Mixed-mode effects on the toughness of polymer interfaces

1990 ◽  
Vol 25 (6) ◽  
pp. 2791-2794 ◽  
Author(s):  
H. R. Brown
Keyword(s):  
Mixed Mode ◽  
Polymer Interfaces ◽  
Mode Effects

scholarly journals A three-dimensional elastoplastic analysis of mixed-mode KI/KII around the crack front

2019 ◽  
Vol 300 ◽  
pp. 11002
Author(s):  
Luiz Fernando Nazaré Marques ◽  
Jaime Tupiassú Pinho de Castro ◽  
Luiz Fernando Martha ◽  
Marco Antonio Meggiolaro
Keyword(s):  
Crack Front ◽  
Mixed Mode ◽  
Three Dimensional ◽  
Local Stress ◽  
Mode I ◽  
Pure Mode ◽  
Mode Effects ◽  
Fatigue And Fracture ◽  
Edge Tension ◽  
Combined Mode

Engineering problems that involve fatigue crack growth and fracture frequently can be studied by taking into account only mode-I features. However, many important problems that involve combined mode I and II loadings cannot be properly analyzed by a pure mode-I approach, which in particular may not be sufficient to estimate fracture toughness for practical purposes in such cases. Such mixed-mode problems involve crack orientation and/or load conditions that lead to combined local Stress Intensity Factors (SIFs) KI/KII around the crack front. Using multiaxial crack tip condition characterized by the crack inclination angle βin a mixed-mode KI/KII modified single edge tension SE(T) specimen, such mixed-mode effects on plastic zone shapes, volumes and plastic work UPL are taken into account to evaluate problems that involve fatigue and fracture.

scholarly journals Mode effects in concurrent mixed-mode surveys

2016 ◽  
Vol 29 (5) ◽  
pp. 787-806
Author(s):  
Jeeseon Baek ◽  
Kyung A Min
Keyword(s):  
Mixed Mode ◽  
Mode Effects

Modelling Mode Effects for a Panel Survey in Transition

2021 ◽  
pp. 63-88
Author(s):  
Paul P. Biemer ◽  
Kathleen Mullan Harris ◽  
Dan Liao ◽  
Brian J. Burke ◽  
Carolyn Tucker Halpern
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Mixed Mode ◽  
Good News ◽  
Longitudinal Change ◽  
Nonresponse Bias ◽  
Two Phase ◽  
Mode Effects ◽  
Analytical Results ◽  
Weighting Adjustments

Funding reductions combined with increasing data-collection costs required that Wave V of the USA’s National Longitudinal Study of Adolescent to Adult Health (Add Health) abandon its traditional approach of in-person interviewing and adopt a more cost-effective method. This approach used the mail/web mode in Phase 1 of data collection and in-person interviewing for a random sample of nonrespondents in Phase 2. In addition, to facilitate the comparison of modes, a small random subsample served as the control and received the traditional in-person interview. We show that concerns about reduced data quality as a result of the redesign effort were unfounded based on findings from an analysis of the survey data. In several important respects, the new two-phase, mixed-mode design outperformed the traditional design with greater measurement accuracy, improved weighting adjustments for mitigating the risk of nonresponse bias, reduced residual (or post-adjustment) nonresponse bias, and substantially reduced total-mean-squared error of the estimates. This good news was largely unexpected based upon the preponderance of literature suggesting data quality could be adversely affected by the transition to a mixed mode. The bad news is that the transition comes with a high risk of mode effects for comparing Wave V and prior wave estimates. Analytical results suggest that significant differences can occur in longitudinal change estimates about 60 % of the time purely as an artifact of the redesign. This begs the question: how, then, should a data analyst interpret significant findings in a longitudinal analysis in the presence of mode effects? This chapter presents the analytical results and attempts to address this question.

scholarly journals Mode Effects on Data Quality and Measurement in a Mixed-Mode Time-Use Survey

2021 ◽  
Author(s):  
Stella Chatzitheochari ◽  
Elena Mylona
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Time Use ◽  
Mixed Mode ◽  
Large Scale ◽  
New Technologies ◽  
Quality Data ◽  
Mode Effects ◽  
Time Use Survey ◽  
Time Diaries

Recent years have witnessed an increasing interest in the use of new technologies for time-use data collection, driven by their potential to reduce survey administration costs and improve data quality. However, despite the steady growth of studies that employ web and app time diaries, there is little research on their comparability with traditional paper-administered diaries that have long been regarded as the “gold standard” for measurement in time-use research. This paper rectifies this omission by investigating diary mode effects on data quality and measurement, drawing on data from a mixed-mode large-scale time diary study of adolescents in the United Kingdom. After controlling for selection effects, we find that web and app diaries yield higher quality data than paper diaries, which attests to the potential of new technologies in facilitating diary completion. At the same time, our analysis of broad time-use domains does not find substantial mode effects on measurement for the majority of daily activity categories. We conclude by discussing avenues for future methodological research and implications for time-use data collection.

scholarly journals A Method for Evaluating Mode Effects in Mixed-mode Surveys

2010 ◽  
Vol 74 (5) ◽  
pp. 1027-1045 ◽  
Author(s):  
J. Vannieuwenhuyze ◽  
G. Loosveldt ◽  
G. Molenberghs
Keyword(s):  
Mixed Mode ◽  
Mode Effects

Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys

2014 ◽  
Vol 22 (3) ◽  
pp. 304-320 ◽  
Author(s):  
Lonna Rae Atkeson ◽  
Alex N. Adams ◽  
R. Michael Alvarez
Keyword(s):  
Multivariate Regression ◽  
Mixed Mode ◽  
Response Patterns ◽  
Sampling Frame ◽  
Mode Effects ◽  
Propensity Matching ◽  
Response Modes ◽  
Registered Voters ◽  
Different Response

We examine the quality of two probability-based polls, one interviewer administered (telephone) and one self-administered (Internet and mail mixed mode survey). The polls use the same sampling frame (registered voters) and the same questions. First, we examine the representativeness of both surveys using information known about the population, and although we find important differences between the two in terms of sampling and nonresponse bias, we also find that both surveys represent the underlying population despite low response rates. We also test for mode effects between surveys due to social desirability and how it influences nondifferentiation or satisficing. Using a variety of methods (t-tests, multivariate regression, and genetic propensity matching), we find evidence that the presence of an interviewer alters response patterns on ego-driven questions. The implications of our work are important, due to the increasing popularity of mixed mode surveys. Researchers need to be methodologically sensitive to these differences when analyzing surveys that allow for different response modes.

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