ASU Regents' Professors Open Access Works
The title “Regents’ Professor” is the highest faculty honor awarded at Arizona State University. It is conferred on ASU faculty who have made pioneering contributions in their areas of expertise, who have achieved a sustained level of distinction, and who enjoy national and international recognition for these accomplishments. This collection contains primarily open access works by ASU Regents' Professors.
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- Creators: Chattopadhyay, Aditi
Description
Although conflict is a normative part of parent–adolescent relationships, conflicts that are long or highly negative are likely to be detrimental to these relationships and to youths’ development. In the present article, sequential analyses of data from 138 parent–adolescent dyads (adolescents’ mean age was 13.44, SD = 1.16; 52 % girls, 79 % non-Hispanic White) were used to define conflicts as reciprocal exchanges of negative emotion observed while parents and adolescents were discussing “hot,” conflictual issues. Dynamic components of these exchanges, including who started the conflicts, who ended them, and how long they lasted, were identified. Mediation analyses revealed that a high proportion of conflicts ended by adolescents was associated with longer conflicts, which in turn predicted perceptions of the “hot” issue as unresolved and adolescent behavior problems. The findings illustrate advantages of using sequential analysis to identify patterns of interactions and, with some certainty, obtain an estimate of the contingent relationship between a pattern of behavior and child and parental outcomes. These interaction patterns are discussed in terms of the roles that parents and children play when in conflict with each other, and the processes through which these roles affect conflict resolution and adolescents’ behavior problems.
ContributorsMoed, Anat (Author) / Gershoff, Elizabeth T. (Author) / Eisenberg, Nancy (Author) / Hofer, Claire (Author) / Losoya, Sandra (Author) / Spinrad, Tracy (Author) / Liew, Jeffrey (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor)
Created2015-08-01
Description
This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.
ContributorsZhang, Jinjun (Author) / Koo, Bonsung (Author) / Liu, Yingtao (Author) / Zou, Jin (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2015-08-01
Description
Identification of early damage in polymer composites is of great importance. We have incorporated cyclobutane-containing cross-linked polymers into an epoxy matrix, studied the effect on thermal and mechanical properties, and, more importantly, demonstrated early damage detection through mechanically induced fluorescence generation. Two cinnamate derivatives, 1,1,1-tris(cinnamoyloxymethyl) ethane (TCE) and poly(vinyl cinnamate) (PVCi), were photoirradiated to produce cyclobutane-containing polymer. The effects on the thermal and mechanical properties with the addition of cyclobutane-containing polymer into epoxy matrix were investigated. The emergence of cracks was detected by fluorescence at a strain level just beyond the yield point of the polymer blends, and the fluorescence intensified with accumulation of strain. Overall, the results show that damage can be detected through fluorescence generation along crack propagation.
ContributorsZou, Jin (Author) / Liu, Yingtao (Author) / Shan, Bohan (Author) / Chattopadhyay, Aditi (Author) / Dai, Lenore (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-09-01
Description
The flexural behavior of epoxies was investigated by performing mechanical tests and applying statistical Weibull theory and analytical methods to the results. The effects of loading systems and environmental conditions were also considered. Three kinds of epoxies were studied: Epon E863, PRI 2002, and PR520. In total, 53 three-point-bending (3PB) Epon E863 samples and 26 3PB PR520 were tested immediately after curing, together with 26 four-point-bending (4PB) PRI2002 samples stored at 60°C and 90% Rh for 48 weeks. The Weibull parameters were estimated using both linear regression and the moments method. The statistical character of the Weibull model leads to uncertainty in the evaluated parameters, even for a large number of experiments. This study analyzed the ratio of flexural strength to tensile strength in bulk epoxy resin polymers. An analytical method previously developed by the authors to study the relationship between uniaxial tension/compression stress-strain curves and flexural load-deflection response was used to obtain the ratio. The results show that the Weibull model overpredicted the aforementioned ratio in different load arrangements.
ContributorsYekani Fard, Masoud (Author) / Raji, B. (Author) / Chattopadhyay, Aditi (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-12-01
Description
The purpose of this study was to examine whether dispositional sadness predicted children's prosocial behavior and if sympathy mediated this relation. Constructs were measured when children (n = 256 at time 1) were 18, 30, and 42 months old. Mothers and non-parental caregivers rated children's sadness; mothers, caregivers, and fathers rated children's prosocial behavior; sympathy (concern and hypothesis testing) and prosocial behavior (indirect and direct, as well as verbal at older ages) were assessed with a task in which the experimenter feigned injury. In a panel path analysis, 30-month dispositional sadness predicted marginally higher 42-month sympathy; in addition, 30-month sympathy predicted 42-month sadness. Moreover, when controlling for prior levels of prosocial behavior, 30-month sympathy significantly predicted reported and observed prosocial behavior at 42 months. Sympathy did not mediate the relation between sadness and prosocial behavior (either reported or observed).
ContributorsEdwards, Alison (Author) / Eisenberg, Nancy (Author) / Spinrad, Tracy (Author) / Reiser, Mark (Author) / Wilkens, Natalie (Author) / Liew, Jeffrey (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-01-01
Description
Because metallic aircraft components are subject to a variety of in-service loading conditions, predicting their fatigue life has become a critical challenge. To address the failure mode mitigation of aircraft components and at the same time reduce the life-cycle costs of aerospace systems, a reliable prognostics framework is essential. In this paper, a hybrid prognosis model that accurately predicts the crack growth regime and the residual-useful-life estimate of aluminum components is developed. The methodology integrates physics-based modeling with a data-driven approach. Different types of loading conditions such as constant amplitude, random, and overload are investigated. The developed methodology is validated on an Al 2024-T351 lug joint under fatigue loading conditions. The results indicate that fusing the measured data and physics-based models improves the accuracy of prediction compared to a purely data-driven or physics-based approach.
ContributorsNeerukatti, Rajesh Kumar (Author) / Liu, Kuang C. (Author) / Kovvali, Narayan (Author) / Chattopadhyay, Aditi (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School for the Engineering of Matter, Transport and Energy (Contributor)
Created2014-04-01