Evaluation of a Loss Estimation Procedure Based on Data from the Loma Prieta Earthquake

1995 ◽  
Vol 11 (1) ◽  
pp. 37-61 ◽  
Author(s):  
Nicholas P. Jones ◽  
Sólveig Thorvaldsdóttir ◽  
Anqi Liu ◽  
Prakash Narayan ◽  
Thomas Warthen

Over the several past decades, methods have been developed to predict structural damage on a regional basis. This paper describes an effort to collect damage and loss data from the Loma Prieta Earthquake and the comparison of these data with the results calculated by an existing loss estimation model. First the intensity prediction was evaluated by comparing the model results with the Modified Mercalli Intensity (MMI) maps issued by the U.S. Geological Survey in areas affected by the Loma Prieta earthquake. Then, the study concentrated on losses of the City of Watsonville in the County of Santa Cruz. The sensitivity of the loss due to variation in some of the basic parameters, such as intensity, deductible and liquefaction potential, were studied and discussed. The damage distribution of wood-frame buildings was also investigated. Results of calculations were compared with the collected real loss data (on-site estimate and permit estimate) from the City of Watsonville. The comparison shows that while the extant model offers some insight into loss distributions, more research is clearly necessary to improve the physical underpinnings of the methodology and to provide the necessary statistical data on which these approaches are based.

1991 ◽  
Vol 81 (5) ◽  
pp. 2111-2126
Author(s):  
R. Shepherd ◽  
E. O. Delos-Santos

Abstract Extensive damage was experienced by wood-frame buildings during the Loma Prieta earthquake. A significant contributory factor was the collapse of cripple walls. This prompted the examination of the behavior of a group of full-scale retrofitted cripple walls subjected to in-plane cyclic loads. The results of investigating seven cripple walls, each 2 ft (0.61 m) high and 16 ft (5 m) long, are presented. Two are control panels, without retrofits. Two are strengthened with 1 by 6 inch (25.4 by 153 mm) braces. Two are retrofitted with 0.5 inch (12.7 mm) plywood and one with a steel strap tie. Stiffness, strength, and damping characteristics are summarized, together with cost aspects. It is shown that relatively cheap and straightforward modifications can substantially eliminate the vulnerability of many existing cripple walls to earthquake shaking.


Author(s):  
Bruce Galloway ◽  
Jason M. Ingham

The South Napa earthquake occurred on Sunday, 24 August 2014 at 3.20 am local time at a depth of 10.7 km, having MW 6.0 and causing significant damage to unreinforced masonry (URM) buildings in the City of Napa and generating strong ground shaking in a region well known for its wine production. Parallels exist between the damage in past New Zealand earthquakes, particularly to unreinforced masonry buildings, and the disruption in the Marlborough region following the recent 2013 MW 6.5 Seddon earthquake. Furthermore, the event was the largest to have occurred in Northern California since the 1989 Loma Prieta earthquake 25 years earlier, and hence was an important event for the local community of earthquake researchers and professionals regarding the use of a physical and virtual clearinghouse for data archiving of damage observations. Because numerous URM buildings in the City of Napa had been retrofitted, there was significant interest regarding the observed performance of different retrofitting methods. Following a brief overview of the earthquake affected area and previous earthquakes to have caused damage in the Napa Valley region, details are provided regarding the characteristics of the 2014 South Napa earthquake, the response to the earthquake including placarding procedures and barricading, and more specific details of observed building and non-structural damage. Aspects of business continuity following the South Napa earthquake are also considered. One conclusion is that in general the seismic retrofitting of URM buildings in the Napa region proved to be very successful, and provides an important benchmark as New Zealand begins to more actively undertake seismic assessment and retrofitting of its earthquake prone building stock. It is also concluded that there are sufficient similarities between New Zealand and California, and a rich network of contacts that has developed following the hosting of many US visitors to New Zealand in conjunction with the 2010/2011 Canterbury earthquakes, that it is sensible for the New Zealand earthquake engineering community to maintain a close focus on ongoing earthquake preparedness and mitigation methods used and being developed in USA, and particularly in California.


2021 ◽  
pp. 1-14
Author(s):  
Mohammad Reza Amiri Shahmirani ◽  
Abbas Akbarpour Nikghalb Rashti ◽  
Mohammad Reza Adib Ramezani ◽  
Emadaldin Mohammadi Golafshani

Prediction of structural damage prior to earthquake occurrence provides an early warning for stakeholders of building such as owners and urban managers and can lead to necessary decisions for retrofitting of structures before a disaster occurs, legislating urban provisions of execution of building particularly in earthquake prone areas and also management of critical situations and managing of relief and rescue. For proper prediction, an effective model should be produced according to field data that can predict damage degree of local buildings. In this paper in accordance with field data and Fuzzy logic, damage degree of building is evaluated. Effective parameters of this model as an input data of model consist of height and age of the building, shear wave velocity of soil, plan equivalent moment of inertia, fault distance, earthquake acceleration, the number of residents, the width of the street for 527 buildings in the city. The output parameter of the model, which was the damage degree of the buildings, was also classified as five groups of no damage, slight damage, moderate damage, extensive damage, and complete damage. The ranges of input and output classification were obtained based on the supervised center classification (SCC-FCM) method in accordance with field data.


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