Impact of freeze-thaw cycles and influent C/N ratios on N2O emissions in subsurface wastewater infiltration systems DOI
Fei Su, Yinghua Li, Jie Qian

et al.

Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: 12(6), P. 114293 - 114293

Published: Oct. 9, 2024

Language: Английский

Soft computing and eddy currents to estimate and classify delaminations in biomedical device CFRP plates DOI Open Access
Mario Versaci, Filippo Laganá,

Laura Manin

et al.

Journal of Electrical Engineering, Journal Year: 2025, Volume and Issue: 76(1), P. 72 - 79

Published: Feb. 1, 2025

Abstract This paper presents an approach based on eddy currents induced by suitable magnetic induction fields to test, estimate, and classify subsurface delaminations in Carbon Fibre Reinforced Polymer (CFRP) plates for biomedical devices. The two-dimensional maps obtained, characterised high fuzziness, required the software development of a procedure highly efficient fuzzy classifier that exploits similarity computations with reduced computational load collecting similar (deriving from equally defects) specific defects. hardware implementation what is designed (plate-probe system) detects evaluates entity defects due classification percentage comparable performances obtained more sophisticated classifiers, providing possible tool evaluating potentially useful assess aircraft compliance applicable safety standards.

Language: Английский

Citations

6

Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model DOI Creative Commons

K.K. Li,

Hailong He

Geoscience Frontiers, Journal Year: 2024, Volume and Issue: 15(6), P. 101898 - 101898

Published: July 31, 2024

As an essential property of frozen soils, change unfrozen water content (UWC) with temperature, namely soil-freezing characteristic curve (SFCC), plays significant roles in numerous physical, hydraulic and mechanical processes cold regions, including the heat transfer within soils at land–atmosphere interface, frost heave thaw settlement, as well simulation coupled thermo-hydro-mechanical interactions. Although various models have been proposed to estimate SFCC, their applicability remains limited due derivation from specific soil types, treatments, test devices. Accordingly, this study proposes a novel data-driven model predict SFCC using extreme Gradient Boosting (XGBoost) model. A systematic database for compiled extensive experimental investigations via testing methods was utilized train XGBoost The predicted freezing curves (SFCC, UWC function temperature) well-trained were compared original data three conventional models. results demonstrate superior performance over traditional predicting SFCC. This provides valuable insights future regarding soils.

Language: Английский

Citations

10

A multi-field coupled model contained volumetric strain for unsaturated frozen soil and thermal-hydro-mechanical evolution characteristics of permafrost tunnel DOI

Hongyu Huang,

Yuanfu Zhou,

Xiaoqing Suo

et al.

Cold Regions Science and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 104510 - 104510

Published: April 1, 2025

Language: Английский

Citations

0

A thermodynamic multi-field model for unsaturated sulfate-saline soils considering crystallization process DOI
Bing Bai, Bixia Zhang,

Yanjie Ji

et al.

Computers and Geotechnics, Journal Year: 2025, Volume and Issue: 184, P. 107251 - 107251

Published: April 8, 2025

Language: Английский

Citations

0

Physics-informed neural networks for solving steady-state temperature field in artificial ground freezing DOI

Kai-Qi Li,

Zhen‐Yu Yin, Ning Zhang

et al.

Canadian Geotechnical Journal, Journal Year: 2025, Volume and Issue: 62, P. 1 - 17

Published: Jan. 1, 2025

Artificial ground freezing (AGF) is a widely used technique for soil stabilization and waterproofing. Numerous studies have been devoted to solving the heat transfer problems in AGF while encountering limitations handling complex geometries boundary conditions being computationally intensive. Recently, using machine learning methods predict temperature fields has gained attention, demonstrating potential achieve higher accuracy than conventional models. However, these are typically limited by need large, labeled datasets, which time-consuming difficult obtain. In this study, we address challenges applying physics-informed neural networks (PINNs) solve steady-state problem AGF, focusing on distribution around single pipe. By embedding conduction equation into loss function, PINNs reduce extensive data. To enhance efficiency, employed, results compared against finite element method. Results show that high accuracy, particularly larger domains with moderate gradients, providing competitive performance more configurations involving steeper gradients. This approach offers promising alternative modeling geotechnical applications, implications reducing computational costs design.

Language: Английский

Citations

0

Atomistic origin of montmorillonite clay subjected to freeze-thaw hysteresis DOI Creative Commons
Pengchang Wei, Zhen‐Yu Yin, Chi Yao

et al.

Journal of Rock Mechanics and Geotechnical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Citations

3

Physics-encoded convolutional attention network for forward and inverse analysis of spatial-temporal parabolic dynamics considering discontinuous heterogeneity DOI Creative Commons
Xi Wang, Zhen‐Yu Yin

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2025, Volume and Issue: 442, P. 118025 - 118025

Published: May 8, 2025

Language: Английский

Citations

0

Stability Analysis of Borehole Walls When Drilling with Normal-Temperature Drilling Fluids in Permafrost Strata DOI Open Access

Jihui Shi,

Li Yang, Chuanliang Yan

et al.

Processes, Journal Year: 2024, Volume and Issue: 12(9), P. 1819 - 1819

Published: Aug. 27, 2024

Permafrost is a temperature-sensitive geological formation characterized by low elasticity and high plasticity. Inappropriate engineering design during borehole drilling in permafrost can result the collapse of surrounding strata. To evaluate stability walls, finite element model was developed based on inherent physical properties permafrost. This utilized to investigate thermal, stress, plastic yield zone evolution around with normal-temperature fluids. The expansion rate employed as quantitative measure assess wall stability. analysis reveals that strata adjacent borehole, when drilled fluids, experience thawing yielding, secondary stress concentrations unthawed driving progressive zone. degree deformation diminishes increasing distance from borehole. Consequently, risk under varying conditions, including thickness, depth, strain thresholds, fluid densities. findings suggest fluids are appropriate for thin layers, whereas thicker permafrost, adjustments density required ensure walls due elevated temperatures geostress at greater depths.

Language: Английский

Citations

1

Impact of freeze-thaw cycles and influent C/N ratios on N2O emissions in subsurface wastewater infiltration systems DOI
Fei Su, Yinghua Li, Jie Qian

et al.

Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: 12(6), P. 114293 - 114293

Published: Oct. 9, 2024

Language: Английский

Citations

1