Source Characteristics Research Articles

A seismic source characterization model of multi-station based on graph neural network

A seismic source characterization model of multi-station based on graph neural network

A quantitative analysis of acoustic field directionality from a seismic airgun array

Marine seismic reflection surveys generate high amplitude impulsive acoustic events using airgun arrays to study geophysical characteristics of the seabed. These data can be used beyond seismic imaging – modeling short range propagation, considering impacts on marine mammals, extracting seabed properties and their effect on the acoustic field, etc. Knowledge of the source characteristics is necessary to utilize these data and proper modeling of sound propagation from these arrays requires characterization of the array beam pattern. Complex simulations of airgun arrays have been used in the past to model airgun array spectra, but beam patterns have not been thoroughly considered in the literature. Delay-and-sum combinations of these airgun signatures provide a simple beam pattern estimate, but this approach ignores variability in airgun position, timing, amplitude, interactions between airguns, etc. The use of more complex notional airgun signatures can yield more accurate estimates, but these are more challenging to model and still ignores shot-to-shot variability. Experimentally-determined beam patterns are evaluated here and the variability in the results considered, showing both similarities and notable differences from simulated results. The experimental results indicate that the source array depth impacts the ghost-free array beam pattern and that variability between shots is enough to significantly alter beam patterns. Overall, the observations suggest that accurate simulation of array beam patterns may require more complexity than is currently considered and that inclusion of uncertainty due to environmental and airgun shot variability is essential.

Risk Assessment Method for Distributed Power Distribution Networks Considering Network Dynamic Reconstruction

A new safety assessment framework has been proposed to address the operational risks of the integration of wind power and photovoltaic grid, which integrates the characteristics of distributed power sources with the dynamic reconfiguration requirements of the distribution grid. The framework comprehensively considers the impacts of wind power and photovoltaic output uncertainties, as well as load fluctuations, on the stability of the distribution grid. It also evaluates the safety under different operational states of the distribution grid. Using Halton sequence sampling technology to accurately simulate the output of distributed power sources and the status of system components, combined with CPLEX optimisation for solving, a dynamic reconfiguration model is constructed to address potential faults in the distribution grid. Introducing the combined weighting method, a comprehensive risk assessment system for voltage violations, power flow violations, and load shedding has been constructed. The effectiveness of this method has been validated through simulations on the IEEE33 bus and IEEE118 bus systems, providing new insights to improve the safety and reliability of distribution grids.

Geochemical Characteristics and Origin of Natural Gas in the Middle of Shuntuoguole Low Uplift, Tarim Basin: Evidence from Natural Gas Composition and Isotopes

Multiple types of reservoirs, including volatile oil reservoirs, condensate gas reservoirs, and dry gas reservoirs, have been discovered in ultra-deep layers buried at depths greater than 7500 m. Understanding the genetic types of natural gas is of utmost importance in evaluating oil and gas exploration potential. The cumulative proved reserves of the super deep layer in the Shuntuoguole low uplift area of the Tarim Basin exceed 1 × 108 t (oil equivalent). The origin, source, and accumulation characteristics of natural gas still remain a subject of controversy. By analyzing the composition and carbon isotope of natural gas, a detailed investigation was conducted to examine the unique geochemical and reservoir formation characteristics of the Ordovician ultra-deep natural gas within different fault zones in the middle region of the Shuntuoguole low uplift. It was determined that most of the natural gas in this area is displaying a characteristic of wet gas with a drying coefficient ranging from 0.41 to 0.99. The carbon isotope composition of methane in the gas reservoir shows relatively light values, ranging from −49.4‰ to −42‰. The carbon and hydrogen isotopes of the components are distributed in a positive order. The natural gas is oil type gas, which is derived from marine sapropelic organic matter and has a good correspondence with the lower Yuertusi formation. The maturity of natural gas in Shunbei No. 1 and No. 5 fault zones is about 1.0%, which is the associated gas of normal crude oil, while the maturity of No. 4 and No. 8 fault zones is higher than 1.0%, which is the mixture of kerogen pyrolysis gas and crude oil pyrolysis gas. The variations in the drying coefficient and carbon isotope composition of the natural gas provide evidence for the migration patterns within the Shuntuoguole low uplift central region. It indicates that the Shunbei No. 5 and No. 8 fault zones have likely migrated from south to north, while the No. 4 fault zone has migrated from the middle to both the north and south sides. These migration patterns are primarily controlled by high and steep strike-slip faults, which facilitate the vertical migration of natural gas along fault planes. Consequently, the gas accumulates in fractured and vuggy reservoirs within the Ordovician formation.

Electricity supply configurations for green hydrogen hubs: A European case study on decarbonizing urban transport

In this study, a techno-economic analysis tool for conducting detailed feasibility studies on the deployment of green hydrogen hubs for fuel cell bus fleets is developed. The study evaluates and compares five green hydrogen hub configurations' operational and economic performance under a typical metropolitan bus fleet refuelling schedule. Each configuration differs based on its electricity sourcing characteristics such as the mix of energy sources, capacity sizing, financial structure, and grid interaction. A detailed comparative analysis of distinct green hydrogen hub configurations for decarbonising a fleet of fuel-cell buses is conducted. Among the key findings is that a hybrid renewable electricity source and hydrogen storage are essential for cost-optimal operation across all configurations. Furthermore, bi-directional grid-interactive configurations are the most cost-efficient and can benefit the electricity grid by flattening the duck curve. Lastly, the paper highlights the potential for cost reduction when the fleet refuelling schedule is co-optimized with the green hydrogen hub electricity supply configuration.

Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017

Abstract We introduce a transportable technique to determine the yield and depth of burial (DOB) from seismic source spectra of underground nuclear explosions. We demonstrate this technique on the six declared North Korean nuclear tests. This approach derives source spectra in absolute units from regional phase (Pg) amplitudes by correcting the observations for geometric spreading, attenuation, and site amplification. We couple the source spectra and explosion source models with a probabilistic programming framework that integrates deep learning techniques and Bayesian modeling. This approach permits the exchange of information across various data categories to quantify both the data and model uncertainty. This technique stands out as an innovative use of broad-area propagation models, making it transportable across various geologic settings. This method proves to be effective in scenarios with diverse and/or limited observational data, even when the source depth is unknown. We present new independent estimates of absolute yield and DOB that are consistent with the prior assessments, underscoring the potential of this method in enhancing transportable nuclear explosion monitoring capabilities.

Characterising harmful data sources when constructing multi-fidelity surrogate models

Surrogate modelling techniques have seen growing attention in recent years when applied to both modelling and optimisation of industrial design problems. These techniques are highly relevant when assessing the performance of a particular design carries a high cost, as the overall cost can be mitigated via the construction of a model to be queried in lieu of the available high-cost source. The construction of these models can sometimes employ other sources of information which are both cheaper and less accurate. The existence of these sources however poses the question of which sources should be used when constructing a model. Recent studies have attempted to characterise harmful data sources to guide practitioners in choosing when to ignore a certain source. These studies have done so in a synthetic setting, characterising sources using a large amount of data that is not available in practice. Some of these studies have also been shown to potentially suffer from bias in the benchmarks used in the analysis. In this study, we approach the characterisation of harmful low-fidelity sources as an algorithm selection problem. We employ recently developed benchmark filtering techniques to conduct a bias-free assessment, providing objectively varied benchmark suites of different sizes for future research. Analysing one of these benchmark suites with the technique known as Instance Space Analysis, we provide an intuitive visualisation of when a low-fidelity source should be used. By performing this analysis using only the limited data available to train a surrogate model, we are able to provide guidelines that can be directly used in an applied industrial setting.

The Formation Mechanism of Soil Interflow in Loess Hill Gully

To address the problems of salinization of the soil in gully control and land-making projects, the formation mechanism of soil interflow from a gully valley on the Loess Plateau was investigated, regarding its interface, water source, and spatial-temporal distribution characteristics, through field location monitoring and isotope tracer technique. The results showed the following: (1) there are two types of soil interflow in the Loess Plateau, namely soil interflow in slope and in gully, with interflow in gully being the main form; (2) adequate water supply, layered soil structure, and geographic disparity are conditions for the formation of soil interflow in the gully; (3) soil water is recharged by precipitation, surface water, and groundwater. Surface water is an important source of soil water recharge at the 0–100 cm depth, whereas groundwater is an important source of soil water recharge at the 100–200 cm depth. The results provide a basis for the regulation of the soil interflow, resource utilization, and land quality improvement in the Loess Plateau.

Intelligent enhanced particle filter with deep residual network surrogate for accurate groundwater pollution source characterization

Accurate groundwater pollution source characterization (GPSC) is crucial for environmental protection and water resource management. Although the particle filter (PF) algorithm is widely employed for GPSC, it suffers from particle degradation and loss of diversity. To address this challenge, this study proposes an intelligent enhanced particle filter (IEPF) method to enhance GPSC’s accuracy and efficiency. First, this method optimizes the resampling process by defining a weight threshold while introducing an information transmission mechanism. This mechanism enables low-weight particles to update their positions by leveraging information from high-weight particles and neighboring particles, thereby enhancing information exchange among particles and improving the algorithm’s global search capability. Crossover and mutation operations are introduced to further increase the particle diversity, effectively preventing particles from concentrating on local optimal solutions. Furthermore, this study employs a deep residual network (ResNet) as a surrogate model for the simulation model. The ResNet has strong feature learning and expression capabilities and efficiently captures nonlinear relationships in data, thus significantly improving computational efficiency while ensuring accuracy. The results demonstrate that the IEPF method significantly enhances GPSC accuracy. In summary, the proposed IEPF method combined with the ResNet surrogate model provides an efficient and accurate approach to GPSC, with considerable benefits for groundwater pollution management.

A Chirped Characteristic-Tunable Terahertz Source for Terahertz Sensing.

In broadband terahertz waves generated by femtosecond lasers, spatial chirp will be simultaneously produced with the introduction of angular dispersion. The chirp characteristics of the terahertz wave will directly affect the frequency response, bandwidth response, and intensity response of the terahertz sensor. To enhance the capability of terahertz sensors, it is necessary to control and improve the chirped characteristics of broadband terahertz sources. We generate a chirped terahertz wave via optical rectification in a LiNbO3 prism using the technique of pulse front tilt. The effect of the pump-beam spot size on THz generation is systematically studied. The pump's spot size is manipulated using a telescope system. With a pump spot diameter of 1.8 mm, the scanning spectrum of the THz pulse is narrower and is divided into multiple distinct peaks. In contrast, using a pump spot diameter of 3.7 mm leads to increased efficiency in the generation of THz pulses. Also, we investigate the underlying properties governing the generation of chirped terahertz pulses using varying pump pulse spot diameters.

Identification of feasible regions for managed aquifer recharge in the Republic of Cyprus using a co-participative multi-criteria decision analysis

This study proposes an integrated approach that aims at finding locations which are eligible for Managed Aquifer Recharge (MAR) installation in Cyprus via the active involvement of key stakeholders of MAR-related sectors during all stages of the decision process to ensure the validity of the outcomes. The MAR problem is jointly formulated with the key stakeholders according to the site needs by introducing the so-called "MAR typology" concept, consisting of the recharge objective, the recharge method, and the available water sources. Tertiary-treated wastewater is adapted as the water source, which is recharged in aquifers via recharge ponds for irrigation. Various sources of information have been considered for assessing the degree of feasibility, aggregated in three thematic clusters (feasibility components), namely intrinsic site-suitability, the availability of water resources for MAR purposes, and water demand. Twelve criteria have been selected jointly with key stakeholders to evaluate the feasibility components via a GIS-MCDA process. Seven of these criteria are associated with the intrinsic suitability of a region (aquifer, land-use, and topographical properties), and five criteria are associated with the amount of water available for MAR (characteristics of the water source and evapotranspiration) and the crop irrigation needs. Stakeholder meetings were conducted to determine weights for each criterion and thematic cluster, leading to thematic and feasibility maps. The results demonstrate large discrepancies among the feasibility components in terms of their spatial variation and the location where the most favourable regions are present. Smoother profiles are observed for intrinsic suitability compared to the other thematic layers, partly attributed to the use of a larger number of criteria. Sensitivity analysis demonstrates that the MAR-favourable regions are weakly influenced by the variation of the relevant importance among the thematic layers, being mostly present in the vicinity of the southern and south-eastern coastlines.

Radio U-Net: a convolutional neural network to detect diffuse radio sources in galaxy clusters and beyond

ABSTRACT The forthcoming generation of radio telescope arrays promises significant advancements in sensitivity and resolution, enabling the identification and characterization of many new faint and diffuse radio sources. Conventional manual cataloguing methodologies are anticipated to be insufficient to exploit the capabilities of new radio surveys. Radio interferometric images of diffuse sources present a challenge for image segmentation tasks due to noise, artifacts, and embedded radio sources. In response to these challenges, we introduce Radio U-Net, a fully convolutional neural network based on the U-Net architecture. Radio U-Net is designed to detect faint and extended sources in radio surveys, such as radio haloes, relics, and cosmic web filaments. Radio U-Net was trained on synthetic radio observations built upon cosmological simulations and then tested on a sample of galaxy clusters, where the detection of cluster diffuse radio sources relied on customized data reduction and visual inspection of Low-Frequency Array Two metre Sky Survey (LoTSS) data. The 83 per cent of clusters exhibiting diffuse radio emission were accurately identified, and the segmentation successfully recovered the morphology of the sources even in low-quality images. In a test sample comprising 246 galaxy clusters, we achieved a 73 per cent accuracy rate in distinguishing between clusters with and without diffuse radio emission. Our results establish the applicability of Radio U-Net to extensive radio survey data sets, probing its efficiency on cutting-edge high-performance computing systems. This approach represents an advancement in optimizing the exploitation of forthcoming large radio surveys for scientific exploration.

Source characterization of the 1996 Biak tsunami based on earthquake and landslide scenarios

Source characterization of the 1996 Biak tsunami based on earthquake and landslide scenarios

Seismic source analysis and directivity of the November 2021 Fin doublet earthquake in southern Iran: challenges and findings

Studying the source characteristics of doublet or multiple earthquake sequences presents significant challenges in seismology, especially with short time intervals between events. On November 14, 2021, a doublet earthquake (Mw 6.0 and Mw 6.1) occurred near Fin city, southern Iran, within a span of less than two minutes and 10 km apart. We employed the Kinematic Waveform Inversion (KIWI) procedure to determine the point and extended source parameters of these events, using a multistep inversion approach for stable solutions. Our analysis highlighted the directivity of the earthquakes: the first event exhibited bilateral directivity, causing a rupture area that reached the surface, while the second event showed unilateral westward directivity, supported by waveform amplitude differences observed at various stations. This directivity analysis plays an essential role in seismic hazard studies. Our findings regarding the source parameters of these recent doublet earthquakes in the Fin region align well with regional geological trends and fault patterns. However, retrieving the main fault plane for the second earthquake was challenging due to the complexities of the waveform. Moment tensor decomposition revealed significant non-double-couple components for the second event, indicating the complexity inherent in analyzing doublet events. This study underscores the critical role of precise waveform analysis and robust inversion techniques in understanding complex seismic events.

The Impact of Source Time Function Complexity on Stress-Drop Estimates

ABSTRACT Earthquake stress drop—a key parameter for describing the energetics of earthquake rupture—can be estimated in several different, but theoretically equivalent, ways. However, independent estimates for the same earthquakes sometimes differ significantly. We find that earthquake source complexity plays a significant role in why theoretically (for simple rupture models) equivalent methods produce different estimates. We apply time- and frequency-domain methods to estimate stress drops for real earthquakes in the SCARDEC (Seismic source ChAracteristics Retrieved from DEConvolving teleseismic body waves, Vallée and Douet, 2016) source time function (STF) database and analyze how rupture complexity drives stress-drop estimate discrepancies. Specifically, we identify two complexity metrics—Brune relative energy (BRE) and spectral decay—that parameterize an earthquake’s complexity relative to the standard Brune model and strongly correlate with the estimate discrepancies. We find that the observed systematic magnitude–stress-drop trends may reflect underlying changes in STF complexity, not necessarily trends in actual stress drop. Both the decay and BRE parameters vary systematically with magnitude, but whether this magnitude–complexity relationship is real remains unresolved.

Isolation and characterization of duck sewage source Salmonella phage P6 and antibacterial activity for recombinant endolysin LysP6

Salmonella is a globally prevalent foodborne pathogen, and adverse events caused by S. Enteritidis and S. Typhimurium are extremely common. With the emergence of drug resistance, there is an urgent need for efficient and specific lytic bacteriophages as alternative to antibiotics in clinical practice. In this study, phage P6 was isolated and screened from effluent and fecal samples from duck farm environments to specifically lyse the duck sources S. Typhimurium and S. Enteritidis. Phage P6 belongs to the genus Lederbergvirus, unclassified Lederbergvirus species. The phage P6 genome did not contained non-coding RNA, virulence genes and drug resistance genes, indicating that phage P6 was biologically safe for clinical applications. Phage P6 lysed 77.78% (28/36) of multidrug-resistant Salmonella and reduced biofilms formed by S. Enteritidis CVCC 3377, 4, and 24, and S. Typhimurium 44 by 44% to 75% within 3 h, and decreased Salmonella in duckling feces by up to 1.64 orders of magnitude. Prokaryotic expression of endolysin LysP6 lysed the chloroform-treated bacterial outer membrane from different serotypes of duck-derived Salmonella and E. coli standard strain ATCC 25922. The host range was expanded compared to phage P6, and the growth of Salmonella was effectively inhibited by LysP6 in conjunction with the membrane permeabilizer EDTA within 24 h. Therefore, phage P6 and phage-derived endolysins LysP6 are suitable for application as potent biocontrol agents to improve poultry health and food safety.

Study on the coupling characteristics of laser-TIG hybrid heat source with different offsets

Study on the coupling characteristics of laser-TIG hybrid heat source with different offsets

Machine Learning Methods for Source Characterization of Ambient Ultrafine Particles in an Urban Community

Machine Learning Methods for Source Characterization of Ambient Ultrafine Particles in an Urban Community

Enhanced Kalman filter methods for end pose measurement of parallel kinematic machine considering the error sensitivity

For robust accuracy, this paper proposes a parallel measurement method for parallel kinematic machine (PKM) combining indirect measurement using grating ruler with direct measurement using monocular vision. However, due to differing error sensitivity of two methods, the general Kalman filter (KF) cannot integrate them under the assumption of equal data weighting. Therefore, a novel Enhanced KF data fusion method designed to account for varying data sensitivities is developed.The paper first outlines the principles of parallel measurement approach for PKMs, followed by modeling the error sensitivities associated with each measurement source. Subsequently, an enhanced KF data fusion model is developed, treating these sensitivities as noise, and validated. Compared to the conventional KF method, the root mean squared (RMS) position error is significantly reduced from 0.569 mm to 0.293 mm. This enhanced KF method presents an innovative approach to multi-source data fusion, tailored to the error characteristics of different measurement sources.

Focal mechanics and disaster characteristics of the 2024 M 7.6 Noto Peninsula Earthquake, Japan

On January 1, 2024, a devastating M 7.6 earthquake struck the Noto Peninsula, Ishikawa Prefecture, Japan, resulting in significant casualties and property damage. Utilizing information from the first six days after the earthquake, this article analyzes the seismic source characteristics, disaster situation, and emergency response of this earthquake. The results show: 1) The earthquake rupture was of the thrust type, with aftershock distribution showing a north-east-oriented belt-like feature of 150 km. 2) Global Navigation Satellite System (GNSS) and Interferometric synthetic aperture radar (InSAR), observations detected significant westward to north-westward co-seismic displacement near the epicenter, with the maximum horizontal displacement reaching 1.2 m and the vertical uplift displacement reaching 4 m. A two-segment fault inversion model fits the observational data well. 3) Near the epicenter, large Peak Ground Velocity (PGV) and Peak Ground Acceleration (PGA) were observed, with the maxima reaching 145 cm/s and 2681 gal, respectively, and the intensity reached the highest level 7 on the Japanese (Japan Meteorological Agency, JMA) intensity standard, which is higher than level 10 of the United States Geological Survey (USGS) Modified Mercalli Intensity (MMI) standard. 4) The observation of the very rare multiple strong pulse-like ground motion (PLGM) waveform poses a topic worthy of research in the field of earthquake engineering. 5) As of January 7, the earthquake had left 128 deaths and 560 injuries in Ishikawa Prefecture, with 1305 buildings completely or partially destroyed, and had triggered a chain of disasters including tsunamis, fires, slope failures, and road damage. Finally, this paper summarizes the emergency rescue, information dissemination, and other disaster response and management measures taken in response to this earthquake. This work provides a reference case for carrying out effective responses, and offers lessons for handling similar events in the future.