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The position and strength of the Hadley cell circulation determine the habitable zones in the tropics, yet our understanding of and ability to predict changes in the circulation is limited. One potentially important source of uncertainty is the dependence of the Hadley cell on turbulent drag. Here, the sensitivity of the Hadley cell and associated features such as the intertropical convergence zone to variations in the magnitude of the turbulent drag is explored with an atmospheric general circulation model in aquaplanet configuration. The tropical circulation and precipitation, and extratropical features such as the polar jet stream, displayed a strong sensitivity to the strength of the parameterized turbulent drag, with distinct low- or high-drag regimes. However, the response of the meridional heat transport produced a surprising departure from previous expectations: with greater drag, simulations exhibited less heat transport than low-drag simulations, which is in the opposite sense to that from Held and Hou. This may be due to the energetic constraints in the present model framework. When exposed to a uniform global warming, the response of the ITCZ precipitation depends strongly on the choice of drag, whereas most simulations exhibit a poleward expansion of the subtropics. Data availability statement: The ICON output subsets used in this work and example bash scripts and Python codes detailing how these subsets were created are available at https://doi.org/10.17043/flynn-2022-icon-drag-1.

A new one-dimensional 1.5-order planetary boundary layer (PBL) scheme, based on the K–ε turbulence closure applied to the Reynolds-averaged Navier–Stokes (RANS) equations, is developed and implemented within the Weather Research and Forecasting (WRF) Model. The new scheme includes an analytic solution of the coupled equations for turbulent kinetic energy and dissipation rate. Different versions of the PBL scheme are proposed, with increasing levels of complexity, including a model for the calculation of the Prandtl number, a correction to the dissipation rate equation, and a prognostic equation for the temperature variance. Five different idealized cases are tested: four of them explore convective conditions, and they differ in initial thermal stratification and terrain complexity, while one simulates the very stable boundary layer case known as GABLS. For each case study, an ensemble of different large-eddy simulations (LES) is taken as reference for the comparison with the novel PBL schemes and other state-of-the-art 1- and 1.5-order turbulence closures. Results show that the new PBL K–ε scheme brings improvements in all the cases tested in this study. Specifically, the more significant are obtained with the turbulence closure including a prognostic equation for the temperature variance. Moreover, the largest benefits are obtained for the idealized cases simulating a typical thermal circulation within a two-dimensional valley. This suggests that the use of prognostic equations for dissipation rate and temperature variance, which take into account their transport and history, is particularly important with the increasing complexity of PBL dynamics.

International audience; We introduce a new mechanism for self-actuating deployable structures, based on printing a dense pattern of closely-spaced plastic ribbons on sheets of pre-stretched elastic fabric. We leverage two shape-changing effects that occur when such an assembly is printed and allowed to relax: first, the incompressible plastic ribbons frustrate the contraction of the fabric back to its rest state, forcing residual strain in the fabric and creating intrinsic curvature. Second, the differential compression at the interface between the plastic and fabric layers yields a bilayer effect in the direction of the ribbons, making each ribbon buckle into an arc at equilibrium state and creating extrinsic curvature. We describe an inverse design tool to fabricate low-cost, lightweight prototypes of freeform surfaces using the controllable directional distortion and curvature offered by this mechanism. The core of our method is a parameterization algorithm that bounds surface distortions along and across principal curvature directions, along with a pattern synthesis algorithm that covers a surface with ribbons to match the target distortions and curvature given by the aforementioned parameterization. We demonstrate the flexibility and accuracy of our method by fabricating and measuring a variety of surfaces, including nearly-developable surfaces as well as surfaces with positive and negative mean curvature, which we achieve thanks to a simple hardware setup that allows printing on both sides of the fabric.

In the present work, a novel algorithm for the continuous projection of point triangles belonging to a triangle mesh is presented. The algorithm uses the normals defined at the vertices of the triangle to perform the projection. The direction of projection is not chosen a priori but depends on the point to be projected: the proposed algorithm, named Fast Continuous Projection method (FCP) lets the projection direction vary continuously on the mesh. Moreover, the direction is coherent with the original surface that is approximated with the triangle mesh. An optimized version of the algorithm is also presented: this uses pre-evaluated matrices to reduce the calculation time. This algorithm can be effectively used when a large set of points has to be projected on a coarse mesh as, for example, to generate the scanning vectors for laser engraving/milling.

Offshore wind energy has seen a steady increase in the latest years as it serves as an ideal alternative energy source to meet our renewable energy goals. Due to this increase in interest and in installations of offshore wind farms a better understanding of the impact of waves on the power production of wind farms in necessary. This wave-wind farm power production interaction has scarcely been examined, however, some exceptions of small scale large-eddy-simulations exist. Unfortunately, these studies are not able to take multiple wind farms under real weather conditions into account. Here, we show the power production and wake lengths of 1250 offshore wind turbines located in the German Bight simulated by a stand-alone atmospheric (WRF) model and a coupled atmosphere-wave (WRF-SWAN) model. The coupled atmosphere-wave model estimates larger (smaller) power production in case of waves and wind traveling in the same (opposed) direction compared to the stand-alone atmospheric model. The relative difference between the two models can be as much as 20% for the two-week averaged grid power production, while the difference in total power over this two-week period is equal to 9%. Moreover, the wind farm wake lengths of waves and wind traveling in the same (opposed) direction are longer (shorter) for the coupled atmosphere-wave model compared to the stand-alone atmospheric model. Here, the relative difference of the mean wake length between the two models can be up to 25%. This shows the importance of waves as a part of the offshore wind environment and can be an important factor in future wind assessment or power production estimation studies.

Bioenergy has been identified as a key component of climate change mitigation. Therefore, quantifying the net carbon balance of bioenergy feedstocks is crucial for accurate projections of climate mitigation benefits. Switchgrass (Panicum virgatum) has many characteristics of an ideal bioenergy crop with high yields, low maintenance, and deep roots with potential for belowground carbon sequestration. However, the assessments of net annual carbon exchange between switchgrass fields and the atmosphere are rare. Here we present observations of net carbon fluxes in a minimally managed switchgrass field in Virginia (Ameriflux site US-SB2) over 5 years (3–7 years since establishment). Average annual net ecosystem exchange (NEE) of carbon was near zero (60 g C m−2 year−1) but the net ecosystem carbon balance that includes harvested carbon (HC) was a net source of carbon to the atmosphere (313 g C m−2 year−1). The field alternated between a large and small source of carbon annually, with the interannual variability most strongly correlated with the day of the last frost and the interaction of temperature and precipitation. Overall, the consistent source of carbon to the atmosphere at US-SB2 differs substantially from other eddy covariance studies that report switchgrass fields to be either neutral or a sink of carbon when accounting for both NEE and HC. This study illustrates that predictions of net carbon climate benefits from bioenergy crops cannot assume that the ecosystem will be a net sink of carbon from the atmosphere. Background climate, management, and land-use history may determine whether widespread deployment of switchgrass as a bioenergy feedstock results in realized climate change mitigation. Published version

International audience; Many different models have been published with the aim of describing electrolyte thermodynamics. In this study two successful Equations of State (EoS) are compared. The models investigated in this work are the electrolyte Cubic Plus Association (e-CPA) EoS and the electrolyte Polar Perturbed Chain Statistical Associating Fluid Theory (e-PPC-SAFT). The model terms are not changed from previous works, but they are reparameterized with various models for the relative static permittivity. The models are parameterized as similarly and fairly as possible by identifying key parameters in the models that are intended to describe the same physics. Several different sets of comparable parameters are investigated to test the models with the inclusion of various physics, and to avoid favoring one model due to the choice of adjustable parameters. The parameters of the models are optimized with an objective function containing the properties mean ionic activity coefficients (MIAC), osmotic coefficients and density in a wide temperature range of 273.15-473.15 K and they are tested for their ability to quantitatively describe these properties. The difference between e-CPA and e-PPC-SAFT is generally found to be relatively minor and the permittivity model and considered adjustable parameters are generally more important for the overall model performance. It is found that the permittivity models that only predict part of experimental decrease tend to perform the best for the properties MIAC, osmotic coefficients and density. It is also found that including both association parameters and dispersion/attractive parameters for ions is better than neglecting one type of parameters, even when the same number of adjustable parameters is included. To be able to capture the temperature trend of MIAC it is found to be important to include an additional temperature dependency, which in this work is a temperature dependent interaction parameter for the physical term. It is also found that it is important to include sufficiently strong ion association to be able to obtain the correct qualitative trend for individual ion activity coefficients.

Необхідний рівень безпеки машин і механізмів досягається за рахунок використання відповідних систем управління безпекою промислового обладнання, в тому числі програмованих електронних. Такі системи зазвичай включають в себе різноманітні охоронні пристрої для управління налаштуваннями промислового обладнання. Оскільки електронні системи управління в даний час вважаються найбільш перспективними системами управління в цій області, вивчення параметрів безпеки їх прикладної підтримки визначає актуальність даного дослідження. У цьому дослідженні проаналізовано основні вимоги стандартів IEC 61508 та IEC 62061 на відповідність сучасним вимогам безпеки вбудованого та прикладного програмного забезпечення для електронних систем управління машинами та механізмами. Дане дослідження пропонує алгоритм покрокового впровадження програмного забезпечення для електронних систем управління машинами відповідно до базових стандартів безпеки як для вбудованого, так і прикладного програмного забезпечення. Тестування визначено як основний метод перевірки прикладного програмного забезпечення. За результатами аналізу було встановлено, що специфікація вимог безпеки, як вбудованого, так і прикладного програмного забезпечення, повинна висвітлювати необхідні характеристики кожної підсистеми, надаючи інформацію, що дозволяє вибрати обладнання, що відповідає існуючим вимогам безпеки. Наводяться відповідні рекомендації щодо специфіки практичного застосування цих стандартів. The required level of safety of machines and mechanisms is achieved through the use of appropriate safety management systems for industrial equipment, including programmable electronic ones. Such systems usually include a variety of security devices for managing industrial equipment settings. Since electronic control systems are currently considered the most promising control systems in this area, the study of the security parameters of their application support determines the relevance of this study. This study analyses the main requirements of IEC 61508 and IEC 62061 standards for compliance with modern safety requirements of embedded and applied software for electronic control systems of machines and mechanisms. This study proposes an algorithm for step-by-step implementation of software for electronic machine control systems in accordance with basic security standards for both built-in and application software. Testing has been determined as the main method of verification of application software. Based on the results of the analysis, it was found that the specification of security requirements, both built-in and application software, should highlight the necessary characteristics of each subsystem, providing information that allows choosing the equipment that meets existing security requirements. Relevant recommendations are given on the specifics of practical application of these standards.

This study develops an advanced physically‐based parameterization of heterogeneous ice nucleation in cirrus clouds that includes an updated parameterization of stochastic homogeneous freezing of supercooled solution droplets. Both components are formulated based on the same methodology and level of approximation, without numerical integration of the underlying ice supersaturation equation. The new scheme includes measured ice nucleation spectra describing deterministic ice activation from an arbitrary number of types of ice‐nucleating particles (INPs), tracks the competition for available water vapor between the different ice nucleation modes, and allows for new ice formation and growth within pre‐existing cirrus clouds. The computationally efficient scheme works with a minimal set of physical input parameters and predicts total nucleated ice crystal number concentrations (ICNCs) along with the maximum ice supersaturation attained during cirrus formation events. Aspects of its implementation into host models are discussed, including the provision of suitably parameterized vertical wind speeds. The parameterization is validated by comparisons to numerical simulations. First off‐line applications to mineral dust and aviation soot particles are presented, including ICNC ensemble statistics resulting from the coupling with statistics of updraft speed variability., Plain Language Summary: Two decades after introduction of the first parameterization of cirrus cloud formation by freezing of ubiquitous liquid solution droplets, an improved version is developed based on the latest experimental findings regarding solid ice‐nucleating particles, a small subset of the atmospheric aerosol. The new scheme allows to predict ice crystal formation in cirrus from competing homogeneous freezing and heterogeneous ice activation more realistically and with greater computational efficiency. It considers new developments regarding the properties of vertical wind speeds (triggering ice formation) and the molecular kinetics of water vapor uptake onto ice crystals (controlling ice growth). This study explains the foundation of cirrus ice formation and growth based on cloud physical theory, derives and explains the parameterization, discusses its use in host models to facilitate applications, checks its performance by comparison to comprehensive numerical simulations, and presents first results involving mineral dust and aircraft‐emitted soot particles as examples for good and poor atmospheric ice‐nucleating particles, respectively., Key Points: Competing ice nucleation processes in cirrus are predicted reliably and efficiently. Partial activation of dust particles may occur frequently in cirrus formation. Nucleation of ice within already‐existing cirrus requires high updraft speeds.

Access point for public codes of WP2.

The aerosol impact on liquid water path (LWP) is a key uncertainty in the overall climate impact of aerosol. However, despite a significant effort in this area, the size of the effect remains poorly constrained, and even the sign is unclear. Recent studies have shown that the relationship between droplet number concentration (Nd) and LWP is an unreliable measure of the impact of Nd variations on LWP due to the difficulty in establishing causality. In this work, we use satellite observations of the short-term development of clouds to examine the role of Nd perturbations in LWP variations. Similar to previous studies, an increase followed by a general decrease in LWP with increasing Nd is observed, suggesting an overall negative LWP response to Nd and a warming LWP adjustment to aerosol. However, the Nd also responds to the local environment, with aerosol production, entrainment from the free troposphere and wet scavenging all acting to modify the Nd. Many of these effects act to further steepen the Nd–LWP relationship and obscure the causal Nd impact on LWP. Using the temporal development of clouds to account for these feedbacks in the Nd–LWP system, a weaker negative Nd–LWP relationship is observed over most of the globe. This relationship is highly sensitive to the initial cloud state, illuminating the roles of different processes in shaping the Nd–LWP relationship. The nature of the current observing system limits this work to a single time period for observations, highlighting the need for more frequent observations of key cloud properties to constrain cloud behaviour at process timescales.

The number of offspring and the population size greatly influence the performance of the Plant Propagation Algorithm, a crossover-less metaheuristic, when applied to the Euclidean traveling salesman problem. However, with large volumes of experimental data, a clearly characterizable relation emerges, facilitating both an exact parameterization as well as opening up perspectives on a precisely predictable outcome. These results directly question its position between exact, approximation, and PTAS algorithms. Although the metaheuristic is thereby officially parameter sensitive when deployed to the Euclidean traveling salesman problem, it does appear to be largely insensitive to different problem instances. This is very different from earlier results on continuous optimization, which were completely opposite. Why is that, and what does it mean for our practices in algorithmic benchmarking?

Cognitive modeling tools have been widely used by researchers and practitioners to help design, evaluate, and study computer user interfaces (UIs). Despite their usefulness, large-scale modeling tasks can still be very challenging due to the amount of manual work needed. To address this scalability challenge, we propose CogTool+, a new cognitive modeling software framework developed on top of the well-known software tool CogTool. CogTool+ addresses the scalability problem by supporting the following key features: (1) a higher level of parameterization and automation; (2) algorithmic components; (3) interfaces for using external data; and (4) a clear separation of tasks, which allows programmers and psychologists to define reusable components (e.g., algorithmic modules and behavioral templates) that can be used by UI/UX researchers and designers without the need to understand the low-level implementation details of such components. CogTool+ also supports mixed cognitive models required for many large-scale modeling tasks and provides an offline analyzer of simulation results. In order to show how CogTool+ can reduce the human effort required for large-scale modeling, we illustrate how it works using a pedagogical example, and demonstrate its actual performance by applying it to large-scale modeling tasks of two real-world user-authentication systems.

Agent-based models have gained considerable notoriety in ecological modeling as well as in several other fields yearning for the ability to capture the emergent behavior of a complex system in which individuals interact with each other and with their environment. These models are implemented by applying a bottom-up approach, where the entire behavior of the system emerges from the local interaction between their components (agents or individuals). Usually, these interactions between individuals and their enclosing environment are modeled by very simple local rules. From the conceptual point of view, another appealing characteristic of this simulation approach is that it is well aligned with the reality whenever the system is composed of a multitude of individuals (behavioral units) that can be flexibly combined and placed in the environment. Due to their inherent flexibility, and despite of their simplicity, it is necessary to pay attention to the adjustments in their parameters which may result in unforeseen changes on the overall behavior of these models. In this paper we study the behavior of an agent-based model of spatial distribution of species, by analyzing the effects of the model parameters and the implications of the environment variables (that compose the environment where the species lives) on the models’ output. The presented experiments show that the behavior of the model depends mainly on the conditions of the environment where the species live, and the main parameters presented in life cycle of the species., This work was supported by operation Centro-01-0145-FEDER-000019 - C4 - Centro de Competências em Cloud Computing, co-financed by the European Regional Development Fund (ERDF) through the Programa Operacional Regional do Centro (Centro 2020), in the scope of the Sistema de Apoio à Investigação Científica e Tecnológica - Programas Integrados de IC\&DT.

ispartof: AGRICULTURAL WATER MANAGEMENT vol:284 status: accepted

Many animals have protective anatomical structures that allow for growth and flexibility; these structures contain thin seams called sutures that help the structure to absorb impacts. In this study, we parameterized the stiffness and toughness of a curved archway structure based on three geometric properties of a suture through finite element, quasi-static, three-point bending simulations. Each archway consisted of two symmetric pieces linked by a dovetail suture tab design. The three parameters included suture tab radii (1–5 mm), tangent lengths (0–20 mm), and contact angles (0–40°). In the simulations, a steel indenter was displaced 6.5 mm to induce progressive tab disengagement. Sutures with large contact angles and large tangent lengths generally led to stiffer and tougher structures. Sutures with a small tab radius exhibited the most sensitivity to the input parameters, and the smallest tab radius led to the stiffest and toughest archways. Results suggested that it was a combination of the largest number of tab repeats with the largest possible contact surface area that improved the mechanical response of the archway. The study revealed several suture geometries that hold significant promise, which can aid in the development of hemispherical 3D structures for dynamic impact applications.

ispartof: QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY vol:147 issue:735 pages:825-846 status: published

Arctic shrubs reduce surface albedo in winter when branches protrude above the snow. To calculate the albedo of those mixed surfaces, the branch area index (BAI) of Arctic shrubs needs to be known. Moreover, an exposed-vegetation function is required to determine the BAI for protruding branches only. This study used a structural analysis of 30Betula glandulosashrubs, sampled near Umiujaq, northern Quebec, to (i) establish an allometric relationship between shrub height and BAI and (ii) determine a specific exposed-vegetation function for Arctic shrubs. The spectral albedo (400–1080 nm) of mixed surfaces was then simulated with the equations derived from this study and validated with in situ measured spectra. Shrubs were sampled from two sites, one along the coast and the other in a nearby valley. The shrub height–BAI relationship varied between both sites. BAI values of shrubs growing in the wind-sheltered valley were 30%–50% lower. The exposed-vegetation function obtained here differed from the linear functions found in the literature. The linear functions strongly overestimated the BAI of exposed branches. Albedo was well simulated with an accuracy of 3% when using an allometric relationship adapted to the environmental conditions of our study site. However, simulated albedo values were consistently higher than field measurements, probably because radiation absorbed by impurities and buried branches was neglected in the model. We conclude that specific exposed-vegetation and allometric equations need to be implemented in models to accurately simulate the albedo of mixed snow–shrub surfaces.

The role of nonlocal transport on the development and maintenance of marine stratocumulus (Sc) clouds in coarse-resolution models is investigated, with a special emphasis on the downdraft contribution. A new parameterization of cloud-top-triggered downdrafts is proposed and validated against large-eddy simulation (LES) for two Sc cases. The applied nonlocal mass-flux scheme is part of the stochastic multiplume eddy-diffusivity/mass-flux (EDMF) framework decomposing the turbulent transport into local and nonlocal contributions. The complementary local turbulent transport is represented with the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme. This EDMF version has been implemented in the Weather Research and Forecasting (WRF) single-column model (SCM) and tested for three model versions: without mass flux, with updrafts only, and with both updrafts and downdrafts. In the LES, the downdraft and updraft contributions to the total heat and moisture transport are comparable and significant. The WRF SCM results show a good agreement between the parameterized downdraft turbulent transport and LES. While including updrafts greatly improves the modeling of Sc clouds over the simulation without mass flux, the addition of downdrafts is less significant, although it helps improve the moisture profile in the planetary boundary layer.

B-spline data interpolation and approximation require parameterization at the first step. For this purpose, many algorithms have been developed, such as the uniform, centripetal, chord length, Foley and universal methods. The uniform method works well if the input data points are distributed regularly. The chord length method produces large deflections if long chords exist in the data polygon. To remove this effect, the centripetal method was developed. The traditional centripetal method uses a fixed power for chord lengths for parameter distribution. In this paper, we propose an improved version of the centripetal parameterization method for B-spline data interpolation. Our experiments show that individual dynamic power calculation can be possible for each chord length. This new parameterization method produces better behavior when compared to the traditional centripetal method and is more robust against fast changes in chord lengths since it uses the natural logarithm of chord lengths to calculate the parameters.

Parameterizing mesoscale eddies in ocean circulation models remains an open problem due to the ambiguity with separating the eddies from large-scale flow, so that their interplay is consistent with the resolving skill of the employed non-eddy-resolving model. One way to address the issue is by using recently formulated dynamically filtered eddies. These eddies are obtained as the field errors of fitting some given reference ocean circulation into the employed coarse-grid ocean model. The main strengths are (i) no explicit spatio-temporal filter is needed for separating the large-scale and eddy flow components, (ii) the eddies are dynamically translated into the error-correcting forcing that perfectly augments the coarse-grid model towards reproducing the reference circulation. We uncovered physical properties of the eddies by interpreting involved nonlinear eddy/large-scale interactions via the classical flux-gradient relation. We described the eddies in terms of their full, space–time dependent transport tensor, which was made unique by constraining it to be the same for the potential vorticity, momentum and buoyancy fluxes. Both diffusive and advective parts of the transport tensor were found to be significant. The diffusive tensor component is characterised by polar eigenvalues and is further decomposed into isotropic and filamentation components. The latter component completely dominates, therefore, it should be taken into account by eddy parameterizations, which is not yet the case. We also showed that spatial inhomogeneities of the transport tensor components are important. Comparing these properties with those obtained for more common, locally filtered eddies revealed that they are distinctly different.

Presentación realizada en: 2nd ACCORD ASW celebrado del 4 al 8 de abril de 2022 en Ljubljana, Eslovenia.

Surface interactions occur near the land–atmosphere interface, thus affecting the temperature, convection, boundary layer, and stability of the atmosphere. A proper representation of surface interactions is a crucial component for numerical atmospheric and air quality modeling. We assessed four land surface schemes—1. 5-layer thermal diffusion scheme (1 5-Layer); 2. unified Noah land surface model (2 Noah); 3. rapid update cycle (3 RUC) land surface model; and 4. Pleim–Xiu land surface model (4 Pleim–Xiu)—from the Weather Research and Forecasting with Chemistry (WRF-Chem V3.2) model for the purposes of atmospheric modeling in Cuenca, which is a region with a complex topography and land use configuration and which is located in the Southern Andean region, in Ecuador. For this purpose, we modeled the meteorological and air quality variables during September 2014. It was found that the meteorological and short-term air quality variables were better modeled through the 2 Noah scheme. Long-term (mean monthly) air quality variables were better modeled by the 1 5-Layer and 3 RUC options. On average, the 2 Noah scheme was better at modeling meteorology and air quality. In addition, we assessed the 2 Noah scheme combined with the urban canopy model (UCM) (5 Noah UCM), which was developed as an option to represent the urban effects at a subgrid-scale. Results indicated that the performance of the 5 Noah UCM scheme was not better at modeling than the 2 Noah scheme alone. Moreover, the 5 Noah UCM scheme notably decreased the modeling performance for carbon monoxide and fine particulate matter. These results complement previous assessments of other schemes, allowing us to recommend a basic configuration of parameters for atmospheric modeling in the Andean region of Ecuador.

This paper takes the garden road system as the research object and proposes a method of generating paths for classical gardens based on parametric design. Firstly, by studying the distribution characteristics of roads, the data on the curvature, angle, and view area of roads were collected. Secondly, the obtained data were transferred to the parameterized platform, and a method of intelligent generation was used for calculation. Finally, the road system was optimized by the genetic algorithm for better application in modern landscape design. According to the current situation, the road system plan generated by the algorithm inherits the characteristics of classical garden roads. This method can be applied to the courtyard, the community park, the urban park, and other objects. This research not only identifies the characteristics of landscape cultural heritage, but also produces an innovative, intelligent design tool. It provides new methods for the parameterized inheritance and application of traditional landscape heritage.

Traditional settlement space contains regional, natural, economic, historical, and cultural characteristics. The spatial texture serves as a material carrier of rural life and production and a vital landscape resource for the traditional villages. Traditional rural settlements have formed relatively unique and stable spatial form genes over time, which contain the “order” and “law” of spatial creation traditionally established in villages. The metropolis erodes traditional village spaces due to fast socioeconomic development and urbanization. In addition, the lack of adequate recognition and continuation of spatial texture in current mainstream village construction planning methods also limits the ability of villages to adapt to environmental changes and promote self-repair and adjustment, which, in turn, causes the gradual disappearance of their distinctive appearance. The reason is the need for more quantitative research and planning on the genes controlling the evolution of spatial texture morphology in traditional villages. They are faced with issues such as blind construction and development, a fracture in the rural characteristic spatial texture inheritance, and a loss of the distinctive vernacular landscape. Adopting an objective and in-depth approach to the cognition of traditional village space texture is an essential demand for the preservation, optimization, and renewal of the spatial appearance of rural settlements. We use the spatial genes of village settlements as its starting point. It then uses the spatial texture of village settlements connected to gene information mining as its specific method. We investigate the autogenous law of traditional village spatial form and determine its application using the CityEngine parametric platform, digitalization, and 3D visualization as the applied technical means. The feasibility and implementation path of the parameterization technique are explored using the traditional village of Xiaoxi in western Hunan Province as an example. We effectively promote the integration of rural spatial landscape resources, feature assessment, optimization guidance, and management control and provide an innovative research perspective and scientific planning path for analyzing the spatial morphological evolution of traditional villages.

The discharge process has undergone major changes in many river basins throughout the world as a result of the simultaneous influences of global climate change and human activity. Flow duration curves (FDCs) are crucial indicators of river basins’ hydrological processes. However, it is challenging to compare FDCs in a quantitative way. This study will identify the best function with which to fit the flow duration curve in a semi-arid region of North China, so as to quantify the FDC, and parameterize the function of the FDC of the region in order to describe the FDCs of ungauged basins. In this work, six small- and medium-sized catchments in North China are selected as the study area, and three functions, i.e., log normal, generalized Pareto and H2018 functions, were chosen to fit the FDC at nineteen hydrological stations. The relationship between the parameters of the FDC and the basin characteristics, such as the climatic factors and geographical features, were analyzed. A regression formula of the parameters of the FDC function was established, and its spatial and temporal distributions were examined. Based on the evaluation of four indicators, the Nash–Sutcliffe efficiency, the root mean square relative error, the logarithmic Nash efficiency coefficient and the coefficient of determination, the results demonstrate that the H2018 function can match FDCs the best. Through the annual runoff, annual precipitation, precipitation in summer, potential evapotranspiration, catchment area, mean elevation, length of the main channel and maximum flow frequency, the parameters of a, b, and k in the H2018 function can be formulated. The regression formula constructed in this study can obtain a regional flow duration curve with satisfactory performance, which provides a reference for the validation of remote-sensing-based runoff data in ungauged regions.

[EN] In engineering, the 3D model of a product is essential. A 3D model allows making modifications by editing the characteristic modeling functions, which implies knowing in detail the process followed in the modeling. In addition, the flexibility in the configuration is limited, since the modifications are made on geometry and parameters that are dependent on each other. In this work, a parametric modeling approach allows the generation of 3D models with different specifications by modifying a reduced number of parameters. To demonstrate the functionality, an application has been developed, using Autodesk Inventor iLogic, for the modeling of an engine with V-cylinder arrangement. Taking as input key parameters (number of cylinders,¿), it can generate virtual prototypes with different configurations, facilitating the selection of the best product configuration by allowing to evaluate different alternatives.

Accurate calculation of the whitecap fraction is of great importance for the estimation of air-sea momentum flux, heat flux and sea-salt aerosol flux in Earth system models. Past whitecap fraction parameterizations were mostly power functions of wind speed, lacking consideration of other factors, while the single wind speed dependence makes it difficult to explain the variability of the whitecap fraction. In this work, we constructed a novel multivariate whitecap fraction parameterization using a deep neural network, which is diagnosed and interpreted. Compared with a recent developed parameterization by Albert and coworkers, the new parameterization can reduce the computational error of the whitecap fraction by about 15%, and it can better characterize the variability of the whitecap fraction, which provides a reference for the uncertainty study of sea-salt aerosol estimation. Through a permutation test, we ranked the importance of different input variables and revealed the indispensable role of variables such as significant wave height, sea surface temperature, etc., in the whitecap fraction parameterization.

In this study, the Acısu Basin—viz., the headwater of the Gediz Basin—in Turkey, was modelled using three types of hydrological models and three different calibration algorithms. A well-known lumped model (GR4J), a commonly used semi-distributed (SWAT+) model, and a skillful distributed (mHM) hydrological model were built and integrated with the Parameter Estimation Tool (PEST). PEST is a model-independent calibration tool including three algorithms—namely, Levenberg Marquardt (L-M), Shuffled Complex Evolution (SCE), and Covariance Matrix Adoption Evolution Strategy (CMA-ES). The calibration period was 1991–2000, and the validation results were obtained for 2002–2005. The effect of the model structure and calibration algorithm selection on the discharge simulation was evaluated via comparison of nine different model-algorithm combinations. Results have shown that mHM and CMA-ES combination performed the best discharge simulation according to NSE values (calibration: 0.67, validation: 0.60). Although statistically the model results were classified as acceptable, the models mostly missed the peak values in the hydrograph. This problem may be related to the interventions made in 2000–2001 and may be overcome by changing the calibration and validation periods, increasing the number of iterations, or using the naturalized gauge data.

In this comprehensive study, a seven-channel ultrafiltration (UF) titania membrane was used to investigate the impact of the pulsatile cleaning process on the crossflow filtration system. Seventeen experimental runs were performed for different operating conditions with a transmembrane pressure (TMP) varying from 0.5 to 1.5 bar, a crossflow velocity (CFV) ranging from 0.5 to 1 m/s, and pulsatile parameters within an interval varying from 60 to 120 s with a duration of 0.8 s, and collecting membrane permeate flux and volume data. The optimized operating conditions revealed that a TMP of 1.5 bar, a CFV of 0.71 m/s, and a pulsatile cycle of 85 s were the best operating conditions to reach the highest steady permeability flux and volume of 302 LMH and 8.11 L, respectively. The UF ceramic membrane under the optimized inputs allowed for an oil-rejection ability of 99%. The Box–Behnken design (BBD) model was used to analyze the effect of crossflow operating conditions on the permeate flux and volume. The analysis of variance (ANOVA) indicated that the quadratic regression models were highly significant. At a 95% confidence interval, the optimum TMP significantly enhanced the flux and permeate volume simultaneously. The results also demonstrated a positive interaction between the TMP and the pulsatile process, enhancing the permeate flux with a slight impact on the permeate volume. At the same time, the interaction between the CFV and pulsatile flow improved the permeability and increased the permeate volume.

Reservoir expansion over the last century has largely affected downstream flow characteristics. Yet very little is known about the impacts of reservoir expansion on the climate. Here, we implement reservoir construction in the Community Land Model by enabling dynamical lake area changes, while conserving mass and energy. Transient global lake and reservoir extent are prescribed from the HydroLAKES and Global Reservoir and Dam databases. Land-only simulations covering the 20th century with reservoir expansion enabled, highlight increases in terrestrial water storage and decreases in albedo matching the increase in open water area. The comparison of coupled simulations including and excluding reservoirs shows only limited influence of reservoirs on global temperatures and the surface energy balance, but demonstrates substantial responses locally, in particular where reservoirs make up a large fraction of the grid cell. In those locations, reservoirs dampen the diurnal temperature range by up to −1.5 K (for reservoirs covering >15% of the grid cell), reduce temperature extremes, and moderate the seasonal temperature cycle. This study provides a first step towards a coupled representation of reservoirs in Earth System Models.

We present a comprehensive study of the mesoscale eddy forcing in the ocean by proposing spatially local filtering of the high-resolution double-gyre ocean circulation solution into its large- and small-scale (eddy) components. The large-scale component is dominated by the mid-latitude gyres, the western boundary currents and their highly transient eastward jet extension; the eddy component is concentrated around the eastward jet and strongly interacts with it. The proposed decomposition method achieves flow filtering based on the local spatial correlations. This is different from the existing decomposition methods, e.g. classical Reynolds decomposition and moving-average (spatial) filtering with a constant filter size based on the first baroclinic Rossby deformation radius. Next, we characterize the dynamical impacts of the resulting eddy forcing on the large-scale flow in terms of their mutual time-lagged spatial correlations, formulated as product integral characteristics. Its temporal statistics uncover robust causality between the eddy forcing and the induced large-scale potential vorticity anomalies – referred to as the eddy backscatter. The results also prove the significance of the transient eddy forcing and the time lag dependence of the eddy backscatter. We argue that these properties are to be considered by eddy parametrization schemes. We further used the decomposed eddy fields to augment a coarse-resolution ocean model. The augmented solution statistically reproduces the missing eastward jet extension, enhances the eddy activities around it and recovers the essential large-scale low-frequency variability. This justifies a reduced-order statistical emulation of the eddies – an emerging methodology for including eddy effects in non-eddy-resolving ocean models.

In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introduce a general optimization management tool called GloMPO (Globally Managed Parallel Optimization) to help address some of the challenges faced by practitioners. GloMPO manages and shares information between traditional optimization algorithms run in parallel. We hope that GloMPO will be a flexible framework which allows for customization and hybridization of various optimization ideas, while also providing a substitute for human interventions and decisions which are a common feature of optimization processes of hard problems. GloMPO is shown to produce lower minima than traditional optimization approaches on global optimization test functions, the Lennard-Jones cluster problem, and ReaxFF reparameterizations. The novel feature of forced optimizer termination was shown to find better minima than normal optimization. GloMPO is also shown to provide qualitative benefits such a identifying degenerate minima, and providing a standardized interface and workflow manager.

This work was funded by NERC Award NE/P011365/1 (CALISMO: Calving laws for ice sheet models) to PI Benn and NERC IRF NE/T011920/1 (Next generation projections of sea level contribution and freshwater export from the Greenland Ice Sheet) to PI Slater. This work received support from the DOMINOS project, a component of the International Thwaites Glacier Collaboration (ITGC). Support from National Science Foundation (NSF: Grant 1738896) and Natural Environment Research Council (NERC: Grant NE/S006605/1). Logistics provided by NSF-U.S. Antarctic Program and NERC British Antarctic Survey. ITGC Contribution No. ITGC-048. Quantifying the impact of submarine melting on calving is central to understanding the response of marine-terminating glaciers to ocean forcing. Modeling and observational studies suggest the potential for submarine melting to amplify calving (the calving multiplier effect), but there is little consensus as to under what conditions this occurs. Here, by viewing a marine-terminating glacier as an elastic beam, we propose an analytical basis for understanding the presence or absence of the calving multiplier effect. We show that as a terminus becomes undercut it becomes more susceptible to both serac failure (calving only of ice that is undercut, driven by vertical imbalance) and rotational failure (full thickness calving of ice behind the grounding line, driven by rotational imbalance). By deriving analytical stress thresholds for these two forms of calving, we suggest that the dominant of the two calving styles is determined principally by the shape of melt undercutting. Uniform undercutting extending from the bed to the waterline promotes serac failure and no multiplier effect, while glaciers experiencing linear undercutting that is greatest at the bed and zero at the waterline are more likely to experience rotational failure and a multiplier effect. Our study offers a quantitative framework for understanding where and when the calving multiplier effect occurs, and, therefore, a route to parameterising the effect in ice sheet-scale models. Publisher PDF

Six recent Langmuir turbulence parameterization schemes and five traditional schemes are implemented in a common single‐column modeling framework and consistently compared. These schemes are tested in scenarios versus matched large eddy simulations, across the globe with realistic forcing (JRA55‐do, WAVEWATCH‐III simulated waves) and initial conditions (Argo), and under realistic conditions as observed at ocean moorings. Traditional non‐Langmuir schemes systematically underpredict large eddy simulation vertical mixing under weak convective forcing, while Langmuir schemes vary in accuracy. Under global, realistic forcing Langmuir schemes produce 6% (−1% to 14% for 90% confidence) or 5.2 m (−0.2 m to 17.4 m for 90% confidence) deeper monthly mean mixed layer depths than their non‐Langmuir counterparts, with the greatest differences in extratropical regions, especially the Southern Ocean in austral summer. Discrepancies among Langmuir schemes are large (15% in mixed layer depth standard deviation over the mean): largest under wave‐driven turbulence with stabilizing buoyancy forcing, next largest under strongly wave‐driven conditions with weak buoyancy forcing, and agreeing during strong convective forcing. Non‐Langmuir schemes disagree with each other to a lesser extent, with a similar ordering. Langmuir discrepancies obscure a cross‐scheme estimate of the Langmuir effect magnitude under realistic forcing, highlighting limited understanding and numerical deficiencies. Maps of the regions and seasons where the greatest discrepancies occur are provided to guide further studies and observations.

An interpretation of eddy form stress via the geometry described by the Eliassen–Palm flux tensor is explored. Complimentary to previous works on eddy Reynolds stress geometry, this study shows that eddy form stress is fully described by a vertical ellipse, whose size, shape, and orientation with respect to the mean flow shear determine the strength and direction of vertical momentum transfers. Following a recent proposal, this geometric framework is here used to form a Gent–McWilliams eddy transfer coefficient that depends on eddy energy and a nondimensional geometric parameter α, bounded in magnitude by unity. The parameter α expresses the efficiency by which eddies exchange energy with baroclinic mean flow via along-gradient eddy buoyancy flux—a flux equivalent to eddy form stress along mean buoyancy contours. An eddy-resolving ocean general circulation model is used to estimate the spatial structure of α in the Southern Ocean and assess its potential to form a basis for parameterization. The eddy efficiency α averages to a low but positive value of 0.043 within the Antarctic Circumpolar Current, consistent with an inefficient eddy field extracting energy from the mean flow. It is found that the low eddy efficiency is mainly the result of that eddy buoyancy fluxes are weakly anisotropic on average. The eddy efficiency is subject to pronounced vertical structure and is maximum at ~3-km depth, where eddy buoyancy fluxes tend to be directed most downgradient. Since α partly sets the eddy form stress in the Southern Ocean, a parameterization for α must reproduce its vertical structure to provide a faithful representation of vertical stress divergence and eddy forcing.

This paper describes the initial implementation of a new toolbox that seeks to balance accuracy, efficiency, and flexibility in radiation calculations for dynamical models. The toolbox consists of two related code bases: Radiative Transfer for Energetics (RTE), which computes fluxes given a radiative transfer problem defined in terms of optical properties, boundary conditions, and source functions; and RRTM for General circulation model applications—Parallel (RRTMGP), which combines data and algorithms to map a physical description of the gaseous atmosphere into such a radiative transfer problem. The toolbox is an implementation of well‐established ideas, including the use of a k‐distribution to represent the spectral variation of absorption by gases and the use of two‐stream, plane‐parallel methods for solving the radiative transfer equation. The focus is instead on accuracy, by basing the k‐distribution on state‐of‐the‐art spectroscopy and on the sometimes‐conflicting goals of flexibility and efficiency. Flexibility is facilitated by making extensive use of computational objects encompassing code and data, the latter provisioned at runtime and potentially tailored to specific problems. The computational objects provide robust access to a set of high‐efficiency computational kernels that can be adapted to new computational environments. Accuracy is obtained by careful choice of algorithms and through tuning and validation of the k‐distribution against benchmark calculations. Flexibility with respect to the host model implies user responsibility for maps between clouds and aerosols and the radiative transfer problem, although comprehensive examples are provided for clouds., Key Points RTE+RRTMGP is a new freely available toolbox for radiation calculations for dynamical modelsRTE+RRTMGP seeks to balance accuracy, efficiency, and flexibility, defined expansivelyBoth code and data continue to evolve to explore different balances among these goals

Seersucker woven fabrics are increasingly used in the textile industry. Unfortunately, their popularity is limited due to the lack of standards and parameterization of their structure. Thus, the designer of the finished product (clothing, bedding, or decorative items) has problems with ordering a fabric with a specific structure and properties. In this context, it is necessary to parameterize them. This paper presents a method for measuring the surface geometry of seersucker woven fabrics using laser techniques. The surface geometry of the seersucker woven fabric was determined using adapted roughness parameters, such as Wz, Ra, and Rz, as well as by using a hypsometric map.

This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from −0.4 to −0.9 W m−2. The standard deviation in annual ERF is 0.3 W m−2, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is −0.54 W m−2 for the pre-industrial era to the mid-1970s and −0.59 W m−2 for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.

© 2019 Author(s). The adverse impacts of urban heat and global climate change are leading policymakers to consider green and blue infrastructure (GBI) for heat mitigation benefits. Though many models exist to evaluate the cooling impacts of GBI, their complexity and computational demand leaves most of them largely inaccessible to those without specialist expertise and computing facilities. Here a new model called The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is presented. TARGET is designed to be efficient and easy to use, with fewer user-defined parameters and less model input data required than other urban climate models. TARGET can be used to model average street-level air temperature at canyon-to-block scales (e.g. 100 m resolution), meaning it can be used to assess temperature impacts of suburb-to-city-scale GBI proposals. The model aims to balance realistic representation of physical processes and computation efficiency. An evaluation against two different datasets shows that TARGET can reproduce the magnitude and patterns of both air temperature and surface temperature within suburban environments. To demonstrate the utility of the model for planners and policymakers, the results from two precinct-scale heat mitigation scenarios are presented. TARGET is available to the public, and ongoing development, including a graphical user interface, is planned for future work. ispartof: GEOSCIENTIFIC MODEL DEVELOPMENT vol:12 issue:2 pages:785-803 status: published

Commonly used disdrometers tend not to accurately measure concentrations of very small drops in the raindrop size distribution (DSD), either through truncation of the DSD at the small-drop end or because of large uncertainties on these measurements. Recent studies have shown that, as a result of these inaccuracies, many if not most ground-based disdrometers do not capture the “drizzle mode” of precipitation, which consists of large concentrations of small drops and is often separated from the main part of the DSD by a shoulder region. We present a technique for reconstructing the drizzle mode of the DSD from “incomplete” measurements in which the drizzle mode is not present. Two statistical moments of the DSD that are well measured by standard disdrometers are identified and used with a double-moment normalized DSD function that describes the DSD shape. A model representing the double-moment normalized DSD is trained using measurements of DSD spectra that contain the drizzle mode obtained using collocated Meteorological Particle Spectrometer and 2D video disdrometer instruments. The best-fitting model is shown to depend on temporal resolution. The result is a method to estimate, from truncated or uncertain measurements of the DSD, a more complete DSD that includes the drizzle mode. The technique reduces bias on low-order moments of the DSD that influence important bulk variables such as the total drop concentration and mass-weighted mean drop diameter. The reconstruction is flexible and often produces better rain-rate estimations than a previous DSD correction routine, particularly for light rain.

Oceanic mesoscale currents (‘eddies’) can have significant effects on the distributions of passive tracers. The associated inhomogeneous and anisotropic eddy fluxes are traditionally parametrised using a transport tensor (K-tensor), which contains both diffusive and advective components. In this study, we analyse the eddy transport tensor in a quasigeostrophic double-gyre flow. First, the flow and passive tracer fields are decomposed into large- and small-scale (eddy) components by spatial filtering, and the resulting eddy forcing includes an eddy tracer flux representing advection by eddies and non-advective terms. Second, we use the flux-gradient relation between the eddy fluxes and the large-scale tracer gradient to estimate the associated K-tensors in their entire structural, spatial and temporal complexity, without making any additional assumptions or simplifications. The divergent components of the eddy tracer fluxes are extracted via the Helmholtz decomposition, which yields a divergent tensor. The remaining rotational flux does not affect the tracer evolution, but dominates the total tracer flux, affecting both its magnitude and spatial structure. However, in terms of estimating the eddy forcing, the transport tensor prevails over its divergent counterpart because of the significant numerical errors induced by the Helmholtz decomposition. Our analyses demonstrate that, in general, the K-tensor for the eddy forcing is not unique, that is, it is tracer-dependent. Our study raises serious questions on how to interpret and use various estimates of K-tensors obtained from either observations or eddy-resolving model solutions.

This study examines the influence of flow nonlinearity in western boundary layers upon the turbulent wind-driven ocean gyres. Our analysis involves comparisons between large-scale circulation properties of the linear and nonlinear states, as well as a Lagrangian particle analysis of relevant flow features. We find that the so-called counter-rotating gyre anomalies, which are nonlinear circulation features embedded in the gyres, are consistent in shape with the linear, weakened, wind-curl response created by the geometric wind effect. However, the linear response is far too weak without considering nonlinear effects. Within the western boundary layer lobe of these features, the nonlinear boundary layer has a pivotal impact upon the global circulation. Effects of potential vorticity advection inhibit viscous relative vorticity fluxes through the western boundary. This creates a significant potential vorticity imbalance between the gyres. Consequently, this generates an accumulation of enstrophy downstream in the inertial recirculation zones, which in turn supports the eastward jet. However, within the ocean basin, the growing imbalance is eventually rectified by inter-gyre potential vorticity exchanges owing to nonlinear fluxes. The Lagrangian particle analysis reveals the inter-gyre exchange mechanism, where particles seeded within the western boundary layer migrate between the gyres and weaken the eastward jet extension.

Interfaces at the edge of an idealised, non-precipitating, warm cloud are studied using Direct Numerical Simulation (DNS) complemented with a Lagrangian particle tracking routine. Once a shell has formed, four zones can be distinguished: the cloud core, visible shell, invisible shell and the environment. The union of the visible and invisible regions is the shell commonly referred to in literature. The boundary between the invisible shell and the environment is the Turbulent-NonTurbulent Interface (TNTI) which is typically not considered in cloud studies. Three million particles were seeded homogeneously across the domain and properties were recorded along individual trajectories. The results demonstrate that the traditional cloud boundary (separating cloudy and non-cloudy regions using thresholds applied on liquid condensate or updraft velocity) are some distance away from the TNTI. Furthermore, there is no dynamic difference between the traditional liquid-condensate boundary and the region extending to the TNTI. However, particles crossing the TNTI exhibit a sharp jump in enstrophy and a smooth increase in buoyancy. The traditional cloud boundary coincides with the location of minimum buoyancy in the shell. The shell pre-mixes the entraining and detraining air and analysis reveals a highly skewed picture of entrainment and detrainment at the traditional cloud boundary. A preferential entrainment of particles with velocity and specific humidity higher than the mean values in the shell is observed. Large-eddy simulation of a more realistic setup detects an interface with similar properties using the same thresholds as in the DNS, indicating that the DNS results extrapolate beyond their idealised conditions.

With this work, we present a protocol for the parameterization of a Linear Vibronic Coupling (LVC) Hamiltonian for quantum dynamics using highly accurate multiconfigurational electronic structure methods such as RASPT2/RASSCF, combined with a maximum-overlap diabatization technique. Our approach is fully portable and can be applied to many medium-size rigid molecules whose excited state dynamics requires a quantum description. We present our model and discuss the details of the electronic structure calculations needed for the parameterization, analyzing critical situations that could arise in the case of strongly interacting excited states. The protocol was applied to the simulation of the excited state dynamics of the pyrene molecule, starting from either the first or the second bright state (S2 or S5). The LVC model was benchmarked against state-of-the-art quantum mechanical calculations with optimizations and energy scans and turned out to be very accurate. The dynamics simulations, performed including all active normal coordinates with the multilayer multiconfigurational time-dependent Hartree method, show good agreement with the available experimental data, endorsing prediction of the excited state mechanism, especially for S5, whose ultrafast deactivation mechanism was not yet clearly understood.

Changes to physical and mechanical properties of pyroclastic flow deposits occur during welding process, resulting from overburden pressure and temperature. A great deal of research has been carried out to identify which physical parameters can enable quantification of the degree of welding within pyroclastic deposits. Material properties, such as density, porosity, hardness, abrasion, and compressive and flexural strength, are critical in assessing the suitability of natural stone as a building material, but they have not been sufficiently integrated. Therefore, an attempt has been made to develop a welding classification which integrates measurements of material properties with petrographic and textural observations. The proposed classification covers physical, index, and strength parameters for pyroclastic flow deposits. The most important aspect of this investigation has been the quantification of material parameters and definition of a welding classification applicable to a wide range of ignimbrites, from nonwelded to densely welded, that are used as natural building stone. This welding classification is proposed to ensure a consistent approach in characterizing key aspects of welded facies in pyroclastic deposits and in the identification of natural stone reserves. © 2021, Saudi Society for Geosciences.

International audience; Mapping a triangulated surface to 2D space (or a tetrahedral mesh to 3D space) is the most fundamental problem in geometry processing. In computational physics, untangling plays an important role in mesh generation: it takes a mesh as an input, and moves the vertices to get rid of foldovers. In fact, mesh untangling can be considered as a special case of mapping where the geometry of the object is to be defined in the map space and the geometric domain is not explicit, supposing that each element is regular. In this paper, we propose a mapping method inspired by the untangling problem and compare its performance to the state of the art.The main advantage of our method is that the untangling aims at producing locally injective maps, which is the major challenge of mapping. In practice, our method produces locally injective maps in very difficult settings, and with less distortion than the previous work, both in 2D and 3D. We demonstrate it on a large reference database as well as on more difficult stress tests. For a better reproducibility, we publish the code in Python for a basic evaluation, and in C++ for more advanced applications.

Объектом исследования является микроструктура деталей из серого чугуна, подвергнутых различным методам поверхностного пластического деформирования; выбор оптимальных технологических параметров поверхностного пластического деформирования для повышения надежности., The object of the study is the microstructure of gray cast iron parts subjected to various methods of surface plastic deformation; selection of optimal technological parameters for surface plastic deformation to improve reliability is discussed.