Simultaneous identification of parameter,initial condition,and boundary condition in groundwater modelling

In this paper, we perform an inverse method to simultaneously estimate aquifer parameters, initial condition, and boundary conditions in groundwater modelling. The parameter estimation is extended to a complete inverse problem that makes the calibrated groundwater flow model more realistic. The adjoint state method, the gradient search method, and the least square error algorithm are combined to build the optimization procedure. Horizontal two‐dimensional groundwater flow in a confined aquifer is exemplified to demonstrate the correlation between unknowns, the contribution of observation, as well as the suitability of applying the inverse method. The correlation analysis shows the connection between storage coefficient and initial condition. Besides, transmissivity and boundary conditions are also highly correlated. More observations at different location and time are necessary to provide sufficient information. A time series of unsteady head is requested for estimation of storage coefficient and initial condition. Observation near boundary is very effective for boundary condition estimation. The observation at pumping well mostly contributes to the estimation of transmissivity. According to all observations, it is possible to identify parameters, initial condition, and boundary condition simultaneously. Furthermore, the results not only illustrate the traditional assumption of known boundary condition but also initial condition, which may cause an incorrect estimation. Copyright © 2009 John Wiley & Sons, Ltd.     

An Adaptive Supervised Nonlinear Feature Extraction for Hyperspectral Imagery Classification

In this paper, an improved version of locally linear Embedding is proposed. In the proposed method, spectral correlation angle is invited to describe the distance between data points, which is expected to fit the hyperspectral image (HSI). The neighborhood graph of the data points is constructed based on supervised method. Different from traditional supervised feature extraction methods, the weight factors, which are used to control the transform, are adaptively achieved. In this way, the input arguments of original algorithm are not increased. To justify the effectiveness of the proposed method, experiments are conducted on two HSIs. Results show that the proposed method can improve the separability of HSI especially in low dimensions.     

Behaviour of an outward inclined-vertical framed retaining wall of an excavation

Acta Geotechnica - A new excavation retaining structure, referred to as an outward inclined-vertical framed retaining wall (OIVFRW), has been developed and adopted in practice. This retaining...     

Coupled thermal–hydraulic modeling of artificial ground freezing with uncertainties in pipe inclination and thermal conductivity

Acta Geotechnica - Artificial ground freezing (AGF) has been widely used as a temporary soil stabilization and waterproofing technique in geotechnical practices (e.g., tunnel construction). Many...     

A Caputo variable-order fractional damage creep model for sandstone considering effect of relaxation time

Acta Geotechnica - Establishing a fractional creep model with few parameters and explicit physical interpretation is of significant meaning for predicting rheological deformation of rock. In this...     

Estimation of constant-damage residual displacements in terms of maximum inelastic displacements for SDOF structures

Bulletin of Earthquake Engineering - This paper investigates the constant-damage residual displacement ratios Cr (i.e., the ratio of the residual displacement in terms of the maximum inelastic...     

Bagging-based machine learning algorithms for landslide susceptibility modeling

Natural Hazards - Landslide hazards have attracted increasing public attention over the past decades due to a series of catastrophic consequences of landslide occurrence. Thus, the mitigation and...     

Quantitative research on drought loss sensitivity of summer maize based on AquaCrop model

Natural Hazards - In this study, the growth periods of summer maize were divided into seedling, booting and flowering-grain stage. Based on the simulation results of AquaCrop model, the drought...     

SPH modeling of tidal bore scenarios

Natural Hazards - The paper presented a smoothed particle hydrodynamics (SPH) method to study the three-dimensional (3D) tidal bore scenarios. The SPH method is a mesh-free particle modeling...