A Coupled Model for the Prediction of Surface Variation in Face Milling Large-Scale Workpiece With Complex Geometry

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Shun Liu ◽  
Sun Jin ◽  
Xue-Ping Zhang ◽  
Kun Chen ◽  
Ang Tian ◽  
...  
Keyword(s):  
Large Scale ◽  
Coupled Model ◽  
Prediction Method ◽  
Face Milling ◽  
Milling Force ◽  
Important Indicator ◽  
Surface Variation ◽  
Local Stiffness ◽  
Machining Parameter ◽  
Complex Components

Face milling commonly generates surface quality of variation, is especially severe for milling of large-scale components with complex surface geometry such as cylinder block, engine head, and valve body. Thus surface variation serves as an important indicator both for machining parameter selection and components' service performance such as sealing, energy consumption, and emission. An efficient and comprehensive numerical model is highly desired for the prediction of surface variation of entire surface. This study proposes a coupled numerical simulation method, updating finite element (FE) model iteratively based on integration of data from abaqus and matlab, to predict surface variation induced by face milling of large-scale components with complex surfaces. Using the coupled model, three-dimensional (3D) variation of large-scale surface can be successfully simulated by considering face milling process including dynamic milling force, spiral curve of milling trajectory, and intermittently rotating contact characteristics. Surface variation is finally represented with point cloud from iterative FE analysis and verified by face milling experiment. Comparison between measured and predicted results shows that the new prediction method can simulate surface variation of complex components well. Based on the verified model, a set of analyses are conducted to evaluate the effects of local stiffness nonhomogenization and milling force variation on machined surface variation. It demonstrates that surface variation with surface peaks and concaves is strongly correlated with local stiffness nonhomogenization especially in feed direction. And thus the coupled prediction method provides a theoretical and efficient way to study surface variation induced by face milling of large-scale complex components.

Coupled Predicting Surface Variation by Face Milling of Engine Block/Head

2018 ◽  
Author(s):  
Shun Liu ◽  
Sun Jin ◽  
Xueping Zhang ◽  
Changhui Liu ◽  
Fuyong Yang ◽  
...  
Keyword(s):  
Surface Quality ◽  
Large Scale ◽  
Prediction Method ◽  
Experimental Methods ◽  
Face Milling ◽  
Milling Force ◽  
Machined Surface ◽  
Surface Variation ◽  
Local Stiffness ◽  
Complex Components

Face milling commonly generates surface quality of roughness or variation, especially severe for the milling of large-scale components with complex surface geometry such as cylinder block, engine head, and valve body. Thus surface variation serves as an important indicator both for machining parameter selection and components’ service performance. Conversely the optimization of machining process is a vital objective to improve the surface quality and its service life of machined components. Many researchers have dedicated to the prediction of machined surface variation generated by face milling using numerical or experimental methods. However, the numerical methods based on finite element analysis (FEA) are good at predicting local deformation of workpiece under instantaneous milling force, particularly applied for online compensation in face milling. Whereas experimental methods can only be used to estimate whole surface variation through reverse correlation analysis of measured data and processing variables. Therefore, an efficient and comprehensive numerical model is highly desired for the prediction of surface variation of entire surface. This study proposes a coupled numerical simulation method, updating FE model literarily based on the integration of data from ABAQUS and MATLAB, to predict surface variation induced by the face milling of large-scale components with complex surfaces. Using the coupled model, the 3D variation of large-scale surface can be successfully simulated by considering face milling process including dynamic milling force, spiral curve of milling trajectory, and intermittently rotating contact characteristics. Surface variation is finally represented with point cloud from totally iterative FE analysis and verified by face milling experiment. Result shows that the new prediction method can simulate surface variation of complex components. Based on the verified model, a set of numerical analyses are conducted to evaluate the effects of local stiffness non-homogenization and milling force variation on machined surface variation. It demonstrates that surface variation with surface peaks and concaves is strongly correlated with local stiffness non-homogenization especially in feed direction. Thus the coupled prediction method provides a theoretical and efficient way to study surface variation induced by face milling of large-scale complex components.

scholarly journals A Data-driven Minimum Stiffness Prediction Method for Machining Regions of Aircraft Structural Parts

2021 ◽  
Author(s):  
Jiarui Chen ◽  
Yingguang Li ◽  
Xu Liu ◽  
Tianchi Deng
Keyword(s):  
Prediction Method ◽  
Cutting Parameters ◽  
Data Driven ◽  
Calculation Methods ◽  
Structural Part ◽  
Average Percentage ◽  
Thin Walled ◽  
Structural Parts ◽  
Local Stiffness ◽  
Machining Parameter

Abstract Large thin-walled structural parts have been widely used in aircrafts for the purpose of weight reduction. These parts usually contain various thin-walled complex structures with weak local stiffness, which are easy to deform during machining if improper cutting parameters are selected. Thus, local stiffness has to be seriously considered during the machining parameter planning. Existing stiffness calculation methods mainly include mechanics calculation methods, empirical formula methods, finite element methods, and surrogate-based methods. However, due to the structural complexity, these methods are either inaccurate or time consuming. To address this issue, this paper proposes a data-driven method for stiffness prediction of aircraft structural parts. First, machining regions of aircraft structural part finishing are classified into bottom, sidewall, rib and corner to further define the minimum stiffness of machining regions. Then, by representing the part geometry with attribute graph as the input feature, while computing the minimum stiffness using FEM as the output label, stiffness prediction is turned to a graph learning task. Thus, a graph neural network (GNN) is designed and trained to map the attribute graph of a machining region to its minimum stiffness. In the case study, a dataset of aircraft structural parts is used to train four GNN models to predict the minimum stiffness of the defined four types of machining regions. Compared with FEM results, the average percentage errors on the test set are 6.717%, 7.367%, 7.432% and 5.962% respectively. In addition, the data driven model once trained, can greatly reduce the time in predicting the stiffness of a new part compared with FEM, which indicates that the proposed method can meet the engineering requirements in both accuracy and computational efficiency.

scholarly journals Impact of air–sea coupling on the climate change signal over the Iberian Peninsula

2021 ◽  
Author(s):  
Alba de la Vara ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Claas Teichmann ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Mediterranean Sea ◽  
Large Scale ◽  
Regional Distribution ◽  
Coupled Model ◽  
Climate Change Signal ◽  
The North ◽  
The Mediterranean ◽  
The Impact

AbstractIn this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

scholarly journals Forecast of International Trade of Lithium Carbonate Products in Importing Countries and Small-Scale Exporting Countries

2021 ◽  
Vol 13 (3) ◽  
pp. 1251
Author(s):  
Yichi Zhang ◽  
Zhiliang Dong ◽  
Sen Liu ◽  
Peixiang Jiang ◽  
Cuizhi Zhang ◽  
...  
Keyword(s):  
International Trade ◽  
Large Scale ◽  
Prediction Method ◽  
Lithium Ion ◽  
Lithium Carbonate ◽  
Raw Material ◽  
Small Scale ◽  
Trade Restrictions ◽  
Energy Field ◽  
Structure Of Trade

As the raw material of lithium-ion batteries, lithium carbonate plays an important role in the development of new energy field. Due to the extremely uneven distribution of lithium resources in the world, the security of supply in countries with less say would be greatly threatened if trade restrictions or other accidents occurred in large-scale exporting countries. It is of great significance to help these countries find new partners based on the existing trade topology. This study uses the link prediction method, based on the perspective of the topological structure of trade networks in various countries and trade rules, and eliminates the influence of large-scale lithium carbonate exporting countries on the lithium carbonate trade of other countries, to find potential lithium carbonate trade links among importing and small-scale exporting countries, and summarizes three trade rules: (1) in potential relationships involving two net importers, a relationship involving either China or the Netherlands is more likely to occur; (2) for all potential relationships, a relationship that actually occurred for more than two years in the period in 2009–2018 is more likely to occur in the future; and (3) potential relationships pairing a net exporter with a net importer are more likely to occur than other country combinations. The results show that over the next five to six years, Denmark and Italy, Netherlands and South Africa, Turkey and USA are most likely to have a lithium carbonate trading relationship, while Slovenia and USA, and Belgium and Thailand are the least likely to trade lithium carbonate. Through this study, we can strengthen the supply security of lithium carbonate resources in international trade, and provide international trade policy recommendations for the governments of importing countries and small-scale exporting countries.

scholarly journals An information theoretic approach to link prediction in multiplex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Large Scale ◽  
Similarity Measures ◽  
Prediction Method ◽  
General Purpose ◽  
Fast Method ◽  
Theoretic Approach ◽  
Multiplex Networks ◽  
Wide Range

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.

Measurements of Secondary Flows Downstream of a Turbine Cascade at Off-Design Incidence

2004 ◽  
Author(s):  
M. W. Benner ◽  
S. A. Sjolander ◽  
S. H. Moustapha
Keyword(s):  
Large Scale ◽  
Prediction Method ◽  
Leading Edge ◽  
Field Measurements ◽  
Inviscid Flow ◽  
Secondary Flows ◽  
Subsequent Paper ◽  
Empirical Prediction ◽  
Pressure Distributions ◽  
Passage Vortex

This paper presents experimental results of the secondary flows from two large-scale, low-speed, linear turbine cascades for which the incidence was varied. The aerofoils for the two cascades were designed for the same inlet and outlet conditions and differed mainly in their leading-edge geometries. Detailed flow field measurements were made upstream and downstream of the cascades and static pressure distributions were measured on the blade surfaces for three different values of incidence: 0, +10 and +20 degrees. The results from this experiment indicate that the strength of the passage vortex does not continue to increase with incidence, as would be expected from inviscid flow theory. The streamwise acceleration within the aerofoil passage seems to play an important role in influencing the strength of the vortex. The most recent off-design secondary loss correlation (Moustapha et al. [1]) includes leading-edge diameter as an influential correlating parameter. The correlation predicts that the secondary losses for the aerofoil with the larger leading-edge diameter are lower at off-design incidence; however, the opposite is observed experimentally. The loss results at high positive incidence have also high-lighted some serious shortcomings with the conventional method of loss decomposition. An empirical prediction method for secondary losses has been developed and will be presented in a subsequent paper.

scholarly journals Large-scale flood risk assessment using a coupled model chain

2016 ◽  
Vol 7 ◽  
pp. 11005 ◽  
Author(s):  
Bruno Merz ◽  
Heiko Apel ◽  
Nguyen Viet Dung ◽  
Daniela Falter ◽  
Yeshewatesfa Hundecha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Coupled Model ◽  
Flood Risk Assessment ◽  
Model Chain

scholarly journals Improved representation of groundwater at a regional scale – coupling of mesocale Hydrologic Model (mHM) with OpeneGeoSys (OGS)

2017 ◽  
Author(s):  
Miao Jing ◽  
Falk Heße ◽  
Wenqing Wang ◽  
Thomas Fischer ◽  
Marc Walther ◽  
...  
Keyword(s):  
Time Series ◽  
Groundwater Flow ◽  
Groundwater Recharge ◽  
Large Scale ◽  
Groundwater Modeling ◽  
Coupled Model ◽  
Hydrologic Model ◽  
Source Modeling ◽  
Prediction Ability ◽  
Groundwater Head

Abstract. Most of the current large scale hydrological models do not contain a physically-based groundwater flow component. The main difficulties in large-scale groundwater modeling include the efficient representation of unsaturated zone flow, the characterization of dynamic groundwater-surface water interaction and the numerical stability while preserving complex physical processes and high resolution. To address these problems, we propose a highly-scalable coupled hydrologic and groundwater model (mHM#OGS) based on the integration of two open-source modeling codes: the mesoscale hydrologic Model (mHM) and the finite element simulator OpenGeoSys (OGS). mHM#OGS is coupled using a boundary condition-based coupling scheme that dynamically links the surface and subsurface parts. Nested time stepping allows smaller time steps for typically faster surface runoff routing in mHM and larger time steps for slower subsurface flow in OGS. mHM#OGS features the coupling interface which can transfer the groundwater recharge and river baseflow rate between mHM and OpenGeoSys. Verification of the coupled model was conducted using the time-series of observed streamflow and groundwater levels. Moreover, we force the transient model using groundwater recharge in two scenarios: (1) spatially variable recharge based on the mHM simulations, and (2) spatially homogeneous groundwater recharge. The modeling result in first scenario has a slightly higher correlation with groundwater head time-series, which further validates the plausibility of spatial groundwater recharge distribution calculated by mHM in the mesocale. The statistical analysis of model predictions shows a promising prediction ability of the model. The offline coupling method implemented here can reproduce reasonable groundwater head time series while keep a desired level of detail in the subsurface model structure with little surplus in computational cost. Our exemplary calculations show that the coupled model mHM#OGS can be a valuable tool to assess the effects of variability in land surface heterogeneity, meteorological, topographical forces and geological zonation on the groundwater flow dynamics.

scholarly journals Current and future occurrences of health-relevant, compound heat and ozone pollution events in six European ozone-temperature regions 

2021 ◽  
Author(s):  
Sally Jahn ◽  
Elke Hertig
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Large Scale ◽  
Coupled Model ◽  
Ground Level ◽  
Future Climate Change ◽  
Ozone Pollution ◽  
Ground Level Ozone ◽  
Ozone Concentrations ◽  
Elevated Ozone

<p>Air pollution and heat events present two major health risks, both already independently posing a significant threat to human health and life. High levels of ground-level ozone (O<sub>3</sub>) and air temperature often coincide due to the underlying physical relationships between both variables. The most severe health outcome is in general associated with the co-occurrence of both hazards (e.g. Hertig et al. 2020), since concurrent elevated levels of temperature and ozone concentrations represent a twofold exposure and can lead to a risk beyond the sum of the individual effects. Consequently, in the current contribution, a compound approach considering both hazards simultaneously as so-called ozone-temperature (o-t-)events is chosen by jointly analyzing elevated ground-level ozone concentrations and air temperature levels in Europe.</p><p>Previous studies already point to the fact that the relationship of underlying synoptic and meteorological drivers with one or both of these health stressors as well as the correlation between both variables vary with the location of sites and seasons (e.g. Otero et al. 2016; Jahn, Hertig 2020). Therefore, a hierarchical clustering analysis is applied to objectively divide the study domain in regions of homogeneous, similar ground-level ozone and temperature characteristics (o-t-regions). Statistical models to assess the synoptic and large-scale meteorological mechanisms which represent main drivers of concurrent o-t-events are developed for each identified o-t-region.</p><p>Compound elevated ozone concentration and air temperature events are expected to become more frequent due to climate change in many parts of Europe (e.g. Jahn, Hertig 2020; Hertig 2020). Statistical projections of potential frequency shifts of compound o-t-events until the end of the twenty-first century are assessed using the output of Earth System Models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6).</p><p><em>Hertig, E. (2020) Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria, Southern Germany. Air Qual. Atmos. Health. doi: 10.1007/s11869-020-00811-z</em></p><p><em>Hertig, E., Russo, A., Trigo, R. (2020) Heat and ozone pollution waves in Central and South Europe- characteristics, weather types, and association with mortality. Atmosphere. doi: 10.3390/atmos11121271</em></p><p><em>Jahn, S., Hertig, E. (2020) Modeling and projecting health‐relevant combined ozone and temperature events in present and future Central European climate. Air Qual. Atmos. Health. doi: 10.1007/s11869‐020‐009610</em></p><p><em>Otero N., Sillmann J., Schnell J.L., Rust H.W., Butler T. (2016) Synoptic and meteorological drivers of extreme ozone concentrations over Europe. Environ Res Lett. doi: 10.1088/ 1748-9326/11/2/024005</em></p>

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