Seepage through construction joints is a major factor affecting uplift pressure and long-term safety of concrete dams. Pre-existing joints with millimeter-scale openings provide preferential flow paths, where hydraulic pressure can induce joint opening and permeability escalation. In this study, seepage-induced joint-opening behavior is investigated using a coupled hydromechanical numerical framework with damage-dependent aperture evolution. The impacts of initial crack width, interface cohesiveness, and interface tensile strength on the evolution of crack opening displacement (COD) and hydraulic instability are comprehensively isolated by parametric studies. The results show that, once tensile opening is activated, variations in cohesion have a negligible influence on pressure–COD responses and failure pressure, indicating that cohesion degradation does not control seepage-induced instability in pre-existing cracks. In divergence, interface tensile strength strongly governs damage initiation, the onset of rapid crack opening, and the critical hydraulic pressure at failure. Larger initial crack widths act as geometric accelerators, leading to earlier instability and enhanced permeability evolution under increasing seepage pressure. A dimensionless, pressure–tensile strength ratio is shown to unify the observed responses, revealing a transition from a geometry-controlled regime to a damage-dominated failure regime. These findings indicate that seepage-induced instability in concrete dams is primarily controlled by tensile resistance of construction joints rather than cohesion degradation, providing guidance for uplift pressure assessment and seepage control design.
The structural and geotechnical characteristics of railroad tracks change abruptly at transition zones. At these locations, a change from ‘rigid’ to ‘flexible’ track conditions or the opposite leads to amplified dynamic responses, large deformations, accelerated track deterioration, and increased maintenance expenses. Researchers have conducted numerous field and numerical studies into track transitions’ behavior; however, their investigations are often limited by point-based and short-term measurements and assumptions that overlook critical mechanisms in track transitions. This review presents current sensor-centric knowledge achieved by integrating insights from field instrumentations and numerical modellings of transition zones. The objective is to expose the overlooked behavioral aspects of track transitions and identify the limitations of conventional monitoring systems. To address these gaps, this review introduces optical fiber sensors (OFSs) as an emerging technology for track condition monitoring. Focusing on recent OFS applications, this study demonstrates how OFSs can improve the quantity and quality of field data through spatial continuity, multiplexing, and higher sensitivity, thus marking a significant practical improvement. This review also outlines OFS-based monitoring challenges, such as sensor durability, measurement quality, temperature-strain cross-sensitivity, and lack of a standardized data interpretation framework. Altogether, this work’s novelty is in connecting transition zone behavior, monitoring limitations, and the inherent potential of OFS systems.
<p>A lower Paleozoic slab of oceanic lithosphere was obducted onto the southern margin of Avalonia during the Variscan orogeny and is now exposed throughout the Lizard District of Cornwall, England. This complexly faulted and metamorphosed region of mafic and ultramafic rocks has been the subject of geological investigation for over two hundred years. Herein the most significant scientific contributions made over a sixty-five-year interval from 1818 to 1883 are reviewed. Early workers, including Ashurst Majendie, Adam Sedgwick, John Rodgers, and Henry De la Beche, conducted field-based studies of the region, making lithologic observations and mapping contacts between the major rock units. Subsequently, an intense phase of investigation into the processes and products of contact and regional metamorphism in Cornwall and the Lake District informed and inspired the field and microscopical studies of the Lizard District by Thomas G. Bonney. Detailed consideration of the pioneering work of these 19th century geologists provides insights into their methodologies as well as an evolving understanding of the complex and enigmatic rocks of the Lizard.</p>
Janis Heuel, Vincent Maurer, Michael Frietsch
et al.
Training deep-learning picking models with several published data sets can be easily done through the Python toolbox SeisBench. Most of the data sets contain earthquakes recorded at local, regional and teleseismic distances, with only limited data in the low magnitude, close distance region. Applying current published PhaseNet models to induced seismicity data leads to only a few events being detected and trained PhaseNet models are not able to outperform well-established workflows in seismology.
Here we present a new seismological data set and trained PhaseNet models for picking induced seismicity with deep-learning (piSDL). PhaseNet was trained with 171,182 three component waveforms from 40,576 events. Noise samples were added in the training data set to reduce the number of false picks. In this study, we noticed that a good earthquake training data set and noise samples from the analysed area are both important to detect more seismic events with a newly trained PhaseNet model. We validated our new PhaseNet models at a geothermal site in Rittershoffen (France). The models trained with the new data set and noise samples clearly outperform PhaseNet’s original published model and traditional methods in seismology by detecting up to 62% more events compared to a seismicity catalogue published by an agency.
Benjamin Fernando, Ross Maguire, Brianna Fernandez
et al.
The 2024-10-05 Iran M 4.5 earthquake took place at a time of heightened tensions in the Middle East. We perform a discrimination and moment tensor analysis and identify a shallow-dipping, reverse fault source commensurate with the compressional setting of the Iranian interior. Nonetheless, the event's aftermath saw widespread dissemination of misinformation, and potentially active disinformation, concluding that it was in fact a test of an Iranian nuclear weapon. The `evidence' for many of these claims was based on inaccurate interpretation of seismic data. In this paper, we analyse how geophysical `fake news' propagated through social media (mainly Twitter/X) following this event, eventually gaining traction in mainstream, earned media. This event is an illustrative warning of how seismic data can be misinterpreted and/or manipulated in public discourse.
This study proposes an automatic classification approach for seismic events, designed to discriminate
between earthquakes and anthropogenic explosions by employing the Random Forest algorithm. The model
operates exclusively on features extracted from the signal recorded at a single seismic station without considering
the source location or depth. The feature vector included amplitude ratios, along with temporal, spectral, and
fractal parameters of the seismogram. A balanced dataset comprising more than 24 000 seismic records from the
Pacific Northwest Curated Seismic Dataset was utilized for training and validation. The trained classifier achieved
an accuracy of about 94 % on the test dataset. Feature importance analysis indicated that temporal, fractal, and
spectral parameters contributed most to the classification, which is consistent with the underlying differences in
the generation of natural and anthropogenic signals. The obtained results demonstrate that the proposed method
ensures reliable and robust classification performance and can be applied for automatic filtering of anthropogenic
events in seismic monitoring.
Andreas Brotzer, Heiner Igel, Felix Bernauer
et al.
In September 2022, a portable, three-component rotational rate sensor, namely a blueSeis-3A gyroscope, has been deployed at the underground vault of the Pinon Flat Observatory (PFO) in southern California. A three-component, broadband seismometer is co-located, jointly forming a six degree-of-freedom (DoF) station for long-term observations of local and regional seismicity and multi-component wavefield studies. The seismic recordings are available online via IRIS FDSN services as PY.BSPF (BlueSeis at Pinon Flat). The instrumentation at PFO additionally provides high-quality strain observations, allowing now to study translation, rotations and strain of the seismic wavefield in a low noise and high seismicity area (e.g. San Andreas fault zone). The seismic array at PFO is used to compute array derived rotations and validate the direct observations of rotational ground motions. We show results of 6-DoF processing applied to a local Mw 4.1 and a regional Mw 6.2 event to obtain backazimuth estimates, which we validate with array beamforming, and estimates of local seismic phase velocities. For observed events between October 2022 and October 2023, we detect more than 400 events of which 118 are triggered on all six components. Peak rotation rate amplitudes are used to derive empirical peak amplitude relations for vertical and horizontal rotation rates to provide valuable insights towards resolvability for comparable 6~DoF campaigns. We find the dominating limitations for rotational motion observations currently to be set by the self-noise level of the blueSeis-3A rotation sensor and encourage further instrumental development.
<p>Apparent temperature (AP) and ground-level aerosol
pollution (PM<span class="inline-formula"><sub>2.5</sub></span>) are important factors in human health, particularly
in rapidly growing urban centers in the developing world. We quantify how
changes in apparent temperature – that is, a combination of 2 m air
temperature, relative humidity, surface wind speed, and PM<span class="inline-formula"><sub>2.5</sub></span>
concentrations – that depend on the same meteorological factors along with
future industrial emission policy may impact people in the greater Beijing
region. Four Earth system model (ESM) simulations of the modest greenhouse
emissions RCP4.5 (Representative Concentration Pathway), the “business-as-usual” RCP8.5, and the stratospheric
aerosol intervention G4 geoengineering scenarios are downscaled using both a
10 km resolution dynamic model (Weather Research and Forecasting, WRF) and a statistical approach (Inter-Sectoral Impact Model Intercomparison
Project – ISIMIP).
We use multiple linear regression models to simulate changes in PM<span class="inline-formula"><sub>2.5</sub></span>
and the contributions meteorological factors make in controlling seasonal AP
and PM<span class="inline-formula"><sub>2.5</sub></span>. WRF produces warmer winters and cooler summers than
ISIMIP both now and in the future. These differences mean that estimates of
numbers of days with extreme apparent temperatures vary systematically with
downscaling method, as well as between climate models and scenarios. Air
temperature changes dominate differences in apparent temperatures between
future scenarios even more than they do at present because the reductions in
humidity expected under solar geoengineering are overwhelmed by rising vapor
pressure due to rising temperatures and the lower wind speeds expected in the
region in all future scenarios. Compared with the 2010s, the PM<span class="inline-formula"><sub>2.5</sub></span>
concentration is projected to decrease by 5.4 <span class="inline-formula">µ</span>g m<span class="inline-formula"><sup>−3</sup></span> in the
Beijing–Tianjin province under the G4 scenario during the 2060s from the WRF
downscaling but decrease by 7.6 <span class="inline-formula">µ</span>g m<span class="inline-formula"><sup>−3</sup></span> using ISIMIP. The relative
risk of five diseases decreases by 1.1 %–6.7 % in G4, RCP4.5, and RCP8.5 using
ISIMIP but has a smaller decrease (0.7 %–5.2 %) using WRF. Temperature
and humidity differences between scenarios change the relative risk of
disease from PM<span class="inline-formula"><sub>2.5</sub></span> such that G4 results in 1 %–3 % higher health risks
than RCP4.5. Urban centers see larger rises in extreme apparent temperatures
than rural surroundings due to differences in land surface type, and since
these are also the most densely populated, health impacts will be dominated
by the larger rises in apparent temperatures in these urban areas.</p>
CENTAUR has been selected as one of the eight initial instruments to be built at the Second Target Station (STS) of the Spallation Neutron Source at Oak Ridge National Laboratory. It is a small-angle neutron scattering (SANS) and wide-angle neutron scattering (WANS) instrument with diffraction and spectroscopic capabilities. This instrument will maximally leverage the high brightness of the STS source, the state-of-the-art neutron optics, and a suite of detectors to deliver unprecedented capabilities that enable measurements over a wide range of length scales with excellent resolution, measurements on smaller samples, and time-resolved investigations of evolving structures. Notably, the simultaneous WANS and diffraction capability will be unique among neutron scattering instruments in the United States. This instrument will provide much needed capabilities for soft matter and polymer sciences, geology, biology, quantum condensed matter, and other materials sciences that need in situ and operando experiments for kinetic and/or out-of-equilibrium studies. Beam polarization and a high-resolution chopper will enable detailed structural and dynamical investigations of magnetic and quantum materials. CENTAUR's excellent resolution makes it ideal for low-angle diffraction studies of highly ordered large-scale structures, such as skyrmions, shear-induced ordering in colloids, and biomembranes. Additionally, the spectroscopic mode of this instrument extends to lower momentum transfers than are currently possible with existing spectrometers, thereby providing a unique capability for inelastic SANS studies.
Subsurface modeling plays an important role in hydrocarbon exploration but remains a challenging task that typically requires a full and reasonable integration of geophysical observations and geologic constraints. We present a workflow to fully utilize seismic amplitudes, well-log properties, and interpreted seismic structures to build geologically reasonable models. We take the Volve field data as an example and apply our workflow step by step as follows: First, we perform some preprocessing on the provided Volve seismic data, horizons, and well-logs to remove anomalous values and adjust seismic-well ties in the depth domain. Second, we use a dynamic-programming based method to infill gaps and refine the vertical positions of the provided horizons and efficiently pick more horizons. We further use the horizon surfaces to interpolate a relative geologic time (RGT) volume which can be considered as an implicit structural model representing seismic structural and stratigraphic features. Third, we integrate the provided well-logs and the computed RGT volume to interpolate a subsurface model that conforms to both well-log properties and seismic struc-tural and stratigraphic features. Finally, we propose a multi-scale neural network to predict a final subsurface model by using a combination of the seismic data and the interpolated model as inputs, and using the well-log data as training labels. Inputing the interpolated model to the network helps to provide a low-frequency control for obtaining a more stable prediction. The results show that our workflow is able to produce geologically reasonable subsurface models with high lateral continuity and vertical resolution.
Frederico A. Jahnert, G. Weber, D. F. Gomes
et al.
Distributed acoustic sensors (DASs) are able to monitor in real-time acoustic excitation and mechanical vibration of the external environment for many kilometers along the length of the optical fiber. In the oil industry, the technology allows the monitoring of well structural health, identifying flow profile, acquiring seismic data, updating reservoir information, and feeding geological models. The spatial resolution of DAS is a limiting factor on the quality of information gathered. In this article, we propose and analyze a novel method of measuring local dynamic strain of structures using DAS. The method uses serpentine configurations to measure the frequency spectrum of the in-phase strain signals at discrete regions of the structure, enabling DAS to determine, among other vibration parameters, the strain frequency response function (SFRF). An experimental study of the sensor application with different arrangements in a small structure has been performed. The structure in the experiment consists of a free–free aluminum beam of approximately 2.7 m. Experiment results show agreement with numerical results developed by the finite element method (FEM) and using reference sensors, demonstrating a significant improvement of the DAS SFRF accuracy using the serpentine configuration and up to 12.9 dB increase in peak-to-noise ratio (PNR) for low excitation forces. The recovered response enabled the reconstruction of mode shapes.
Insights into macromolecules of coal were critical for improving the understanding of the coal upgrading and coalification process. Here, the creation and generation of macromolecular representation for Dongsheng coal vitrinite was clarified using industry analysis, elemental analysis, and the peak fitting technology of 13C nuclear magnetic resonance (13C NMR), Fourier transform infrared spectrum, and X-ray diffraction. The structural parameters and macromolecular representation (C167H148N2O27) were innovatively calculated and created based on these characterization results and chemical shift correction, finally obtaining the plane macromolecular models whose 13C NMR spectrum was close to the experimental spectrum. The property parameters of basic structural units were La (average lateral sizes) = 19.917 Å, Lc (stacking heights) = 24.776 Å, d002 (interlayer spacing) = 3.488 Å, N (number of stacking layers) = 5.6213, and La/Lc < 1. Suffering from the dynamic metamorphism effects, the length of intermolecular aromatic lamellae for Dongsheng coal vitrinite was 7–8 aromatic rings in size. The aromatic clusters were dominated by benzene, naphthalene, and anthracene, and their numbers were 2, 4, and 2 per vitrinite model, respectively. Hydrogenated aromatic rings, ether bonds, and oxygen-methylene serve as the main bridge bonds to connect the aromatic clusters, where the short aliphatic chains were distributed around the edge of aromatic rings. Oxygen atoms exist in the form of hydroxyl, ether bond, carbonyl, and carboxyl groups, and their numbers were 2, 7, 4, and 8 per vitrinite model, respectively. The nitrogen atoms exist in the form of pyridine and pyrrole. The entropy weighting method was used to estimate the rationality of the macromolecular representation of long frame coal vitrinite, providing a new mathematical evaluation method for molecular simulation. Comparison of various macromolecular models from different geological conditions indicates that tectonic stress can promote the degree of aromatization and ring condensation. The thermal history and tectonic stress have a compensation effect for promoting the aromatization process. Aliphatic carbons were the most unstable units under thermal history and tectonic stress, and they are more easily removed from the aliphatic structure, followed by methyl. This finding of this paper can provide significance for coal liquefaction engineering in Dongsheng coalfield.
Restoration of underwater images plays a vital role in underwater target detection and recognition, underwater robots, underwater rescue, sea organism monitoring, marine geological survey, and real-time navigation. Mostly, physics-based optimization methods do not incorporate structural differences between the guidance and transmission maps (TMs) which affect the performance. In this paper, we propose a method for underwater image restoration by utilizing a robust regularization of coherent structures. The proposed method incorporates the potential structural differences between TM and the guidance map. The optimization of TM is modeled through a nonconvex energy function which consists of data and smoothness terms. The initial TM is taken as a data term whereas the smoothness term contains static and dynamic structural priors. Finally, the optimization problem is solved using majorize-minimize (MM) algorithm. The proposed method is tested on benchmark dataset and its performance is compared with the state-of-the-art methods. The results from the experiments indicate that the proposed regularization scheme adequately improves the TM, which results in high-quality restored images.
The article presents the results of inventory checking of objects of natural and cultural heritage of mankind. Preservation of cultural heritage has been noted as an important task during any period in history. The article specifies what objects can be considered cultural or natural heritage of mankind. We describe what advantages the status of world heritage site give to the site itself and to the country as a whole. The existence of the UNESCO World Heritage List allows one to identify a number of unresolved issues regarding the protection and preservation of cultural heritage in the countries. Despite the fact that the UNESCO World Heritage List is the object of scientific attention of many authors, the data presented in their publications are outdated and therefore unable to provide current coverage of the geographical structure of the World Heritage, as it is quite dynamic and changing every year. We analyzed researches on the chosen subject by domestic and foreign authors, finding that the main array of scientific publications for the query “UNESCO World Heritage” offers studies of the effects of UNESCO sites on tourist flows or the tourist brand of the region or country. At the same time, there is a range of scientific publications criticizing the very existence of the UNESCO World Heritage List, as well as the current criteria for nomination and inclusion of sites in the UNESCO World Heritage, uneven distribution of sites between developing and developed countries – geopolitical axis “North – South” and the lack of effective protection and conservation mechanisms in the UNESCO and even in the UN, even for places already included in the List of Sites. At the same time, there is a lack of geographical research on the distribution of the UNESCO World Heritage sites and complete absence of research on the territorial organization of intangible cultural heritage sites. A historiographical analysis of UNESCO World Heritage sites has been carried out, and the dynamics of changes in the number of sites has been analyzed. The article presents structural-territorial analysis of the distribution of objects : we determined absolute and relative indicators of the number of objects by macroregions and types, analyzed the typological ratio of objects within the regions, and identified the leading and outsider countries of each region. A cartographic model of the distribution of objects by the planet is presented. The expediency of regular monitoring of the current state of recreational and tourist resources of world importance and analysis of the tendency of deterioration or improvement of the related situation regarding non-compliance with the norms of protection and preservation of cultural and natural monuments is substantiated. We also analyzed the territorial distribution of the “Under threat” list, which includes 53 objects from 33 countries. The article contains our ideas about the prescriptive rather than the recommendatory nature of the remarks of the UNESCO World Heritage Committee, which could radically effect the elimination of all processes that threaten UNESCO sites. Territorial analysis of the distribution of intangible cultural heritage of mankind has been carried out.
This work presents the first results obtained by applying in situ and remote-sensing methodologies to monitor the Ponte della Musica-Armando Trovajoli located in Rome, within the activities of the WP6 “Structural Health Monitoring and Satellite Data” 2019-21 Reluis Project. In particular, the use of remote-sensing Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) measurements provided a spatial map of the displacement of the investigated infrastructure and the corresponding time-series, with the aim of monitoring deformation phenomena, focusing on the local scale analysis, which produces suitable results for urban monitoring and damage assessment. The DInSAR results have been integrated with the identification of the dynamic characteristics of the bridge, performed through an experimental campaign of ambient vibration measurements carried out in October 2020 and with the local-scale definition of the engineering geological setting of the foundation soil. The subsoil of the bridge is constituted by more than 50 m of recent alluvial deposits resting on Pliocene stiff clay acting as a geological bedrock. A substantially stable behavior of the bridge structural elements has been observed based on the analysis of both satellite and velocimetric data. This case represents a good example about how the integration of in situ sensors with remotely sensed data and the exploitation of a detailed knowledge regarding the on-site conditions represent a key factor for a sustainable structural and infrastructural monitoring and can support the planning both of maintenance and safety management.
In view of the coal and gas outburst accidents occur frequently caused by blasting in geological structural belt, in order to study the mechanical characteristics of coal rock in tectonic belt disturbance by blasting and blasting vibration effect influenced on the stability of surrounding rock, coal–rock damage and failure characteristics within a reverse fault caused by a blasting stress wave were investigated using numerical analyses and experiments. According to the experimental results, the causes of coal and gas outburst dynamic disasters within a reverse fault during blasting are analyzed. The outcomes indicated that the crushing circle created by the crack propagation near the blasting hole severely damaged the fault plane and floor rocks adjacent to the footwall of the reverse fault. Fractures also extended to the upper and lower coal seams of the reverse fault; this caused the surface of the coal seam to fall off and severe internal damage. According to theoretical analysis, the reflection of the blasting stress wave propagating to the reverse fault intensified the damage to coal and rock. Elastic strain energy accumulation within the reverse fault structural zone was accompanied by high-stress concentration. The reverse fault tectonic region was destroyed by blasting vibration. It increased gas pressure and caused a weak surface, which provided a channel for gas flow and a dynamic basis for the occurrence of coal and gas outburst. The research results have important theoretical value to reveal the mechanism of coal and gas outburst in tectonic belt induced by blasting.
A holistic-modular approach has been taken to study the evolution of three straight to low-sinuosity drainage systems (=SSS) in an uplifted basement block of the Central European Variscides. The development of the SSS is described by means of a quadripartite model. (1) The geological framework of the SSS: Forming the lithological and structural features in the bedrock as a result of different temperature, pressure and dynamic-metamorphic processes. (2) Prestage of SSS: Forming the paleo-landscape with a stable fluvial regime as a starting point for the SSS. (3) Proto-SSS: Transition into the metastable fluvial regime of the SSS. (4) Modern SSS: Operation of the metastable fluvial regime Tectonics plays a dual role. Late Paleozoic fold tectonic creates the basis for the studied SSS and has a guiding effect on the development of morphotectonic units during the Neogene and Quaternary. Late Cenozoic fault tectonics triggered the SSS to incise into the Paleozoic basement. The change in the bedrock lithology has an impact on the fluvial and colluvial sediments as well as their landforms. The latter reflects a conspicuous modification: straight drainage system ⇒ higher sinuosity and paired terraces ⇒ hillwash plains. Climate change has an indirect effect controlling via the bedrock the intensity of mechanical and chemical weathering. The impact on the development of the SSS can be assessed as follows: Tectonics >> climate ≅ bedrock lithology. The three parameters cause a facies zonation: (1) wide-and-shallow valley (Miocene), (2) wide-angle V-shaped valley (Plio-Pleistocene), (3) acute-angle V-shaped valley (Pleistocene), (4) V-shaped to U-shaped valleys (Pleistocene-Holocene). Numerical data relevant for the hydrographic studies of the SSS are determined in each reference area: (1) Quantification of fluvial and colluvial deposits along the drainage system, (2) slope angles, (3) degree of sinuosity as a function of river facies, (4) grain size distribution, (5) grain morphological categorization, (6) grain orientation (“situmetry”), (7) channel density, (8) channel/floodplain ratios. Thermodynamic computations (Eh, pH, concentration of solubles) are made to constrain the paleoclimatic regime during formation of the SSS. The current model of the SSS is restricted in its application to the basement of the Variscan-Type orogens, to an intermediate crustal maturity state.