In Situ Data-Driven Analysis and Learning of Turbulence Closures at Scale

2021 ◽  
Author(s):  
Riccardo Balin
Keyword(s):  
Data Driven ◽  
In Situ Data ◽  
Turbulence Closures

Sensor Fusion and On-Line Monitoring of Friction Stir Blind Riveting for Lightweight Materials Manufacturing

2021 ◽  
pp. 1-36
Author(s):  
Zhe Gao ◽  
Haris Khan ◽  
Jingjing Li ◽  
Weihong Guo
Keyword(s):  
Sensor Fusion ◽  
Failure Modes ◽  
Processing Parameters ◽  
Data Driven ◽  
Structure Property ◽  
Cross Sectional ◽  
Friction Stir ◽  
In Situ Data ◽  
Lap Shear

Abstract This research focused on developing a hybrid quality monitoring model through combining the data driven and key engineering parameters to predict the friction stir blind riveting (FSBR) joint quality. The hybrid model was formulated through utilizing the in-situ processing and joint property data. The in-situ data involved sensor fusion (force and torque signals) and key processing parameters (spindle speed, feed rate and stacking sequence) for data-driven modeling. The quality of the FSBR joints was defined by the tensile strength. Further, the joint cross-sectional analysis and failure modes in lap-shear tests were employed to confirm the efficacy of the proposed model and development of the process-structure-property relationship.

scholarly journals High‐Speed Atomic Force Microscopy: Large‐Range HS‐AFM Imaging of DNA Self‐Assembly through In Situ Data‐Driven Control (Small Methods 7/2019)

Small Methods ◽  
2019 ◽  
Vol 3 (7) ◽  
pp. 1970022
Author(s):  
Adrian P. Nievergelt ◽  
Christoph Kammer ◽  
Charlène Brillard ◽  
Eva Kurisinkal ◽  
Maartje M. C. Bastings ◽  
...  
Keyword(s):  
Atomic Force Microscopy ◽  
Self Assembly ◽  
High Speed ◽  
Large Range ◽  
Data Driven ◽  
Force Microscopy ◽  
In Situ Data ◽  
Atomic Force ◽  
Afm Imaging

scholarly journals Large‐Range HS‐AFM Imaging of DNA Self‐Assembly through In Situ Data‐Driven Control

Small Methods ◽  
2019 ◽  
Vol 3 (7) ◽  
pp. 1900031 ◽  
Author(s):  
Adrian P. Nievergelt ◽  
Christoph Kammer ◽  
Charlène Brillard ◽  
Eva Kurisinkal ◽  
Maartje M. C. Bastings ◽  
...  
Keyword(s):  
Self Assembly ◽  
Large Range ◽  
Data Driven ◽  
In Situ Data ◽  
Afm Imaging

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

scholarly journals Critical Dynamics of Defects and Mechanisms of Damage-Failure Transitions in Fatigue

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2554
Author(s):  
Oleg Naimark ◽  
Vladimir Oborin ◽  
Mikhail Bannikov ◽  
Dmitry Ledon
Keyword(s):  
Fatigue Damage ◽  
Kinetic Equations ◽  
Experimental Methodology ◽  
Preliminary Deformation ◽  
Scaling Properties ◽  
In Situ Data ◽  
Number Of Cycles ◽  
Fish Eye ◽  
Very High

An experimental methodology was developed for estimating a very high cycle fatigue (VHCF) life of the aluminum alloy AMG-6 subjected to preliminary deformation. The analysis of fatigue damage staging is based on the measurement of elastic modulus decrement according to “in situ” data of nonlinear dynamics of free-end specimen vibrations at the VHCF test. The correlation of fatigue damage staging and fracture surface morphology was studied to establish the scaling properties and kinetic equations for damage localization, “fish-eye” nucleation, and transition to the Paris crack kinetics. These equations, based on empirical parameters related to the structure of the material, allows us to estimate the number of cycles for the nucleation and advance of fatigue crack.

scholarly journals Measuring and inferring the ice thickness distribution of four glaciers in the Tien Shan, Kyrgyzstan

2020 ◽  
pp. 1-18
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes J. Fürst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Cross Validation ◽  
Thickness Distribution ◽  
Tien Shan ◽  
Ice Thickness ◽  
Ice Volume ◽  
In Situ Data ◽  
Radio Echo Sounding ◽  
Thickness Measurements ◽  
Tien Shan Mountains

Abstract Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.

scholarly journals Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008

2016 ◽  
Vol 16 (14) ◽  
pp. 9435-9455 ◽  
Author(s):  
Matthew J. Alvarado ◽  
Chantelle R. Lonsdale ◽  
Helen L. Macintyre ◽  
Huisheng Bian ◽  
Mian Chin ◽  
...  
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Aerosol Size Distribution ◽  
Visible Radiation ◽  
Submicron Aerosol ◽  
In Situ Data ◽  
Aerosol Absorption ◽  
Aerosol Scattering ◽  
The Impact

Abstract. Accurate modeling of the scattering and absorption of ultraviolet and visible radiation by aerosols is essential for accurate simulations of atmospheric chemistry and climate. Closure studies using in situ measurements of aerosol scattering and absorption can be used to evaluate and improve models of aerosol optical properties without interference from model errors in aerosol emissions, transport, chemistry, or deposition rates. Here we evaluate the ability of four externally mixed, fixed size distribution parameterizations used in global models to simulate submicron aerosol scattering and absorption at three wavelengths using in situ data gathered during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. The four models are the NASA Global Modeling Initiative (GMI) Combo model, GEOS-Chem v9-02, the baseline configuration of a version of GEOS-Chem with online radiative transfer calculations (called GC-RT), and the Optical Properties of Aerosol and Clouds (OPAC v3.1) package. We also use the ARCTAS data to perform the first evaluation of the ability of the Aerosol Simulation Program (ASP v2.1) to simulate submicron aerosol scattering and absorption when in situ data on the aerosol size distribution are used, and examine the impact of different mixing rules for black carbon (BC) on the results. We find that the GMI model tends to overestimate submicron scattering and absorption at shorter wavelengths by 10–23 %, and that GMI has smaller absolute mean biases for submicron absorption than OPAC v3.1, GEOS-Chem v9-02, or GC-RT. However, the changes to the density and refractive index of BC in GC-RT improve the simulation of submicron aerosol absorption at all wavelengths relative to GEOS-Chem v9-02. Adding a variable size distribution, as in ASP v2.1, improves model performance for scattering but not for absorption, likely due to the assumption in ASP v2.1 that BC is present at a constant mass fraction throughout the aerosol size distribution. Using a core-shell mixing rule in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for modeling the time-varying mixing states of aerosols in future versions of ASP.

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