The National Forest Soil Inventory (NFSI) provides the Greenhouse Gas Reporting in Germany with a quantitative assessment of organic carbon (C) stocks and changes in forest soils. Carbon stocks of ...the organic layer and the mineral topsoil (30 cm) were estimated on the basis of ca. 1.800 plots sampled from 1987 to 1992 and resampled from 2006 to 2008 on a nationwide grid of 8 × 8 km. Organic layer C stock estimates were attributed to surveyed forest stands and CORINE land cover data. Mineral soil C stock estimates were linked with the distribution of dominant soil types according to the Soil Map of Germany (1 : 1 000 000) and subsequently related to the forest area. It appears that the C pool of the organic layer was largely depending on tree species and parent material, whereas the C pool of the mineral soil varied among soil groups. We identified the organic layer C pool as stable although C was significantly sequestered under coniferous forest at lowland sites. The mineral soils, however, sequestered 0.41 Mg C ha⁻¹ yr⁻¹. Carbon pool changes were supposed to depend on stand age and forest transformation as well as an enhanced biomass input. Carbon stock changes were clearly attributed to parent material and soil groups as sandy soils sequestered higher amounts of C, whereas clayey and calcareous soils showed small gains and in some cases even losses of soil C. We further showed that the largest part of the overall sample variance was not explained by fine‐earth stock variances, rather by the C concentrations variance. The applied uncertainty analyses in this study link the variability of strata with measurement errors. In accordance to other studies for Central Europe, the results showed that the applied method enabled a reliable nationwide quantification of the soil C pool development for a certain period.
The radon-deficit technique is a powerful tool to detect and delineate sub-surface accumulations of organic contaminants. Field measurements of 222Rn in soil air, however, are affected by several ...confounding factors that can lead to the misinterpretation of results. Among the most influential are: vertical and lateral changes of lithology, fluctuating contaminant saturations with depth, varying water saturation ratios along the soil profile and atmospheric (and, therefore, soil) thermal oscillations. To evaluate and minimize the effect of these confounding factors on the interpretation of the results of the Rn deficit technique, a Matlab® based multi-layer model of 222Rn production-partition-diffusion in unsaturated porous media (1D_RnDPM: One-Dimensional 222Rn Diffusion and Partition Model) has been developed and is freely available as Supplementary Material in this work. A laboratory protocol has also been proposed to obtain site-specific input parameters for the model, i.e., 222Rn equilibrium concentration (as determined by the accumulation chamber method), soil bulk density and soil solid-phase density. The model predictions have been contrasted with field information obtained from successive sampling campaigns in which 222Rn in soil air was measured at a site where the vadose zone, consisting of an anthropogenic backfill underlain by a silt layer, is affected by a complex mixture of benzene, phenol, (poly) chlorobenzenes, (poly) chlorophenols and hexachlorocyclohexane isomers, among other compounds. The model has successfully predicted the vertical profile of 222Rn concentrations in soil air, including the effect of the oscillations of the water table and of ground-level temperature. The results also underline that 222Rn measurements in subsoil air are representative only of local conditions around the sampling point, an expected result given that 222Rn maximum effective diffusion length is very limited. As a consequence, the influence of a highly fluctuating water table at the site goes undetected at the sampling depths used in the field campaigns.
The combination of a numerical model and a laboratory protocol allows to predict the activity of 222Rn along the soil profile and to assess the influence of site-specific confounding factors.
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•A numerical model of 222Rn production-partition-diffusion has been developed.•The numerical code is freely available and user-adaptable.•Combining laboratory and numerical simulation improves 222Rn deficit interpretation.•Key factors in the application of the 222Rn deficit technique have been identified.
The Medical Research Council published the second edition of its framework in 2006 on developing and evaluating complex interventions. Since then, there have been considerable developments in the ...field of complex intervention research. The objective of this project was to update the framework in the light of these developments. The framework aims to help research teams prioritise research questions and design, and conduct research with an appropriate choice of methods, rather than to provide detailed guidance on the use of specific methods.
There were four stages to the update: (1) gap analysis to identify developments in the methods and practice since the previous framework was published; (2) an expert workshop of 36 participants to discuss the topics identified in the gap analysis; (3) an open consultation process to seek comments on a first draft of the new framework; and (4) findings from the previous stages were used to redraft the framework, and final expert review was obtained. The process was overseen by a Scientific Advisory Group representing the range of relevant National Institute for Health Research and Medical Research Council research investments.
Key changes to the previous framework include (1) an updated definition of complex interventions, highlighting the dynamic relationship between the intervention and its context; (2) an emphasis on the use of diverse research perspectives: efficacy, effectiveness, theory-based and systems perspectives; (3) a focus on the usefulness of evidence as the basis for determining research perspective and questions; (4) an increased focus on interventions developed outside research teams, for example changes in policy or health services delivery; and (5) the identification of six 'core elements' that should guide all phases of complex intervention research: consider context; develop, refine and test programme theory; engage stakeholders; identify key uncertainties; refine the intervention; and economic considerations. We divide the research process into four phases: development, feasibility, evaluation and implementation. For each phase we provide a concise summary of recent developments, key points to address and signposts to further reading. We also present case studies to illustrate the points being made throughout.
The framework aims to help research teams prioritise research questions and design and conduct research with an appropriate choice of methods, rather than to provide detailed guidance on the use of specific methods. In many of the areas of innovation that we highlight, such as the use of systems approaches, there are still only a few practical examples. We refer to more specific and detailed guidance where available and note where promising approaches require further development.
This new framework incorporates developments in complex intervention research published since the previous edition was written in 2006. As well as taking account of established practice and recent refinements, we draw attention to new approaches and place greater emphasis on economic considerations in complex intervention research. We have introduced a new emphasis on the importance of context and the value of understanding interventions as 'events in systems' that produce effects through interactions with features of the contexts in which they are implemented. The framework adopts a pluralist approach, encouraging researchers and research funders to adopt diverse research perspectives and to select research questions and methods pragmatically, with the aim of providing evidence that is useful to decision-makers.
We call for further work to develop relevant methods and provide examples in practice. The use of this framework should be monitored and the move should be made to a more fluid resource in the future, for example a web-based format that can be frequently updated to incorporate new material and links to emerging resources.
This project was jointly funded by the Medical Research Council (MRC) and the National Institute for Health Research (Department of Health and Social Care 73514).
Axial compressors are susceptible to uncertainties during their manufacturing and operation, resulting in reduced efficiency and performance dispersion. However, uncertainty quantification and robust ...design of compressors remains challenging due to the complexity of structure and internal flow. In this study, an automated framework for uncertainty quantification and robustness optimization of micro axial compressors is proposed. Ten geometrical uncertainties are propagated for the nominal design point and two off-design points, i.e., near stall and choke conditions, respectively. The main objective of this paper is to optimize the aerodynamic robustness performance at these operating points. The sparse grid-based probabilistic collocation method is used to propagate these uncertainties, and a multi-objective genetic algorithm is employed to perform robust optimization based on a novel constructed surrogate model.
The results show that the optimal configuration achieves an improvement in aerodynamic robustness and mean performance across the entire characteristic map, with greater improvement at the design working point than at the off-design points. At the design working point, the mean isentropic efficiency and pressure ratio of the optimal configuration increase by 0.6% and 0.5%, respectively, while the standard deviation of isentropic efficiency, pressure ratio, and mass flow rate decreases by 32.4%, 41.2%, and 25.1%, respectively. This optimization framework proves to be both feasible and efficient and can be applied to aerodynamic robust optimization of turbomachinery. In the future, we will apply this framework to different aspects of the gas turbine life cycle to model and analyze uncertainties of larger orders of magnitude.
•A framework for uncertainty qualification and robust optimization of a micro compressor is established.•The SOM model visualizes the correlations between uncertain variables and performance responses.•The constructed SOM-RBF-NSGA-III successfully achieves multi-objective robust optimization.•Optimizing the performance parameters of a micro compressor at three working conditions.
This paper proposes a level set-based robust topology optimization (RTO) method for computational design of metamaterials under hybrid uncertainties, e.g. auxetics with negative Poisson’s ratio, ...where the Young’s modulus of the solid is described as a random variable while the Poisson’s ratio is regarded as an interval variable. Firstly, the robust objective function is formulated by a combination of interval mean and interval variance of the deterministic objective function. Secondly, the interval mean and interval variance are computed by a hybrid uncertain analysis approach, termed as Polynomial Chaos-Chebyshev Interval (PCCI) method. Thirdly, the design sensitivities of the robust objective function are obtained after the implementation of the PCCI method. Finally, a powerful parametric level set method (PLSM) in conjunction with the numerical homogenization method is applied to achieve the robust topological design for the auxetic microstructure. Several numerical cases are used to demonstrate the effectiveness of the proposed method for the robust topology optimization problems. This method is non-intrusive and general, and can be easily extended to a range of design problems of micro-structured metamaterials.
•Level-set topology optimization method for auxetic metamaterials under hybrid uncertainties.•Interval and random variables accounting for the formulation of robust topology optimization.•Polynomial Chaos-Chebyshev Interval (PCCI) method for analysis of interval mean and variance.•Sensitivities of the robust objective function are obtained after the implementation of the PCCI method.•Parametric Level Set Method to achieve topological shape changes of the auxetic microstructure.
XPS study of the nitridation of hafnia on silicon Mayorga-Garay, Marisol; Cortazar-Martinez, Orlando; Torres-Ochoa, Jorge Alejandro ...
Applied surface science,
12/2024, Letnik:
678
Journal Article
Recenzirano
Odprti dostop
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•Hf 4f peaks identified for hafnia, hafnium silicate, and their nitrided forms.•The composition of nitrided hafnia is HfO1.66N0.33.•A Si2+-2N1- dipole layer at the interface causes a ...shift of the spectra.•Saturation shows that excited N2+ ions are the nitridation agent for hafnia.•Hafnium silicate nitrides sooner than hafnia in HfO2/Si structures.•Lower plasma pressure enhances the nitridation of hafnia.
We report a comprehensive quantitative ARXPS study of 20-cycle ALD-grown HfO2 films on Si (001) substrates with and without remote plasma nitridation. The films comprised a 0.6 nm HfO2 layer atop a 1 nm hafnium-rich silicate interlayer. A detailed analysis of the Hf 4f, Si 2p, O 1s, C 1s, and N 1s core level spectra is presented for samples with and without nitridation. The fitting of the Hf 4f spectra reveals four contributing components associated with silicate, hafnia, and their respective nitrided species. The Hf 4f, O 1s, and C 1s spectra exhibit a negative binding energy shift of about 0.2 eV upon nitridation induced by a Si2+-N dipole formed at the interface. Quantitative ARXPS analysis, employing the MultiLayer Model, enabled the determination of the thicknesses, and composition together with their associated uncertainties. The analysis showed that the composition of the nitrided hafnia is HfO1.66N0.33. There is a higher degree of nitridation in the silicate interlayer compared to the overlying hafnia layer. The degree of nitridation is found to increase with plasma power; N2+ is identified as the primary plasma species responsible for the nitridation of hafnia.
Uncertainty propagation of the frequency response function is crucial for vibration problems such as model calibration, and the probability assessment is another indispensable item in structural ...optimization. Considering only one of them will inevitably lead to a lack of uncertain knowledge of practical engineering structures. However, it is still challenging to evaluate the system response bounds and probability characteristics simultaneously and maximally reduce the computational cost. This paper focuses on the frequency response function involving correlated uncertainties and proposes a novel uncertainty propagation and probability assessment method. First, a convex model was established to quantify the correlated uncertainty parameters, and then, the Chebyshev polynomial function was developed as the surrogate model to efficiently quantify the uncertainty propagation from uncertainty parameters to system response. Subsequently, the novel normalized and coordinated transformation combined the uncertainty propagation method, making the uncertainty system response easy to assess. Note that the response value at the interpolation point can be employed as the input of probability assessment. One can also estimate the probability characteristics at different frequency positions during the construction of the surrogate model. Finally, two numerical examples were presented to demonstrate the effectiveness and cheaper computation by a discrete system and a continuous system, respectively. Results indicate that the proposed method can be conveniently and accurately applied to assess the bounds and probability characteristics of frequency response function involving correlated uncertainties.
•Concurrent topology optimization for multiscale dynamic composite structures.•A hybrid dimensional reduction method to estimate interval mean and variance.•A new robust topology optimization method ...under random-interval hybrid uncertainties.•Robust objective function defined as a weighted sum of mean and standard variance.
A new robust topology optimization method based on level sets is developed for the concurrent design of dynamic structures composed of uniform periodic microstructures subject to random and interval hybrid uncertainties. A Hybrid Dimensional Reduction (HDR) method is proposed to estimate the interval mean and the interval variance of the uncertain objective function based on a bivariate dimension reduction scheme. The robust objective function is defined as a weighted sum of the mean and standard variance of the dynamic compliance under the worst case. The sensitivity information of the robust objective function with respect to the macro and micro design variables can then be obtained after the uncertainty analysis. Several examples are used to validate the effectiveness of the proposed robust topology optimization method.
High-accuracy numerical method for uncertainty propagation analysis is a crucial issue in the field of structural reliability design. In this work, a novel iterative algorithm is proposed to study ...the free vibration of the functionally graded (FG) thin plates with material uncertainties. As a highly accurate approach distinct from the existing non-iterative model, the frequency analysis of FG thin plates can be achieved by updating the lower and upper bounds of natural frequency step by step. Based on the classic plate theory, the governing equations of the FG thin plate resting on an elastic medium are derived and the analytical formulation for the natural frequency is presented. By introducing interval parameters to quantify the material uncertainties, a non-probabilistic model for evaluating the natural frequency response of the embedded FG thin plate is developed. Subsequently, the deduction of the novel iterative algorithm for solving the non-probabilistic model is given based on interval mathematics. The developed model and the proposed iterative algorithm are validated by the Monte Carlo method, and then the detailed parametric studies are carried out to explore the combined influences of material uncertainties, power-law index, and elastic foundation parameters, as well as size parameters on the natural frequency of the FG thin plate. Numerical results can provide useful guidance in the precise design of FG structures.
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