scholarly journals On the loading and unloading of metal-to-metal seals: A two-scale stochastic approach

2018 ◽  
Vol 232 (12) ◽  
pp. 1525-1537 ◽  
Author(s):  
Francesc Pérez-Ràfols ◽  
Roland Larsson ◽  
Egbert J van Riet ◽  
Andreas Almqvist
Keyword(s):  
Plastic Deformation ◽  
Beneficial Effect ◽  
Stochastic Approach ◽  
Global Scale ◽  
Scale Model ◽  
Real Situation ◽  
Metal Seal ◽  
Flow Through ◽  
Loading And Unloading ◽  
Stochastic Element

During operation, the mating surfaces of a metal-to-metal seal typically undergo significant plastic deformation, which in turn can have beneficial effect on its performance. In previous studies, it has, for instance, been shown that plastic deformation can provide for better sealing during unloading. Those studies did, however, only consider flow through unrealistically small domains. Therefore, it is possible that this might be a size effect, which would not be apparent in a real situation with a much larger domain. In this paper, we develop a model which can handle real-sized seal domains at the same time as fine details of the surface topography. More precisely, we construct a two-scale model, in which the global scale represents the seal domain and where the influence of the fine details at the local scale are represented by a stochastic element. By means of this stochastic two-scale model, we show that the beneficial effect associated with the plastic deformation persists also when real-sized seal domains are considered.

scholarly journals A stochastic two-scale model for pressure-driven flow between rough surfaces

2016 ◽  
Vol 472 (2190) ◽  
pp. 20160069 ◽  
Author(s):  
Francesc Pérez-Ràfols ◽  
Roland Larsson ◽  
Staffan Lundström ◽  
Peter Wall ◽  
Andreas Almqvist
Keyword(s):  
Flow Pattern ◽  
Present Model ◽  
Global Scale ◽  
Local Scale ◽  
Scale Model ◽  
Small Domain ◽  
Small Flow ◽  
Pressure Driven Flow ◽  
Stochastic Element ◽  
Scale Roughness

Seal surface topography typically consists of global-scale geometric features as well as local-scale roughness details and homogenization-based approaches are, therefore, readily applied. These provide for resolving the global scale (large domain) with a relatively coarse mesh, while resolving the local scale (small domain) in high detail. As the total flow decreases, however, the flow pattern becomes tortuous and this requires a larger local-scale domain to obtain a converged solution. Therefore, a classical homogenization-based approach might not be feasible for simulation of very small flows. In order to study small flows, a model allowing feasibly-sized local domains, for really small flow rates, is developed. Realization was made possible by coupling the two scales with a stochastic element. Results from numerical experiments, show that the present model is in better agreement with the direct deterministic one than the conventional homogenization type of model, both quantitatively in terms of flow rate and qualitatively in reflecting the flow pattern.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

scholarly journals Carbon monoxide (CO) and ethane (C<sub>2</sub>H<sub>6</sub>) trends from ground-based solar FTIR measurements at six European stations, comparison and sensitivity analysis with the EMEP model

2011 ◽  
Vol 11 (17) ◽  
pp. 9253-9269 ◽  
Author(s):  
J. Angelbratt ◽  
J. Mellqvist ◽  
D. Simpson ◽  
J. E. Jonson ◽  
T. Blumenstock ◽  
...  
Keyword(s):  
Transport Model ◽  
Global Scale ◽  
Global Model ◽  
Scale Model ◽  
Chemical Transport Model ◽  
Suitable Alternative ◽  
European Model ◽  
Time Period ◽  
Volatile Organic ◽  
Made In

Abstract. Trends in the CO andC2H6 partial columns ~0–15 km) have been estimated from four European ground-based solar FTIR (Fourier Transform InfraRed) stations for the 1996–2006 time period. The CO trends from the four stations Jungfraujoch, Zugspitze, Harestua and Kiruna have been estimated to −0.45 ± 0.16% yr−1, −1.00 ± 0.24% yr−1, −0.62 ± 0.19 % yr−1 and −0.61 ± 0.16% yr−1, respectively. The corresponding trends for C2H6 are −1.51 ± 0.23% yr−1, −2.11 ± 0.30% yr−1, −1.09 ± 0.25% yr−1 and −1.14 ± 0.18% yr−1. All trends are presented with their 2-σ confidence intervals. To find possible reasons for the CO trends, the global-scale EMEP MSC-W chemical transport model has been used in a series of sensitivity scenarios. It is shown that the trends are consistent with the combination of a 20% decrease in the anthropogenic CO emissions seen in Europe and North America during the 1996–2006 period and a 20% increase in the anthropogenic CO emissions in East Asia, during the same time period. The possible impacts of CH4 and biogenic volatile organic compounds (BVOCs) are also considered. The European and global-scale EMEP models have been evaluated against the measured CO and C2H6 partial columns from Jungfraujoch, Zugspitze, Bremen, Harestua, Kiruna and Ny-Ålesund. The European model reproduces, on average the measurements at the different sites fairly well and within 10–22% deviation for CO and 14–31% deviation for C2H6. Their seasonal amplitude is captured within 6–35% and 9–124% for CO and C2H6, respectively. However, 61–98% of the CO and C2H6 partial columns in the European model are shown to arise from the boundary conditions, making the global-scale model a more suitable alternative when modeling these two species. In the evaluation of the global model the average partial columns for 2006 are shown to be within 1–9% and 37–50% of the measurements for CO and C2H6, respectively. The global model sensitivity for assumptions made in this paper is also analyzed.

A FRACTAL SCALING LAW BETWEEN TORTUOSITY AND POROSITY IN POROUS MEDIA

Fractals ◽  
2020 ◽  
Vol 28 (02) ◽  
pp. 2050025
Author(s):  
PENG XU ◽  
LIPEI ZHANG ◽  
BINQI RAO ◽  
SHUXIA QIU ◽  
YUQING SHEN ◽  
...  
Keyword(s):  
Porous Media ◽  
Chemical Engineering ◽  
Oil And Gas ◽  
Scaling Law ◽  
Morphological Characteristics ◽  
Fractal Model ◽  
Statistical Characteristics ◽  
Scale Model ◽  
Reservoir Water ◽  
Flow Through

Hydraulic tortuosity is one of the key parameters for evaluating effective transport properties of natural and artificial porous media. A pore-scale model is developed for fluid flow through porous media based on fractal geometry, and a novel analytical tortuosity–porosity correlation is presented. Numerical simulations are also performed on two-dimensional Sierpinski carpet model. The proposed fractal model is validated by comparison with numerical results and available experimental data. Results show that hydraulic tortuosity depends on both statistical and morphological characteristics of porous media. The exponents for the scaling law between tortuosity and porosity depend on pore size distribution and tortuous fractal dimension. It has been found that hydraulic tortuosity indicates evident anisotropy for asymmetrical particle arrangements under the same statistical characteristics of porous media. The present work may be helpful to understand the transport mechanisms of porous materials and provide guidelines for the development of oil and gas reservoir, water resource and chemical engineering, etc.

scholarly journals A global comparison of grassland biomass responses to CO 2 and nitrogen enrichment

2010 ◽  
Vol 365 (1549) ◽  
pp. 2047-2056 ◽  
Author(s):  
Mark Lee ◽  
Pete Manning ◽  
Janna Rist ◽  
Sally A. Power ◽  
Charles Marsh
Keyword(s):  
Large Scale ◽  
Meta Analysis ◽  
C Sequestration ◽  
Global Scale ◽  
Scale Model ◽  
Published Data ◽  
Climate Data ◽  
Forage Production ◽  
Global Comparison ◽  
N Enrichment

Grassland ecosystems cover vast areas of the Earth's surface and provide many ecosystem services including carbon (C) storage, biodiversity preservation and the production of livestock forage. Predicting the future delivery of these services is difficult, because widespread changes in atmospheric CO 2 concentration, climate and nitrogen (N) inputs are expected. We compiled published data from global change driver manipulation experiments and combined these with climate data to assess grassland biomass responses to CO 2 and N enrichment across a range of climates. CO 2 and N enrichment generally increased aboveground biomass (AGB) but effects of CO 2 enrichment were weaker than those of N. The response to N was also dependent on the amount of N added and rainfall, with a greater response in high precipitation regions. No relationship between response to CO 2 and climate was detected within our dataset, thus suggesting that other site characteristics, e.g. soils and plant community composition, are more important regulators of grassland responses to CO 2 . A statistical model of AGB response to N was used in conjunction with projected N deposition data to estimate changes to future biomass stocks. This highlighted several potential hotspots (e.g. in some regions of China and India) of grassland AGB gain. Possible benefits for C sequestration and forage production in these regions may be offset by declines in plant biodiversity caused by these biomass gains, thus necessitating careful management if ecosystem service delivery is to be maximized. An approach such as ours, in which meta-analysis is combined with global scale model outputs to make large-scale predictions, may complement the results of dynamic global vegetation models, thus allowing us to form better predictions of biosphere responses to environmental change.

scholarly journals The origins of modern biodiversity on land

2010 ◽  
Vol 365 (1558) ◽  
pp. 3667-3679 ◽  
Author(s):  
Michael J. Benton
Keyword(s):  
Regional Scale ◽  
Global Scale ◽  
Scale Model ◽  
Time Range ◽  
Geological Time ◽  
New Methods ◽  
Evolution Of Life ◽  
History Of ◽  
Extinction Events ◽  
Mass Extinction Events

Comparative studies of large phylogenies of living and extinct groups have shown that most biodiversity arises from a small number of highly species-rich clades. To understand biodiversity, it is important to examine the history of these clades on geological time scales. This is part of a distinct ‘phylogenetic expansion’ view of macroevolution, and contrasts with the alternative, non-phylogenetic ‘equilibrium’ approach to the history of biodiversity. The latter viewpoint focuses on density-dependent models in which all life is described by a single global-scale model, and a case is made here that this approach may be less successful at representing the shape of the evolution of life than the phylogenetic expansion approach. The terrestrial fossil record is patchy, but is adequate for coarse-scale studies of groups such as vertebrates that possess fossilizable hard parts. New methods in phylogenetic analysis, morphometrics and the study of exceptional biotas allow new approaches. Models for diversity regulation through time range from the entirely biotic to the entirely physical, with many intermediates. Tetrapod diversity has risen as a result of the expansion of ecospace, rather than niche subdivision or regional-scale endemicity resulting from continental break-up. Tetrapod communities on land have been remarkably stable and have changed only when there was a revolution in floras (such as the demise of the Carboniferous coal forests, or the Cretaceous radiation of angiosperms) or following particularly severe mass extinction events, such as that at the end of the Permian.

Editorial overview: Water quality: A new challenge for global scale model development and application

2019 ◽  
Vol 36 ◽  
pp. A1-A5 ◽  
Author(s):  
Nynke Hofstra ◽  
Carolien Kroeze ◽  
Martina Flörke ◽  
Michelle TH van Vliet
Keyword(s):  
Water Quality ◽  
Model Development ◽  
Global Scale ◽  
Scale Model

Hydrodynamic Analysis of Macroalgae Local Model Using Computational Fluid Dynamics

2020 ◽  
Author(s):  
Ming Chen ◽  
Solomon C. Yim ◽  
Daniel Cox ◽  
Zhaoqing Yang ◽  
Thomas Mumford
Keyword(s):  
Fluid Dynamics ◽  
Experimental Data ◽  
Computational Fluid Dynamics ◽  
Current Model ◽  
Global Scale ◽  
Local Scale ◽  
Constant Current ◽  
Scale Model ◽  
Effective Diameter ◽  
Hydrodynamic Coefficients

Abstract In this article, a local scale, fully nonlinear coupled fluid-structural interaction (FSI) sugar kelp model has been developed using a computational fluid dynamics (CFD) method. In this model, to be consistent with available experimental data, the sugar kelp is approximated as elongated rectangles with smoothed isosceles triangles at the ends and a single kelp model with one end fixed in a channel with constant current model is developed. Several different current speeds are simulated, and the resulting drag forces and calculated drag coefficients are validated by comparison with experimental data from the literature. In a previous study, a global scale model was developed using a computational structural dynamics (CSD) method to simulate macroalgae farming system and guide the system configuration design. In the global scale model, the hydrodynamic forces are calculated using Morison’s equation and the kinematics and dynamics of the sugar kelp are simplified and the group of kelps attached to the long line is modeled as a slender structure with the same length and an effective diameter such that the volumes are consistent with the real physical system. This simplified model matches the weight and buoyancy but adjusting the hydrodynamic properties when the general hydrodynamic coefficients are employed. Therefore, optimal hydrodynamic coefficients used in global scale model were determined to obtain the hydrodynamic force more accurately. The validated local scale model is then be applied to determine the hydrodynamic coefficients of the simplified sugar kelp model for global dynamic analysis.

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