H-adaptive finite element analysis of consolidation problems in geomechanics

In this paper, a computational framework based on the h-adaptive finite element strategy is presented for the solution of consolidation problems in geomechanics. The efficiency and performance of alternative error estimation techniques is demonstrated via the analysis of a slope stability problem

Removal of total petroleum hydrocarbons from polluted urban soils of the outskirts of Ahvaz, southwestern Iran

Earlier phases of economic expansion and urban development have resulted in significant sources of urban soil contamination. Petroleum hydrocarbons are one of the most common groups of persistent organic contaminants in the environment. In this study, two types of treatment in 3 concentrations were prepared that were included plant treated by 1% oil pollution, treatment by 1% contamination without plant (as control), plant treated by 5% oil pollution, the 5% pollution treatment without plant (control), 10% oil pollution treatment with plant and 10% treatment without plant (control) that 3 replicates were prepared for each treatment. The obtained extracts were concentrated to 1 mL under a gentle stream of nitrogen gas, and then 2 μg of the sample was injected into a UNICAM 610 series gas chromatograph equipped with a flame ionization detector. Primary Total petroleum hydrocarbons amount in 1%, 5% and 10% concentration was respectively: 9027.40 mg/kg, 49599.03 mg/kg and 99548.28 mg/kg. After 4 months its amount in different concentration with plant was 126.43 mg/kg, 4463.92 mg/kg and 19611.50 mg/kg. The best total petroleum hydrocarbons removal efficiency was observed in all concentration at 120th day. The results of this study showed that vetiver can remove petroleum hydrocarbons from contaminated soils effective. <br /

Evaluating the clinical feasibility of an artificial intelligence–powered, web-based clinical decision support system for the treatment of depression in adults: longitudinal feasibility study

Background:- Approximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence–powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows. Objective:- This study aims to examine the feasibility of an artificial intelligence–powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network–based individualized treatment remission prediction. Methods:- Owing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews. Results:- Data were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F2,24=0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change. Conclusions:- Our findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies

On the application of the maximum entropy meshfree method for elastoplastic geotechnical analysis

In this study, the Maximum Entropy Meshfree (MEM) method is employed for analysing geotechnical problems involving material nonlinearity, assuming small strains. The efficiency of the MEM method is evaluated through several solution schemes for the global governing equations as well as the local constitutive equations. The conventional implicit approach involving the Newton-Raphson method and an explicit adaptive dynamic relaxation technique are employed for solving the governing equations, while local constitutive equations are solved numerically as well as analytically. Two- and three-dimensional numerical experiments are performed to study the efficiency of different configurations of the solution scheme, which leads to some important conclusions about application of the MEM method in geotechnical problems

Large deformation analysis of geomechanics problems by a combined rh-adaptive finite element method

Finite element analysis of large deformation problems is a major challenge in computational geomechanics, due largely to the severe mesh distortion that may occur after updating the spatial configuration of the nodal points using a conventional Updated-Lagrangian approach. There are two alternative and reasonably well-known strategies to tackle this issue of mesh distortion, viz., the r-adaptive and h-adaptive methods. The r-adaptive finite element method has been designed to eliminate possible mesh distortion by changing and optimising the locations of the nodal points without modifying the overall topology of the mesh adopted to solve a given problem. In order to obtain an accurate solution by this method a relatively fine mesh is required right from the beginning of the analysis, which potentially increases the overall analysis time. On the other hand, the h-adaptive finite element method improves the accuracy of the solution by gradually decreasing the size of the elements based on an error assessment method. However, this approach may leave the very small elements in the mesh vulnerable to distortion. To eliminate the individual drawbacks of these adaptive methods, while preserving the accuracy of the solution, a combined rh-adaptive finite element method has been developed and is presented in this paper for the analysis of sophisticated problems of geomechanics that involve large deformations and changing boundary conditions. The proposed method is designed to improve the accuracy of the solution obtained using the h-refinement strategy while successfully avoiding the mesh distortion by the use of r-adaptive refinement. It is shown that this new combination can significantly increase the efficiency of adaptive finite element methods

H-adaptive finite element analysis of consolidation problems in geomechanics

In this paper, a computational framework based on the h-adaptive finite element strategy is presented for the solution of consolidation problems in geomechanics. The efficiency and performance of alternative error estimation techniques is demonstrated via the analysis of a slope stability problem

Analysis of soil penetration problems by high-order elements

This paper addresses the application of high-order elements in the analysis of soil penetration problems, particularly those involving inertia forces and large deformations. Among others, 15-node triangular elements are formulated within an Arbitrary Lagrangian-Eulerian finite element method. Preliminary studies indicate that high-order elements can significantly decrease the analysis time without significant loss of accuracy. © (2014) Trans Tech Publications, Switzerland

Strain-rate-dependent plasticity of Ta-Cu nanocomposites for therapeutic implants

Abstract Recently, Ta/Cu nanocomposites have been widely used in therapeutic medical devices due to their excellent bioactivity and biocompatibility, antimicrobial property, and outstanding corrosion and wear resistance. Since mechanical yielding and any other deformation in the patient's body during treatment are unacceptable in medicine, the characterization of the mechanical behavior of these nanomaterials is of great importance. We focus on the microstructural evolution of Ta/Cu nanocomposite samples under uniaxial tensile loading conditions at different strain rates using a series of molecular dynamics simulations and compare to the reference case of pure Ta. The results show that the increase in dislocation density at lower strain rates leads to the significant weakening of the mechanical properties. The strain rate-dependent plastic deformation mechanism of the samples can be divided into three main categories: phase transitions at the extreme strain rates, dislocation slip/twinning at lower strain rates for coarse-grained samples, and grain-boundary based activities for the finer-grained samples. Finally, we demonstrate that the load transfer from the Ta matrix to the Cu nanoparticles via the interfacial region can significantly affect the plastic deformation of the matrix in all nanocomposite samples. These results will prove useful for the design of therapeutic implants based on Ta/Cu nanocomposites

Unraveling the temperature-dependent plastic deformation mechanisms of polycrystalline Ta implants through numerical analysis of grain boundary dynamics

Nanostructured tantalum (Ta)-based dental implants have recently attracted significant attention thanks to their superior biocompatibility and bioactivity as compared to their titanium-based counterparts. While the biological and chemical aspects of Ta implants have been widely studied, their mechanical features have been investigated more rarely. Additionally, the mechanical behavior of these implants and, more importantly, their plastic deformation mechanisms are still not fully understood. Accordingly, in the current research, molecular dynamics simulation as a powerful tool for probing the atomic-scale phenomena is utilized to explore the microstructural evolution of pure polycrystalline Ta samples under tensile loading conditions. Various samples with an average grain size of 2–10 nm are systematically examined using various crystal structure analysis tools to determine the underlying deformation mechanisms. The results reveal that for the samples with an average grain size larger than 8 nm, twinning and dislocation slip are the main sources of any plasticity induced within the sample. For finer-grained samples, the activity of grain boundaries—including grain elongation, rotation, migration, and sliding—are the most important mechanisms governing the plastic deformation. Finally, the temperature-dependent Hall–Petch breakdown is thoroughly examined for the nanocrystalline samples via identification of the grain boundary dynamics