Efficient random field modeling of soil deposits properties. Issue 108 (May 2018)
- Record Type:
- Journal Article
- Title:
- Efficient random field modeling of soil deposits properties. Issue 108 (May 2018)
- Main Title:
- Efficient random field modeling of soil deposits properties
- Authors:
- Yue, Qingxia
Yao, Jingru
Ang, Alfredo H.-S.
Spanos, Pol D. - Abstract:
- Abstract: The autocorrelation function (ACF) of the soil profile in some sites in Shandong province, China is studied using cone penetration test (CPT) data. This is done in the context of a random field modeling of the soil deposits. It is found that the different types of soil profile have different stochastic parameters, and there is no obvious trend along the depth of the soil profile. Thus, the soil profile is examined within each layer. Numerical values for three existing analytical (ACF) models are derived by the least squares fitting approach for the different types of soil. Further, comparisons of the autocorrelation function between the tip resistance and sleeve friction were examined. Based on the autocorrelation data analysis, a new autocorrelation model, named linear-exponential-cosine (LNCS), is considered with differentiability at the origin of the spatial lag axis, and alternating sign along this axis. For all of the four ACF models, a related integral equation is numerically solved for determining the associated Karhunen-Loeve (K-L) representation. In this regard, it is noted that the new model is not only more physics-consistent, but also yields quite good computational efficiency. In the end, the random field of the soil profile is modeled using a two-dimensional K-L expansion with the new model, assuming separability in two dimensions. Highlights: A new autocorrelation model, named linear-exponential-cosine (LNCS), is proposed. The autocorrelationAbstract: The autocorrelation function (ACF) of the soil profile in some sites in Shandong province, China is studied using cone penetration test (CPT) data. This is done in the context of a random field modeling of the soil deposits. It is found that the different types of soil profile have different stochastic parameters, and there is no obvious trend along the depth of the soil profile. Thus, the soil profile is examined within each layer. Numerical values for three existing analytical (ACF) models are derived by the least squares fitting approach for the different types of soil. Further, comparisons of the autocorrelation function between the tip resistance and sleeve friction were examined. Based on the autocorrelation data analysis, a new autocorrelation model, named linear-exponential-cosine (LNCS), is considered with differentiability at the origin of the spatial lag axis, and alternating sign along this axis. For all of the four ACF models, a related integral equation is numerically solved for determining the associated Karhunen-Loeve (K-L) representation. In this regard, it is noted that the new model is not only more physics-consistent, but also yields quite good computational efficiency. In the end, the random field of the soil profile is modeled using a two-dimensional K-L expansion with the new model, assuming separability in two dimensions. Highlights: A new autocorrelation model, named linear-exponential-cosine (LNCS), is proposed. The autocorrelation function of tip resistance and sleeve friction are quite similar. The new model is physics-consistent and yields quite good computational efficiency. The random field of the soil profile is modeled using the K-L expansion. … (more)
- Is Part Of:
- Soil dynamics and earthquake engineering. Issue 108(2018)
- Journal:
- Soil dynamics and earthquake engineering
- Issue:
- Issue 108(2018)
- Issue Display:
- Volume 108, Issue 108 (2018)
- Year:
- 2018
- Volume:
- 108
- Issue:
- 108
- Issue Sort Value:
- 2018-0108-0108-0000
- Page Start:
- 1
- Page End:
- 12
- Publication Date:
- 2018-05
- Subjects:
- Soil deposit -- New autocorrelation model -- Karhunen-Loeve expansion -- Random field simulation
Soil dynamics -- Periodicals
Earthquake engineering -- Periodicals
Sols -- Dynamique -- Périodiques
Génie parasismique -- Périodiques
624.176205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02677261 ↗
http://www.sciencedirect.com/science/journal/02617277 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.soildyn.2018.01.036 ↗
- Languages:
- English
- ISSNs:
- 0267-7261
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8322.225000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11473.xml