Failure mode and strength prediction of laterally braced Litzka-type castellated beams

2021 ◽  
Vol 184 ◽  
pp. 106796
Author(s):  
João J.V. Braga ◽  
Daniel A. Linhares ◽  
Daniel C.T. Cardoso ◽  
Elisa D. Sotelino
Keyword(s):  
Failure Mode ◽  
Strength Prediction

scholarly journals Stochastic strength prediction of masonry structures: a methodological approach or a way forward?

2020 ◽  
Vol 4 ◽  
pp. 122-129
Author(s):  
Vasilis Sarhosis ◽  
Tamas Forgacs ◽  
Jose Lemos
Keyword(s):  
Spatial Variability ◽  
Failure Mode ◽  
Mechanical Behaviour ◽  
Material Properties ◽  
Computational Models ◽  
Strength Prediction ◽  
External Loading ◽  
Masonry Structures ◽  
Material Parameters ◽  
Masonry Material

Today, there are several computational models to predict the mechanical behaviour of masonry structures subjected to external loading. Such models require the input of material parameters to describe the mechanical behaviour and strength of masonry constructions. Although such masonry material parameters are characterised by stochastic-probabilistic nature, engineers are assigning the same material properties throughout the structure to be analysed. The aim of this paper is to propose a methodology which considers material spatial variability and stochastic strength prediction for masonry structures. The methodology is illustrated on a case study covering the in-plane behaviour of a low bond strength masonry wall panel containing an opening. A 2D non-linear computational model based on the Discrete Element Method (DEM) is used. The computational results are compared against those obtained from the experimental findings in terms of failure mode and structural capacity. It is shown that computational models which consider the spatial variability of masonry material properties better predict the load carrying capacity, stiffness and failure mode of the masonry structures. These observations provide new insights into structural behaviour of masonry constructions and lead to suggestions for improving assessment techniques for masonry structures.

Analytical electron microscopy of grain boundaries in Al-Cu metallizations

1992 ◽  
Vol 50 (2) ◽  
pp. 1684-1685
Author(s):  
J. R. Michael ◽  
A. D. Romig ◽  
D. R. Frear
Keyword(s):  
Electron Microscopy ◽  
Integrated Circuits ◽  
Failure Mode ◽  
Current Density ◽  
Thermal History ◽  
Analytical Electron Microscopy ◽  
Cu Metallization ◽  
Analytical Electron ◽  
Interconnect Lines

Al with additions of Cu is commonly used as the conductor metallizations for integrated circuits, the Cu being added since it improves resistance to electromigration failure. As linewidths decrease to submicrometer dimensions, the current density carried by the interconnect increases dramatically and the probability of electromigration failure increases. To increase the robustness of the interconnect lines to this failure mode, an understanding of the mechanism by which Cu improves resistance to electromigration is needed. A number of theories have been proposed to account for role of Cu on electromigration behavior and many of the theories are dependent of the elemental Cu distribution in the interconnect line. However, there is an incomplete understanding of the distribution of Cu within the Al interconnect as a function of thermal history. In order to understand the role of Cu in reducing electromigration failures better, it is important to characterize the Cu distribution within the microstructure of the Al-Cu metallization.

Risk analysis of cutting system under intuitionistic fuzzy environment

2020 ◽  
Vol 1 (1) ◽  
pp. 162-173
Author(s):  
Dinesh Kumar Kushwaha ◽  
◽  
Dilbagh Panchal ◽  
Anish Sachdeva ◽  
◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Thermal Power ◽  
Failure Detection ◽  
Engineering System ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Mode Effect ◽  
Cutting System ◽  
Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

Case Study of Electro-Optical Probing Signal with High Signal-Noise Ratio

2019 ◽  
Author(s):  
Ryan Xiao ◽  
William Wang ◽  
Ang Li ◽  
Shengqiu Xu ◽  
Binghai Liu
Keyword(s):  
Failure Mode ◽  
High Signal ◽  
Signal Noise ◽  
Electrical Failure ◽  
Current Path ◽  
Probing Signal ◽  
Optical Probing ◽  
Noise Ratio ◽  
Case Collection

Abstract With the development of semiconductor technology and the increment quantity of metal layers in past few years, backside EFA (Electrical Failure Analysis) technology has become the dominant method. In this paper, abnormally high Signal Noise Ratio (SNR) signal captured by Electro-Optical Probing (EOP)/Laser Voltage Probing (LVP) from backside is shown and the cause of these phenomena are studied. Based on the real case collection, two kinds of failure mode are summarized, and simulated experiments are performed. The results indicate that when a current path from power to ground is formed, the high SNR signal can be captured at the transistor which was on this current path. It is helpful of this consequence for FA to identify the failure mode by high SNR signal.

Analysis of Delta Iddq Soft Fails on Pass Chips

2006 ◽  
Author(s):  
I. Österreicher ◽  
S. Eckl ◽  
B. Tippelt ◽  
S. Döring ◽  
R. Prang ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Failure Mode ◽  
Photon Emission ◽  
Complete Analysis ◽  
Functional Tests ◽  
Analysis Techniques ◽  
Atomic Force ◽  
Current Consumption ◽  
Emission Microscopy ◽  
Failure Localization

Abstract Depending on the field of application the ICs have to meet requirements that differ strongly from product to product, although they may be manufactured with similar technologies. In this paper a study of a failure mode is presented that occurs on chips which have passed all functional tests. Small differences in current consumption depending on the state of an applied pattern (delta Iddq measurement) are analyzed, although these differences are clearly within the usual specs. The challenge to apply the existing failure analysis techniques to these new fail modes is explained. The complete analysis flow from electrical test and Global Failure Localization to visualization is shown. The failure is localized by means of photon emission microscopy, further analyzed by Atomic Force Probing, and then visualized by SEM and TEM imaging.

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