Shallow foundation design: a comparative study of partial safety factors and full probabilistic methods.

In the past two decades, Europe has witnessed a significant transition in the design codes used for assessing foundation structures, with the widespread adoption of the Eurocodes (EC). This shift remains a pertinent topic within the engineering community, particularly concerning the transition from traditional design methodologies to those prescribed by the Eurocodes, as well as the potential for fully probabilistic design. While the Eurocodes' methodology is described as probabilistic, it is crucial to recognize that the achievement of the target reliability level is predominantly facilitated through a system of partial safety factors.

Spatiotemporal monitoring of hard tissue development reveals unknown features of tooth and bone development.

Mineralized tissues, such as bones or teeth, are essential structures of all vertebrates. They enable rapid movement, protection, and food processing, in addition to providing physiological functions. Although the development, regeneration, and pathogenesis of teeth and bones have been intensely studied, there is currently no tool to accurately follow the dynamics of growth and healing of these vital tissues in space and time.

From computed tomography to finite element space: A unified bone material mapping strategy.

Background: The spatially varying mechanical properties in finite element models of bone are most often derived from bone density data obtained via quantitative computed tomography. The key step is to accurately and efficiently map the density given in voxels to the finite element mesh.

Methods: The density projection is first formulated in least-squares terms and then discretized using a continuous and discontinuous variant of the finite element method.

Bone mineral density modeling via random field: Normality, stationarity, sex and age dependence.

Background And Objective: Capturing the population variability of bone properties is of paramount importance to biomedical engineering. The aim of the present paper is to describe variability and correlations in bone mineral density with a spatial random field inferred from routine computed tomography data.

Methods: Random fields were simulated by transforming pairwise uncorrelated Gaussian random variables into correlated variables through the spectral decomposition of an age-detrended correlation matrix.