Simulations of Complex Visco-Thermal Fluids with an AI-based CFD Emulator

Physical phenomena evolve in space and time following governing laws with a high level of complexity and mathematical models can help to make accurate predictions of their behavior, describing complex fluids with a good balance between accuracy and computational costs. We have long used detailed Computational Fluid Dynamics (CFD) models to simulate complex dynamics with high accuracy, but these simulations typically entail high computational costs, resulting in long execution times and the use of expensive computational resources. To overcome these limitations, we have recently integrated CFD with Artificial Intelligence (AI), in the so-called Emulators, to expand the scope of fluid modeling, improving its performance. Here, we present an AI-based CFD emulator for Smoothed Particle Hydrodynamics (SPH) simulations, which uses an Artificial Neural Network (ANN) to enhance simulations of complex fluids with viscous and thermal components. We show the model capability to reproduce the spatio-temporal evolution of natural visco-thermal fluids. In addition, we demonstrate the emulator capacity to generalize its applicability to problems not encountered during the training phase. We also conduct a detailed error evaluation, showing that the minimal observed discrepancies do not compromise model accuracy and robustness, especially given the theoretical and computational advantages. These key points open this emulator to practical applications for natural fluids, e.g., oil, honey, or geophysical fluids such as lava, enhancing fluidmodeling performance and extending functionalities. The innovation of this method improves studies in the field of numerical simulations, for example in its use as a digital Twin of a physical phenomenon, for the study of the dynamics of the system without the need of large costs for field analysis or laboratory experiments.

Research on Conventional ERT Inversion and Improved AMT Inversion Based on Deep Learning Denoising Data in Tunnel and Road Detection: A Case Study in Sichuan Province

The safety of tunnels and roads is crucial for traffic safety. Due to the presence of adverse geological features, which can cause serious problems in tunnels and on roads, there is an urgent need for comprehensive geophysical investigations to determine their distribution. This will provide additional technical information to help ensure the safety of engineering projects. This study uses the tunnels and roads in Jiulong County, Sichuan Province, as an example. Integrated geophysical methods were employed to arrange ERT sections at tunnel entrances and exits, as well as on geophysical slopes. The primary focus was on the thickness of the overlying layers and the geological conditions of the rock and soil within a certain depth range above the tunnel design line. For the longitudinal cross-section of the main tunnel, Audio Magnetotelluric (AMT) were primarily used to investigate fault zones, karst formations, aquifers and rock mass grades. Combining electromagnetic data denoising and inversion using a U-Net neural network with ERT inversion clearly revealed the underground geological conditions of the tunnel. The tunnel alignment is characterised by a mixture of stable quartz-rich rock masses and metamorphic rock masses. Overall, the deep rock mass of the tunnel axis is stable, with fractures in some transverse sections. The intersection is relatively stable, interspersed with weathered and fractured zones. These findings provide valuable insights into advancing geophysical techniques for investigating tunnel sites under complex geological conditions

Insights into the Salse di Regnano mud volcanoes: integrating geomagnetism, UAV photogrammetry and historical data

This study tries to advance the understanding of the Salse di Regnano mud volcanoes within the framework of an INGV project by integrating geomorphological, geochemical, historical, and remote-sensing data. Detailed analyses of morphology and geochemistry revealed distinctive geometric features and enabled reconstruction of the historical configuration of the area. The research was then extended by integrating drone-based geomagnetic surveys with digitized historical maps transformed into normalized 3D models. High-resolution topography derived from Structure-from-Motion (SfM) photogrammetry, complemented by satellite imagery and archival sources, allowed a comprehensive analysis of surface and subsurface patterns. The resulting geomagnetic anomaly maps reveal a “tongue” of low values descending from the northern upper slope into the main mud area, which broadly aligns with relative morphological features. Additional anomalies highlight structures of potential geophysical interest for further investigation. Historical reconstruction indicates a markedly different summit in the early 20th century, dominated by a prominent emission cone that reshaped the area following a paroxysmal event in the 1930s. Building upon previous findings, these new observations continue to provide guidance for subsequent investigations, which will include a targeted geophysical campaign combining passive seismic and electrical resistivity surveys to probe the subsurface. This multidisciplinary approach demonstrates the potential of integrating modern geophysical measurements with historical and morphological information, providing an evolving framework that adapts as new data become available and enhancing our understanding of the evolution of mud volcano systems over time

3‑D inversion and accuracy assessment of gravitational data to determine the depth of sedimentary layers; An Application in the Burg El‑Arab Area, Northwestern Desert of Egypt

The study aims to determine the depth of subsurface sedimentary layers using a Fourier‑based 3‑D stripping inversion method and assess its accuracy. The seismic‑based depth maps of the topDabaa, Kharita, and El Alamein Formations in the Burg El‑Arab Area were utilized to evaluate the inversion process’s accuracy. The calculated gravity effects of the top Dabaa, Kharita, and El Alamein Formations range were analytically estimated from thickness and density contrast and assigned to the surface observation level (Bouguer stations) before sequential stripping. The apparent density was calculated in addition to the upper and lower depth bounds of each sedimentary layer, which were used as constraints during 3‑D Fourier‑domain inversion procedure. The inversion results showed satisfactory fit statistics compared to seismic‑based depth data. The analysis of the inversion’s performance for the three inverted sedimentary layers showed that the percentage error between the inverted‑based depth and the seismic‑based depth was ranging from ±0.004 to 21.67%. The seismic and inverted‑based depths of the top Dabaa, Kharita, and El Alamein Formations were found to have correlation coefficient values of 0.88, 0.82, and 0.75, respectively. A 2‑D model was created for four horizons, including the basement layer. The 2‑D modeling indicated that the study area is affected by a number of normal faults that cross most of the layers and dip into the NE and SW directions, with dipping angles ranging from 70° to 80° and 75° to 85°, respectively. The 3‑D inversion results demonstrated that gravity measurements can accurately determine the depth of the sedimentary layer when stripping is performed at the Bouguer‑station level and the inversion is constrained by density and seismic information, with a tolerance of up to 21.67% and decrease until it matches the true depth in some locations

Integrating the FXLand network into the real‑time earthquake surveillance and monitoring system of Italy

The Ionian margin of southern Italy is one of the most complex geodynamic regions in the central Mediterranean, where ongoing convergence between the African and Eurasian plates results in intense seismic activity and highly heterogeneous crustal structures. To improve seismic monitoring in this region, within the framework of the ERC Advanced Grant FOCUS (2018‑2025), a temporary onshore seismic network (FXLand) was deployed along the Ionian coasts of Sicily and Calabria from December 2021 to June 2023, complementing a marine array of ocean‑bottom seismometers operating during the same period. In this study we describe the deployment and performance of the 13 temporary broadband stations of FXLand. The network was integrated in real time into the Italian national seismic surveillance system, enhancing data availability and coastal network geometry. During the deployment, FXLand recorded, more than 1,500 local earthquakes and more than 200 teleseismic events with magnitude M ≥ 6. We also present results from the analysis of three seismic sequences that occurred during the network operational period. The application of a Template Matching technique to the combined permanent station and FXLand network dataset, we significantly increased the number of detected low‑magnitude earthquakes in onshore area, improving catalog completeness compared to real‑time surveillance and Italian Seismic Bulletin. On the other hand, the offshore sequence highlights the main limitations of land‑based networks in detecting and accurately locating submarine seismicity. The integration of marine observations from the ocean‑bottom seismometer network in the Ionian Sea is expected to provide substantial improvements in the detection and location accuracy of offshore earthquakes, contributing to a more complete characterization of seismic activity along the Ionian margin

Application of the Vertical‑to‑Horizontal (VH) Ratio of the Peak Ground Velocity (PGV) in the Bay of Algiers using Data from Weak to Moderate Earthquakes

This research aims to identify the most appropriate predictor for the Vertical‑to‑Horizontal (VH) ratio of the Peak Ground Velocity (PGV) from the five existing models in the literature useful for regional or site‑specific probabilistic seismic hazard assessment, and practical applications in the Bay of Algiers. Firstly, dataset of 285 observed VH ratios of PGV was compiled from nine seismic stations within the study area, installed on different flat and irregular surfaces. This dataset was derived from earthquakes with moment magnitude (Mw) ranging from 3.3 to 5.3. Next, the dataset was categorized into two groups based on the soil type at the station locations: rock (S1) (Vs30 above 800 m/s) and stiff (S2) (Vs30 360‑800 m/s) soils. After that, a preliminary linear regression analysis was performed for each group of observed VH ratios of PGV as a function of the Joyner‑Boore distance (RJB) of near field and compared with three selected candidature predictors: Akkar et al. (2014), Bozorgnia and Campbell (2016), and Ramadan et al. (2021) (RA2021). For an extensive evaluation, the Euclidean Distance‑based ranking method (EDR) was applied on the three mentioned candidature predictors. For rocky soil, the results indicate that all models closely align with the linear regression fit, around a VH ratio of PGV of 0.6. However, RA2021 appears to provide a reasonable fit, with a VH ratio of PGV of 0.4 for stiff soil, despite the significant site‑effects at the respective stations. The EDR showed that RA2021 gives the lowest sigma with the observed ratios for S1 and S2 soil classes. For the far field, estimates of the VH ratio of PGV are provided for three strong earthquake magnitudes (6.5, 7.0, and 7.5) and different soil classes, using the existing models

Discriminating the origin of obsidian fragments in archaeological contexts based on morphological features and geochemical data: the Breccia Museo (Campanian Ignimbrite eruption, Italy) case study

A recent archaeological discovery on Vivara, the small islet next to Procida (Campania region, Italy), has documented the prehistoric use of finely crushed obsidian fragments as abrasive powder for polishing wooden artifacts. These fragments originated from a local deposit known as Breccia Museo – whose exploitation in prehistoric times had not been previously attested – and were found mixed with obsidian tools sourced from other well‑known Italian deposits widely used throughout prehistory. To develop effective methods for discriminating obsidian provenance, as required in this case, we carried out geochemical, isotopic, and mineralogical analyses on obsidian samples collected from the Breccia Museo outcrop at Punta della Lingua (~4 km NE of Vivara), one of the richest and most accessible deposit on Procida Island. The results were compared with those obtained from Breccia Museo obsidians from other local (Campi Flegrei) outcrops, as well as with reference samples from the major obsidian sources exploited in the Central‑Western Mediterranean during prehistory (Monte Arci, Palmarola, Lipari, and Pantelleria). In addition, a micromorphological and microanalytical study was performed to identify further distinctive features useful for recognizing Breccia Museo obsidian across different archaeological contexts. This interdisciplinary investigation highlights the potential of combining relatively rapid major/minor element analyses, mineralogical and morphological characterization, with more time‑consuming but highly precise isotopic measurements (87Sr/86Sr, 143Nd/144Nd) to achieve robust provenance discrimination

Magnetic Inversion under Remanent Conditions Using Equivalent Layer Direction Estimation and VOXI Earth Modelling

Remanent magnetisation is a critical challenge in magnetic interpretation, often leading to mispositioned anomalies and unreliable inversion results when neglected. This study applies and validates a practical, sequential two‑step workflow that integrates existing techniques to improve magnetic modelling in scenarios where remanent components significantly influence the anomaly geometry. In the first stage, the total magnetisation direction is estimated using the Equivalent Layer technique, which reconstructs the effective magnetisation vector from the observed anomaly without decomposing it into induced and remanent components. The magnetisation direction estimated via the equivalent layer technique was used to perform the reduction to the pole (RTP), and the inversion was subsequently carried out assuming a vertical inducing field (D = 0°, I = 90°). The methodology was tested on synthetic models with varying remanent contributions to evaluate its performance in controlled conditions. Results demonstrate that incorrect directional assumptions lead to distorted source geometries and underestimated susceptibilities, whereas using the Equivalent Layer estimated direction significantly improves inversion accuracy. The approach was also applied to a real airborne magnetic dataset from Espírito Santo State, Brazil, where it successfully recovered a westward‑dipping magnetic body with coherent susceptibility structure. Residual analysis confirmed strong agreement between predicted and observed fields, reinforcing the method’s robustness. While the current implementation assumes a constant magnetisation direction within the target volume, making it less suitable for geologically complex bodies, it offers a stable and interpretable solution for cases where remanence is spatially coherent. This study provides a practical, reproducible workflow for the integrated application of EL‑based direction estimation, RTP, and VOXI susceptibility inversion to remanence‑affected datasets. This workflow is compatible with standard modelling platforms and provides a practical reference for remanence‑affected magnetic interpretation

Seismic event location with a small aperture DASarray: a case‑study from DIVE ICDP drilling project

Distributed Acoustic Sensing (DAS) has emerged as an innovative technology in seismology, sensing seismic waves along fiber optic cables and, thus, increasing ten‑folds the spatial density of seismic measurements. However DAS potential in seismic monitoring is still under investigation. In this study, we assess the differences in seismic event detection and localization when using DAS, conventional seismometers, and combination of both, by analyzing a dataset acquired during a field experiment in Megolo di Mezzo (Northern Italy). A ~1 km buried fiber optic cable was deployed with an almost L‑shape configuration. Seismic data were continuously recorded from November 2023 to February 2024 and compared with simultaneous observations from the local seismic network (DIVEnet). Several local earthquakes were detected, including microseismic events not listed in the official catalog. P‑wave arrival times were extracted from DAS recordings using different picking algorithms and compared to manual picks from seismometers. Event localization was performed through a Bayesian Monte Carlo approach applied separately to DAS and seismometer data, and jointly. Results demonstrate that DAS shows considerable potential in earthquake detection, particularly for low‑magnitude events and those occurring close to the fiber optic cable, as potentially expected during anthropic activities underground. The joint inversion of DAS and seismometer datasets reduced localization uncertainties and produced solutions consistent with the official INGV catalog. However, differences of up to ~2 km between DAS – and seismometer – based epicenters highlight the limitations of simplified velocity models and the impact of network geometry. These findings confirm the complementarity of DAS and traditional networks and underline the potential of hybrid monitoring strategies for advancing earthquake detection and characterization in complex geological environments

Application of the relocation-error distribution on geomagnetic databases. Analyses on the «Historical Italian Geomagnetic Data Catalogue»

The reliability of the Historical Italian Geomagnetic Data Catalogue, comprising 536 directions and 393 intensities, has been assessed by comparing the historical geomagnetic measurements with the GUFM1 model predictions. Such measurements were assessed at three selected relocation centres. For all the data contained in the Catalogue it has been calculated the discrepancy between the relocated data and the GUFM1-model prediction at the relocation centres. There is a correlation between relocation distance and the mean discrepancy. The upper limit of discrepancy assumable as relocation error has been selected using error distributions previously calculated using geomagnetic field models. Angular and intensity threshold lines have been slightly shifted upwards to account for the estimated error of GUFM1 model itself at the considered region, mainly due to the crustal field. The Italian database proved to contain reliable data, as only a very low percentage of data (namely 14 directions and 20 intensities) can be considered anomalous. Possible explanations for such questionable data are suggested. All the remaining data of this catalogue could thus be added to the databases used to produce regional or global geomagnetic models