Probabilistic Hazard Research Articles

Throttle and expansion characteristics of supercritical carbon dioxide during its venting

Supercritical CO2 has important applications in the fields of power cycle generation systems and carbon capture, utilization and storage (CCUS). The venting equipment represents a fundamental pressure-relief method for the purpose of depressurizing sections of those systems for inspection, maintenance or repair. The extremely low temperatures, dry ice blockage and overpressurization will appear in the system due to the throttling and expansion effect during venting. Meanwhile, the released CO2 may cause the exposure for the high density gaseous CO2, solid CO2 particles and cryogenics to the people in the venting area. The study of flow characteristics during CO2 venting is absolutely essential for assessing the hazard probability of dry ice formation and the blockage of relief valves during emergency or routine operational venting. In this paper, the theoretical analysis and experimental tests were conducted to study the throttle and expansion characteristics through the elbow, valve and orifice during straight vertical venting of supercritical CO2 with a 258 m long, 233 mm inner diameter pipeline system. The pressures and temperatures inside the main pipe and vent pipe, and the temperatures near field region were recorded during venting. After the valve was opened, the pressure in the vent pipe rose rapidly, and the rising range decreased with the decrease of the distance from the orifice. The temperature drops of CO2 were obvious after supercritical CO2 passed through the bend, the valve and the orifice. The supercritical CO2 in the main pipe changed into gas-liquid two-phase, and the liquid CO2 were produced in the vent pipe due to the throttling expansion effect. The CO2 temperature near the orifice were in quasi steady state after reaching the lowest value due to the continuous vaporization of liquid-phase CO2 and sublimation of dry ice particles, accompanied by the air entrainment process.

Environmental hazard quantification toolkit based on modular numerical simulations

Abstract. Quantifying impacts on the environment and human health is a critical requirement for geological subsurface utilisation projects. In practice, an easily accessible interface for operators and regulators is needed so that risks can be monitored, managed, and mitigated. The primary goal of this work was to create an environmental hazards quantification toolkit as part of a risk assessment for in-situ coal conversion at two European study areas: the Kardia lignite mine in Greece and the Máza-Váralja hard coal deposit in Hungary, with complex geological settings. A substantial rock volume is extracted during this operation, and a contaminant pool is potentially left behind, which may put the freshwater aquifers and existing infrastructure at the surface at risk. The data-driven, predictive tool is outlined exemplary in this paper for the Kardia contaminant transport model. Three input parameters were varied in a previous scenario analysis: the hydraulic conductivity, as well as the solute dispersivity and retardation coefficient. Numerical models are computationally intensive, so the number of simulations that can be performed for scenario analyses is limited. The presented approach overcomes these limitations by instead using surrogate models to determine the probability and severity of each hazard. Different surrogates based on look-up tables or machine learning algorithms were tested for their simplicity, goodness of fit, and efficiency. The best performing surrogate was then used to develop an interactive dashboard for visualising the hazard probability distributions. The machine learning surrogates performed best on the data with coefficients of determination R2>0.98, and were able to make the predictions quasi-instantaneously. The retardation coefficient was identified as the most influential parameter, which was also visualised using the toolkit dashboard. It showed that the median values for the contaminant concentrations in the nearby aquifer varied by five orders of magnitude depending on whether the lower or upper retardation range was chosen. The flexibility of this approach to update parameter uncertainties as needed can significantly increase the quality of predictions and the value of risk assessments. In principle, this newly developed tool can be used as a basis for similar hazard quantification activities.

Practical workflow for assessment of seismic hazard in low enthalpy geothermal systems

It is of vital importance to be able to determine the seismic hazard in advance of any geothermal operation in the subsurface, especially in a densely populated area such as The Netherlands. The author aims to arrive at a practical assessment of the seismic hazard in low-enthalpy geothermal doublet systems specifically designed for heat exchange in porous and permeable aquifers operated on a volume balance, at a depth range of 1800 to 3300 m having temperatures in the range of 60 °C to 100 °C. The article presents a practical workflow aiming to determine the probability distribution for mechanical re-activation along pre-existing weak faults. After presenting the tectonic structural setting the criticality criterion based on shear mobilisation is introduced. Existing stress models are reviewed and a practical manner to estimate and limit all geomechanical input parameters is presented, including fault mechanical properties. The workflow is demonstrated both for early period operation times and at final thermal breakthrough. The uncertainty is addressed through probabilistic logic tree analysis quantifying the variation of the four most uncertain input parameters: fault cohesion and friction coefficient, the thermal stress parameter and the initial minimum Earth stress. The probabilistic hazard assessment is characterised by four output parameters: the expected value, the probability that unity is exceeded and two more probabilities. In case unity is exceeded the range of fault dips prone to mechanical re-activation is shown. Exceedance of this first necessary condition requires the assessment of the other two necessary conditions: seismogeneity and moment magnitude.Article highlightsThe article presents a practical workflow to assess the seismic hazard associated with geothermal operations.To be able to perform the necessary uncertainty analysis, four main input parameters are treated probabilistic.The first necessary condition for seismicity to occur is characterised by four probabilities: the expected probability, the probability that seismicity can occur and two higher probabilities.

Influence of tidal level on quantifying the probability of nearshore tsunami hazard

Nearshore tsunami hazard can be greatly affected by the tidal level, especially when large tsunami waves meet the high tidal level. This study aims to quantify the probability of the peak nearshore tsunami elevation (PNTE) caused by seismic tsunamis considering the randomness of event occurrence time and the variation of tidal level. The coast around the Pearl River Estuary has been chosen as the study area to show the influence of tidal level on the probability of nearshore tsunami hazard. Two approaches are proposed to calculate the PNTE considering the effect of tide in a probabilistic tsunami assessment framework. One approach is a linear superposition of tsunami wave upon the tidal level, and the other considering the influence of tidal level on tsunami nearshore amplification. The probability of the PNTE along the concern coast is obtained. The results considering the effect of tide show that the PNTE corresponding to short return period is obviously larger than that based on the mean sea level, but no obvious difference in the case of long return period. Moreover, in the study area, the two approaches considering the effect of tide show only slight difference in estimating the probability of PNTE, which suggests the applicability of the linear superposition method in nearshore tsunami hazard assessments.

Optimizing Earthquake Nowcasting With Machine Learning: The Role of Strain Hardening in the Earthquake Cycle.

Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process of determining the uncertain state of the economy, markets or the weather at the current time by indirect means. In this paper, we describe a simple two-parameter data analysis that reveals hidden order in otherwise seemingly chaotic earthquake seismicity. One of these parameters relates to a mechanism of seismic quiescence arising from the physics of strain-hardening of the crust prior to major events. We observe an earthquake cycle associated with major earthquakes in California, similar to what has long been postulated. An estimate of the earthquake hazard revealed by this state variable time series can be optimized by the use of machine learning in the form of the Receiver Operating Characteristic skill score. The ROC skill is used here as a loss function in a supervised learning mode. Our analysis is conducted in the region of 5° ×5° in latitude-longitude centered on Los Angeles, a region which we used in previous papers to build similar time series using more involved methods (Rundle & Donnellan, 2020, https://doi.org/10.1029/2020EA001097; Rundle, Donnellan etal., 2021, https://doi.org/10.1029/2021EA001757; Rundle, Stein etal., 2021, https://doi.org/10.1088/1361-6633/abf893). Here we show that not only does the state variable time series have forecast skill, the associated spatial probability densities have skill as well. In addition, use of the standard ROC and Precision (PPV) metrics allow probabilities of current earthquake hazard to be defined in a simple, straightforward, and rigorous way.

How Urban Expansion Triggers Spatio-Temporal Differentiation of Systemic Risk in Suburban Rural Areas: A Case Study of Tianjin, China

Rapid urban expansion has strongly impacted rural development in China’s suburbs. The increasing probability of socio-ecosystem hazards, such as the shrinking and fragmentation of ecological space, the outflow of labor force, the disintegration of traditional society, and the decline in collective economy has become a systemic risk restricting the sustainable development of rural areas in the suburbs. At present, the influence of urban expansion on rural systemic risk in the suburbs is not clear, which is not conducive to putting forward differentiated and targeted strategies for rural revitalization. Therefore, in this study, we propose the ecological, industrial, social, and livelihood elements of rural systemic risk in the suburbs and construct a multi-dimensional risk resistance analysis framework involving functionality, stability, and sustainability. Taking 93 villages in the western suburbs of Tianjin as an example, and using spatial econometric methods such as remote sensing interpretation, GIS analysis, multiple linear regression, and random forest model testing, we analyze the relationship between external transportation construction, urban employment attraction, construction of land growth, rural risk factors, and the dimension of risk resistance. Finally, the influence of urban expansion on the spatial–temporal differentiation of rural systemic risk and the risk management strategy are discussed. The results show that the difference in the urban expansion intensities is the main factor of the spatial differentiation of rural systemic risk in the suburbs. With the acceleration of the land replacement rate between urban and rural areas, the proportion of urban construction of land is increasing, leading to various degrees of change in the rural land use pattern and the ecological security pattern. Meanwhile, because of the urban employment attraction, part of the rural labor force continues to decrease, leading to the spatial differentiation of rural industrial risks and social risks aggravated. Precise risk management strategies are put forward according to the systemic risks in different types of villages. In villages with a high proportion of urban construction land and inefficient land consolidation, ecological restoration projects should be carried out. For villages severely divided by transit roads, internal spatial connections should be strengthened by constructing public transport. For villages with good accessibility, the allocation of rural non-agricultural industries and service facilities should be strengthened to mitigate the impact of urban expansion on the rural social structure. From the perspective of risk management, the research results will provide a basis for making decisions regarding rural public policymaking and spatial resource allocation in the suburbs of developing countries.

Assessment of various seismic fragility analysis approaches for structures excited by non-stationary stochastic ground motions

A probabilistic assessment is performed using different seismic fragility analysis approaches for structures under non-stationary stochastic ground motions. Four commonly used probabilistic seismic fragility analysis (PSFA) approaches are adopted, which are least squares regression (LSR), maximum likelihood estimation (MLE), kernel density estimation (KDE) and Monte Carlo simulation (MCS). The principles of the four PSFA approaches are first introduced, and the theories of non-stationary stochastic acceleration time series are introduced in light of the spectral representation of random functions. Then an analytical procedure of different PSFA approaches is constructed for structures under non-stationary stochastic motions. After that a case study is carried out to analyze the results of the four PSFA approaches. The demand distributions of univariate random variable under certain intensity measure levels are discussed, and multiple fragility curves under different limit states for all the approaches are compared. In general, the MCS approach is set as the benchmark to verify the effectiveness of other approaches, but it is computationally consuming. The non-parametric KDE approach is recommended to estimate the univariate distribution under specified IM levels, because it can reflect the real distribution characteristics with combined efficiency and accuracy. For the seismic fragility under different limit states, the LSR approach is suitable for efficient data processing and general trend assessment, at the expense of accuracy. The MLE approach indicates a better applicability under a smaller response threshold and slighter damage conditions, while the KDE approach shows a better applicability under a larger response threshold and severer damage conditions. The paper compares the accuracy and applicability of various PSFA approaches under multiple conditions, and provides a basis to link probabilistic hazard and risk analyses for performance assessment in the future research.

Spatial Distribution of Tsunami Hazard Posed by Earthquakes along the Manila Trench

Quantitative probability has been computed for the tsunami hazard posed by earthquakes from the Manila Trench, which has been regarded as a huge threat in the South China Sea. This study provides a spatial distribution of the tsunami hazard covering the affected area with a spatial resolution of 0.1° for disaster prevention of islands and continental coasts. The quantitative probability of the tsunami hazard is computed by an efficient model, which can realize a large amount of potential tsunami scenarios analysis in order to consider the randomness and uncertainty in earthquake magnitude, source location and focal depth. In the model, for each potential tsunami scenario, the occurrence probability of the corresponding earthquake and the intensity of tsunami waves at each target location are computed. The occurrence probability of each scenario is estimated based on the historical earthquake records. Then, the subsequent tsunami caused by each scenario is computed using a new, efficient approach, instead of direct simulation using an ocean dynamics model. A total of 1,380,000 scenarios are computed in order to obtain a stable statistical result. Based on the results, the spatial distribution of the tsunami hazard is discussed and high-hazard regions along the coast have been identified.

Categorizing and Harmonizing Natural, Technological, and Socio-Economic Perils Following the Catastrophe Modeling Paradigm.

The literature on probabilistic hazard and risk assessment shows a rich and wide variety of modeling strategies tailored to specific perils. On one hand, catastrophe (CAT) modeling, a recent professional and scientific discipline, provides a general structure for the quantification of natural (e.g., geological, hydrological, meteorological) and man-made (e.g., terrorist, cyber) catastrophes. On the other hand, peril characteristics and related processes have yet to be categorized and harmonized to enable adequate comparison, limit silo effects, and simplify the implementation of emerging risks. We reviewed the literature for more than 20 perils from the natural, technological, and socio-economic systems to categorize them by following the CAT modeling hazard pipeline: (1) event source → (2) size distribution → (3) intensity footprint. We defined the following categorizations, which are applicable to any type of peril, specifically: (1) point/line/area/track/diffuse source, (2) discrete event/continuous flow, and (3) spatial diffusion (static)/threshold (passive)/sustained propagation (dynamic). We then harmonized the various hazard processes using energy as the common metric, noting that the hazard pipeline’s underlying physical process consists of some energy being transferred from an energy stock (the source), via an event, to the environment (the footprint).

Application of external flood probabilistic safety assessment methodology to Prototype Fast Breeder Reactor

ABSTRACT This paper presents the methodology adopted, accident sequence analysis and salient results from the external flood probabilistic safety analysis exercise for Prototype Fast Breeder Reactor. The major steps performed are the probabilistic hazard estimation, fragility computation, system reliability modelling and risk quantification. The hazard analysis has been performed for rainfall, storm surge and tsunami as typically associated with a coastal site, from which correlation function relating flood level to the annual exceedance frequency is estimated. The fragility analysis of different safety systems is estimated by considering submergence mode of failure using step fragility functions. The secondary effects of flood such as debris impact, load falling and flood-induced sodium fires are not considered. The human reliability analysis of manual operations necessary for plant safety is done for the control room as well as onsite actions. The challenges encountered during the analysis, salient results and uncertainties involved are presented with inferences. Abbreviations: AHX: air heat exchanger; CDF: core damage frequency; EFPSA: external flood probabilistic safety assessment; EL: elevation levels; EOP: emergency operation procedure; ET: event tree; FT: fault tree; HRA: human reliability analysis; IE: initiating events; NPP: nuclear power plant; OGDHRS: operation grade decay heat removal system; PFBR: prototype fast breeder reactor; POT: peak over threshold; PSA: probabilistic safety assessment; PTHA: probabilistic tsunami hazard assessment; RY: reactor year; RCB: reactor containment building; RP: return period; SGDHRS: safety grade decay heat removal system; SSC: structures, systems and components

Hydrological Analysis and Statistical Modelling of Swat River Basin for Flood Risk Assessment

The climatic variations and anthropogenic activities in the river catchments worldwide are causing severe weather events and flooding. The narrowing down of natural floodplains/ channels, land-use changes, deforestation and mushroom urbanisation with unplanned infrastructure development are aggravating causes of severe storms and floods, especially in developing countries. Hydrological studies, flood modelling and statistical flood frequency analysis are considered imperative to assess the hazards/ risks of flooding and their mitigation measures. Estimating predicted storms/ floods for different return periods can give a reasonable idea about the frequency of storm events. This study analysed the Swat river basin to determine the predicted return periods with expected storm/ flood in its catchment and Swat river. The weather and rainfall in the Swat river basin remain unpredictable. Historically, it has seen peak precipitation of 150mm – 274mm and a super flood of 10050 m3/sec in 2010, more than its 200 years return period. Flood frequency and statistical analysis using Log Pearson 3 (LP3), Generalized Extreme Value (GEV) and Gumbel Maximum (Gumb-Max) on Easy Fit software and Log Pearson 3 equations have predicted weather instability in the Swat basin with the prediction of super flood like 2010 happening in 40 years return period. Construction of Swat expressway on elevated embankment will disturb the natural drainage pattern and likely result in inundation in flood plains due to inadequate capacity of cross drainage structures to withstand the spontaneous flash flooding. However, these have been designed on 100 years return period. However, probability density and hazard functions show a lesser probability of any mega hazard; therefore, cross drainage structures and crisscrossing channels in the river catchments may be planned on a minimum 100 years return period as an economic/ reasonable safe limit. Still, additional structural/ non-structural measures should augment these for efficient flood-fighting like plantation and maintenance of drainage structures, construction of small dams/ reservoirs for swift water management in case of a flash flood and placement of rescue/ relief resources at accessible points as per flood zoning.

О формировании научно-методического аппарата для оценки факторов, влияющих на комплексную безопасность предприятий нефтегазового комплекса России

The article presents a formalized model description of the sequence of solving the problem associated with the assessment of the state of the integrated safety system at the enterprises of the oil and gas complex of Russia. The rational variant is substantiated concerning the set of elements (methods, stages, means) included in the content of the scientific and methodological apparatus proposed for use in a certain logical sequence for solving specific problems. Determination of the hazard probability indicator, which is assigned to the activity that became the reason of causing damage from hazard (accident or fire). This allows to consider the integrated safety system not as a limited, closed system, but capable of accumulating new knowledge about the impact of hazards on industrial and fire safety subsystems. Determination of the indicator of the weight coefficient of influence assigned to the event that caused damage from the hazard (accident and fire). Determination of the probability indicator of occurrence of a hazard, which is considered in addition to the weighting coefficient of influence, is used to obtain an a priori estimate of the end events. This allows to speak about the reliability of the research results, which directly depend on the accuracy of the data presentation (taking into account the error) and the adequacy of the methods used (their compliance to achieving goals). At the output, the problem is solved by determining the indicator of the weighting factor of influence assigned to the event that caused the damage from the danger, as well as by determining the indicator of the probability of danger, which is considered in addition to the weighting factor of influence to obtain an a priori assessment of the final events. The use of the proposed approach will allow to take measures in advance to minimize (exclude) the conditions for the occurrence of the considered hazards, as a result, to transfer the management of the safety system of the enterprises of the oil and gas complex of Russia to a new qualitative level.

Risk assessment of Naproxen and Sulfamethoxazole in Aquatic Ecosystem

The development of science and technology has greatly contributed to the extension of human lifespan, resulting in an increase in the number of chronic diseases due to the aging of the population. For that reason, due to the development of new drugs and the use of life-prolonging treatments, the amounts of domestic pharmaceuticals used has increased rapidly, and the amount used to improve the productivity of agricultural and marine products and livestock is also showing a steady increase. In line with this trend, discharge standards for water pollutants have been steadily tightened, but water quality standards for pharmaceutical substances that may be contained in effluent have not yet been clearly established. In this research, we carried out the ecological impact stage test at “Pseudokirchneriella subcapitata”, “Daphina magna” and “Danio rerio’s embryo” for investigated the hazard identification of Naproxen and Sulfamethoxazole on aquatic organisms which is according to the OECD test guidelines. In consequence, we find the E(L)C50 of Naproxen and Sulfamethoxazole are 22.89 mg/l, 100.12 mg/l, 6.63 mg/l, and 0.69 mg/l, 104.21 mg/l, 22.32 mg/l. By these stats, we figure out PNEC of Naproxen and Sulfamethoxazole as 0.0663 mg/l and 0.0069 mg/l. With these results, 0.528 μg/l and 2.017 μg/l is maximum detectable amount about Naproxen and Sulfamethoxazole in government’s research for Young-San rivers in Korea, we figure out hazard quotient about Naproxen and Sulfamethoxazole as 0.0080 and 0.2923. It shows that Naproxen and Sulfamethoxazole has low hazard probability to currently water system in Korea. However, at present, both pharmaceutical substances are managed based on extremely low chronic toxicity values overseas and due to the characteristics of pharmaceutical substances, the amount used is steadily increasing, and it is very difficult to identify the discharge route and prevent discharge into the water system. Also, since various types of harmful substances exist in a mixture in water systems, continuous and regular monitoring is considered necessary, taking into consideration the mixed values of the hazard index for each substance.

Regional prediction and prevention analysis of rockburst hazard based on the Gaussian process for binary classification

Rockburst is a complex dynamic disaster in coal mining and affected by many factors. To accurately predict the rockburst hazard among complex influencing factors, a prediction model of rockburst hazard based on the Gaussian process for binary classification (GPC) was proposed after the identification of the intrinsic relationship between multiple factors of coal mines and rockburst. Through computerized machine learning and integrated intelligent analysis, the non-linear mapping of rockburst hazard and its influencing factors was established. The multi-factor pattern recognition model was constructed using artificial intelligence. The prediction criteria of the rockburst hazard probability and the hazard probability value of the prediction area unit were determined by applying neural network and fuzzy inference methods. In addition, the rockburst hazardous zone was classified, and the corresponding technical scheme for the prevention was put forward. The validity and feasibility of the regional prediction of rockburst hazard based on GPC were verified in the engineering practice. This method is highly targeted and can improve the accuracy and precision of rockburst prediction, thus contributing to the safe and efficient production of coal mines.

A probabilistic hazard and risk assessment of exposure to metals and organohalogens associated with a traditional diet in the Indigenous communities of Eeyou Istchee (northern Quebec, Canada)

Hunting, trapping, and fishing are part of an Indigenous lifestyle in subarctic Canada. However, this lifestyle may be a route of exposure to contaminants and may pose a risk for the people who rely on a subsistence diet. Monte Carlo simulations for the chemical concentration of eight game species and one fish species were carried out by randomly sampling 10,000 samples from the contaminant measures for each species. We then calculated a probabilistic non-carcinogenic hazard quotient or carcinogenic risk values to estimate the human health risk of exposure to contaminants. Of the species examined, ducks were of concern for potential carcinogenic risk. There was a modeled probabilistic 95th-percentile risk associated with the consumption of ducks and polybrominated biphenyl (PBB) congener 153 in boys, women, and men (1.09 × 10−6, 1.57 × 10−6, and 2.17 × 10−6, respectively) and, to a lesser extent, with geese and polychlorinated biphenyl (PCB) congener 153 in men (1.19 × 10−6). Contaminant concentration in the intake rate (food consumption) for PBB congener 153 exposure risk was more important than that for PCB congener 153, where intake rate had greater relevance. The consumption of waterfowl may increase the exposure to organohalogens; however, there are health and wellness benefits associated with the harvesting and consumption of subsistence foods that must also be considered. We recommend follow-up species-specific studies focused on ducks to clarify and elucidate the results in the present study.

Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet

The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA method, we determined the seismic activity parameters and discussed the relationship of ground motion attenuation, the seismic hazard probability, and the horizontal bedrock ground motion acceleration peak value under different transcendence probabilities in this area. The calculation results show that the PSHA method divides the potential source area via specific tectonic scales and detailed tectonic markers, which reduces the scale of the potential source area and better reflects the uneven spatial distribution of seismic activity in the vicinity of Najin. The corrected attenuation relationship is also in line with the actual work requirements and is suitable for earthquake risk analysis. In addition, the major influences on the peak acceleration of ground motion in the study area are mainly in the potential source areas of Qushui (M7.5), Dangxiong (M8.5), and Kangma (M7.5). The peak horizontal ground motion acceleration (PGA) with a transcendence probability of 10% in 50 years is 185.9 cm/s2, and that with a transcendence probability of 2% in 50 years is 265.9 cm/s2.

Research on b Value Estimation Based on Apparent Amplitude-Frequency Distribution in Rock Acoustic Emission Tests

The rock acoustic emission (AE) technique has often been used to study rock destruction properties and has also been considered an important measure for simulating earthquake foreshock sequences. Among them, the AE b value is an essential parameter for the size distribution characteristics and probabilistic hazard analysis of rock fractures. Variations in b values obtained in rock AE tests and earthquakes are often compared to establish analogies in the damage process and precursory analysis. Nevertheless, because the amplitudes measured on the sample boundary by an acoustic sensor (apparent amplitude) are often used to estimate the b value, which cannot descript the source size distribution, it is necessary to develop a method to obtain the size distribution characteristics of the real source from the apparent amplitude in doubly truncated distribution. In this study, we obtain AE apparent amplitudes by applying an attenuation operator to source amplitudes generated by a computer with an underlying exponential distribution and then use these simulated apparent amplitudes to perform a comparative analysis of various b value estimation methods that are used in earthquakes and propose an optimal b value estimation procedure for rock AE tests through apparent amplitudes. To further verify the reliability of the newly proposed procedure, a b value characteristics analysis was carried out on a non-explosive expansion agent rock AE test and transparent refractive index experiment with red sandstone, marble, granite, and limestone. The results indicate that mineral grains of different sizes and compositions and different types of discontinuities of rock specimens determine the rock fracture characteristics, as well as the b value. The dynamic b values decreased linearly during the loading process, which confirms that variations in the b value also depend on the stress. These results indicate that the newly proposed procedure for estimating the b value in rock AE tests based on apparent amplitudes has high reliability.

Earthquake-induced liquefaction hazard mapping at national-scale in Australia using deep learning techniques

Australia is a relatively stable continental region but not tectonically inert, having geological conditions that are susceptible to liquefaction when subjected to earthquake ground motion. Liquefaction hazard assessment for Australia was conducted because no Australian liquefaction maps that are based on modern AI techniques are currently available. In this study, several conditioning factors including Shear wave velocity (Vs30), clay content, soil water content, soil bulk density, soil thickness, soil pH, distance from river, slope and elevation were considered to estimate the liquefaction potential index (LPI). By considering the Probabilistic Seismic Hazard Assessment (PSHA) technique, peak ground acceleration (PGA) was derived for 50 yrs period (500 and 2500 yrs return period) in Australia. Firstly, liquefaction hazard index (LHI) (effects based on the size and depth of the liquefiable areas) was estimated by considering the LPI along with the 2% and 10% exceedance probability of earthquake hazard. Secondly, ground acceleration data from the Geoscience Australia projecting 2% and 10% exceedance rate of PGA for 50 yrs were used in this study to produce earthquake induced soil liquefaction hazard maps. Thirdly, deep neural networks (DNNs) were also exerted to estimate liquefaction hazard that can be reported as liquefaction hazard base maps for Australia with an accuracy of 94% and 93%, respectively. As per the results, very-high liquefaction hazard can be observed in Western and Southern Australia including some parts of Victoria. This research is the first ever country-scale study to be considered for soil liquefaction hazard in Australia using geospatial information in association with PSHA and deep learning techniques. This study used an earthquake design magnitude threshold of Mw 6 using the source model characterization. The resulting maps present the earthquake-triggered liquefaction hazard and are intending to establish a conceptual structure to guide more detailed investigations as may be required in the future. The limitations of deep learning models are complex and require huge data, knowledge on topology, parameters, and training method whereas PSHA follows few assumptions. The advantages deal with the reusability of model codes and its transferability to other similar study areas. This research aims to support stakeholders’ on decision making for infrastructure investment, emergency planning and prioritisation of post-earthquake reconstruction projects.

An approach for quantifying nearshore tsunami height probability and its application to the Pearl River Estuary

This study focuses on the coast around the Pearl River Estuary, and assesses tsunami hazard posed by the earthquakes along the Manila Trench. A probabilistic tsunami hazard assessment (PTHA) has been conducted based on 1,380,000 potential earthquake scenarios, in order to consider the uncertainty of seismic parameters as much as possible. To achieve such a large number of scenario simulations, the tsunami at an offshore position is firstly simulated based on a superposition approach proposed in previous studies, and then the joint probability density of incident tsunami period and height at the offshore position is obtained. After that, an amplification factor is adopted to estimate nearshore tsunami height probability from the offshore position. The amplification factor is the main concern in this study. It is commonly estimated from the Green’ law based on the linear wave shoaling theory, which is a simple and effective way. However, it may loss accuracy in the coast with complicate topography and tortuous shoreline. This study numerically obtained a dataset of wave amplification factors along the concerned coast, using the two-dimensional FUNWAVE-TVD model based on the Boussinesq equations. The results confirm the significance of incident wave period and height on the amplification factor, and suggest a more carefully estimation on the amplification factor should be taken into consideration. Based the newly obtained dataset of wave amplification factors, the quantified tsunami hazard probability along the concerned coast is given.

Creating a Communication Framework for FACETs: How Probabilistic Hazard Information Affected Warning Operations in NOAA’s Hazardous Weather Testbed

Abstract Scientists at NOAA are testing a new tool that allows forecasters to communicate estimated probabilities of severe hazards (tornadoes, severe wind, and hail) as part of the Forecasting a Continuum of Environmental Threats (FACETs) framework. In this study, we employ the embedded systems theory (EST)—a communication framework that analyzes small group workplace practices as products of group, organizational, and local dynamics—to understand how probabilistic hazard information (PHI) is produced and negotiated among multiple NWS weather forecast offices in an experimental setting. Gathering feedback from NWS meteorologists who participated in the 2020 Hazard Services (HS)-PHI Interoffice Collaboration experiment, we explored implications of local and interoffice collaboration while using this experimental tool. By using a qualitative thematic analysis, it was found that differing probability thresholds, forecasting styles, social dynamics, and workload will be social factors that developers should consider as they bring PHI toward operational readiness. Warning operations in this new paradigm were also implemented into the EST model to create a communication ecosystem for future weather hazard communication research. Significance Statement Meteorologists are currently exploring how to use probabilities to communicate life-saving information. From tornadoes to hail, a new type of probabilistic hazard information could fundamentally change the way that NWS meteorologists collaborate with one another when issuing weather products, especially near and along the boundaries of County Warning Areas. To explore potential collaboration challenges and solutions, we applied a communication framework and explored perceptions that NWS meteorologists had while using this new tool in an experimental setting. NWS meteorologists expressed that differing ways of communicating hazard information between each office, along with forecasting styles and workload, would change the way they go about producing critical hazard information to the public.