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Related Concept Videos

Drying Shrinkage01:21

Drying Shrinkage

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When hardened concrete is exposed to air with a relative humidity of less than 100 percent, it begins to lose the free water within its capillaries. As this water evaporates, the water initially adsorbed onto the calcium silicate hydrates migrates towards these now empty spaces and eventually evaporates as well. Over time, as more water leaves, the volume of the concrete decreases, a phenomenon known as drying shrinkage.
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Shrinkage in concrete is primarily due to water loss from evaporation, hydration of cement, or carbonation, leading to a reduction in volume. The volumetric contraction results in volumetric strain in concrete. However, in practice, shrinkage is measured as linear strain, which is one-third of the volumetric strain.
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Atmospheric CO2 penetrates the concrete's pores and, in the presence of moisture, forms carbonic acid, which then reacts with calcium hydroxide in the hydrated cement, forming calcium carbonate. This process reduces the concrete's volume and is termed carbonation shrinkage.
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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A material's elastic behavior is characterized by the disappearance of stress once the load is removed, allowing the material to return to its original state. However, when stress surpasses the yield point, yielding commences, marking the onset of plastic deformation or permanent set. This change from elastic to plastic behavior is influenced by the peak stress value and the duration before the load is removed. An intriguing observation occurs when a specimen is loaded, unloaded, and...
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Residual stresses reside in a structure even after removing the original stress inducer. This phenomenon often arises from varied plastic deformations across different parts of a structure. Consider a rod stretched beyond its yield point. It will not regain its original length due to permanent deformation. Even after load removal, the rod does not entirely lose stress because of uneven plastic deformations, resulting in residual stresses. The computation of these stresses in structures is...
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Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation
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On Reverse Shrinkage Effects and Shrinkage Overshoot.

Pascal Jordan1

  • 1University of Hamburg, Von-Melle-Park 5, 20146, Hamburg, Germany. pascal.jordan@uni-hamburg.de.

Psychometrika
|June 6, 2022
PubMed
Summary
This summary is machine-generated.

Shrinkage estimates can sometimes move components further from the prior mean than original estimates, a phenomenon observed in regression models. This effect, including sign reversals, is not a mathematical artifact but occurs in practice, impacting psychometrics.

Keywords:
Lagrange multiplierMAPeducational testingpriorshrinkage

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Area of Science:

  • Statistics
  • Statistical Modeling
  • Psychometrics

Background:

  • Shrinkage estimation is a statistical technique used to improve estimates by pulling them towards a prior value.
  • Traditional shrinkage methods, while effective, have properties that are not always fully understood.
  • Understanding these properties is crucial for reliable statistical inference, particularly in complex models.

Purpose of the Study:

  • To investigate less-known properties of shrinkage estimates under a squared Euclidean norm penalty.
  • To analyze the phenomenon where shrinkage estimators can move components further from the prior mean than the original estimate.
  • To explore the practical implications of these effects, including sign reversals, in various regression settings and psychometrics.

Main Methods:

  • Analysis of shrinkage estimates with a squared Euclidean norm penalty.
  • Examination across three modeling settings: linear, logistic, and ordinal regression.
  • Conducting simulations to validate the observed effects and assess their practical occurrence.

Main Results:

  • Demonstrated that shrinkage estimators can place some components further from the prior mean than the original estimate.
  • Confirmed this effect is not a mathematical artifact but occurs in practical simulations.
  • Observed sign reversals ('overshoots') as a byproduct of this phenomenon in shrinkage estimates.

Conclusions:

  • Shrinkage estimation exhibits counterintuitive behavior where estimates can deviate more from the prior mean.
  • These effects, including overshoots, are relevant in real-world applications, particularly in psychometric modeling.
  • Further attention is needed to address the practical consequences and challenges posed by these shrinkage estimate properties.