Estimation of Global Stress State in Mt.Torigata Region.

A micromechanical model representing two adjacent grains is developed. Rapid crack propagation from one grain into another driven by a constant global stress state is simulated. The normal of the crack face in the grain where the micro-crack initiates coincides with the principle loading direction. In the adjacent grain, the propagation direction changes and separation occurs in a mixed way, involving both normal and shear separation. The largest grain size that can arrest a rapidly propagating micro-crack is defined as the critical grain size. The effects of the global stress state and temperature on the critical grain size is examined. The influence of the mismatch in lattice orientation between two neighboring grains is qualitatively described. The influence of temperature is modeled by a temperature dependent viscoplastic response.

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The global distribution of giant radiating dike swarms on Venus: Implications for the global stress state

Geophysical Research Letters ◽

10.1029/94gl00592 ◽

1994 ◽

Vol 21 (8) ◽

pp. 701-704 ◽

Cited By ~ 81

Author(s):

Eric B. Grosfils ◽

James W. Head

Keyword(s):

Stress State ◽

Global Distribution ◽

Global Stress ◽

Dike Swarms

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Short Stress State Questionnaire

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000200 ◽

2015 ◽

Vol 31 (1) ◽

pp. 20-30 ◽

Cited By ~ 28

Author(s):

William S. Helton ◽

Katharina Näswall

Keyword(s):

Stress State ◽

Factor Structure ◽

Human Performance ◽

Self Report ◽

Confirmatory Factor ◽

Stress States ◽

Related Stress ◽

Using Data ◽

Task Conditions ◽

Multiple Samples

Conscious appraisals of stress, or stress states, are an important aspect of human performance. This article presents evidence supporting the validity and measurement characteristics of a short multidimensional self-report measure of stress state, the Short Stress State Questionnaire (SSSQ; Helton, 2004 ). The SSSQ measures task engagement, distress, and worry. A confirmatory factor analysis of the SSSQ using data pooled from multiple samples suggests the SSSQ does have a three factor structure and post-task changes are not due to changes in factor structure, but to mean level changes (state changes). In addition, the SSSQ demonstrates sensitivity to task stressors in line with hypotheses. Different task conditions elicited unique patterns of stress state on the three factors of the SSSQ in line with prior predictions. The 24-item SSSQ is a valid measure of stress state which may be useful to researchers interested in conscious appraisals of task-related stress.

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