixing Gram Sise and Plasticity Characteristics, I: Solid- Line Mixes, NSE Technical Transactions Vol.33, 4.
 Patel H.S., 2012. A Review on Effects of Stabilizing Agents for Stabilization of Weak Soil. Civil and Environmental Research 2: 6.
 Ugbe F.C., 2011. Basic Engineering Geological Properties of Lateritic Soils from Western Niger Delta. Research Journal of Environmental and Earth Sciences, 3(5): 571-577.
Presented in this study is a combined approach for determining turning movements at traffically indeterminate T-junctions with U-turns. This approach combines the use of turning movement counts for the three redundant turning movements together with a mathematical model to be developed that relies on link counts and a volume count at a chosen section within the intersection. The model consists of a consistent system of six linearly independent algebraic equations in nine unknowns. The paper shows that the use of an internal section for volume count inside the junction is required for the system of equations to be linearly independent. For each chosen internal section within the junction, the Gaussian elimination process on the system of equations shows that there is a certain traffic stream (turning movement) that can be determined directly as it is independent of the three redundant traffic streams. The choice of the three redundant turning movements, determined manually or by video-camera, is subjected to some restrictions depending on the internal section used. The choice of all three Uturns as the redundant turning movements is always correct and possible. The paper reveals also that other combinations of three redundant turning movements, are also possible. Such a combination represented by two right-turning movements with a U-turn, was applied successfully. The application of the developed approach on a T-junction with U-turns and known O-D matrix validated this economic approach. One case study for a T-junction utilizing traffic data collected from the urban area of a city in Iraq, are set up to demonstrate the application of the proposed combined approach. The traffic data was collected both manually and by automatic traffic counters. Before using the automatic counts in the developed approach, they were corrected for undercounting and inconsistency of in- and outflows. The estimated turning movements using the developed approach are in good agreement with those obtained manually indicating the reliability of the developed approach for T-junctions with U-turns.
Keywords: mathematical modeling, O-D matrix, traffic engineering, T-junction, traffically indeterminate intersections, turning movements.
 J.E. Hummer, Intersection and Interchange Design, Chapter 10
in the Handbook of Transportation Engineering, Second edition,
New York, McGraw-Hill, 2011.
 M. Owais, G. Moussa and K. Hussain. "Robust deep learning architecture for traffic flow estimation from a subset of link sensors," ASCE Transportation Engineering Journal, Part A: Systems,vol.146 (1),2020. ISSN (Online):247-2893. https://doi.org/10.1061/JTEPBS.0000290.
 S.S.Razouki S.S. and K.S. Jadaan, "Estimation of turning movements at three-arm rotaries.," Dirasat, An International refereed research Journal, Natural and Engineering Sciences, vol.24 (2), pp. 305-312,1997.
C. Mallikarjuna ,A. Phaninda, ,R.K. Rao ,"Traffic data collection under mixed traffic conditions using video image processing," ASCE, Transportation Engineering Journal, vol. ,135 ( 4), pp. 174-182, 2009.
 T.R. Currin , Introduction to traffic engineering, a manual for data collection and analysis, Second Edition, U.K., Cengage Learning, 2013.
 N.Y. Al-Shaekhli ."Optimization of number of observers for determining traffic movements at three-arm road junctions,". M.Sc. thesis, College of Engineering, University of Baghdad, Iraq, 1993.
 K. Jadaan, "Accuracy of turning flow estimates at road junctions," Journal of Transportation Engineering, ASCE ,vol. 115(4), pp.438-449, 1989.
 O. Adebisi," Improving manual counts of turning traffic volumes at road junctions," ASCE , Journal of Transportation Engineering, vol. 113 (3),pp. 256-267,1987.
 P. Liu , X. Qu, H. Yu, W. Wang, and B. Cao, "Development of a VISSIM simulation model for U-turns at unsignalized intersections,". ASCE, Transportation Engineering Journal ,vol. 138 (11),pp 1-16, 2012. DOI: 101061/(ASCE)TE.1943- 5436.0000438
 R Ashworth, Highway Engineering. London, Heinemann Educational Books, 1986.
 M. Jeffreys and M. Norman, "On finding realistic turning flows at road junctions.," Traffic Engineering and Control, vol. 18(1),pp. 19-25, 1977.
 A. Chen , P. Chootinan, S. Ryu, , M. Lee, and W. Recker, 2012. "An intersection movement estimation procedure based on path flow estimator, " Journal of Advanced Transportation, vol. 46, pp. 161-176. DOI: 10.1002/atr.151
 S.M. Eisenman ,and G. List , "A technique for data collection and estimation of turning movements at roundabouts," Proceedings of the 84th Annual Conference of the Transportation Research Board, 2005, Washington D.C.
 M.G. Bell, "The estimation of junction turning volumes from traffic counts: the role of prior information," Traffic Engineering and Control, vol. 25 (5),pp. 279-283,1984.
 P. Zheng, and M. McDonald, "An investigation on the manual traffic count accuracy". 8th International Conference on Traffic and Transportation Studies, Procedia – Social and Behavioral Sciences, vol. 43, pp. 226-231, 2012.
 A. Saha, S. Chandra and I. Ghosh ," Delay at signalized intersections under mixed traffic conditions," ASCE, J. Transp. Eng., Part A: Systems, vol. 143(8): 04017041, 2017.
 L.C. W ylie a nd C .R , B arrett, " Advanced engineering mathematics," Fifth edition, London, McGraw-Hill Book Company, 1985.
 H.J. Van Zuylen, "The estimation of turning flows on a junction," Traffic Engineering and Control, vol. 20 (11), pp. 539- 541, 1979.