Planar laser induced fluorescence in aqueous flows

By John P. Crimaldi. 2008

325 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computational Mechanics, Global and Planetary Change

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Zhicheng Wang
2. Shengze Cai
3. Klavs F. Jensen
4. S. Kuhn
5. Maizar Raissi
6. G. Em Karniadakis
7. Alireza Yazdani
8. A. Woitalka

In Computational Mechanics

1. G. Em Karniadakis
2. Maizar Raissi
3. Shengze Cai
4. Zhicheng Wang
5. Alireza Yazdani
6. Klavs F. Jensen
7. S. Kuhn
8. Frederik Fuest

In Global and Planetary Change

1. Maizar Raissi
2. G. Em Karniadakis
3. Alireza Yazdani
4. Klavs F. Jensen
5. S. Kuhn
6. A. Woitalka

Citations in the corpus

• Scalability of mass transfer in liquid-liquid flow (2014, methodology): “Dessimoz et al. (2008) observed similar mass transfer coefficients for slug flow and stratified flow.”
• Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data (2018, methodology): “Moreover, recent techniques in planar laser induced fluorescence imaging combined with particle image velocimetry have been developed to assess the relationships between scalar and velocity/vorticity fields [9, 10].”
• Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks (2021, background): “Compared to other flow visualization technologies, such as particle image velocimetry (PIV) (Raffel et al. 2018) and laser induced † Email address for correspondence: george karniadakis@brown.edu fluorescence (LIF) (Crimaldi 2008), BOS is less expensive and more flexible to set up in different exper”