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Abstract AP1000® Generation III+ reactor bases its safety concept on passive systems, differently from the previous Generation II reactors. This fact has led the approximations and methodologies previously used for modeling active safety systems to be reviewed and adapted to simulate the physics of passive systems. Diverse studies about the AP1000 containment have demonstrated the difficulty to correctly model the occurring phenomenology. In this paper, an integral AP1000 3D containment GOTHIC model is presented, including the Passive Containment Cooling System (PCCS). The model includes the compartments inside and outside the metallic containment liner that influence the thermal–hydraulic behavior. The model is tested against a Large Break Loss of Coolant Accident (LBLOCA) to assess its thermal–hydraulic performance, assuming a PCS tank malfunction, what is a conservative hypothesis. The pressure and temperature evolution predicted by the 3D containment model is analyzed and compared with a single node Lumped Parameters model, allowing to evaluate some preliminary benefits of 3D modeling for containment safety analysis. The 3D containment model allows to predict the thermal evolution in each containment compartment capturing the heterogeneity of this phenomenon, with higher resolution than the lumped parameters models traditionally used in this kind of analyses. It allows to observe the thermohydraulic conditions locally at any time during the transient.

These 285 documents have been used for the three sections that are part of the results of this article (documents statistics, bibliometric analysis, and literature review statistics). For this purpose, it was necessary to carry out an exhaustive review of the 285 selected documents and to complement this information with the data provided by Scopus. The data-charting process was as follows: the four researchers agreed on the types of data to be extracted, two of them carried out the review while the other two supervised. If any type of data worthy of investigation emerged during the reading, it was discussed, and if appropriate, included, making it an iterative process. For each of the documents, the following variables were collected in a table: author/s, title of the document, year of publication, journal in which it was published, type of document (article or review), number of citations and citations per year, relevance (weighting given by Scopus), DOI, geographical location of researchers, abstract, author keywords and keywords suggested by Scopus, JIF, JCI and H-index information of the journal in which the document is published (with quartiles and percentiles), subject area categories provided by Scopus, territory studied, renewable energy source studied, research technique or methodology used, primary data source used and years collected. In addition, for articles using quantitative techniques, all variables included in each model have been collected.

Vegetated coastal ecosystems, in particular mangroves, tidal marshes and seagrasses are highly efficient at sequestering and storing carbon, making them valuable assets for climate change mitigation and adaptation. The state of Queensland, in northeastern Australia, contains almost half of the total area of these blue carbon ecosystems in the country, yet there are few detailed regional or state-wide assessments of their total sedimentary organic carbon (SOC) stocks. We compiled existing SOC data and used boosted regression tree models to evaluate the influence of environmental variables in explaining the variability in SOC stocks, and to produce spatially explicit blue carbon estimates. The final models explained 75 % (for mangroves and tidal marshes) and 65 % (for seagrasses) of the variability in SOC stocks. Total SOC stocks in the state of Queensland were estimated at 569 ± 98 Tg C (173 ± 32 Tg C, 232 ± 50 Tg C, and 164 ± 16 Tg C from mangroves, tidal marshes and seagrasses, respectively). Regional predictions for each of Queensland's eleven Natural Resource Management regions revealed that 60 % of the state's SOC stocks occurred within three regions (Cape York, Torres Strait and Southern Gulf Natural Resource Management regions) due to a combination of high values of SOC stocks and large areas of coastal wetlands. Protected areas in Queensland play an important role in conserving SOC assets in Queensland's coastal wetlands. For example, ~19 Tg C within terrestrial protected areas, ~27 Tg C within marine protected areas and ~ 40 Tg C within areas of matters of State Environmental Significance. Using multi-decadal (1987-2020) mapped distributions of mangroves in Queensland; we found that mangrove area increased by approximately 30,000 ha from 1987 to 2020, which led to temporal fluctuations in mangrove plant and SOC stocks. We estimated that plant stocks decreased from ~45 Tg C in 1987 to ~34.2 Tg C in 2020, while SOC stocks remained relatively constant from ~107.9 Tg C in 1987 to 108.0 Tg C in 2020. Considering the level of current protection, emissions from mangrove deforestation are potentially very low; therefore, representing minor opportunities for mangrove blue carbon projects in the region. Our study provides much needed information on current trends in carbon stocks and their conservation in Queensland's coastal wetlands, while also contributing to guide future management actions, including blue carbon restoration projects.

In theoretical ecology, recent field experiments on terrestrial vertebrates observe that the predator-prey interaction can not only be curtailed by direct consumption but also governed by some indirect effects such as the fear of predator which may reduce the reproduction rate of prey individuals. Based on this fact, we have developed and explored the predator-prey interaction with the influence of both cost and benefit of fear effect (felt by prey). A Holling type III functional response with the effect of habitat complexity has been taken to consume the prey biomass. Positivity and boundedness of the studied system prove that the model is well-behaved. The uniform persistence of the studied system is derived analytically under some parametric restrictions. The feasibility conditions and stability criteria of each equilibrium points have been discussed. Next, we have exhibited the existence of Hopf-bifurcation around the interior equilibrium point. Our mathematical analyses show that habitat complexity and fear effect both have a great impact on the persistence of the predator biomass. Furthermore, we have investigated the effect of breeding delay parameter such that the system loses its stability behaviour and enters into a limit cycle oscillations through Hopf-bifurcation. Numerical simulations are illustrated to verify our analytical outcomes. Numerically, we have perturbed the death rates of prey and predator species with Gaussian white noise terms due to the effects of environmental fluctuations.