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Wedge analysis needs to be performed for all excavations in hard rock.
This relies on the Williams wedge analysis and permits: (a) the response of any prototype of complex geometry to be predicted, including the amount of fretting damage likely to be experienced and (b) the fretting fatigue strength measured in a simple laboratory experiment to be used to predict, reliably, the behaviour of any engineering component.
In the analysis of rock slope stability, the method of wedge analysis proposed by Hoek and Bray in their classic textbook Rock Slope Engineering (1981) [1] and the computer program SWEDGE (Rocscience, 2001) [18], which was developed based on this method, are widely applied, especially in practical engineering situations.
The FOS of wedge analysis for sections RS-4 and RS-6 are 11.54 and 26.31 respectively.
The spatial distribution of the dendritic processes from the centroid of the cell body was studied using Wedge analysis.
Although the NPY-cluster regrouped neurons presenting heterogeneous aspects, the most prominent traits of this group are a relatively high number of primary dendrites emerging from the soma (7.9 ± 4.5), a dendritic arborization radially organized (equipolarity = 0.98 ± 0.10, see Wedge analysis presented in Fig. 3 A 3), and a notable tortuosity of the processes (1.4 ± 0.1).
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As you know I spent some time in "The Climate Fix" explaining how the wedges analysis dramatically underestimated the magnitude of the stabilization and the technology challenge.
Just this week Worldwatch released their analysis of changes in energy intensity which also shows the wedges analysis to have been completely over optimistic as to what BAU deacrbonization rates would be in the current decade.
In the debate between Hoffert et al. and Socolow/Pacala there is no doubt that unfolding experience has come down on the side of Hoffert et al. — far from being "affirmed" the wedges analysis has proven to dramatically underestimate the scale of the challenge.
We recommend that the within-wedge analysis reported as a secondary analysis from stepped-wedge designs in future.
Meta-regression can be applied to within-wedge analysis outcomes to identify situations that may make stepped-wedge designs more or less prone to bias.
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