Multiscale Validation and Uncertainty Quantification for Problems With Sparse Data

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Anchal Jatale ◽  
Philip J. Smith ◽  
Jeremy N. Thornock ◽  
Sean T. Smith ◽  
Jennifer P. Spinti ◽  
...  
Keyword(s):  
Experimental Data ◽  
Wind Tunnel ◽  
Uncertainty Quantification ◽  
Real World ◽  
Ghg Emissions ◽  
Sparse Data ◽  
World Systems ◽  
Global Approach ◽  
Real World Problem ◽  
Helium Plume

Quantification of uncertainty in the simulation results becomes difficult for complex real-world systems with little or no experimental data. This paper describes a validation and uncertainty quantification (VUQ) approach that integrates computational and experimental data through a range of experimental scales and a hierarchy of complexity levels. This global approach links dissimilar experimental datasets at different scales, in a hierarchy, to reduce quantified error bars on case with sparse data, without running additional experiments. This approach was demonstrated by applying on a real-world problem, greenhouse gas (GHG) emissions from wind tunnel flares. The two-tier validation hierarchy links, a buoyancy-driven helium plume and a wind tunnel flare, to increase the confidence in the estimation of GHG emissions from wind tunnel flares from simulations.

Developing a Numerical Model of the Virginia Tech Stability Wind Tunnel for Uncertainty Quantification Based On Real-World Geometry

2020 ◽  
Author(s):  
Máté Szoke ◽  
Vidya Vishwanathan ◽  
Tim Loeschen ◽  
Aldo Gargiulo ◽  
Daniel J. Fritsch ◽  
...  
Keyword(s):  
Numerical Model ◽  
Wind Tunnel ◽  
Uncertainty Quantification ◽  
Real World ◽  
Virginia Tech

Phenomenological Modelling

2018 ◽  
Author(s):  
Ray Huffaker ◽  
Marco Bittelli ◽  
Rodolfo Rosa
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
Real World ◽  
Biological Diversity ◽  
False Positives ◽  
World Systems ◽  
Economic Activities ◽  
Essential Services ◽  
Low Dimension ◽  
Convergent Cross Mapping

Detecting causal interactions among climatic, environmental, and human forces in complex biophysical systems is essential for understanding how these systems function and how public policies can be devised that protect the flow of essential services to biological diversity, agriculture, and other core economic activities. Convergent Cross Mapping (CCM) detects causal networks in real-world systems diagnosed with deterministic, low-dimension, and nonlinear dynamics. If CCM detects correspondence between phase spaces reconstructed from observed time series variables, then the variables are determined to causally interact in the same dynamic system. CCM can give false positives by misconstruing synchronized variables as causally interactive. Extended (delayed) CCM screens for false positives among synchronized variables.

Systems theories

2018 ◽  
Author(s):  
Marc J. Stern
Keyword(s):  
Social Networks ◽  
Problem Solving ◽  
Natural Resources ◽  
Real World ◽  
Common Pool Resources ◽  
Ecological Systems ◽  
Effective Governance ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Real World Problem

This chapter covers systems theories relevant to understanding and working to enhance the resilience of social-ecological systems. Social-ecological systems contain natural resources, users of those resources, and the interactions between each. The theories in the chapter share lessons about how to build effective governance structures for common pool resources, how to facilitate the spread of worthwhile ideas across social networks, and how to promote collaboration for greater collective impacts than any one organization alone could achieve. Each theory is summarized succinctly and followed by guidance on how to apply it to real world problem solving.

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Asymmetry underlies stability in power grids

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ferenc Molnar ◽  
Takashi Nishikawa ◽  
Adilson E. Motter
Keyword(s):  
Symmetry Breaking ◽  
Real World ◽  
Power Grids ◽  
Stable Operation ◽  
World Systems ◽  
Symmetric State ◽  
Network Systems ◽  
Additional Improvement ◽  
The Stability ◽  
General Method

AbstractBehavioral homogeneity is often critical for the functioning of network systems of interacting entities. In power grids, whose stable operation requires generator frequencies to be synchronized—and thus homogeneous—across the network, previous work suggests that the stability of synchronous states can be improved by making the generators homogeneous. Here, we show that a substantial additional improvement is possible by instead making the generators suitably heterogeneous. We develop a general method for attributing this counterintuitive effect to converse symmetry breaking, a recently established phenomenon in which the system must be asymmetric to maintain a stable symmetric state. These findings constitute the first demonstration of converse symmetry breaking in real-world systems, and our method promises to enable identification of this phenomenon in other networks whose functions rely on behavioral homogeneity.

Numerical and Experimental Study of Turbulent Flows Around Clark Y-14 Aerofoil

2015 ◽  
Author(s):  
Kshitij Vadake ◽  
Jie Cui
Keyword(s):  
Fluid Dynamics ◽  
Wind Tunnel ◽  
Real World ◽  
Force Measurement ◽  
Test Model ◽  
Wind Tunnel Testing ◽  
Cfd Simulations ◽  
Measurement Device ◽  
Tunnel Testing

Experimental Fluid Dynamics (EFD) and Computational Fluid Dynamics (CFD) have been instrumental in Fluid Mechanics to help solve scientific and engineering problems. This research attempts to use both techniques to perform a parametric study of turbulence flow around airfoil ClarkY-14 at various velocity and angle of attack (AoA). Clark Y-14 airfoil was designed in the 1920’s. It demonstrated good overall performance at low and moderate Reynolds numbers. With the progress in the aviation field, its performance was sub-optimal for newer aircraft designs. However, with the advent of RC airplanes and model aircrafts, there is a renewed interest in this airfoil. Various research projects have been conducted using this airfoil, but there hasn’t been a combined EFD and CFD study of the performance characteristics of the airfoil itself, which still finds real world applications today. One important aspect of this research included the investigation of the effects of a Force Measurement Device/Sensor, which is typically used in scaled/full-size wind tunnels to mount the test model as well as measure the forces/moments acting on it during the testing. The presence of such a device could affect the quality of the data obtained from the wind tunnel testing when compared to a real world application scenario where the aforementioned device may not be present. To the best of the author’s knowledge, no detailed study has been published on the effects of such devices. In this study, the results with and without the measuring device were generated by using CFD simulations. The results were then compared to see to what extent the inclusion of these devices will affect the results. The methodology used for this research was experimental as well as computational. In the present research, a commercially available CFD software STAR-CCM+ was employed to simulate the flows around airfoil Clark Y-14. The experimental data was obtained from wind tunnel tests using AEROLAB Educational Wind Tunnel (EWT) and compared with the simulation data from the CFD. The two data sets were in good agreement. Both experimental and simulation results were used to understand the effects of the measurement device/sensor used in the scaled wind tunnel on the lift and drag coefficients of the airfoil. Two separate CFD simulation setups were designed to model the presence and absence of the measurement device/sensor. These setups replicated the wind tunnel setup. The airfoil was tested and simulated at different speeds as well as different AoA. The comparative study gave a useful insight on the accuracy of the CFD simulations in relation to the actual testing. The analysis of results concluded that the force measurement device/sensor had insignificant effects on the accuracy and quality of data collected through wind tunnel testing.

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