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The leakage of the injection–production string is one of the important hidden dangers for the safe and efficient operation of underground salt cavern gas storage. Although distributed fiber optic temperature measurement system (DTS) can accurately locate the position of the string leakage port, how to establish the quantitative relationship between the temperature difference and leakage rate of the leakage port still needs further exploration. This paper proposes a new quantitative prediction model based on a DTS for the leakage monitoring of the injection–production string of salt cavern gas storage. The model takes into account the gas's physical parameters, unstable temperature conditions, and the Joule–Thomson effect. In order to verify the accuracy of the model, a simulation experiment of string leakage based on a DTS was carried out. The test results show that the relative deviation between the predicted leakage rate and the measured value is less than 5% compared with the calculated value. When the leakage rate drops to 0.16 m3/h and the temperature range is less than 0.5 °C, it is difficult to accurately monitor the DTS. The results of this study help to improve the early warning time of underground salt cavern gas storage string leakage. [ABSTRACT FROM AUTHOR]

Cave entrances directly connect the surface and subsurface geomorphology in karst landscapes. Understanding the spatial distribution of these features can help identify areas on the landscape that are critical to flow in the karst groundwater system. Sinkholes and springs are major locations of inflow and outflow from the groundwater system, respectively, however not all sinkholes and springs are equally connected to the main conduit system. Predicting where on the landscape zones of high connectivity exist is a challenge because cave entrances are difficult to detect and imperfectly documented. Wildlife research has a similar issue of understanding the complexities of where a given species is likely to exist on a landscape given incomplete information and presence-only data. Species distribution models can address some of these issues to create accurate predictions of species or event occurrence across the landscape. Here we apply a species distribution model, MaxEnt, to predict cave entrance locations in three geomorphic regions of Kentucky. We built the models with cave locations from the Kentucky Speleological Survey database and landscape predictor variables, including distance from sinkholes, distance from springs, distance from faults, elevation, lithology, slope, and aspect. All three regional models predict cave locations well with the most important variables for predicting cave entrance locations consistent between models. Throughout all three models, sinkholes and springs had the largest influence on the likelihood of cave entrance presence. This unique use of species distribution modeling techniques shows that they are potentially valuable tools to understand spatial patterns of other landscape features that are either ephemeral or difficult to identify using standard techniques. [ABSTRACT FROM AUTHOR]

The Rudolf‐Fettweis hydropower plant, owned and operated by EnBW Energie Baden‐Württemberg AG, is situated in the Murg valley in the Northern Black Forest. The construction of a new underground Lower Basin is planned to upgrade the existing hydropower station. The in‐situ rock mass consists of Forbach Granite with local weakness zones, as encountered in the boreholes. Considering the extent of the project area, a 3D geological prediction model was used to allow a better interpretation of the spatial relationships of weakness zones in the rock mass and to optimize the orientation of the underground caverns. Adverse effects for the public were counteracted at a very early stage, so that the project received a high level of public acceptance. The present paper describes the current state of the project. [ABSTRACT FROM AUTHOR]

Construction prediction is the key for the shape control of energy storage salt caverns, which benefits with the storage capacity and long-term operational safety. However, the conventional grid discretization methods using elastic grid could not accurately tracking the three-dimensional boundary movements of salt cavern. This paper introduced a novel construction prediction model of salt cavern using a Volume-of-fluid based method. The tracking of the salt caverns' dissolving boundary is successfully reconstructed and tracked by the fluid volume fractions (0-1) in structural grids. The model was validated by indoor experiment and field data. In the simulation of indoor experiment, the lateral expansion, which was difficult to reproduce in previous models, is successfully simulated. The volume of the simulation chamber is 392.8 ml with an error of 1.9 %. During the simulation of Volgograd horizontal cavern construction, the simulated cavern shape is close to the sonar detection, with an average error in radius about 3.6 %. And the brine-discharge concentration is consistent with the site monitoring, with an average error about 4.5 %. These results validate the capability of the proposed method in three-dimensional dynamic boundary tracking and shape prediction of salt cavern. • A salt cavern construction prediction model is introduced using a Volume-of-Fluid method. • Three dimentional simulation of the movement of dissolving salt cavern interfaces is achieved for the first time. • A demo C++ program has been developed for numerical implementation of the proposed model. • model's reliability is verified through simulations of an indoor experiment and a field project. [ABSTRACT FROM AUTHOR]

Rock salt cavities are commonly utilized for underground gas energy storage on a big scale due to their characteristics of low permeability and low porosity. Salt cavern wellbore leaks typically originate from depths of several hundred meters or greater beneath the Earth's surface. The intricate geological characteristics of these areas pose challenges in accurately assessing the traceability of such leaks. In this study, a mathematical model was developed to forecast the seepage path of wellbore leakage in the presence of complex geological conditions. The proposed model encompasses the resolution of equations governing the flow dynamics of cement sheath fractures. It also establishes the ontological correlation between the net pressure within micro-annuli and their geometric characteristics. The verification of the stability and reliability of the seepage mathematical model was conducted by completing cement penetration experiments carried out under different confining pressure settings and damage pretreatment conditions. The mathematical model was further enhanced to provide visualization software capable of real-time calculations for gas flow within the pore space, the extent of cement sheath debonding, and the diffusion process of pore pressure. Finally, a wellbore leakage evaluation approach for gas storage salt caverns incorporating permeability channel and pore pressure gradient is presented. [ABSTRACT FROM AUTHOR]

Previous prediction models have faced challenges in characterizing the three-dimensional (3D) surface subsidence of salt caverns with different shapes. In order to overcome these limitations, this study proposes a novel theoretical model based on stochastic medium theory. This model provides a theoretical formula for characterizing the 3D surface subsidence of salt caverns with different shapes (oblate spherical, spherical, and vertical ellipsoidal). By employing the Particle Swarm Optimization (PSO) algorithm to address the theoretical model, it can generate a three-dimensional settlement surface and subsequently compare it with the numerical results. The results demonstrate a strong consistency between the theoretical and numerical results. By conducting the parameter sensitivity analysis, it becomes evident that the shape of salt caverns holds paramount significance and should not be disregarded in the study of 3D surface subsidence. As the main influence angle increases and the burial depth decreases, the maximum settlement value of the salt cavern continues to increase while the maximum influence radius continues to decrease. The maximum settlement value and maximum influence radius of salt caverns gradually increase with the increase of the span. This suggests that the proposed theoretical model can effectively and intuitively describe the 3D surface subsidence characteristics of salt caverns. • A theoretical model of 3D surface subsidence has been proposed based on stochastic medium theory. • The proposed model can accurately predict 3D surface subsidence of salt caverns with different shapes. • The proposed model can effectively describe the 3D surface subsidence characteristics of salt caverns. [ABSTRACT FROM AUTHOR]

The area of the Inner Asian Mountain Corridor (IAMC) follows the foothills and piedmont zones around the northern limits of Asia's interior mountains, connecting two important areas for human evolution: the Fergana valley and the Siberian Altai. Prior research has suggested the IAMC may have provided an area of connected refugia from harsh climates during the Pleistocene. To date, this region contains very few secure, dateable Pleistocene sites, but its widely available carbonate units present an opportunity for discovering cave sites, which generally preserve longer sequences and organic remains. Here we present two models for predicting karstic cave and rockshelter features in the Kazakh portion of the IAMC. The 2018 model used a combination of lithological data and unsupervised landform classification, while the 2019 model used feature locations from the results of our 2017–2018 field surveys in a supervised classification using a minimum-distance classifier and morphometric features derived from the ASTER digital elevation model (DEM). We present the results of two seasons of survey using two iterations of the karstic cave models (2018 and 2019), and evaluate their performance during survey. In total, we identified 105 cave and rockshelter features from 2017–2019. We conclude that this model-led approach significantly reduces the target area for foot survey. [ABSTRACT FROM AUTHOR]

Vertical displacement (VD) estimation is one of the most important topics in construction of an underground powerhouse cavern. This phenomenon commonly depends on excavation progress and corresponding geometrical, geological and geomechanical conditions of surrounding rock masses. Although many researchers investigated this issue, however, application of the new powerful predictive models is essential due to the topic complexities and limitations of previous methods. This study focuses on the estimation of VDs at the middle and key points on the roof and floor of a powerhouse cavern using the numerical analysis (NA), neural network (NN), fuzzy logic (FL) and statistical analysis (SA) models under various conditions. Rock geomechanical characteristics and geometrical variables of powerhouse related structures regarded as inputs in numerical analysis of VDs. On the basis of a large number of numerical simulations, a new predictive equation considering seven effective basic factors was fitted to predict the elasto-plastic vertical displacement at the key points on roof and floor of powerhouse cavern. Through the numerical analysis, an enough datasets was introduced to construct and develop the NN, FL and SA models. Based on the testing datasets, the achieved results from these models were compared with each other as well as with the results of NA-based equation using the relevant statistical indices. This comparison confirmed that the performance of FL and NN models are relatively better than the NA-based equation. Moreover, these three models are more relevant than the SA model. At the end of modeling, conducted sensitivity analysis proved that overburden depth, lateral stress coefficient are the most effectual variables on the VDs whereas the tensile strength is the least ones. [ABSTRACT FROM AUTHOR]

Burning cave is becoming more and more popular in rural areas of northern China. It also has some disadvantages such as uneven temperature distribution, partial higher temperature and lower thermal efficiency. In order to research the heat transfer performance of the burning cave, an unsteady heat transfer model has been established, and a theoretical calculation formula has been deduced and verified by experimental data. It shows that both the thermal characteristic of the radiant floor on the burning cave and the heat generated from different biomass fuels inside the burning cave have a large impact on the surface temperature and heat transfer of radiant floor. Moreover, while the heat transfer coefficient of the radiant floor was a constant, the surface temperature of the radiant floor changed with the heat released from different fuels was consistent with exponential variation form. However, as using the same biomass fuel, the thermal resistance of the radiant floor was increased by 0.5(m 2 K)/W, the heat transferred from the burning cave to the heating room could be reduced to 0.67 times of the original heat before optimized. Therefore, the valid theoretical analysis calculation formula could provide theoretical support for reasonable design on a burning cave, and predict thermal performance on different types of burning caves more easily. [ABSTRACT FROM AUTHOR]

Knowledge of weathered depth is critically important for repairing and protecting stone relics that are open to elements. Weathered depth is an important basis of stability/durability evaluation and protection plan formulation for stone carving and grottoes. Weathered depth is the basis for identifying the part that has been weathered or the material properties that have been changed, as well as the basis for determining weathered speed or weathered depth. Weathered depth is also used to determine the strengthening methods and reinforcing depth of stone carving and grottoes. To obtain the weathered depth of Yungang Grottoes, an intelligent and efficient regression forecasting support vector machines (SVM) model based on terahertz spectra is established. Terahertz time domain spectroscopy (THz-TDS) is used to measure the terahertz spectra of the Yungang Grottoes. The transmission spectra of all samples are then analyzed. Only minor differences among the transmission spectra of different samples and no characteristic absorption peaks have been observed. The SVM model based on the transmission spectra of samples is applied to distinguish and predict the depth. The results are in accordance with the real depth, and the relative errors are less than 0.85%. The results indicate that the spectra-based model can distinguish samples of Yungang Grottoes and effectively predict their depths, which can provide an important reference for the repair of the Yungang Grottoes. [ABSTRACT FROM AUTHOR]

Reference 1 Cuthbertson P, Ullmann T, Büdel C, Varis A, Namen A, Seltmann R, et al. (2021) Finding karstic caves and rockshelters in the Inner Asian mountain corridor using predictive modelling and field survey. The caption for Fig 6 is incorrect. [Extracted from the article]

Abstract: The interpretation of taphonomic and behavioral lithic edge wear formation is complicated by equifinality of edge damage morphologies. Rejecting hypotheses that edge damage originates from taphonomic processes is standard practice for many archaeological analyses and should be incorporated into lithic use-wear more explicitly. Quantitative hypothesis testing is advocated here, and facilitated by recording edge wear observations in an image referenced GIS spatial environment. A taphonomic predictive model was generated using trampling and flint-knapping experiments. Trampling experiments were conducted to determine how edge damage is distributed along tool edges due to non-use related, taphonomic processes. Experiments designed to test the assumption that undisturbed flakes do not preferentially orient either surface side-up (dorsal or ventral) were performed. Furthermore, it is argued that artifact orientation data, if available, can also be used to assess whether the frequency of edge damage is correlated with the degree of disturbance. This taphonomic predictive model is then statistically compared with frequency and distribution edge damage data from two South African Middle Stone Age sites. The research presented here illustrates the usefulness of edge damage distribution analysis for accounting for taphonomic processes as causal agents of edge damage formation, and strengthening behavioral interpretations regarding tool function. Bringing tool wear observations into a uniform spatial structure is one avenue for standardization of lithic use-wear analysis. [Copyright &y& Elsevier]

Abstract: Based on an opening complex for a hydropower station in China, an equation considering four basic factors was fitted for prediction of displacement at the key point on the high sidewalls of the powerhouse, on the basis of a large number of numerical simulations. The basic factors include rock deformation modulus, overburden depth of caverns, height of the powerhouse and the lateral pressure coefficient of the initial stress. Quasi-three-dimensional stability analyses were carried out by using FLAC3D. With an equation, the elasto-plastic displacement and elastic displacement at a sidewall key point can be calculated quickly. The equation was applied to predict the displacements at key points on the sidewalls for caverns of nine projects. The computation results were compared with numerical modeling or back-analysis results. In addition, in order to consider the effects of cavern spacing, a new equation was proposed. Finally, three possible criteria for stability evaluation of the rock masses were considered. It is suggested that the rock stability is assessed by the ratio θ c between the elasto-plastic displacement and the elastic displacement, which is commonly applicable. The stability of the surrounding rock for the above-mentioned nine underground projects was evaluated by the method. Long prestressed cables were considered to be needed to reinforce the sidewalls in order to ensure the stability of the caverns for some of the projects. For the actual design and construction of the five relevant projects, long prestressed cables were employed for reinforcement of high sidewalls. This showed that the evaluation criterion was valid. [ABSTRACT FROM AUTHOR]

• Evaluation of In-situ ore fragmentation to predict hang-up occurrence probability. • Uncertainty of rock block geometry and its impact on blockiness level. • In-situ ore fragmentation prediction at real mine scale and real time. • Hybrid Predictive modeling of hanging-up frequency in block cave mining. • Large scale discrete fracture network modeling application at block cave mine. The in-situ ore fragmentation and probability of occurrence of hang-ups at draw points are the most significant factors on the performance of block cave mining. In this study we develop a hybrid methodology to study the uncertainty in the block geometry in the context of blockiness variable and hang-up frequency at a cave mine. This hybrid approach is based on the combination of geostatistical simulation, probabilistic discrete fracture network, geometrical and topological characterization of the fracture networks and supervised Poisson regression models. Our results and hybrid predictive models provide guidance on the systematic characterization of the fractured rock mass at a cave mine for its design, evaluation of production rates, and for risk evaluation purposes. This study can serve as a reference for the rock block geometry analysis in other related fields. [ABSTRACT FROM AUTHOR]

This paper describes the micromammalian remains and paleoenvironment of the Upper Paleolithic sequence of Manot Cave (46-34 ka), southern Levant. Micromammal remains were identified from Ahmarian (46-42 ka), Levantine Aurignacian (38-34 ka) and post-Levantine Aurignacian (34-33 ka) layers. To identify taphonomic agents, molar digestion was modelled for seven local raptor species, and model predictions were compared with observed digestion scores in the Manot Cave material. Raptor species differed significantly in molar digestion patterns, allowing us to identify Tyto alba as the bone accumulator in the Ahmarian and Post-Levantine Aurignacian units. Data were insufficient for species-level identification of the taphonomic agent in the Levantine Aurignacian. Günther's voles (Microtus guentheri) were dominant, though woodland species (Apodemus spp., Sciurus anomalus and Dryomys nitedula) also occurred through the entire sequence. Manot Cave furnished the first fossil record of the Eurasian snow vole (Chionomys nivalis) in the southern Levant during the Late Pleistocene and its first secure record of the water vole (Arvicola terrestris) outside the Hula Valley. Records of other taxa (Acomys dimidiatus and D. nitedula) provide the earliest occurrence datum in the region. Using counts of both identified specimens and distinct elements (lower first molars) we modelled paleoenvironmental conditions through both Weighted Averaging Partial Least Squares regression and a qualitative analysis considering niche preferences of species. Model predictions indicate the unexpectedly pronounced dominance of open habitats compared to present conditions near the cave, though the occurrence and abundance of woodland species also indicate some woodland expansion relative to the preceding Middle Paleolithic period. Combining statistical models and species niche considerations we show that the time span between the Ahmarian, Levantine Aurignacian and post-Levantine Aurignacian was marked by a clear-cut climatic oscillation to cooler and likely wetter conditions. [ABSTRACT FROM AUTHOR]

• Palaeolithic parietal art is expanded across Western Europe but with an unequal distribution. • Discoveries have often been made by chance. • The study proposes a selective surveying system employing multivariate statistical analysis and GIS. • This predictive model has been tested with positive results; new rock art findings. Since the discovery of Altamira Cave in 1879, the archaeological record of Palaeolithic parietal art has expanded steadily across Western Europe but with an unequal distribution. Discoveries have often been made by chance, but at other times as the result of painstaking searches by archaeologists and/or speleologists, eventually reaching some 500 sites currently known. The present study proposes a selective surveying system based on the current characterisation of parietal ensembles in the Autonomous Community of the Basque Country (North Spain) but applicable to any other territory or region in the world. In this way, by employing multivariate statistical analysis and GIS, we have designed a predictive model that focuses fieldwork on the areas with the greatest potential of containing caves with Palaeolithic decoration. The positive results of applying this approach to survey in the North of Spain from 2018 to 2020 have validated its efficacy. [ABSTRACT FROM AUTHOR]