Hazard Evaluation Research Articles

Rockburst Hazard Evaluation Using an Extended COPRAS Method with Interval-Valued Fuzzy Information

Rockburst is a major disaster in deep mining engineering, which can cause serious injury, death and economic losses. This study aims to solve rockburst hazard evaluation problems and determine the hazard levels of mines under uncertain circumstances. To this end, a novel multicriteria decision-making (MCDM) method was proposed in an interval-valued fuzzy context. The main contributions are three-fold. First, considering the heterogeneity of rock masses and the complexity of mining engineering, interval-valued fuzzy numbers (IVFNs) were adopted to express initial indicator information. Second, accounting for the uncertainty of indicator weights, the decision-making trial and evaluation laboratory (DEMATEL) and entropy methods were extended with IVFNs to determine fuzzy indicator weights comprehensively. Third, the complex proportional assessment (COPRAS) approach was extended with IVFNs to determine the rockburst hazard level. Finally, the proposed method was applied to evaluate rockburst hazards in the Jiaojia gold mine, and the ranking results were consistent with field status. Meanwhile, sensitivity and comparison analyses were performed to reveal the stability and effectiveness of the proposed method. The results indicated that the extended COPRAS method was reliable for rockburst hazard evaluation in deep mining engineering.

COASTAL VULNERABILITY ASSESSMENT OF THE FRENCH MEDITERRANEAN COASTS TO STORMS FLOODING AND EROSION PHENOMENA, AND MORPHODYNAMIC MODELING UNDER CLIMATE CHANGE PROJECTIONS

Storm events on sandy coastal environments already weakened by a sediment deficit can generate a strong erosion of the beach-dune system, accentuating the phenomena of marine flooding and damage to infrastructures. In order to assess this risk of coastal flooding under stormy conditions and taking into account climate change and the new IPCC projection (IPCC, 2021), modeling approaches nowadays provide a robust tool. In this study, a modeling chain is used to simulate present-day and future coastal hazards on the Mediterranean French coastline, taking into account the complex interaction of hydrodynamic and morphodynamic phenomena. In order to build a regional strategy for the evaluation of the coastal hazards under storm events, a methodology is proposed to evaluate the reality of a potential increase of coastal flooding following dune/beach erosion and to identify the concerned coastal regions for prioritizing regional coastal zone management actions.

Biases and Skill of Four Two-Moment Bulk Microphysics Schemes in Convection-Allowing Forecasts for the 2018 Hazardous Weather Testbed Spring Forecasting Experiment Period

Abstract A proof-of-concept systematic evaluation of convective hazards is applied to short-term (1–6 h) forecasts using the Morrison, National Severe Storms Laboratory (NSSL), Predicted Particle Properties (P3), and Thompson two-moment microphysics schemes for the 2018 NOAA Hazardous Weather Testbed Spring Forecasting Experiment (HWT SFE) period (hereafter “MORR,” “NSSL,” “P3,” and “THOM” experiments, respectively). Four convective line cases are highlighted to elaborate on relative experiment biases/skill. Composite reflectivity and 1-h accumulated precipitation are examined to determine storm coverage/precipitation biases/skill utilizing point-based verification with a neighborhood. Simulated 1–6-km updraft helicity and observed 3–6-km azimuthal shear and MESH are examined to consider simulated rotation and hail core prediction with object-based scores. Over the full season, MORR displays little overall storm coverage bias relative to NSSL, P3, and THOM underprediction. The equitable threat score (ETS) and fractions skill score (FSS) of P3 are lower than the other experiments. P3 and THOM underpredict convective regions with intense reflectivity relative to MORR and NSSL overprediction. All experiments underpredict precipitation amounts. P3 light precipitation FSS is lower than other experiments. Rotation object verification exhibits sensitivity to microphysics experiments, as microphysics has an indirect influence on storm dynamics. While P3 has the largest hail object underprediction, all experiments grossly overpredict the number of hail objects in convective line cases despite forecast objects defined with the same product (MESH) and threshold as observations. The importance of microphysics ice parameterization and ongoing scheme updates highlight the need to apply this verification framework to optimal/updated schemes before optimizing ensemble design.

Safety Measures and Risk Assessment of High Powered Motor Rocket

High powered motor rockets are used for various professional and semi-professional applications like high altitude research, payload delivery, education and outreach. For successful practices of these applications various safety measures, regulations and restrictions are considered. This research paper delves into the crucial aspects of safety measures and risk assessment associated with high-powered motor rockets, aiming to provide a comprehensive understanding of the best practices and strategies for ensuring safe launches and operations. The study begins by analyzing the inherent risks associated with high powered motor rockets following up with hazard identification, risk analysis and evaluation along with their mitigation strategies and emergency response planning. Subsequently, the research delves into current safety standards and regulations governing high-powered motor rockets at the national and international levels, we have also taken an account of the design considerations, their manufacturing and quality control processes for high powered motor rockets. This paper also presents the analysis of successful rocket launches with identification of common practices and techniques along with the key factors that made them successful. Moreover, the research identifies advanced technological innovations for risk management and safety measures of high powered motor rockets. In conclusion, this research paper emphasizes the paramount importance of a comprehensive safety culture surrounding high-powered motor rockets. It consolidates essential safety guidelines and risk assessment frameworks to promote responsible and secure rocket launches. KEY WORDS: Payload, High altitude, Mitigation strategies, Hazard identification, Innovations.

Comparing Gardner-Knopoff, Gruenthal, and Uhrhammer Earthquake Declustering Methods in Aceh, Indonesia

The sudden release of energy from inside the earth, which generates seismic waves, causes earthquakes on the earth’s surface. Foreshock, mainshock, and aftershock are terms commonly used in this subject. These phrases refer to the three stages of an earthquake event—before the main event, the primary event, and after the main event. The earthquake data catalogue, however, typically does not distinguish between mainshock data and foreshocks/aftershocks. For seismic-related studies, justifying the mainshock is very crucial. There are several methods for separating the mainshock of earthquake data from the foreshocks/aftershocks. This study employs three declustering techniques, including Gardner-Knopoff (1974), Gruenthal, and Uhrhammer (1986). The present study collected and analyzed 3543 earthquake events from 1971 to 2021 for Aceh region. In order to determine which method provides the highest a-value and b-value outcomes for Aceh’s seismicity conditions, this study compares the aforementioned three approaches. The Uhrhammer method (1986) has an a-value of 5.82, a b-value of 1.05, 1893 main shock events, 305 clusters, and 3.3 percent of the total seismic moment generated at that location are the findings from this study. According to the Gruenthal method, the results had an a-value of 4.53, a b-value of 0.823, 776 mainshock events, 304 clusters, and released 1.3 percent of the total seismic moment at that location. a-value of 5.1, b-value of 0.929, 1097 main shock events, 319 clusters, and a release of 1.08 percent of the total seismic moment at that location were the results of the Gardner-Knopoff method (1974). For seismic hazard evaluation with the highest level of risk, the Uhrhammer (1986) technique is appropriate. The Gruenthal approach is suggested for more conservative cases.

INFLUENCE OF DIGITAL ELEVATION MODEL RESOLUTION ON MAPPING TERRITORY SUSCEPTIBILITY TO LANDSLIDE DEVELOPMENT

Link for citation: Van B. Duong, Fomenko I.K., Duc T. Ta, Trung K. Nguyen, Zerkal O.V., Gorobtsov D.N., Hong D. Vu. Influence of digital elevation model resolution on mapping territory susceptibility to landslide development. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 164-181. In Rus. The relevance. Landslides are one of the most hazardous natural disasters in the world, causing significant economic damage and human deaths. For 20 years (1995–2014), 3876 landslides killed 163658 people and injured 11689 people, as reported by the U. Haque study (2019), based on the data from 128 countries. Excluding events triggered by earthquakes, the total number of fatal landslides from 2004 to 2016 was 4862, and most landslides (75 %) occurred in Asia. In Vietnam, particularly in the northern mountainous regions, landslides frequently caused considerable losses of life and property. The systematic evaluation of landslide hazards is a crucial component of Vietnam's disaster prevention strategy. The main aim of this study is to assess the landslide susceptibility of the Batxat district, Laocai province (Vietnam), using four digital elevation model resolutions (10, 30, 40, and 60 m) and nine landslide causative factors: slope aspect, elevation, slope, distance to roads, distance to faults, distance to drainage, average monthly precipitation, land use, and weathering crust. Object of the study is the landslide susceptibility in Batxat district, Laocai province, Vietnam. Methods: Certainty Factor method, fractal method. Results. The performed analyses indicated a statistically significant relationship between the distribution of landslides and the landslide causative factors in the study area. As a result, the territory was divided into five zones according to its susceptibility to the landslide process: very low, low, moderate, high, and very high. The very low landslide susceptibility zone is less than 10 % of the study area, while the very high susceptibility zone varies from 14,95 to 18,32 %, depending on the digital elevation model spatial resolution. Analysis of the Receiver Operating Characteristics curve revealed that all models, independent of digital elevation model resolution, have good prediction efficiency, with the area under the receiver operating characteristic curve over 70 %. In addition, the Receiver operating characteristic and fractal analysis results indicated that the model with a digital elevation model spatial resolution of 60 m has the highest accuracy. This significant conclusion may be explained by the fact that the accuracy of the landslide susceptibility assessment result is dependent not only on the digital elevation model resolution but also on the ratio of the digital elevation model resolution and the average area of landslides in the study area. This conclusion proves that it is necessary to depict landslide locations and their detailed morphological characteristics on the landslide inventory maps.

Deaggregation of probabilistic seismic hazard results for some selected cities in Western Mexico

ABSTRACT Here we present a deaggregation appraisal conducted for 15 selected significant cities in Western Mexico, for four oscillation periods (PGA, SA (0.2 s), SA (1.0 s), and SA (2.0 s)), also considering a different input for the soil condition (for B, B/C and C NEHRP site classes), and for two return periods (475 and 975 years). This study is based on a previous complete recently published seismic hazard evaluation for the region. An area source model consisting of thirty-seven seismic sources has been used alternatively in a logic tree with a spatially smoothed seismicity model for the same region. The obtained hazard deaggregation results prove that for most of the studied cities –those located along the Pacific coast–, nearby seismic sources are contributing most to the seismic hazard at the studied location, especially for lower periods (PGA and SA (0.2 s)). However, for a few cities far from the Middle America Trench, distant large-magnitude earthquakes contribute more to the seismic hazard, especially at larger spectral periods (SA (1.0 s) and SA (2.0 s)). Additionally, this study shows that the differences in the soil conditions for the computed return periods, have a little influence on the obtained deaggregation results.

Risk assessment framework for microplastic in marine environments

Constantly raising microplastic (MP) contamination of water sources poses a direct threat to the gentle balance of the marine environment. This study focuses on a multifactor hazard evaluation of conventional (polyethylene - PE, polypropylene - PP, and polystyrene - PS) and alternative (polyethylene terephthalate with 25 % or 50 % recycled material and polylactic acid) plastics. The risk assessment framework explored included MP abundance, water acidification potential, surface oxidation, fragmentation, and bacterial growth inhibition. Based on MP monitoring campaigns worldwide, we conclude that PE-based plastics are the most abundant MPs in water samples (comprise up to 82 % the MP in those samples). A year-long weathering experiment showed that PS-based and PP-based plastics were oxidized to a higher extent, resulting in the highest water acidification with pH reduction of up to three orders of magnitude. Finally, our laboratory experiments showed that weathered PS was the most fragile plastic during mechanical degradation, while both PP- and PS-based plastic extracts showed a significant growth inhibition toward the marine microorganisms (Bacillus sp. and Pseudoaltermonas sp). Using the examined factors as weighted inputs into our framework, this holistic evaluation of hazards suggest that PP-based plastic products were the most hazardous compared to the other conventional and alternative plastic types.

A review on radionuclide pollution in global soils with environmental and health hazards evaluation.

Human populations are being exposed to a wide spectrum of radiation from soils as a result of the availability of radiation sources. Assessing the ecological and health effects of radionuclides in soils is crucial to support the optimal soil management practices but large-scale studies are limited. This study compiled data on radionuclides (226Ra, 232Th, 40K, 238U, and 137Cs) in soils located across the world (44 countries and 159 places) between 2008 and 2022 and applied radiological hazards indices and several multivariate statistical approaches. The average activity concentration (Bq/kg) of 226Ra, 232Th, 40K, 238U, and 137Cs were 408.56, 144.80, 508.78, 532.78, and 83.12, respectively, whereas 226Ra, 232Th, 40K, and 238U exceeded the standard limits. The principal component analysis explained more than 91% of variation in soils. Based on the geoaccumulation index, 40K posed moderately to heavy contamination whereas 238U and 226Ra posed moderate contamination in soils. Moreover, the mean values of radiological hazards evaluation such as radium equivalent activity (487.17Bq/kg), external radiation hazard indices (1.32), internal hazard indices (2.15), absorbed dose rate (247.86 nGyh-1), annual effective dose rate (1.82 mSvy-1), activity utilization index (4.54) and excess lifetime cancer risk (63.84 × 10-4) were higher than recommended limit suggesting significant radiological risks in study region soils. The findings indicated that the study area soils were contaminated by radionuclides and unsafe for hazards in terms of the health risks linked with studied radioactive contents. The study is valuable for mapping radioactivity across the globe to determine the level of radioactivity hazards.

Projected Changes in Spawning Ground Distribution of Mature Albacore Tuna in the Indian Ocean under Various Global Climate Change Scenarios

The present study utilised a geometric mean model in which sea surface temperature, oxygen, and sea surface salinity were used to predict the effects of climate change on the habitats of mature albacore tuna in the Indian Ocean under multiple representative concentration pathway (RCP) scenarios. Data pertaining to the albacore tuna fishing conducted by Taiwanese longline fisheries during the October–March period in 1998–2016 were analysed. The fishery data comprised fishing location (latitude and longitude), fishing effort (number of hooks used), number of catches, fishing time (month and year), and fish weight. Nominal catch per unit effort data were standardised to mitigate the potential effects of temporal and spatial factors in causing bias and overestimation. The Habitat Suitability Index (HSI) scores of potential habitats for mature albacore in the Indian Ocean are predicted to change considerably in response to varying levels of predicted climate change. Under projected warm climate conditions (RCP 8.5), the stratification of water is predicted to cause low HSI areas to expand and potential habitats for mature albacore to shift southward by 2100. The findings derived from these mature albacore habitat forecasts can contribute to the evaluation of potential hazards and feasible adaptation measures for albacore fishery resources in the context of climate change. The distribution trends pertaining to potential habitats for mature albacore should be used with caution and can provide resource stakeholders with guidance for decision-making.

Evaluation of radiological hazards in lower zab river sediments

In this study, the activity concentrations of natural and artificial radionuclides in 18 sediment samples were investigated from Iraq’s Upper and Lower Dukan Dam using the high-purity germanium (HPGe) detector as a gamma-ray spectrometry technique. The results revealed that the values of the activity concentration of 226Ra, 232Th, 40K, and 137Cs sediment ranged from (2.85–24.60 Bq kg−1), (1.27–7.56 Bq kg−1), (42.14–346.60 Bq kg−1), and (0.14–3.62 Bq kg−1), respectively. The radiological risk parameters such as radium equivalent activity, absorbed dose rate, annual effective dose equivalent, and external hazard index were determined and found to be 30.98 Bq kg−1, 14.97 nGy h−1, 29.62 nGy h−1, 0.019 mSv y−1, 0.153 mSv y−1, 0.08, and 0.11, respectively. The observed mean values were comparable to internationally recommended values. The field dose rates were measured using the RIIDEye Handheld Radiation Isotope Identifier, and the range was 23.5 nsv h−1–80.6 nsv h−1. The data obtained in this study can be used as a baseline for future investigations of radioactivity background in the investigated area.

River widening in mountain and foothill areas during floods: Insights from a meta-analysis of 51 European Rivers

River widening, defined as a lateral expansion of the channel, is a critical process that maintains fluvial ecosystems and is part of the regular functioning of rivers. However, in areas with high population density, channel widening can cause damage during floods. Therefore, for effective flood risk management it is essential to identify river reaches where abrupt channel widening may occur. Despite numerous efforts to predict channel widening, most studies have been limited to single rivers and single flood events, which may not be representative of other conditions. Moreover, a multi-catchment scale approach that covers various settings and flood magnitudes has been lacking. In this study, we fill this gap by compiling a large database comprising 1564 river reaches in several mountain regions in Europe affected by floods of varying magnitudes in the last six decades. By applying a meta-analysis, we aimed to identify the types of floods responsible for more extensive widening, the river reach types where intense widening is more likely to occur, and the hydraulic and morphological variables that explain widening and can aid in predicting widening. Our analysis revealed seven groups of reaches with significantly different responses to floods regarding width ratios (i.e., the ratio between channel width after and before a flood). Among these groups, the river reaches located in the Mediterranean region and affected by extreme floods triggered by short and intense precipitation events showed significantly larger widening than other river reaches in other regions. Additionally, the meta-analysis confirmed valley confinement as a critical morphological variable that controls channel widening but showed that it is not the only controlling factor. We proposed new statistical models to identify river reaches prone to widening, estimate potential channel width after a flood, and compute upper bound width ratios. These findings can inform flood hazard evaluations and the design of mitigation measures.

An integrated model for occupational health and safety risk assessment based on probabilistic linguistic information and social network consensus analysis

As a critical activity in occupational risk management, the occupational health and safety risk assessment (OHSRA) aims at assessing occupational hazards in the workplace and prioritizing them to ensure employees’ safety and reduce occupational risk to an acceptable level. In this paper, we develop a new integrated OHSRA model for the risk evaluation and prioritization of occupational hazards based on probabilistic linguistic information and social network consensus analysis. The probabilistic linguistic term sets are applied to handle the hesitant risk evaluations of occupational hazards provided by experts. A combinative distance-based assessment technique is introduced for determining the risk priority of the identified occupational hazards. Additionally, the social network consensus analysis with minimum adjustment distance is used to help individual experts reach consensus. Finally, a healthcare case study is implemented for illustrating the developed OHSRA model and its effectiveness is validated with a sensitivity analysis and a comparative analysis.

Brain‐regulated learning for classifying on‐site hazards with small datasets

AbstractMachine vision technologies have the potential to revolutionize hazard inspection, but training machine learning models requires large labeled datasets and is susceptible to biases. The lack of robust perception capabilities in machine vision systems for construction hazard inspection poses significant safety concerns. To address this, we propose a novel method that leverages human knowledge extracted from electroencephalogram (EEG) recordings to enhance machine vision through transfer learning. By pretraining convolutional neural networks with EEG data recorded during construction hazard evaluations, we investigated three common on‐site hazard classifications using small datasets. Our results demonstrated that the proposed method resulted in improved accuracy (with an 11% increase) and enhanced rationality of machine learning predictions (as revealed by network visualization analysis). This research opens avenues for further exploration and industry applications, aiming to achieve more intelligent and human‐like artificial visual perception, ultimately enhancing safety and efficiency in automated hazard inspection.

Health and safety challenges in medical entities and the powers of the social labor inspector: Lessons related to the COVID-19 outbreak in the context of internal control of employee health and safety

Employees in the medical profession in a situation where the life of a patient is at risk cannot refrain from working due to unsafe working conditions. Therefore, enforcing the right to safe and hygienic working conditions is particularly important so that employees can provide health care services without additional burdens. The purpose of the study is to determine how the social labour inspector can respond to Occupational Health and Safety (OHS) hazards and whether the current powers of the social labor inspectorate as the employer's internal OHS control body are sufficient. The study conducted a regulatory analysis and used relevant literature, including recent studies on law enforcement. In addition, a questionnaire survey was conducted among trade union representatives of medical professionals on the evaluation of social labour inspector activities and OHS hazards during the COVID-19 epidemic period. In this period characterized by many OHS risks in medical entities, the difficulties faced by employers in carrying out their duty to protect the health of their employees became apparent. The system of internal control with the participation of the social labour inspection in this context needs changes, due to the fact that it is used in an inefficient manner. The reasons for this are primarily incomplete legal regulations. The legislator should guarantee the social labour inspector the right to use both methods of rewarding the employer as an incentive for the proper performance of duties and measures to deter violations of the law. Despite the fact that Polish labour law guarantees mechanisms for OHS control by the social labour inspector, it would be appropriate to expand the catalog of measures used by him to effectively motivate employers to protect worker health. This study is a prelude to a broader discussion of OHS monitoring in the context of OHS hazards occurring in healthcare entities. Med Pr Work Health Saf. 2023;74(4):301-16.

Preliminary Results from a Dense Short-Period Seismic Deployment around the Source Zone of the 1886 M 7 South Carolina Earthquake

Abstract The 1886 magnitude ∼7 Summerville, South Carolina, earthquake was the largest recorded on the east coast of the United States. A better understanding of this earthquake would allow for an improved evaluation of the intraplate seismic hazard in this region. However, its source fault structure remains unclear. Starting in May 2021, a temporary 19-station short-period seismic network was deployed in the Summerville region. Here, we present our scientific motivation, station geometry, and quality of the recorded seismic data. We also show preliminary results of microearthquake detections and relocations using recordings from both our temporary and four permanent stations in the region. Starting with 52 template events, including two magnitude ∼3 events on 27 September 2021, we perform a matched filter detection with the one year of continuous data, resulting in a catalog of 181 total events. We then determine precise relative locations of a portion of these events using differential travel-time relocation methods, and compare the results with relocation results of 269 events from a previous seismic deployment in 2011–2012. We also determine focal mechanism solutions for three events from 27 September 2021 with magnitudes 2.0, 3.1, and 3.3, and infer their fault planes. Our relocation results show a south-striking west-dipping zone in the southern seismicity cluster, which is consistent with the thrust focal mechanism of the magnitude 3.3 earthquake on 27 September 2021 and results from the previous study based on the temporary deployment in 2011–2012. In comparison, the magnitudes 3.1 and 2.0 events likely occur on a north–south-striking right-lateral strike-slip fault further north, indicating complex patterns of stress and faulting styles in the region.

Comparison between Machine Learning and Physical Models Applied to the Evaluation of Co-Seismic Landslide Hazard

A comparative methodology between advanced statistical tools and physical-based methods is carried out to ensure their reliability and objectivity for the evaluation of co-seismic landslide hazard maps. To do this, an inventory of landslides induced by the 2011 Lorca earthquake is used to highlight the usefulness of these methods to improve earthquake-induced landslide hazard analyses. Various statistical models, such as logistic regression, random forest, artificial neural network, and support vector machine, have been employed for co-seismic landslide susceptibility mapping. The results demonstrate that machine learning techniques using principal components (especially, artificial neural network and support vector machine) yield better results compared to other models. In particular, random forest shows poor results. Artificial neural network and support vector machine approaches are compared to the results of physical-based methods in the same area, suggesting that machine learning methods can provide better results for developing co-seismic landslide susceptibility maps. The application of different advanced statistical models shows the need for validation with an actual inventory of co-seismic landslides to ensure reliability and objectivity. In addition, statistical methods require a great amount of data. The results establish effective land planning and hazard management strategies in seismic areas to minimize the damage of future co-seismic landslides.

Hazard evaluation and safety assessment for subsea HIPPS

AbstractThe safety practice of depressurization of pipelines by flare system in the hydrocarbon industry is not sufficient for pipelines in the subsea production process. There are many challenges in the subsea production process due to multiphase fluid flow. Failure of a process to arrive at its safe state could result in fatality, significant property damage, and can lead to a disastrous environment. The safe state of a process is identified through the consequence of hazard and risk assessments at critical modes of operations. A well‐designed safety instrumented function (SIF) can prevent escalation of minor malfunction into an accident. The prime objective of this work is to obtain the required safety integrity level (SIL) for subsea High Integrity Pressure Protection System (HIPPS). Based on hazard assessment (HAZOP) and risk assessment (LOPA), SIL for SIF is recommended, and finally through reliability calculations, the SIL for subsea HIPPS is determined.

Evaluation of radioactivity levels and radiological hazards of some endemic plants used as medicine in Ankara, Turkey

In this study, natural radioactivity levels (226Ra, 232Th, and 4 K) of some medicinal plant samples with known anti-oxidative properties, which are frequently consumed by animals and humans, were obtained from Ankara province and its surroundings (Mamak, Kızılcahamam, Beypazarı, Kahramankazan, and Polatlı districts) were determined using a thallium-doped sodium iodide NaI(Tl) gamma spectrometry. By using the determined natural radioactivity concentrations in the collected plant samples, the number of radiological doses that people could be exposed by consuming these plants was calculated. As a result of the study, 226Ra, 232Th, and 4 K radioactivity concentration ranges of the plant samples were found be 14.69 ± 1.27–59.08 ± 3.12 Bq kg−1, 1.78 ± 0.04–50.05 ± 2.76 Bq kg−1 and 207.24 ± 34.09–826.13 ± 25.40 Bq kg−1, respectively. The highest 226Ra, 232Th, and 4 K activity concentrations were measured in Astragalus densifolius subsp. ayashensis (Kahramankazan), Astragalus kochakii (Kahramankazan) and Rumex patientia (Patience Dock) (Kahramankazan) plants, respectively. The lowest 226Ra, 232Th and,4 K activity concentration plants were determined respectively as Rumex patientia (Mamak), Lavandula angustifolia (Kızılcahamam), and Astragalus acikirensis (Polatlı). The establishment and routine repetition of environmental radioactivity monitoring programs in each region are important for human and animal health, and the results of this study gain importance for Ankara and its surroundings in terms of environmental health.

An optimal step-size simulation framework for large-scale heat-electric integrated energy system considering fault states

Dynamic simulation plays a crucial role in the development of integrated energy systems, which are typically governed by a set of partial differential equations. The selection of an appropriate simulation step-size is essential for balancing the accuracy and speed of the system simulation. However, determining the optimal simulation step-size is challenging, particularly for large-scale and fault-state systems. To address this issue, this paper proposes a novel approach for determining the optimal step-size in simulations of large-scale systems and fault-state systems. Firstly, an iteration simulation approach and a multi-step-size simulation framework are introduced to accelerate the simulation of large-scale systems without compromising accuracy. Additionally, a fault hazard evaluation model and a fault-state system variable-step-size simulation framework are developed to ensure accurate simulation results for fault-state systems. To validate the proposed methodology, comprehensive analyses are conducted on different scenarios using a 4536-node and a 38-node testbed. The results demonstrate that the proposed large-scale system simulation strategy reduces simulation time by 69.1%, while the fault-state simulation approach improves simulation accuracy by 61.99%.