scholarly journals Dam failure analysis for the Lago de Matrullas Dam, Orocovis, Puerto Rico

2015 ◽  
Author(s):  
Heriberto Torres-Sierra ◽  
Julieta Gómez-Fragoso
Keyword(s):  
Puerto Rico ◽  
Failure Analysis ◽  
Dam Failure

scholarly journals Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico

2016 ◽  
Author(s):  
Julieta Gómez-Fragoso ◽  
Heriberto Torres-Sierra
Keyword(s):  
Puerto Rico ◽  
Failure Analysis ◽  
Dam Failure

Landslide Dam Failure Analysis Using Imaging and Ranging Sensors

2021 ◽  
pp. 3-17
Author(s):  
Keivan Tavakoli ◽  
Ehsan Zadehali ◽  
Arsalan Malekian ◽  
Sara Darsi ◽  
Laura Longoni ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Landslide Dam ◽  
Dam Failure

Prediction of Concrete Dam Failure: A Wavelet Approach

2011 ◽  
Vol 105-107 ◽  
pp. 1470-1475
Author(s):  
Qiang Li ◽  
Qing Wen Ren
Keyword(s):  
Failure Analysis ◽  
Mechanical Test ◽  
Arch Dam ◽  
Local Failure ◽  
Dam Failure ◽  
Global Instability ◽  
Concrete Dam ◽  
Good Consistency ◽  
Singularity Point ◽  
Scale Difference

The failure of concrete dam is a process started from local failure to global instability, and there is a huge scale difference in the process, so the analysis should be conducted in a multiscale manner. Choosing a typical failure curve as a signal, the precursor load is determined in the form of singularity point in the curve. With a numerical example, the previous reported methods for determining precursor load are compared with the wavelet approach, and it is shown that the wavelet approach gives more accuracy and reasonable results. Besides the precursor load, the failure mode, local failure or global instability, can also be figured out by the wavelet approach. By applying it to the Jinping arch dam, the obtained results are in good consistency with geology mechanical test. It is shown that the wavelet approach is of good applicability and accuracy for dam failure analysis.

scholarly journals An elicitation process to quantify Bayesian networks for dam failure analysis

2020 ◽  
Author(s):  
Andrea Verzobio ◽  
Ahmed El-Awady ◽  
Kumaraswamy Ponnambalam ◽  
John Quigley ◽  
Daniele Zonta
Keyword(s):  
Bayesian Networks ◽  
Failure Analysis ◽  
System Reliability ◽  
Real Life ◽  
Dam Failure ◽  
Subjective Probabilities ◽  
Conditional Probabilities ◽  
Elicitation Process ◽  
Probabilistic Failure Analysis

Bayesian networks support the probabilistic failure analysis of complex systems, e.g. dams and bridges, needed for a better understanding of the system reliability and for taking mitigation actions. Bayesian networks are useful in representing the interactions among system components graphically, while the quantitative strength of the interrelationships between the variables is measured using conditional probabilities. However, due to a lack of objective data it often becomes necessary to rely on expert judgment to provide subjective probabilities to quantify the model. This paper proposes an elicitation process that can be used to support the collection of valid and reliable data with the specific aim of quantifying a Bayesian Network, while minimizing the adverse impact of biases. To illustrate how this framework works, it is applied to a real-life case study regarding the safety of the Mountain Chute Dam and Generating Station, which is located on the Madawaska River in Ontario, Canada.

Failure Analysis With the Scanning Electron Microscope

1972 ◽  
Vol 30 ◽  
pp. 482-483
Author(s):  
John R. Devaney
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Integrated Circuits ◽  
Failure Analysis ◽  
High Reliability ◽  
Military Applications ◽  
Small Structure ◽  
Useful Life ◽  
Insight Into ◽  
Scanning Electron

Occasionally in history, an event may occur which has a profound influence on a technology. Such an event occurred when the scanning electron microscope became commercially available to industry in the mid 60's. Semiconductors were being increasingly used in high-reliability space and military applications both because of their small volume but, also, because of their inherent reliability. However, they did fail, both early in life and sometimes in middle or old age. Why they failed and how to prevent failure or prolong “useful life” was a worry which resulted in a blossoming of sophisticated failure analysis laboratories across the country. By 1966, the ability to build small structure integrated circuits was forging well ahead of techniques available to dissect and analyze these same failures. The arrival of the scanning electron microscope gave these analysts a new insight into failure mechanisms.

Using the scanning electron microscope for failure analysis of high density magnetic media

1987 ◽  
Vol 45 ◽  
pp. 392-393
Author(s):  
Evelyn R. Ackerman ◽  
Gary D. Burnett
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Failure Analysis ◽  
High Density ◽  
Magnetic Media ◽  
Specific Data ◽  
Retrieval Systems ◽  
Operating Environments ◽  
The Media ◽  
Scanning Electron

Advancements in state of the art high density Head/Disk retrieval systems has increased the demand for sophisticated failure analysis methods. From 1968 to 1974 the emphasis was on the number of tracks per inch. (TPI) ranging from 100 to 400 as summarized in Table 1. This emphasis shifted with the increase in densities to include the number of bits per inch (BPI). A bit is formed by magnetizing the Fe203 particles of the media in one direction and allowing magnetic heads to recognize specific data patterns. From 1977 to 1986 the tracks per inch increased from 470 to 1400 corresponding to an increase from 6300 to 10,800 bits per inch respectively. Due to the reduction in the bit and track sizes, build and operating environments of systems have become critical factors in media reliability.Using the Ferrofluid pattern developing technique, the scanning electron microscope can be a valuable diagnostic tool in the examination of failure sites on disks.

Puerto Rico: A Cultural Crossroads

ASHA Leader ◽  
2008 ◽  
Vol 13 (15) ◽  
pp. 38-40
Author(s):  
Albert Villanueva-Reyes
Keyword(s):  
Puerto Rico
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