Source Model Research Articles

Service spacecraft for space debris removal

The problem of space debris removal from the near-Earth space is being studied in almost every country taking part in space exploration. This is due to the global threat of critical increase in the number of space debris objects predicted for the near future, in particular as a result of significant growth in demand for multi-satellite constellations for various purposes. To date, researchers have proposed a large number of different methods for space debris removal. The work presented is the development of one of the promising contactless methods of space debris removal by an ion beam. The results of modeling and optimization of physical processes in the ion source to be mounted on board a service spacecraft that is necessary for implementing the considered method of space debris removal are presented. Besides, the results of thermal modeling and thermal mapping of the ion source during its operation are presented also, and the calculation results of its output parameters are compared to experimental data, which verified the small divergence angles of the generated ion beam. To assess the prospects of using a system for contactless space debris transportation by an ion beam using the obtained data on the operating parameters of the ion source, the trajectory design and mission analysis were carried out, which revealed the feasibility of removing seven space debris objects out of the protected region in geostationary orbit by a single service spacecraft. Besides, the preliminary service spacecraft design is presented.

Addressing magnetometer inconsistencies in drone-borne total field gradiometer surveys: case study from Rånbogen, Arctic Norway

SUMMARY Inconsistencies between (lightweight optical pumped) magnetometers in total field gradiometer surveys can introduce instrument-dependent responses, complicating geological interpretation. Here, we present an equivalent source-based processing method that combines equivalent sources with kernel regression to eliminate these instrument-dependent responses. We evaluate the method using a drone-borne triangular gradiometer survey from Rånbogen, Arctic Norway. The Rånbogen survey exhibits instrument-dependent responses in the measured total field differences, likely resulting from differences in the magnetometer’s heading error and the complexities from the induced field from the system itself. A synthetic gradiometer survey was generated to test the method, where different nonlinear synthetic heading errors were added to the synthetic magnetometer readings. The equivalent source-based processing method effectively removed these heading errors while constructing an equivalent source model that fits the actual underlying synthetic model. Furthermore, applying the method to the Rånbogen survey removes the data’s correlation to its orientation, thereby minimizing the effect of the instrument-dependent response. The method condenses the gradiometer data to a single equivalent source surface where the derivatives of the total field can be calculated to facilitate interpretation. The results suggest that the equivalent source-based method removes the inconsistencies between the magnetometers in a total field gradiometer survey, allowing for drone-borne gradiometer systems with multiple lightweight magnetometers.

Dynamic phase measurement based on two-step phase-shifting interferometry with geometric phase grating

Abstract This paper proposes a novel dynamic 2-step phase-shifting interferometry method with a geometric phase grating and direct aberration-free object phase recovery algorithm. By exploring the amplitude-phase modulation property of the geometric phase grating, two-step phase-shifting interferograms with π / 2 phase shift can be obtained in a single shot through two kinds of spatial-multiplexing arrangements. Then the restriction on the background uniformity of the 2-step phase-shifting algorithms and the system aberration can be avoided simultaneously, based on the presented direct and fast object phase demodulation strategy with an object-free state recorded in advance, so an accurate object measurement result can be guaranteed. Accordingly, a detailed analysis of the theoretical model of error sources is conducted by taking the depolarization error of geometric phase grating and phase measurement model error into consideration, with a Least Squares Iteration optimization strategy established to further improve the measurement accuracy. Experiments on various types of phase objects, such as a photo-etched quartz substrate, the spatial light modulator, and a silicon chip, validate the effectiveness and accuracy of our method when compared with the reference phase obtained from 4-step temporal phase-shifting method. The dynamic phase measurement capability is demonstrated by exhibiting the evaporation process of alcohol droplet.

Cathode-less RF plasma thruster design and optimisation for an atmosphere-breathing electric propulsion (ABEP) system

Atmosphere-breathing electric propulsion (ABEP) is a concept that ingests residual atmospheric gases as a source of propellant for an electric thruster, removing the need for onboard propellant storage. This would enable continuous low-thrust drag compensation, extending the lifetime of spacecraft in Very-Low Earth Orbit (VLEO); <250 km. VLEO is an appealing region for spacecraft operations, enabling new remote sensing missions with improved radiometric performance and spatial resolution, whilst reducing size, mass and power requirements, as well as mission cost. A preliminary design review and optimisation is therefore conducted for an ABEP system that uses the cathode-less radio frequency (RF) plasma thruster from Technology for Innovation & Propulsion (T4i) S.p.A. This removes the issue of thruster erosion by means of magnetic confinement and offers reduced susceptibility to varying atmospheric composition. A semi-empirical oxygen-nitrogen global source model (GSM) has been developed which considers the volume-averaged flux, momentum, and energy balance of the RF discharge. This includes a detailed chemistry model for the complex electron-molecular reactions and energy-loss channels of air plasma in the ionisation chamber. The GSM is coupled to an analytical model of flux balance for an air intake, verified by Direct Simulation Monte-Carlo (DSMC) simulation, to consider its design for maximum collection efficiency. This is then utilised in a robust multi-objective optimisation of the ABEP system, accounting also for spacecraft aerodynamics and power requirements.

On the implausible physical implications of a claimed lensed neutral hydrogen detection at redshift z = 1.3

Abstract The Square Kilometre Array mid-frequency array will enable high-redshift detections of neutral hydrogen (H i) emission in galaxies, providing important constraints on the evolution of cold gas in galaxies over cosmic time. Strong gravitational lensing will push back the H i emission frontier towards cosmic noon (z ∼ 2), as has been done for all prominent spectral lines in the interstellar medium of galaxies. Chakraborty &amp; Roy (2023, MNRAS, 519, 4074) report a z = 1.3 H i emission detection towards the well-modelled, galaxy-scale gravitational lens, SDSS J0826+5630. We carry out H i source modelling of the system and find that their claimed H i magnification, μHI = 29 ± 6, requires an H i disk radius of ≲ 1.5 kpc, which implies an implausible mean H i surface mass density in excess of ΣHI &amp;gt; 2000 M⊙ pc−2. This is several orders of magnitude above the highest measured peak values (ΣHI ∼ 10 M⊙ pc−2), above which H i is converted into molecular hydrogen. Our re-analysis requires this to be the highest H i mass galaxy known (MHI ∼ 1011 M⊙), as well as strongly lensed, the latter having a typical probability of order 1 in 103 − 4. We conclude that the claimed detection is spurious.

Study on the thermal radiation characteristics caused by two fires in a tunnel based on multi-layer zone model

The radiation of fire source and hot flue gas plays a very important role in the process of smoke movement. The radiation effect, which was little included in the earlier studies, was included in the present work. So the thermal radiation characteristics caused by two fires will be studied in a tunnel combined with multi-layer zone (MLZ) model, small-scale experiments and numerical simulations. Based on the data obtained by the aforementioned methods, research on the thermal radiation model is carried and a piecewise fire source model is proposed. Subsequently, the longitudinal thermal radiation model caused by two fires in a tunnel is investigated and then modified and verified. The results showed that the thermal radiation model caused by two fires for MLZ model in a tunnel is reliable, which can make a general and reliable judgment on the immediate fire disaster situation, and can also provide reference for the follow-up work.

Comparative Assessment of Otolaryngology Knowledge Among Large Language Models

ObjectiveThe purpose of this study was to evaluate the performance of advanced large language models from OpenAI (GPT‐3.5 and GPT‐4), Google (PaLM2 and MedPaLM), and an open source model from Meta (Llama3:70b) in answering clinical test multiple choice questions in the field of otolaryngology—head and neck surgery.MethodsA dataset of 4566 otolaryngology questions was used; each model was provided a standardized prompt followed by a question. One hundred questions that were answered incorrectly by all models were further interrogated to gain insight into the causes of incorrect answers.ResultsGPT4 was the most accurate, correctly answering 3520 of 4566 questions (77.1%). MedPaLM correctly answered 3223 of 4566 (70.6%) questions, while llama3:70b, GPT3.5, and PaLM2 were correct on 3052 of 4566 (66.8%), 2672 of 4566 (58.5%), and 2583 of 4566 (56.5%) questions. Three hundred and sixty‐nine questions were answered incorrectly by all models. Prompts to provide reasoning improved accuracy in all models: GPT4 changed from incorrect to correct answer 31% of the time, while GPT3.5, Llama3, PaLM2, and MedPaLM corrected their responses 25%, 18%, 19%, and 17% of the time, respectively.ConclusionLarge language models vary in their understanding of otolaryngology‐specific clinical knowledge. OpenAI's GPT4 has a strong understanding of core concepts as well as detailed information in the field of otolaryngology. Its baseline understanding in this field makes it well‐suited to serve in roles related to head and neck surgery education provided that the appropriate precautions are taken and potential limitations are understood.Level of EvidenceN/A Laryngoscope, 2024

MURDA: Multisource Unsupervised Raman Spectroscopy Domain Adaptation Model with Reconstructed Target Domains for Medical Diagnosis Assistance.

Artificial intelligence combined with Raman spectroscopy for disease diagnosis is on the rise. However, these methods require a large amount of annotated spectral data for modeling to achieve high diagnostic accuracy. Annotating labels consumes significant medical resources and time. To reduce dependence on labeled medical data resources, we propose a method called Multisource Unsupervised Raman Spectroscopy Domain Adaptation Model with Reconstructed Target Domains (MURDA). It transfers knowledge learned from source domain data sets of different diseases to an unlabeled target domain data set. Compared to knowledge transfer from a single source domain, knowledge from multiple disease source domains provides more generalized knowledge. Considering the diversity of autoimmune diseases and the limited sample size, we apply MURDA to assist in the medical diagnosis of autoimmune diseases. Additionally, we propose a Double-Branch Multiscale Convolutional Self-Attention (DMCS) feature extractor that is more suitable for spectral data feature extraction. On three sets of serum Raman spectroscopy data sets for autoimmune diseases, the multisource domain adaptation diagnostic accuracy of MURDA was superior to traditional single source and multisource models, with accuracy rates of 73.6%, 83.4%, and 82.9%, respectively. Compared with pure source tasks without domain adaptation, it improved by 15.1%, 36%, and 21.6%, respectively. This demonstrates the effectiveness of Raman spectroscopy combined with MURDA in diagnosing autoimmune diseases. We investigated the important decision dependency peaks in migration tasks, providing assistance for future research on artificial intelligence combined with Raman spectroscopy for diagnosing autoimmune diseases. Furthermore, to validate the effectiveness and generalization performance of MURDA, we conducted experiments on the publicly available RRUFF data set, exploring the application of multisource unsupervised domain adaptation in more Raman spectroscopy scenarios.

Statistical Analysis of Characteristic Parameters and Probability Distribution of Near-Fault Velocity Pulses—A Case Study on the 1999 Mw 7.6 Chi-Chi Earthquake

Abstract The 1999 Mw 7.6 Chi-Chi earthquake in the Taiwan region generated valuable ground motions, providing an opportunity for studying the characteristic parameters and distribution of near-fault velocity pulses. Using the finite-difference method, we built a source model, simulated the 1999 Mw 7.6 Chi-Chi earthquake ground motions, and obtained synthetic velocity waveforms consistent with the observed waveforms. On this basis, we analyzed the distribution of velocity pulses in the near-fault region and compared it with the pulse probability distribution (PPD) curve of the near-fault velocity pulse. We found that the complex rupture process of the Mw 7.6 Chi-Chi earthquake resulted in velocity pulses still being recorded in Miaoli and Xinzhu. In addition, we analyzed the relationship between pulse period, pulse peak, and fault distance. The pulse peak indicates a clear attenuation trend with increasing fault distance (Rrup) and no statistical relationship between the pulse period and Rrup. More velocity pulses in normal-fault components reveal the reverse fault of the Chi-Chi earthquake. Finally, structures with natural periods within the 1–7 s are more susceptible to resonance from near-fault velocity pulses, and it is necessary to take appropriate seismic measures. This study lays the foundation for a deeper understanding of the ground motion and pulse characteristics caused by earthquakes and contributes to sustained efforts in seismic hazard assessment.

Probabilistic Seismic Hazard Assessment of Lisbon (Portugal)

The 1755 Lisbon earthquake holds significant historical importance in Portuguese history. The subsequent tsunami resulted in extensive destruction and damage, affecting not only Lisbon but also other regions of Portugal, Spain, and North Africa. This significant and hazardous event led to an increase in awareness about earthquake and tsunami risks, not only within Portugal but throughout Europe. This heightened awareness facilitated advancements in scientific developments, including design codes, standards, and earthquake engineering. However, recent studies focusing on hazard assessment for Lisbon are limited. For this reason, this paper aims to present a comprehensive probabilistic seismic hazard analysis (PSHA) for the Lisbon metropolitan area. The first stage of PSHA involves defining applicable and active seismic source models (area and line sources) within the study area. Subsequently, historical and instrumental earthquake records are collected to build a homogenized earthquake catalog, utilizing both global and local earthquake databases. Following this, the completeness level of the earthquake catalog is tested. By incorporating suitable ground motion models to the region and local soil characteristics, seismic hazard maps for various return periods and hazard curves in terms of peak ground acceleration (PGA) are developed. The findings based on the area source model agree with existing literature, indicating PGA values ranging from 0.3 g to 0.9 g, 0.2 g to 0.7 g, 0.2 g to 0.5 g, and 0.1 g to 0.3 g for return periods of 2475, 975, 475, and 50 years, respectively.

Development of the Quantitative Property-Consequence Relationship Model for Prediction of Hydrogen Leakage and Dispersion Using Response Surface Method and Artificial Neural Network Approaches.

Hydrogen, an environmentally friendly and highly regarded future energy source, can form flammable vapor clouds upon leakage, which may transition into explosion. Predicting the dispersion behavior of hydrogen is crucial for preventing such incidents. This study aims to develop a quantitative property-consequence relationship (QPCR) model using the response surface method (RSM) and artificial neural network (ANN) to swiftly and accurately predict dispersion behavior. Initially, 8 variables were defined from source and dispersion models, constructing a data set through 6,561 PHAST simulations. Subsequently, the RSM-BBD (Box-Behnken design) and ANN-BPNN (Backpropagation neural network) models were developed, alongside a hybrid model incorporating BPNN after excluding four low-influence variables based on analysis of variance (ANOVA). All models achieved an R2 value exceeding 0.99. The hybrid model notably reduced computational costs by 97% compared to ANN-BPNN and exhibited lower mean square error (MSE). These results introduce a cost-effective approach for high-accuracy QPCR modeling and highlight the viability of diverse statistical methods.

A 3D Seismotectonic Model and the Spatiotemporal Relationship of Two Historical Large Earthquakes in the Linfen Basin, North China

The Shanxi Graben is a transitional zone between the Ordos Block and North China Plain with complex structures and frequent earthquakes. Six earthquakes with M ≥ 7.0 have been recorded in the area, including the 1303 Hongtong M 8 and 1695 Linfen M 7.8 earthquakes in the Linfen Basin. Research on these two large earthquakes, closely related in time and space, is lacking. Our objective was to use deep seismic reflection profiles and 3D velocity structure data from previous research, along with seismological observation results, to interpret the geological structure near the source of the two earthquakes. A 3D geometric model of the seismogenic fault was constructed, and the relationships among the deep and shallow structures, deep seismogenic environment, and two large earthquakes were explored. Differences in seismogenic environment between the southern and northern Linfen Basin were identified. The distribution of small earthquakes in the southern Linfen Basin was scattered, and the overall distribution was at depths &lt;25 km. The small earthquakes in the northern part of the basin were dense and concentrated at depths of 25–35 km. Low-velocity layers at an approximate depth of 15–20 km in the southern basin led to differences in seismogenesis between the two regions. Based on the area of the 3D geometric model of the Huoshan Fault, the maximum magnitude of an earthquake caused by fault rupture is Mw 7.7, so the magnitude of the 1303 Hongtong earthquake might be overestimated. Numerical simulation results of Coulomb stress showed that the 1303 Hongtong earthquake had a stress-loading effect on the 1695 Linfen earthquake. The change in Coulomb rupture stress was 1.008–2.543 bar, which is higher than the generally considered earthquake trigger threshold (0.1 bar). We created a new 3D source model of large earthquakes in the Linfen Basin, Shanxi Province, providing a reference and typical cases for risk assessment of large earthquakes in different regions of the Shanxi Graben.

Seismogenic Quasi-Stationary Electric Fields and Currents from Large-Scale Sources on the Earth’s Surface: Comparison of Model Representations

A comparative analysis of various model representations of seismogenic quasi-stationary electric fields/currents from large-scale sources on the Earth’s surface was carried out. It has been established that previously proposed analytical models of seismogenic quasi-stationary sources of electric field/current with field/current amplitudes continuously decreasing to zero at infinity are consistent with extreme values of electric field/current experimentally observed in epicentral zones before earthquakes. It is also shown that sharply spatially limited models of seismogenic sources of quasi-stationary electric fields/currents in the epicentral zones of future earthquakes on the Earth’s surface lead to their values being an order of magnitude or more greater than those actually observed.

Kinematics of the 2023 Kahramanmaraş Earthquake Doublet: Biased Near-Fault Data and Shallow Slip Deficit

Abstract Accurate estimate of the shallow slip deficit (SSD) for large strike-slip events is highly dependent on near-fault data. Previous studies have estimated the SSD of the 2023 Kahramanmaraş earthquake doublet, which may vary from a few percent to about 50%. Whether this reduced shallow slip is real or artificial is crucial for understanding the seismic hazards during and following the earthquake doublet. In this study, we inverted for the kinematic slip of this earthquake doublet with refined near-fault Interferometric Synthetic Aperture Radar observations and compared the results with the source model without further data processing. The model that excludes nonphysical data produced only ∼6% and ∼22% SSD for the M7.8 and 7.6 events, respectively, compared to ∼44% and ∼53% SSD of the model using original data. The increased data gap generally leads to overestimated SSD, but when the data coverage is almost complete, our result shows that the SSD is very sensitive to biased near-fault data which may induce significant artificial SSD. Our results suggest that overestimated SSD may be accompanied by slip migration from shallow toward deeper depths, to meet the total moment or energy release constrained by surface displacement data. The M7.8 event increased static Coulomb stress at where the second M7.6 event nucleated and thus may have triggered the following event.

Deep-neural-network model for predicting ground motion parameters using earthquake horizontal-to-vertical spectral ratios

This study proposed a deep-neural-network (DNN) model for seismic ground motion prediction by utilizing a unified strong motion database by the National Research Institute for Earth Science and Disaster Resilience, and earthquake horizontal-to-vertical spectral ratio (EHVR) database in Japan. The model aims to enhance the accuracy of predictions by incorporating the EHVRs for complementing site effects, and utilizing existing ground motion prediction equations (GMPE) as the base model for source and propagation path effects. The hybrid approach enables the prediction of peak ground accelerations (PGAs), peak ground velocities (PGVs), and 5% damped absolute acceleration response spectra (SAs). After classifying the training and test sets from the database, the trained DNN models were applied on the test set to evaluate the performance of the predicted results. The accuracy assessment by the residuals, R-squared ( R2), and root mean square error (RMSE) between the predicted and observed values in the test set revealed the superior performance of the proposed model compared with the traditional GMPE with proxy-based site effects such as V S30s especially in predicting both the spectral amplitude and shape of SAs.

A large-scale-outdoor continuous release of cryogenic liquid onto ground

The accidental release of cryogenic liquids can cause several hazards to humans, assets, and the environment. Therefore, this phenomenon has drawn significant attention and has been investigated as part of quantitative risk assessment associated with the use of cryogenic liquids. However, the effects of release conditions on pool spread have not been thoroughly studied, and the mechanism of pool retraction has not been discussed. In this study, an attempt was made to address these gaps by both experimental and numerical analyses. Firstly, large-scale-outdoor release tests with a systematic measurement system were performed using liquid nitrogen to compare with large-scale release tests of liquid hydrogen. The release height and orientation were varied. It was observed that the pool shape was affected by the release orientation. However, the maximum pool size and average vaporization rate were insensitive to both the release height and orientation. The conductive heat from the ground was confirmed to be the major heat source for pool vaporization, accounting for over 90 % of the total heat transferred into the liquid pool. Subsequently, release scenarios were simulated using integral source models. Especially, several hypotheses were thoroughly discussed, implemented in the source models, and validated against experimental results to determine the most appropriate mechanism for pool retraction. The findings of this study are expected to be beneficial for the consequence estimation of cryogenic release scenarios and for the validation and improvement of source models.

Overcoming learning bias via Prototypical Feature Compensation for source-free domain adaptation

The focus of Source-free Unsupervised Domain Adaptation (SFUDA) is to effectively transfer a well-trained model from the source domain to an unlabelled target domain. During the target domain adaptation, the source domain data is no longer accessible. Prevalent methodologies attempt to synchronize the data distributions between the source and target domains, utilizing pseudo-labels to impart categorical information, which has made some progress in improving the model’s performance. However, performance impairments persist due to the introduction of learning bias from the source model and the impact of noisy pseudo-labels generated for the target domain. In this research, we reveal that the central cause for feature misalignment during domain transition is the learning bias, which is generated by the discrepancy of information between source and target domain data. The source domain data may contain distinguishable features that do not appear on the target domain, which causes the pre-trained source model to fail to work during domain adaptation. To overcome the information discrepancy, we propose a Prototypical Feature Compensation (PFC) Network. The network extracts representative feature maps of the source domain. Then use them to minimize the discrepancy information in the target domain feature maps. This mechanism facilitates feature alignment across different domains, allowing the model to generate more accurate categorical data through pseudo-labelling. The experimental results and ablation studies demonstrate exceptional performance on three SFUDA datasets and provide evidence of the proposed PFC method’s ability to adjust the feature distribution of both source and target domain data, ensuring their overlap in the latent space.

A Composite Seismic Source Model for the First Major Event During the 2022 Hunga (Tonga) Volcanic Eruption

AbstractThe violent eruption of the Hunga (Tonga) submarine volcano on 15 January 2022 caused a 58 km‐heigh ash plume, catastrophic tsunami, and significant global seismic and infrasound waves. However, the physical mechanism underpinning its multiple‐explosive events remains unclear, and its resolvability relies on the seismic waveform source inversion. The studies of two different point‐source models, the seismic moment tensor (MT) and the single force (SF), have been performed separately for this eruption, which, interestingly, can explain the seismic data adequately. Here, we use a joint inversion of MT and SF to unravel a composite source of an explosion‐like MT and a significant upward force for the first major explosive event. Regarding the direction and magnitude, we propose that the upward force is likely a rebound force in response to the pressure drop on the seafloor because the water body above the volcano was abruptly uplifted by the shallow underwater explosion.

Analysis of the Impact of Multiple Explosion Source Layouts on the Kinetic Characteristics of Gas Explosions in Blind Roadways

To investigate the changes in conditions within a blind roadway when multiple gas explosion sources are simultaneously detonated, the fluid dynamics software Fluent14.0 was used to conduct numerical simulation experiments with different numbers (2 and 3) and varying intervals (5 m, 10 m, and 15 m) of explosion sources. The results revealed that multiple explosion sources in gas explosions generate shock waves that propagate in opposite directions, creating pressure overlap zones within the roadway. The pressure waves and shock waves in these overlap zones continuously couple within the roadway. The number of overlap zones decreases incrementally with each encounter of opposing shock waves in the roadway. Unlike single explosion source models, the pressure at various positions within the roadway in multiple explosion source models oscillates due to the coupling of multiple shock waves, with significant peak pressures occurring at the closed end of the roadway and in the pressure overlap zones. Additionally, the propagation patterns of shock waves and flames within the roadway are not associated with the interval distance between explosion sources, whereas the encounter time, speed, and pressure of shock waves increase with the interval distance.

Studying Past Earthquakes with Modern Techniques: Ground-Motion Simulations for the 11 January 1693 Noto Earthquake in Italy

Abstract The 1693 Noto earthquake, which struck on 11 January, is one of the Italy’s largest and most devastating earthquakes. According to the Italian Parametric Earthquake Catalogue, it reached a maximum intensity of 11 on the Mercalli–Cancani–Sieberg scale and had an estimated magnitude of M 7.3. Nevertheless, its precise location and source definition remain subjects to debate due to the complexity of the seismic sequence and lack of geological evidence. A series of potential seismic sources differing in location, dimension, and kinematics have been proposed in the literature based on seismotectonic data and interpretations. The goal of this work is to perform a retrospective experiment to verify which of the proposed seismic sources have a better fit with the observed intensity data. To do so, novel simulation techniques are used to study this historical earthquake. We generated ground-motion scenarios for each proposed source model through a stochastic finite-fault simulation approach. Then, the simulated ground-motion parameters were converted to intensities using two different ground-motion intensity conversion equations for Italy. Finally, we compared these converted intensities with the observed intensity data in terms of normalized root mean square errors and converted intensities from ground-motion models. Our results generally show good consistency between converted intensities from the simulated and predicted ground motions, whereas the observed intensities fit better to converted ones from the peak ground velocity rather than peak ground acceleration. Our analysis reveals that the source model reproducing the best of the macroseismic data of the Noto earthquake is the Canicattì–Villasmundo fault system with a magnitude of 7.1.