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High-performance structural materials (HPSMs) are needed for the successful and safe design of fission and fusion reactors. Their operation is associated with unprecedented fluxes of high-energy neutrons and thermomechanical loadings. In fission reactors, HPSMs are used, e.g., for fuel claddings, core internal structural components and reactor pressure vessels. Even stronger requirements are expected for fourth-generation supercritical water fission reactors, with a particular focus on the HPSM’s corrosion resistance. The first wall and blanket structural materials in fusion reactors are subjected not only to high energy neutron irradiation, but also to strong mechanical, heat and electromagnetic loadings. This paper presents a historical and state-of-the-art summary focused on the properties and application potential of irradiation-resistant alloys predominantly strengthened by an oxide dispersion. These alloys are categorized according to their matrix as ferritic, ferritic–martensitic and austenitic. Low void swelling, high-temperature He embrittlement, thermal and irradiation hardening and creep are typical phenomena most usually studied in ferritic and ferritic martensitic oxide dispersion strengthened (ODS) alloys. In contrast, austenitic ODS alloys exhibit an increased corrosion and oxidation resistance and a higher creep resistance at elevated temperatures. This is why the advantages and drawbacks of each matrix-type ODS are discussed in this paper.

Multiprincipal-element alloys are an enabling class of materials owing to their impressive mechanical and oxidation-resistant properties, especially in extreme environments. Here we develop a new oxide-dispersion-strengthened NiCoCr-based alloy using a model-driven alloy design approach and laser-based additive manufacturing. This oxide-dispersion-strengthened alloy, called GRX-810, uses laser powder bed fusion to disperse nanoscale Y2O3 particles throughout the microstructure without the use of resource-intensive processing steps such as mechanical or in situ alloying. We show the successful incorporation and dispersion of nanoscale oxides throughout the GRX-810 build volume via high-resolution characterization of its microstructure. The mechanical results of GRX-810 show a twofold improvement in strength, over 1,000-fold better creep performance and twofold improvement in oxidation resistance compared with the traditional polycrystalline wrought Ni-based alloys used extensively in additive manufacturing at 1,093 °C. The success of this alloy highlights how model-driven alloy designs can provide superior compositions using far fewer resources compared with the ‘trial-and-error’ methods of the past. These results showcase how future alloy development that leverages dispersion strengthening combined with additive manufacturing processing can accelerate the discovery of revolutionary materials.

The paper presents the transport module of the System for Integrated modeLling of Atmospheric coMposition SILAM v.5 based on the advection algorithm of Michael Galperin. This advection routine, so far weakly presented in the international literature, is positively defined, stable at any Courant number, and efficient computationally. We present the rigorous description of its original version, along with several updates that improve its monotonicity and shape preservation, allowing for applications to long-living species in conditions of complex atmospheric flows. The scheme is connected with other parts of the model in a way that preserves the sub-grid mass distribution information that is a cornerstone of the advection algorithm. The other parts include the previously developed vertical diffusion algorithm combined with dry deposition, a meteorological pre-processor, and chemical transformation modules. The quality of the advection routine is evaluated using a large set of tests. The original approach has been previously compared with several classic algorithms widely used in operational dispersion models. The basic tests were repeated for the updated scheme and extended with real-wind simulations and demanding global 2-D tests recently suggested in the literature, which allowed one to position the scheme with regard to sophisticated state-of-the-art approaches. The advection scheme performance was fully comparable with other algorithms, with a modest computational cost. This work was the last project of Dr. Sci. Michael Galperin, who passed away on 18 March 2008.

In order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the feature extraction of ship-radiated noise signal (SNS) compared with permutation entropy (PE), dispersion entropy (DE), fluctuation dispersion entropy (FDE), and reverse dispersion entropy (RDE), so that the effectiveness of SlEn is verified, and SlEn has the highest recognition rate calculated by the k-Nearest Neighbor (KNN) algorithm. Secondly, SlEn is combined with PE, DE, FDE, and RDE, respectively, to extract the feature of SNS for a higher recognition rate, and SlEn&PE has the highest recognition rate after the calculation of the KNN algorithm. Lastly, the recognition rates of SlEn and SlEn&PE are compared, and the recognition rates of SlEn&PE are higher than SlEn by 4.22%. Therefore, the double feature extraction method proposed in this paper is more effective in the application of ship type recognition.

Dispersion processes in environmental flows have been traditionally studied under the strong assumption of homogeneous, isotropic and stationary turbulence. To overcome this limitation, we propose a new approach that combines autocorrelation analysis of simulated Lagrangian trajectories together with unsupervised clustering. To test the approach, we consider several dynamic scenarios around a coastal gulf, subject to different forcing, in order to compare our method with other approaches. Lagrangian trajectories forced by the varying coastal circulation exhibited different behaviors, looping and non‐looping paths, and produced a variety of Lagrangian autocorrelation functions. Our approach proves to be able to reveal spatio‐temporal variations in ocean dispersion processes without any a priori knowledge of the character of the trajectories. Clusters based on the autocorrelation functions are associated to different inhomogeneous dispersion processes. Finally, we propose a new stochastic model capable of predicting the different forms of autocorrelations. Plain Language Summary Ocean and coastal circulations develop in complex domains, especially along the shorelines, and the resulting flow is turbulent in character and inherits the inhomogeneities from the generating forces. When we come to study how these chaotic circulations transport mass, we must expect that the associated dispersion is equally turbulent and high variable in time and space. Observations of particle paths taught us how the trajectories could be complicated, often showing looping behaviors generated by different mechanisms. Despite this complexity, many available studies on ocean and coastal dispersion rely on considering the process as homogeneous (no variations in space) and, applying different spatial and temporal averages, try to grasp the overall picture of the dispersion. We propose a new approach that combines the fundamentals of the dispersion theories with an automated algorithm for clustering. We show that this approach is able to retain the highly inhomogeneous character of the ocean dispersion, at the same time, showing the physical link between the circulations and its ability to transport mass. Key Points We formulated and applied a clustering algorithm to classify oceanographic dispersion processes starting from Lagrangian trajectories A new analytic model for the autocorrelation functions is proposed which well describes loopers and non‐loopers particles behaviors We identified three characteristic time scales to distinguish complex inhomogeneous dispersion processes typical of ocean circulations

Providing a clear description of the theory of polydisperse multiphase flows, with emphasis on the mesoscale modelling approach and its relationship with microscale and macroscale models, this all-inclusive introduction is ideal whether you are working in industry or academia. Theory is linked to practice through discussions of key real-world cases (particle/droplet/bubble coalescence, break-up, nucleation, advection and diffusion and physical- and phase-space), providing valuable experience in simulating systems that can be applied to your own applications. Practical cases of QMOM, DQMOM, CQMOM, EQMOM and ECQMOM are also discussed and compared, as are realizable finite-volume methods. This provides the tools you need to use quadrature-based moment methods, choose from the many available options, and design high-order numerical methods that guarantee realizable moment sets. In addition to the numerous practical examples, MATLAB scripts for several algorithms are also provided, so you can apply the methods described to practical problems straight away.

Atmospheric dispersion models are applied to describe and predict the dispersion of emitted plumes. Here, we describe the Lagrangian Atmospheric Radionuclide Transport Model (ARTM) 2.8.0 which was developed to simulate the atmospheric dispersion of the emissions of nuclear facilities under routine operation for regulatory purposes over annual time scales. ARTM includes a diagnostic wind field model and a particle dispersion model. It simulates size-dependent wet and dry deposition, plume rise and γ-cloud shine of radioactive exhaust plumes in the simulation domain. This work presents an extensive overview of the different components of the model and of the physical and mathematical concepts of ARTM. We investigate the dependence of the plume dispersion in terms of plume volume, position of maximum concentration and dry deposition rates on key input parameters such as atmospheric stability, surface roughness, zero plane displacement height, source height and the particle size in the case of particulate matter tracers. The results indicate a strong dependence of plume volume and position of the maximum concentration on the stability as well as a minor influence on surface roughness. The source height above ground level has a low impact on the plume volume as the zero plane displacement only slightly affects the position of maximum concentration. Strong turbulence under unstable conditions tends to reduce the impact of sedimentation and decreases deposition in general. This computational model serves to advance the understanding of the dispersion of radioactive plumes in the boundary layer.

The Met Office’s atmospheric dispersion model Numerical Atmospheric-Dispersion Modeling Environment (NAME) is validated against controlled tracer release experiments, considering the impact of the driving meteorological data and choices in the parameterization of unresolved motions. The Cross-Appalachian Tracer Experiment (CAPTEX) and Across North America Tracer Experiment (ANATEX) were long-range dispersion experiments in which inert tracers were released and the air concentrations measured across North America in the 1980s. NAME simulations of the experiments have been driven by both reanalysis meteorological data from European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the Advanced Research version of the Weather Research and Forecasting (WRF) Model. NAME predictions of air concentrations are assessed against the experimental measurements, using a ranking method composed of four statistical parameters. Differences in the performance of NAME according to this ranking method are compared when driven by different meteorological sources. The effect of changing parameter values in NAME for the unresolved mesoscale motions parameterization is also considered, in particular, whether the parameter values giving the best performance rank are consistent with values typically used. The performance ranks are compared with analyses in the literature for other particle dispersion models, namely, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), Stochastic Time-Inverted Lagrangian Transport (STILT), and Flexible Particle (FLEXPART). It is found that NAME performance is comparable to the other dispersion models considered, with the different models responding similarly to differences in driving meteorological data.

In a complex environment such as an urban area, accurate prediction of the atmospheric dispersion of airborne harmful materials such as radioactive substances is necessary for establishing response actions and assessing risk or damage. Given the variety of urban atmospheric dispersion models available, evaluation and inter-comparison exercises are vital for assessing quantitatively and qualitatively their capabilities and differences. To that end, the European Commission/Directorate General Joint Research Centre with support from the European Commission/Directorate General-Migration and Home Affairs, and with the contribution of the U.S. Defense Threat Reduction Agency, launched the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. Within UDINEE, nine atmospheric dispersion models are evaluated and intercompared. Sulphur hexafluoride concentrations from puffs released near the ground during the Joint Urban 2003 (JU2003) field experiment are used in UDINEE to evaluate atmospheric dispersion models. The JU2003 experiment is chosen because UDINEE aims at the better understanding of modelling capabilities for radiological dispersal devices in urban areas, and the neutrally-buoyant puff releases performed in the JU2003 experiment are the closest scenario to this purpose. The present study evaluates the capability of models at simulating the presence and concentration levels of the tracer at sampling locations. The fraction of predicted concentrations and time-integrated concentrations within a factor-of-two of observations are less than 0.36 and 0.4 respectively. The analysis reveals an improvement in the performance of models by using time-varying inflow conditions. Since the simulation of the dispersion of puff release is particularly challenging, the results of UDINEE could constitute a benchmark for future model developments.

Pollutant dispersion processes over complex terrain are much more complicated than over flat areas, as they are affected by atmospheric interactions with the orography at different spatial scales. This paper reviews recent findings and progress in this field, focusing on both experimental and modeling perspectives. It highlights open questions and challenges to our capability for better understanding and representing atmospheric processes controlling the fate of pollutants over mountainous areas. In particular, attention is focused on new measurement techniques for the retrieval of spatially distributed turbulence information and air quality parameters, and on challenges for meteorological and dispersion models to reproduce fine-scale processes influenced by the orography. Finally, specific needs in this field are discussed, along with possible directions for future research efforts.