Equivalent Vehicle Load Factors for Slab Design of a Parking Garage

2009 ◽  
Author(s):  
H.-G. Kwak ◽  
J.-Y. Song
Keyword(s):  
Parking Garage ◽  
Vehicle Load ◽  
Load Factors

scholarly journals Structural Analysis of Underground Parking Garage Under Vehicle Load

2013 ◽  
Vol 4 (4) ◽  
pp. 22-29 ◽  
Author(s):  
Young-Jin Kim ◽  
Bum-Sick Lee ◽  
Dong-Sub Choi ◽  
Hyo-Keon Oh ◽  
Chang-Bum Kang
Keyword(s):  
Structural Analysis ◽  
Parking Garage ◽  
Vehicle Load

Live load factors for parking garage members

2000 ◽  
Vol 22 (3) ◽  
pp. 251-279 ◽  
Author(s):  
Hyo-Gyoung Kwak ◽  
Jong-Young Song
Keyword(s):  
Live Load ◽  
Parking Garage ◽  
Load Factors

Sarasota County Parking Garage

PCI Journal ◽  
1991 ◽  
Vol 36 (3) ◽  
pp. 34-39
Author(s):  
Andrew J. Zekany ◽  
Ede Vessey ◽  
William M. Bollinger
Keyword(s):  
Parking Garage

scholarly journals Code Calibration of the Eurocodes

2021 ◽  
Vol 11 (12) ◽  
pp. 5474
Author(s):  
Tuomo Poutanen
Keyword(s):  
High Reliability ◽  
High Accuracy ◽  
Variable Load ◽  
Reliability Model ◽  
Safety Factors ◽  
Rounding Errors ◽  
Code Calibration ◽  
Load Factors ◽  
Characteristic Values

This article addresses the process to optimally select safety factors and characteristic values for the Eurocodes. Five amendments to the present codes are proposed: (1) The load factors are fixed, γG = γQ, by making the characteristic load of the variable load changeable, it simplifies the codes and lessens the calculation work. (2) Currently, the characteristic load of the variable load is the same for all variable loads. It creates excess safety and material waste for the variable loads with low variation. This deficiency can be avoided by applying the same amendment as above. (3) Various materials fit with different accuracy in the reliability model. This article explains two options to reduce this difficulty. (4) A method to avoid rounding errors in the safety factors is explained. (5) The current safety factors are usually set by minimizing the reliability indexes regarding the target when the obtained codes include considerable safe and unsafe design cases with the variability ratio (high reliability/low) of about 1.4. The proposed three code models match the target β50 = 3.2 with high accuracy, no unsafe design cases and insignificant safe design cases with the variability ratio 1.07, 1.03 and 1.04.

Reliability Analysis of Prestressed Concrete Bridges in Mexico: Assessment and Live Load Factors Proposal

2021 ◽  
Author(s):  
Rolando Salgado-Estrada ◽  
Sergio A. Zamora-Castro ◽  
Agustín L. Herrera-May ◽  
Yessica A. Sánchez-Moreno ◽  
Yair S. Sánchez-Moreno
Keyword(s):  
Reliability Analysis ◽  
Prestressed Concrete ◽  
Concrete Bridges ◽  
Live Load ◽  
Prestressed Concrete Bridges ◽  
Load Factors

scholarly journals Sound Event Detection in Underground Parking Garage Using Convolutional Neural Network

2020 ◽  
Vol 4 (3) ◽  
pp. 20 ◽  
Author(s):  
Giuseppe Ciaburro
Keyword(s):  
Event Detection ◽  
High Accuracy ◽  
Surveillance Systems ◽  
Urban Mobility ◽  
Parking Garage ◽  
Large Size ◽  
Car Crash ◽  
Sound Event ◽  
Parking Management ◽  
Sound Event Detection

Parking is a crucial element in urban mobility management. The availability of parking areas makes it easier to use a service, determining its success. Proper parking management allows economic operators located nearby to increase their business revenue. Underground parking areas during off-peak hours are uncrowded places, where user safety is guaranteed by company overseers. Due to the large size, ensuring adequate surveillance would require many operators to increase the costs of parking fees. To reduce costs, video surveillance systems are used, in which an operator monitors many areas. However, some activities are beyond the control of this technology. In this work, a procedure to identify sound events in an underground garage is developed. The aim of the work is to detect sounds identifying dangerous situations and to activate an automatic alert that draws the attention of surveillance in that area. To do this, the sounds of a parking sector were detected with the use of sound sensors. These sounds were analyzed by a sound detector based on convolutional neural networks. The procedure returned high accuracy in identifying a car crash in an underground parking area.

Dynamic Response of the Steel Bridge Deck Thin Surfacing due to Vehicle Load

2010 ◽  
Vol 156-157 ◽  
pp. 677-677
Keyword(s):  
Dynamic Response ◽  
Bridge Deck ◽  
Advanced Materials ◽  
Steel Bridge ◽  
Vehicle Load ◽  
Materials Research

This paper has been published in Advanced Materials Research Volumes 148 - 149, pp 544 http://www.scientific.net/AMR.148-149.544

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