For construction quality control, the compaction delay referred to as mellowing time (MT) is crucial for achieving the desired outcomes of the chemical soil stabilization process in the field. In the current study, fly ash-based geopolymer (GFA) is used as a chemical stabilizer for expansive clay because of its significance in resource utilization and waste repurposing for soil stabilization through an enhanced process. The MT-influenced macroscopic physicomechanical properties and microstructural and mineralogical properties of expansive clay treated with varying GFA and curing period (CP) were investigated. The significant amelioration of strength and compression properties is observed through the unconfined compression test, California bearing ratio test, and one-dimensional (1D) consolidation test with an increase in GFA content and CP. This improvement is caused by the formation of cementitious [(N, C)-A-S-H] compounds as confirmed by SEM, EDAX, and XRD analyses. Meanwhile, as the MT increases, a decline in both the strength and compression characteristics of the GFA-treated specimens is observed. However, these specimens exhibit a reversal in deformability and brittleness with an increase in MT, which can be attributed to the development of a porous aggregated soil structure resulting from initial hydration before densification. In addition, a generalized mathematical modeling framework was established based on three-dimensional (3D) response surface modeling to quantify the MT-influenced strength and brittleness-related characteristics using MT, GFA, and CP as predictors. The established mathematical framework showed generality and reasonable accuracy in the prediction based on the experimental data. This article outlines the implications for practitioners and researchers of using GFA for the stabilization of expansive clay considering MT-influenced mechanical characteristics in the field.

Soil erosion is a major issue in the Indian Himalayan region, affecting both mountainous areas and the Terai. In the Terai, significant surface soil loss is driven by factors such as sandy soils, shallow soil depth, high rainfall, and the erosive force of young rivers. Human activities, including the conversion of forests and grasslands to croplands and settlements, along with poor agricultural practices, exacerbate the problem. This pilot-scale study aimed to quantify surface soil erosion and the loss of soil organic matter and nutrients in a watershed of the eastern Himalayan Terai region of India, utilizing the Revised Universal Soil Loss Equation (RUSLE) model on a Geographic Information System (GIS) platform. The results revealed substantial soil loss (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{x }$$\end{document} = 32.0 Mg ha-1 yr-1), along with the removal of organic matter (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{x }$$\end{document} = 0.95 Mg ha-1 yr-1), available nitrogen (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{x }$$\end{document} = 1.49 kg ha-1 yr-1), available phosphorus (P2O5) (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{x }$$\end{document} = 0.50 kg ha-1 yr-1), and available potassium (K2O) (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{x }$$\end{document} = 5.02 kg ha-1 yr-1). Ground surveys indicated that a significant portion of the local population was directly or indirectly affected by the annual loss of fertile topsoil, with farmers, agricultural workers, and tea garden owners being the most impacted. The erosion problem of Terai region remains unheard of as it does not cause direct damage like landslides. However, loss of topsoil every year declines the land productivity and curbs the agricultural financial benefit margin. The study recommends expanding soil erosion monitoring and modelling across the entire eastern Himalayan Terai region. Being a cost and time friendly reliable method, use of RUSLE on the GIS platform can be the best option for that. With updated erosion data, comprehensive management measures can be developed involving policymakers, administrators, researchers, and local communities.

In many areas around the world, there are clayey soils that have the potential to change their volume caused by the variation in their water content. Increasing or decreasing the water content caused the clayey soils to swell or shrink, respectively. This phenomenon may cause the uplifting and settlement of structures, which may lead to considerable financial damages. The estimation of swelling displacement without addressing the swelling rate have been published by several research works. This drawback leads to the development of a new model that takes into account the swelling behavior of soils with time. The model, which consists of two hyperbolic curves, was compared with swelling test results performed on soil samples taken from several locations in Israel. Data test results were used to compare the newly introduced model with other existing mathematical models found in the literature. This analysis shows that the new model represents more accurately the behavior with time of the swelling clayey soils measured in laboratory test results than the existing hyperbolic models.

This study presents a novel approach to forecasting the evolution of hysteresis stress-strain response of different types of soils under repeated loading-unloading cycles. The forecasting is made solely from the knowledge of soil properties and loading parameters. Our approach combines mathematical modeling, regression analysis, and Deep Neural Networks (DNNs) to overcome the limitations of traditional DNN training. As a novelty, we propose a hysteresis loop evolution equation and design a family of DNNs to determine the parameters of this equation. Knowing the nature of the phenomenon, we can impose certain solution types and narrow the range of values, enabling the use of a very simple and efficient DNN model. The experimental data used to develop and test the model was obtained through Torsional Shear (TS) tests on soil samples. The model demonstrated high accuracy, with an average R 2 value of 0.9788 for testing and 0.9944 for training.

This study investigated the effect of compaction effort and soaking time on the shear strength properties of fine-grained gypsum-containing soils. The objective was to demonstrate that increasing compaction effort increases soil strength, specifically cohesion and the angle of shear strength, when subjected to soaking in freshwater. Unconsolidated undrained triaxial tests were carried out on CBR soil samples with different soaking times. The results showed a transition from brittle to ductile failure behaviour as the soaking time increased. Mohr-Coulomb failure envelopes showed reduced cohesion and angle of shear strength with increasing soak time. Regression models were developed to establish correlations between soaked and unsoaked strength parameters. Strong relationships were found between soil strength properties, compaction effort and soaking time. Empirical equations were proposed to estimate the cohesion and angle of shear strength from compaction effort and soaking time. This study highlighted the importance of considering gypsum-rich soils in civil engineering design. Gypsum dissolution during wetting significantly affected soil strength parameters. The regression models and empirical equations provide engineers with tools to assess the influence of compaction effort and soaking time on soil strength, thus aiding decision making when designing structures on gypsum-rich soils.

Soil massif fracturing has a significant impact on change in engineering and geological conditions and, as a result, on stability of structures. Development of tectonic fracturing of local structures, taking into account the history of the process, its mechanism, resulting stresses in the massif and subsequent deformations of the rocks, led to a change in their structure, composition and strength characteristics, activation of hypergenesis and exogenous processes. The above circumstances require careful attention to identification of areas of increased fracturing, as the most dangerous in terms of risks during the construction of engineering structures. Field methods for assessing the fracturing of rock masses are laborious. It is not always possible to conduct instrumental surveys that allow solving the final problem - establishing patterns and sizes of damaged areas within local structures. The existing mathematical models for assessing fracturing, as a rule, are used to solve local problems: assessing the stability of developed pits, water content of rock masses, degree of fragmentation of individual blocks, etc. This information is not sufficient when assessing the areal distribution of weakened zones and clarifying their boundaries, since it does not take into account the history of the development of the structure, its parameters (dimensions, amplitude of the foundation block uplift, deformation properties of rocks). Aim. To develop a mathematical model of formation of the red -colored strata tectonic fracturing zones based on deformation criterion of destruction and mechanism of development of local structures. Results. The authors have developed a new mathematical model for predicting damage (fracturing) of terrigenous rocks of the red -colored strata that make up local structures, based on the mechanism of formation of local tectonic structures of the 3rd order and the deformation criterion of destruction. The paper introduces the mathematical dependencies that make it possible to predict the size (area) of taxa based on the data on the uplift amplitude of local structures. The results of the research can be used in assessing the fracturing of massifs composed of terrigenous rocks, and make it possible to judge the regularities in distribution of weakened zones within the entire massif being assessed.

The process of wells ecology drilling without a preliminary drilled soil mechanical properties assessment is studied. An analytical mathematical model of a drilling unit as the object under control has been worked out. It is shown that due to the interaction through the power plant and a drillable soil, there is a natural cross-link between the feed control contour and the drill rotation control contour, which has a significant influence on the drilling dynamics. Cross-link parameters depend on the soil mechanical properties and conditions. To compensate for cross-connection, it is proposed to use a three-level control system, with a neural network at the middle hierarchical level. The structure of the neural network has been worked out, and tasks, solved in each neuron layer, are determined. The algorithm of digital controller adjusting, allowing to achieve the optimal ecology drilling modes has been developed

In China's Chang'e 7 mission, a miniflyer will be carried for in-situ water ice measurement in permanently shadowed regions (PSRs) around the lunar south pole. The extreme cold environment within PSRs causes serious challenges for the safety of the miniflyer. Predication of temperatures in PSR is critical for designing the internal heating system and the heat source capacity. Conducting in-situ detection mission in relatively warm temperature can reduce the threat of the cold environment and save energy to maintain a suitable operation temperature for payloads. Since the polar-orbiting satellite lunar reconnaissance orbiter passes over the same location in the polar region with intervals of about a month, the temporally continuous observation is unavailable. Simulation is necessary to determine the temporally continuous temperatures of PSR during the mission. In this article, a numerical model of the temperatures in PSR is presented. The ray tracing approach is used to calculate the shadowing effect of terrain on scattered sunlight and thermal radiation. The PSR temperatures are simulated with the one-dimensional heat conduction equation. Simulated temperatures are compared with Diviner data for validation. The spatial and temporal temperature distributions of PSRs in crater Shackleton, which is the preferred landing site for the Chang'e 7 mission, are simulated from 2026 to 2028. The simulated temperature in high temporal resolution of one Earth hour can be applied to analyzing diurnal and seasonal temperatures in PSRs and is helpful for thermal management and design of the internal heating system. The time windows with relatively warm temperature in PSR at regions with slope angles less than 5(degrees) are recommended to save energy and reduce the hazards of the extremely cold environment.

The freezing front depth (z(ff)) of annual freeze-thaw cycles is critical for monitoring the dynamics of the cryosphere under climate change because z(ff) is a sensitive indicator of the heat balance over the atmosphere-cryosphere interface. Meanwhile, although it is very promising for acquiring global soil moisture distribution, the L-band microwave remote sensing products over seasonally frozen grounds and permafrost is much less than in wet soil. This study develops an algorithm, i.e., the brightness temperature inferred freezing front (BT-FF) model, for retrieving the interannual z(ff) with the diurnal amplitude variation of L-band brightness temperature (?T-B) during the freezing period. The new algorithm assumes first, the daily-scale solar radiation heating/cooling effect causes the daily surface thawing depth (z(tf)) variation, which leads further to ?T-B; second, ?T-B can be captured by an L-band radiometer; third, z(tf) and z(ff) are negatively linear correlated and their relation can be quantified using the Stefan equation. In this study, the modeled soil temperature profiles from the land surface model (STEMMUS-FT, i.e., simultaneous transfer of energy, mass, and momentum in unsaturated soil with freeze and thaw) and T-B observations from a tower-based L-band radiometer (ELBARA-III) at Maqu are used to validate the BT-FF model. It shows that, first, ?T-B can be precisely estimated from z(tf) during the daytime; second, the decreasing of z(tf) is linearly related to the increase of z(ff) with the Stefan equation; third, the accuracy of retrieved z(ff) is about 5-25 cm; fourth, the proposed model is applicable during the freezing period. The study is expected to extend the application of L-band T-B data in cryosphere/meteorology and construct global freezing depth dataset in the future.

Alpine permafrost environments are highly vulnerable and sensitive to changes in regional and global climate trends. Thawing and degradation of permafrost has numerous adverse environmental, economic, and societal impacts. Mathematical modeling and numerical simulations provide powerful tools for predicting the degree of degradation and evolution of subsurface permafrost as a result of global warming. A particularly significant characteristic of alpine environments is the high variability in their surface geometry which drives large lateral thermal and fluid fluxes along topographic gradients. The combination of these topography-driven fluxes and unsaturated ground makes alpine systems markedly different from Arctic permafrost environments and general geotechnical ground freezing applications, and therefore, alpine permafrost demands its own specialized modeling approaches. In this work, we present a multi-physics permafrost model tailored to subsurface processes of alpine regions. In particular, we resolve the ice-water phase transitions, unsaturated conditions, and capillary actions, and account for the impact of the evolving pore space through freezing and thawing processes. Moreover, the approach is multi-dimensional, and therefore, inherently resolves the topography-driven horizontal fluxes. Through numerical case studies based on the elevation profiles of the Zugspitze (DE) and the Matterhorn (CH), we show the strong influence of lateral fluxes in 2D on active layer dynamics and the distribution of permafrost.