Reliability-based design of truck escape ramps

2020 ◽  
Vol 47 (4) ◽  
pp. 395-404
Author(s):  
Kaitlyn Greto ◽  
Said M. Easa

The design method of truck escape ramps (TERs) presented by the Transportation Association of Canada and other organizations is deterministic and assumes fixed values of the design speed, rolling resistance, and ramp grade. This paper presents a reliability-based method for TER design based on the first-order second-moment (FOSM) method and the advanced FOSM (AFOSM) method. These methods rely on the distribution of the component random variables. Each method was used to analyze a TER with one grade and two grades. The FOSM is simple and can be easily used by practitioners, even with calculators. The AFOSM is more complicated but more accurate as it considers the design points in determining the probability of failure. The AFOSM method was used to establish design graphs for the required length of TERs. Application of the proposed method is illustrated using actual TERs in the United States and considering a hypothetical design scenario.

2021 ◽  
Author(s):  
Kaitlyn Ann Greto

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.


2021 ◽  
Author(s):  
Kaitlyn Ann Greto

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.


2003 ◽  
Author(s):  
Quazi A. Hossain

For more than the last fifteen years, the United States Department of Energy (DOE) has been using a probabilistic performance goal-based seismic design method for structures, systems, and components (SSCs) in its nuclear and hazardous facilities. Using a graded approach, the method permits the selection of probabilistic performance goals or acceptable failure rates for SSCs based on the severity level of SSC failure consequences. The method uses a site-specific probabilistic seismic hazard curve as the basic seismic input motion definition, but utilizes the existing national industry consensus design codes for specifying load combination and design acceptance criteria in such a way that the target probabilistic performance goals are met. Recently, the American Nuclear Society (ANS) and the American Society of Civil Engineers (ASCE) have undertaken the development of a number of national consensus standards that will utilize the performance goal-based seismic design experience base in the DOE complex. These standards are presently in various stages of development, some nearing completion. Once completed, these standards are likely to be adopted by various agencies and organizations in the United States. In addition to the graded approach of DOE’s method, these standards incorporate design provisions that permit seismic design of SSCs to several levels of functional performance. This flexibility of choosing a functional performance level in the design process results in an optimum, but risk-consistent design. The paper will provide an outline of two of these standards-in-progress and will present the author’s understanding of their basic philosophies and technical bases. Even though the author is an active member of the development committees for these two standards, the technical opinions expressed in this paper are author’s own, and does not reflect the views of any of the committees or the views of the organizations with which any member of the committees are affiliated.


2006 ◽  
Vol 23 (11) ◽  
pp. 1621-1624 ◽  
Author(s):  
Stanley A. Changnon

Abstract Various interests desire information and data on heavy snowfalls to define their spatial and temporal occurrences. Historical data at the nation’s 208 first-order stations for events with 15.2 cm or more snowfall in 2 days or less was assessed, and revealed various serious data problems at 118 stations with climatological quality data available for 90 stations. The data problems are described as guidelines for those seeking to utilize heavy snowfall data, and stations with quality data are listed.


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