Hasil untuk "Engineering geology. Rock mechanics. Soil mechanics. Underground construction"

Chuanqing Zhang, Qiangqiang Zhang, Qiang Cui et al.

The axial load-bearing capacity of grouted anchorage systems is critical for rock reinforcement and reflects the interactions among system components. Hence, the mechanical response and failure characteristics of the anchorage system under axial loading are of vital importance. They serve as the foundation for establishing the mechanical model of the anchorage system and provide significant guidance for the optimization design of bolts and the assessment of anchorage conditions. However, as the most widely used research method, current pullout tests have not paid sufficient attention to simulating actual rock mass stiffness, have not fully revealed the radial mechanical response during the pullout process, and have not clarified the locations and modes of pullout failure. To address these issues, a testing method simulating hard rock stiffness and strength was developed using elasticity and stiffness equivalence theories. Tests revealed three anchorage failure modes under equivalent hard rock stiffness: tooth cutting, sliding, and sliding-tooth cutting composite failure, with the composite failure being dominant. The pullout load-displacement curves exhibited bimodal patterns for composite failure and single peaks for tooth cutting and sliding failures. Post-peak softening showed up-convex curves for tooth cutting and down-concave curves for sliding failure, while bolt yielding displayed distinct plateaus. The radial stress trends at the rock-grout interface paralleled pullout load curves, with sliding failure exhibiting approximately 10 MPa lower peak radial stress compared to tooth cutting failure. Anchorage length most strongly affected peak load, while grout properties predominantly governed failure mode.

Aghileh Khajeh, Mahdi Salimi, Hossein MolaAbasi et al.

Mohammad Nabizadeh, Abbas Soroush, Seyed Mohammad Fattahi et al.

Deyun Liu, Mengting Wang, Ci Wang

Utilizing the Discrete Element Method, this research studied the stiffness distribution of gap-graded soils by modifying the conventional static method. By acknowledging the inherent particle property disparity between coarser and finer particles, this research differentiates the stiffness distribution of gap-graded soils from the perspective of contact and particle types. Results indicate that particle property disparity significantly influence the small-strain stiffness characteristics, consequently altering the overall stiffness distribution in gap-graded soil specimens. Specifically, with the equivalent coarser particle property, an increase in particle Young's modulus of finer particles results in an augmentation of small-strain stiffness values, alongside an increased stiffness distribution contribution from finer particles. Nevertheless, this study reveals that even with a higher particle Young's modulus of finer particles, the proportion of small-strain stiffness transferred by finer particles remains consistently lower than their volume fraction. Furthermore, the proportion of stiffness transferred by finer particles may fall below their contribution to stress transmission. This investigation accentuates the subtle yet significant effects of particle property variations on small strain stiffness and its subsequent distribution, providing a foundation for advancing the significance of particle property disparities in evaluating soil responses.

Shixin Zhang, Yufeng Wei, Yanling Liu et al.

Earthquakes contribute to the failure of anti-dip bedding rock slopes (ABRSs) in seismically active regions. The pseudo-static method is commonly employed to assess the ABRSs stability. However, simplifying seismic effects as static loads often underestimates rock slope stability. The development of a practical stability analysis approach for ABRSs, particularly in slope engineering design, is imperative. This study proposes a stability evaluation model for ABRSs, incorporating the viscoelastic properties of rock, to quantitatively assess the safety factor and failure surface under seismic conditions. The mathematical description of the pseudo-dynamic method, derived in this study, accounts for the viscoelastic properties of ABRSs and integrates the Hoek–Brown failure criterion with the Kelvin-Voigt stress-strain relationship of rocks. Furthermore, to address concurrent translation-rotation failure in ABRSs, upper bound limit analysis is utilized to quantify the safety factor. Through a comparison with existing literature, the proposed method considers the effect of harmonic vibration on the stability of ABRSs. The obtained safety factor is lower than that of the quasi-static method, with the resulting percentage change exceeding 5%. The critical failure surface demonstrates superior positional accuracy compared to the Aydan and Adhikary basal planes, with minimal error observed between the physical model test and the numerical simulation test. The parameter sensitivity analysis reveals that the inclination of ABRSs exhibits the highest sensitivity (Sk) value across the three levels of horizontal seismic coefficient (kh). The study aims to devise an expeditious calculation approach for assessing the stability of ABRSs during seismic events, intending to offer theoretical guidance for their stability analysis.

WANG Kai, FENG Guorui, BAI Jinwen et al.

To investigate the actual dynamic fracture process and energy dissipation mechanisms of coal under triaxial loading conditions, a visual experimental study was conducted using a self-developed multi-field coupled Split Hopkinson Pressure Bar (SHPB) testing system. This research systematically examined crack evolution characteristics in coal samples under varying water confining pressure conditions. The relationships between dynamic mechanical parameters (impact velocity, strain rate, and water confining pressure) were quantitatively analyzed, along with the influence of water confining pressure on energy absorption, conversion, and release processes during coal failure. The research results show that the dynamic strength of coal shows obvious strain rate effect under water confining pressure environment. There is a good quadratic function relationship between water confining pressure and the dynamic strength of coal mass, and the failure strain of coal samples shows a decreasing trend with the increase of water confining pressure. With the increase of water confining pressure, the fracture mode of coal mass will change from "axial splitting failure" to "compression-shear failure". The greater the impact load, the higher the total energy input to the coal body and the dissipated energy used for damage and deformation, and the more serious the deformation of the coal body. With the increase of water confining pressure, the total input energy shows a trend of gradual increase, and more energy is required from the outside when the coal body is damaged.

António Gomes Correia, Eduardo Fortunato

Morgan D. Sanger, Mertcan Geyin, Brett W. Maurer

Using machine learning (ML), high performance computing, and a large body of geospatial information, we develop surrogate models to predict soil liquefaction across regional scales. Two sets of models - one global and one specific to New Zealand - are trained by learning to mimic geotechnical models at the sites of in-situ tests. Our geospatial approach has conceptual advantages in that predictions: (i) are anchored to mechanics, which encourages more sensible response and scaling across the domains of soil, site, and loading characteristics; (ii) are driven by ML, which allows more predictive information to be used, with greater potential for it to be exploited; (iii) are geostatistically updated by subsurface data, which anchors the predictions to known conditions; and (iv) are precomputed everywhere on earth for all conceivable earthquakes, which allows the models to be executed very easily, thus encouraging user adoption and evaluation. Test applications suggest that: (i) the proposed models outperform others to a statistically significant degree; (ii) the geostatistical updating further improves performance; and (iii) the anticipated advantages of region-specific models may largely be negated by the benefits of learning from larger global datasets. These models are best suited for regional-scale liquefaction hazard simulation and near-real-time response and are accompanied by variance products that convey where, and to what degree, the ML-predicted liquefaction response is influenced by local geotechnical data.

Guodong Jiang, Minghao Dai, Guozhu Zhang et al.

The emergence of curved shield tunnels poses a significant construction challenge. If the quality of the segment assembly is not guaranteed, many segment cracks and damage will result from the stress concentration. Sensing the contact stresses between segmental joints is necessary to improve the quality of segments assembled for shield tunnel construction. Polyvinylidene difluoride (PVDF) piezoelectric material was chosen for the sensor because it can convert contact stresses into electrical signals, allowing the state of the segmental joints to be effectively sensed. It matches the working environment between the segmental joints of the shield tunnel, where flexible structures such as rubber gaskets and force transfer pads are present. This study proposes a piezoelectric sensing method for segmental joints in shield tunnels and conducts laboratory tests, numerical analyses, and field tests to validate the feasibility of the method. The results indicate that the PVDF film sensor can effectively sense the entire compression process of the gasket with different amounts of compression. The piezoelectric cable sensor can effectively sense the joint offset direction of the gasket. For differently shaped sections, the variation in the force sensed by the piezoelectric cable sensors was different, as verified by numerical simulation. Through the field test, it was found that the average contact stress between the segmental joints was in the range of 1.2–1.8 MPa during construction of the curved shield tunnels. The location of the segmental joints and the type of segment affect the contact stress value. The field monitoring results show that piezoelectric sensing technology can be successfully applied during assembly of the segments for effective sensing of the contact stress.

Javanshir AziziMobaser, Erfan Faraji Amogein

IntroductionIrrigation planning is one of the management strategies, which is based on determining the exact water requirement. The lysimetric method is the most accurate method of determining the water requirement of the plant, but due to the high cost and the need for high technical knowledge, it cannot be used anywhere. The basis for determining the water requirement in the Ardabil Plain is the use of NETWAT software output information, which is known as the National Water Document of Iran. This software calculates the water requirement using the Penman-Monteith FAO model. The output of this software due to the need to update climate information, not introducing the exact range of plains, ignoring sub-climates in some plains and catchments (including Ardabil Plain), and not considering some important crops in the plain (lack of potato water requirement in Ardabil Plain) and the creation of new databases in recent years, should be reconsidered. Material and MethodsThis study in Ardabil Plain and water requirement of the dominant crop pattern including wheat, barley, potato, alfalfa, and bean crops was calculated by the Penman-Monteith method and CROPWAT software. To calculate the net irrigation requirement, first, the evapotranspiration potential of the plain was obtained using climatic information from three stations Ardabil, Abi Biglou, and Namin. Then, the effective rainfall of the plain was extracted by the information from Ardabil, Abybeigloo, Namin, Koozeh Topraghi, Gilande, and Samian rain gauge stations. Required information on plain soil was prepared using 22 points in the plain. In the last step of the information preparation phase, the characteristics of the cropping pattern plants were defined using field measurements, local experiments, and FAO publication No. 56. The cropping pattern (91.4% of the cultivated area of Ardabil Plain) included wheat, barley, potatoes, alfalfa, and beans, which according to the five-year statistics ending in 2021, the cultivated area of these crops was 18,300 (32.6%), 10300 (19.4%), 15700 (28%), 5200 (9.2%) and 1200 (2.2%) hectares. After preparing the case information, the water requirement was calculated for each of the wheat, barley, potato, alfalfa and bean products in each of the soil sampling points in 10-day periods during the growing season. Based on the point information obtained, a zoning map of net irrigation needs in the Ardabil Plain was prepared. Results and DiscussionBased on the obtained point information, a zoning map of net irrigation needs in the Ardabil Plain was prepared. The results showed that the zoning of the net need for irrigation divides the Ardabil Plain into three separate parts in this regard. The northern part and the southern part are divided into high consumption, the eastern and southeastern parts are low consumption, and the western part and parts of the center are divided into medium consumption. In addition, according to the zoning results, the average, minimum, and maximum net irrigation needs of the crops were calculated. For the wheat crop, the average, minimum, and maximum net irrigation requirements were 164, 314, and 259 mm, respectively. For the barley crop, the average, minimum, and maximum net irrigation requirements were 110, 255, and 205 mm, respectively. For the potato crop, the average, minimum, and maximum net irrigation requirements were calculated as 325, 613, and 484 mm, respectively. In addition, for alfalfa and bean crops, the mean, minimum, and maximum net irrigation requirements were estimated at 425, 872, and 670 mm and 337, 637, and 497 mm, respectively. ConclusionThe results showed that if the average of the whole plain is used for wheat, barley, potato, alfalfa, and bean crops, instead of point or regional information, about 18, 20, 21, 23, and 22% deficit irrigation, respectively, and in Low consumption sector accounts for about 58, 86, 49, 58, and 48% of excess irrigation. Also, the results showed that using the output numbers of NETWAT software will cause wrong water management in Ardabil Plain. Therefore, using the results of the National Water Document (NETWAT) will lead to incorrect water management due to the problems mentioned. That is if the results of the national document are used as the basis for determining the water requirement in the Ardabil Plain, compared to the minimum and maximum numbers obtained from this research, about 32 and 38 MCM will occur in the exceeding irrigated and deficit irrigated plains, respectively (without considering the impact potato crop due to not calculating its water requirement in the national water document for Ardabil Plain). Considering climate change and also the development of different databases, it is suggested to use up-to-date information for water requirement calculations. Also, considering that the Ardabil Plain is divided into three separate parts in terms of the net need for irrigation, therefore it is recommended that instead of using one number as the consumption in the whole plain, from point or regional information obtained from this research for wheat, barley, Use potatoes, alfalfa and beans.

Keiji Jindo, Omar El Aroussi, Joris de Vente et al.

Soil organic carbon (SOC) is essential in semi-arid agricultural land for enhancing soil health, particularly through the promotion of microbial activities. This study assessed the impact of different agronomic practices on soil properties, microbial communities, and SOC levels in semi-arid Moroccan wheat fields. Three treatments were investigated: eucalyptus (Eucalyptus spp.) companion planting (EU), and fallowing with harvest residue mulching (FA), with the latter involving both short (3 months; FAS) and long (15 months; FAL) fallow periods. The study revealed significant variation in soil characteristics and microbial communities between these agronomic management regimes. Notably, soils managed with FAL contained elevated SOC levels (1.2%) compared to other treatments (FAS and EU) which show lower SOC range (0.62–0.86%). Both labile C (water-soluble carbon) and recalcitrant C (humic substances) were increased by FAL. Additionally, soil microbial biomass and dehydrogenase activity were observed to be high in FAL-managed soils, along with increased levels of extracellular enzymes related to nutrient cycling (β-glucosidase, alkaline phosphatase, and urease). Phospholipid fatty acid (PLFA) analysis indicated positive correlation between carbon content in soils and microbial populations. In contrast, soils managed with EU had significantly lower SOC levels, possibly due to differences in carbon fractionation. FAL increased soil enzymatic activities and enriched the microbial community when compared to EU management. In conclusion, this study indicated the importance of fallowing and fallowing period for conservation of SOC, and potential to mitigate negative effects of biophysical constraints on agricultural productivity in semi-arid soils of Northwest Africa.

Jieke Shi, Zhou Yang, David Lo

Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to developing efficient LLM4SE techniques that demand minimal computational cost, time, and memory resources, as well as green LLM4SE solutions that reduce energy consumption, water usage, and carbon emissions. This paper aims to redirect the focus of the research community towards the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance of LLM4SE and highlights the need for efficient and green LLM4SE solutions. Subsequently, the paper presents a vision for a future where efficient and green LLM4SE revolutionizes the LLM-based software engineering tool landscape, benefiting various stakeholders, including industry, individual practitioners, and society. The paper then delineates a roadmap for future research, outlining specific research paths and potential solutions for the research community to pursue. While not intended to be a definitive guide, the paper aims to inspire further progress, with the ultimate goal of establishing efficient and green LLM4SE as a central element in the future of software engineering.

Johanna Müller, Florian Sammüller, Matthias Schmidt

We give an introductory account of the recently identified gauge invariance of the equilibrium statistical mechanics of classical many-body systems [J. Müller et al., Phys. Rev. Lett. Phys. Rev. Lett. 133, 217101 (2024)]. The gauge transformation is a non-commutative shifting operation on phase space that keeps the differential phase space volume element and hence the Gibbs integration measure conserved. When thermally averaged any observable is an invariant, including thermodynamic and structural quantities. Shifting transformations are canonical in the sense of classical mechanics. They also form an infinite-dimensional group with generators of infinitesimal transformations that build a non-commutative Lie algebra. We lay out the connections with the underlying geometry of coordinate displacement and with Noether's theorem. Spatial localization of the shifting yields differential operators that satisfy commutator relationships, which we describe both in purely configurational and in full phase space setups. Standard operator calculus yields corresponding equilibrium hyperforce correlation sum rules for general observables and order parameters. Using Monte Carlos simulations we demonstrate explicitly the gauge invariance for finite shifting. We argue in favour of using the gauge invariance as a statistical mechanical construction principle for obtaining exact results and for formulating smart sampling algorithms.

Mario Guevara

Development of a spatial-temporal and data-driven model of soil respiration at the global scale based on soil temperature, yearly soil moisture, and soil organic carbon (C) estimates. Prediction of soil respiration on an annual basis (1991-2018) with relatively high accuracy (NSE 0.69, CCC 0.82). Lower soil respiration trends, higher soil respiration magnitudes, and higher soil organic C stocks across areas experiencing the presence of sustainable soil management practices.

Chengyu Xie, Hoang Nguyen, Xuan-Nam Bui et al.

Asskar Janalizadeh Choobbasti, Saman Soleimani Kutanaei

Jianbin Tang, Xi Chen, Liusheng Cui et al.

To address the problems of strain localization, the exact Mohr-Coulomb (MC) model is used based on second-order cone programming (mpcFEM-SOCP) in the framework of micropolar continuum finite element method. Using the uniaxial compression test, we focused on the earth pressure problem of rigid wall segment involving non-associated plasticity. The numerical results reveal that when mpcFEM-SOCP is applied, the problems of mesh dependency can be effectively addressed. For geotechnical strain localization analysis involving non-associated MC plasticity, mpcFEM-SOCP in conjunction with the pseudo-time discrete scheme can improve the numerical stability and avoid the unreasonable softening issue in the pressure-displacement curves, which may be encountered in the conventional FEM. It also shows that the pressure-displacement responses calculated by mpcFEM-SOCP with the pseudo-time discrete scheme are higher than those calculated by mpcFEM-SOCP with the Davis scheme. The inclination angle of shear band predicted by mpcFEM-SOCP with the pseudo-time discrete scheme agrees well with the theoretical solution of non-associated MC plasticity.

Danial Khari, Aslan Egdernezhad, Niazali Ebrahimipak

IntroductionWater resources are strongly influenced by the hydrological cycle and the estimation of evapotranspiration as the main component of the hydrological cycle plays an important role in water resources management. This phenomenon is nonlinear and very difficult to estimate in the sense that there are many parameters involved in its estimation. There are many methods to estimate evapotranspiration none of which is free from problems. Some of these methods, such as Lysimeter, are costly and time-consuming, and others, such as empirical methods only have local value. Therefore, the application of a method which is able to model this phenomenon based on its entity and with minimum data seems necessary. In recent years, the use of artificial intelligence models to simulate various problems has become very popular. In terms of performance, artificial neural networks are very efficient models whose computational speed is completely independent of the mathematical complexity of the algorithms or the method used. The purpose of this research is to compare artificial neural network models, neural network model optimized with genetic algorithm and experimental models in estimation of reference evaporation and transpiration using meteorological data in Ramhormoz synoptic station. Materials and MethodsAs mentioned above, the aim of this study was to compare the models of artificial neural network (ANN), artificial neural network optimized with genetic algorithm (ANN + GA) and experimental models (Hargreaves-Samani, Blaney-Criddle and Irmak) in estimating reference evapotranspiration compared to the results obtained from the Penman-Monteith FAO standard model by using Meteorological data in Ramhormoz synoptic station. For this purpose, meteorological parameters of Ramhormoz synoptic station were collected monthly during the years 2011 to 2018. This information includes: minimum temperature, maximum temperature, average temperature, wind speed at 2 meters, minimum relative humidity, maximum relative humidity and was sunny hours.Artificial neural networks are simplified models of the working system of the human brain, which are not comparable to natural systems. These models try to imitate human thought processes.The process of using artificial neural network models includes three stages of training, verification and testing. In the present study, 70% of the data was considered for training, 10% for validation and 20% for testing. Also, the stimulus function considered for the training and test phase is the sigmoid tangent.To extract better results from the artificial neural network model, it is necessary to optimize the parameters used. To determine the most optimal parameters required for the artificial neural network model, such as the number of layers, neurons and the weight of the layers, a lot of time is spent on their calibration using the trial and error method. For this reason, in this research, the combination of artificial neural network model and genetic algorithm (ANN+GA) was used in order to achieve the optimal parameters of the artificial neural network model. Minimizing the amount of simulation error as a function of the objective function and the number of iterations was considered as the stopping condition of the optimization algorithm. Results and DiscussionOverall, the results showed that artificial neural network models to empirical models used to model higher correlation with the Penman-Monteith FAO model. In addition, among the neural network models used, the integrated neural network model with the genetic algorithm has a higher correlation with the Penman-Monteith FAO model. So that the value of R2 in Blaney Kridel, Hargreaves Samani, Airmak, ANN and ANN+GA models is 0.65, 0.819, 0.781, 0.969 and 0.973, respectively. The results of using scenarios using meteorological parameters as input for ANN and ANN + GA models showed that the highest accuracy of estimating reference evapotranspiration in both models is related to the scenario with input data such as temperature. The minimum is the maximum temperature, wind speed at a height of 2 meters, minimum relative humidity, maximum relative humidity and sunny hours, and the lowest accuracy of the model was in a scenario with two inputs of maximum temperature and minimum temperature. Among the experimental models, Hargreaves-Samani, Irmak and Blaney-Criddle models had the highest correlation with the standard Penman-Monteith FAO model, respectively. ConclusionEvapotranspiration is one of the important factors in the hydrological cycle and among the determining factors of energy equations on the earth's surface and water balance. In this regard, many researchers tried to estimate the amount of evaporation and transpiration with a suitable approximation using a cheap and easier method for different regions. The purpose of this research is to compare artificial neural network (ANN) models, artificial neural network optimized with genetic algorithm (ANN+GA) and experimental models (Blaney-Criddle, Hargreaves Samani and Irmak) in estimating reference evaporation and transpiration compared to the obtained results. It was done from the standard Penman-Monteith-FAO model, using meteorological data at Ramhormoz synoptic station. The general results of this research showed that the artificial neural network models have a higher correlation with the Penman-Manteith-Fau model than the used experimental models. In addition, among the used neural network models, the integrated neural network model with genetic algorithm has a higher correlation with the Penman-Manteith-Fau model than the artificial neural network model. Also, among the experimental models used, respectively, Hargreaves Samani, Irmak, and Blaney-Criddle models have the highest correlation with the standard Penman-Monteith-Fau method. In line with the results of the present research, it is suggested to compare the results of experimental models and artificial neural network with the data obtained from the evaporation pan.

Jinwu Ye

In the realm of statistical mechanics, it has been established that there is no distinction between the micro-canonical and canonical ensembles in the thermodynamic limit. However, this paradigm may alter when addressing statistical mechanics in the context of a moving sample with a velocity $ v $. Our investigation reveals significant disparities between the two ensembles when considering relativistic effects up to the order of $ (v/c)^2 $. While the temperature remains the same in the former, it experiences an increase in the latter. If the system undergoes a finite-temperature phase transition, the critical temperature decreases in the co-moving frame of the latter ensemble. The implications of these findings on the thermodynamic zeroth to the third laws and the eigenstate thermalization hypothesis are analysed. The potential for the experimental detection of these novel effects in condensed matter systems are discussed.

Constantinos Kanellopoulos, Peter Rangelow, Boris Jeremic et al.

The paper explores the linear and nonlinear dynamic interaction between the reactor and the auxiliary buildings of a Nuclear Power Plant, aiming to evaluate the effect of the auxiliary building on the seismic response of crucial components inside the reactor building. Based on realistic geometrical assumptions, high-fidelity 3D finite element (FE) models of increasing sophistication are created in the Real-ESSI Simulator. Starting with elastic soil conditions and assuming tied soil-foundation interfaces, it is shown that the rocking vibration mode of the soil-reactor building system is amplified by the presence of the auxiliary building through a detrimental out-of-phase rotational interaction mechanism. Adding nonlinear interfaces, which allow for soil foundation detachment during seismic shaking, introduces higher excitation frequencies (above 10 Hz) in the foundation of the reactor building, leading to amplification effects in the resonant vibration response of the biological shield wall inside the reactor building. A small amount of sliding at the soil-foundation interface of the auxiliary building slightly decreases its response, thus reducing its aforementioned negative effects on the reactor building. When soil nonlinearity is accounted for, the rocking vibration mode of the soil-reactor building system almost vanishes, thanks to the strongly nonlinear response of the underlying soil. This leads to a beneficial out-of-phase horizontal interaction mechanism between the two buildings, reducing the spectral accelerations at critical points inside the reactor building by up to 55% for frequencies close to the resonant one of the auxiliary building. This implies that the neighboring buildings could offer mutual seismic protection to each other, in a similar way to the recently emerged seismic resonant metamaterials, provided that they are properly tuned during the design phase.