CONSTRUCTIVE AND PROBABILISTIC ANALYSIS OF EXCAVATED PILES WITH LOST METALLIC SHIRT

This work brings in its scope some analyzes around the constructive methodology of a case study that refers to the implantation of a dolphin (a structure that in this case has the purpose of mooring ships) at Pier III, located in Ponta da Madeira Maritime Terminal, in the city of São Luís, Maranhão, and with a focus on the process of building its infrastructure, more precisely the adopted foundation. This type of work, being port and in a maritime environment is called offshore, the foundation used in this case is the deep type, more precisely called piles excavated with a lost metallic shirt whose constructional scope will be detailed in this work, from the driving from shirts to concreting the piles that made up the system. The theme is approached from a practical and theoretical point of view, with a probabilistic study of the load capacity of foundations based on geometrical data from surveys carried out in the region, in order to define results that include any variability of the location and guarantee functionality and safety necessary for the foundation to achieve the project's objectives and be optimized throughout its useful life. The analysis of the probability of rupture was made using the semi-empirical method of Aoki-Velloso, combined with the First Order Second Moment method in order to compare the result achieved with the established parameter values. The work also aims to serve as a basis for future guidance and guidance on the topic, which does not have such a vast bibliography, mainly in view of the installation of new similar projects in the region and in other locations.

Probabilistic Liquefaction Potential of Kathmandu Soil Based On Standard Penetration Tests

Despite being a liquefaction susceptible zone, Kathmandu Valley soil in Nepal has limited studies on liquefaction potential and most of them are based on the deterministic approach. Although this method is widely used, it ignores the uncertainties of seismic parameters such as peak ground acceleration, amax, and earthquake magnitude, Mw as well as the inherent variabilities of soil layers, in-situ testing procedures, and geotechnical properties. On the other hand, the probabilistic approach helps assess the liquefaction potential by considering all these uncertainties. In this study, we assess the liquefaction hazard in the Kathmandu Valley using the first-order second-moment (FOSM) method as a probabilistic approach for liquefaction hazard assessment. The assessment is done for three likely-to-recur scenario earthquakes utilizing the geotechnical data of 1510 boreholes. The soils are characterized geotechnically to further assess susceptibility criteria of liquefaction in the valley. The assessment reveals that the central part of the valley is more vulnerable to liquefaction than other parts and the liquefaction probability increases with increasing depth up to 9 m, after which has geared down the value. Moreover, a relationship between the probability of liquefaction (PL) and the factor of safety (FS) against liquefaction is established. The hazard maps prepared for different earthquake scenarios can be useful for future infrastructure planning in Kathmandu Valley.

Probabilistic Design of Retaining Wall Using Machine Learning Methods

Retaining walls are geostructures providing permanent lateral support to vertical slopes of soil, and it is essential to analyze the failure probability of such a structure. To keep the importance of geotechnics on par with the advancement in technology, the implementation of artificial intelligence techniques is done for the reliability analysis of the structure. Designing the structure based on the probability of failure leads to an economical design. Machine learning models used for predicting the factor of safety of the wall are Emotional Neural Network, Multivariate Adaptive Regression Spline, and SOS–LSSVM. The First-Order Second Moment Method is used for calculating the reliability index of the wall. In addition, these models are assessed based on the results they produce, and the best model among these is concluded for extensive field study in the future. The overall performance evaluation through various accuracy quantification determined SOS–LSSVM as the best model. The obtained results show that the reliability index calculated by the AI methods differs from the reference values by less than 2%. These methodologies have made the problems facile by increasing the precision of the result. Artificial intelligence has removed the cumbersome calculations in almost all the acquainted fields and disciplines. The techniques used in this study are evolved versions of some older algorithms. This work aims to clarify the probabilistic approach toward designing the structures, using the artificial intelligence to simplify the practical evaluations.

Reliability analysis of truck escape ramp design

The truck escape ramp design presented by the Transportation Association of Canada is based on deterministic values of the design variables which include the required stopping distance, design speed, rolling resistance, and grade. Currently, a reliability analysis of the design of truck escape ramps does not exist. This report presents two methods used to analyze the reliability of truck escape ramp design; the first order second moment reliability method and the advanced first order second moment reliability method. These methods do not rely on deterministic values rather the mean and variance (moments) of each random variable’s probability distribution. Each reliability method was used to analyze truck escape ramps with one grade and two grades, for a total of four cases. The results of each case are provided and discussed along with an application to two existing truck escape ramps. The results show that the advanced first order second moment reliability method ensures more accurate results as well as a larger safety margin in comparison to the first order second moment method due to the nature of the methodology itself which considers design points.

Reliability analysis of truck escape ramp design

The truck escape ramp design presented by the Transportation Association of Canada is based on deterministic values of the design variables which include the required stopping distance, design speed, rolling resistance, and grade. Currently, a reliability analysis of the design of truck escape ramps does not exist. This report presents two methods used to analyze the reliability of truck escape ramp design; the first order second moment reliability method and the advanced first order second moment reliability method. These methods do not rely on deterministic values rather the mean and variance (moments) of each random variable’s probability distribution. Each reliability method was used to analyze truck escape ramps with one grade and two grades, for a total of four cases. The results of each case are provided and discussed along with an application to two existing truck escape ramps. The results show that the advanced first order second moment reliability method ensures more accurate results as well as a larger safety margin in comparison to the first order second moment method due to the nature of the methodology itself which considers design points.

Optimization of Culvert Dimensions and Reliability

A culvert is a hydraulic structure constructed to increase the water carrying capacity away from highway and buildings in the environment. Culverts have received less attention over the years because they are not highly visible, even if they have sufficient performance. Culverts offer much smaller investment options compared with bridges and in many cases they have replaced small bridges. Culverts are also less hazardous in the case of failure. This study brings together results about several variables of culverts including optimum dimensions, shapes, materials and inlet configurations. During culvert design, hydraulic testing was required for sizing of structures, where risk analysis calculation has been performed regarding the probability of inadequate capacity of culvert design to pass floods. The failure probability is estimated using the advanced first order second moment (AFOSM) method. Therefore, the methodology ensures the design of the hydraulic structure fulfills the required role, while minimizing its future effects in the environment.

Reliability Analysis Approach For Intersection Sight Distance Of A Symmetrical Single-Lane Roundabout

The current intersection sight distance values on a roundabout provided by ASSHTO and other worldwide guidelines are based on deterministic methods considering only single variables as the design inputs. However, most of the input design variables such as entering speed and the deceleration rate are random variables which are stochastic in nature. Therefore, this study proposes a reliability analysis approach to add uncertainty to the current deterministic models. Two different reliability approaches; the first order second moment and advanced first order second moment are presented in this paper. These approaches rely on the normal distribution of the random variables using the mean, variance and the covariance of the probability distribution of each variable rather than the single deterministic values. Results show that the AFOSM reliability methodology provides a more conservative outcome which ensures a greater safety margin comparing to FOSM which appears to be a more efficient and robust methodology.

Analysis of passing sight distance using first-order reliability method

Current passing sight distance requirements for two lane highways by the American Association of State Highway and Transportation Officials are based on field studies conducted between 1938 and 1941 which use deterministic values for its design variables such as passing sight distance, speed of the passing vehicle, speed differential between the passed and passing vehicle etc. This report presents three methods to analyze reliability and serves as an extension to the revised model presented by Yasser Hassan, Said Easa and A.O.Abd El Halim whose model sought to improve older models by equally considering both observed passing behaviours of drivers and passing maneuvers that are consistent with two lane highways. Analysis of passing sight distance using first order second moment reliability method, advanced first order second moment and the ellipsoid approach to measure the probability of failure of the passing sight distance design, rely solely on the mean and variance (moments) of each randomly distributed variable in contrast to methods that rely only on deterministic values. Results show the advanced first order second moment and the ellipsoid approach provided more accurate results than first order second moment method which in turn provide a greater safety margin with the later also proving to be a much more robust and efficient method of performing a reliability

Reliability Analysis Approach For Intersection Sight Distance Of A Symmetrical Single-Lane Roundabout

The current intersection sight distance values on a roundabout provided by ASSHTO and other worldwide guidelines are based on deterministic methods considering only single variables as the design inputs. However, most of the input design variables such as entering speed and the deceleration rate are random variables which are stochastic in nature. Therefore, this study proposes a reliability analysis approach to add uncertainty to the current deterministic models. Two different reliability approaches; the first order second moment and advanced first order second moment are presented in this paper. These approaches rely on the normal distribution of the random variables using the mean, variance and the covariance of the probability distribution of each variable rather than the single deterministic values. Results show that the AFOSM reliability methodology provides a more conservative outcome which ensures a greater safety margin comparing to FOSM which appears to be a more efficient and robust methodology.

Reliability of stopping and decision sight distance at roundabouts

The existing Stopping Sight Distance (SSD) and Decision Sight Distance (DSD) design methods for roundabouts are deterministic. This means that all of the design variables are predetermined, fixed values. This study presents a probabilistic method for the determination of SSD and DSD at roundabouts based on the equation recommended by the American Association of State Highway and Transportation Officials (AASHTO 2011). The reliability-based method considers all design parameters as random variables. Three types of SSD (SSD for approaches, SSD along the circulatory lane, and SSD for exiting vehicles to the pedestrian crosswalk) were considered in this study. DSD was considered for roundabout approaches. The First-Order Second-Moment and Advanced First-Order Second-Moment methods were used to model SSD and DSD. Once the required SSD and DSD were determined, the lateral clearance requirements at every point of the roundabout were calculated.