Brian F. Farrell
· Robert P. Burden Professor of MeteorologyVerifiedHarvard University · Environmental Science & Engineering
Active 1973–2024
About
Brian F. Farrell is the Robert P. Burden Professor of Meteorology at Harvard University, affiliated with the Harvard John A. Paulson School of Engineering and Applied Sciences. His primary teaching area is Environmental Science & Engineering. Farrell is involved in academic programs across undergraduate and graduate levels, including applied mathematics, bioengineering, computer science, electrical engineering, environmental science & engineering, materials science, and mechanical engineering. His work focuses on meteorology and environmental science, contributing to the university's research and educational missions in these fields.
Research topics
- Physics
- Mechanics
- Optics
- Engineering
- Mathematics
- Statistical physics
- Environmental science
- Meteorology
- Statistics
- Geophysics
- Aerospace engineering
- Acoustics
Selected publications
Physical Review Fluids · 2024-02-21 · 3 citations
articleOpen access1st authorCorrespondingIn wall turbulence, the time-mean flow is returned to after almost any disturbance, which indicates that it is a stable statistical feature underlying the disorder of turbulence. However, the stability of this statistical feature can not be determined directly from the stability of the time-mean flow itself. What is required is a statistical stability analysis method. We determine the statistical stability of the time-mean state by averaging the dynamics of the return to the time-mean state over the turbulent attractor using the linear inverse model method.
Fluctuation covariance-based study of roll-streak dynamics in Poiseuille flow turbulence
Journal of Fluid Mechanics · 2024-05-31 · 1 citations
articleOpen accessSenior authorAlthough the roll-streak (R-S) is fundamentally involved in the dynamics of wall turbulence, the physical mechanism responsible for its formation and maintenance remains controversial. In this work we investigate the dynamics maintaining the R-S in turbulent Poiseuille flow at $R=1650$ . Spanwise collocation is used to remove spanwise displacement of the streaks and associated flow components, which isolates the streamwise-mean flow R-S component and the second-order statistics of the streamwise-varying fluctuations that are collocated with the R-S. This partition of the dynamics into streamwise-mean and fluctuation components facilitates exploiting insights gained from the analytic characterization of turbulence in the second-order statistical state dynamics (SSD), referred to as S3T, and its closely associated restricted nonlinear dynamics (RNL) approximation. Symmetry of the statistics about the streak centreline permits separation of the fluctuations into sinuous and varicose components. The Reynolds stress forcing induced by the sinuous and varicose fluctuations acting on the R-S is shown to reinforce low- and high-speed streaks, respectively. This targeted reinforcement of streaks by the Reynolds stresses occurs continuously as the fluctuation field is strained by the streamwise-mean streak and not intermittently as would be associated with streak-breakdown events. The Reynolds stresses maintaining the streamwise-mean roll arise primarily from the dominant proper orthogonal decomposition (POD) modes of the fluctuations, which can be identified with the time average structure of optimal perturbations growing on the streak. These results are consistent with a universal process of R-S growth and maintenance in turbulent shear flow arising from roll forcing generated by straining turbulent fluctuations, which was identified using the S3T SSD.
Journal of Fluid Mechanics · 2023 · 16 citations
- Physics
- Mechanics
- Optics
Turbulence in the restricted nonlinear (RNL) dynamics is analysed and compared with direct numerical simulations (DNS) of Poiseuille turbulence at Reynolds number $R=1650$ . The structures are obtained by proper orthogonal decomposition (POD) analysis of the two components of the flow partition used in RNL dynamics: the streamwise mean flow and fluctuations. POD analysis of the streamwise mean flow indicates that the dominant POD modes, in both DNS and RNL dynamics, are roll-streaks harmonic in the spanwise direction. However, we conclude that these POD modes do not occur in isolation but rather are Fourier components of a coherent roll-streak structure. POD analysis of the fluctuations in DNS and RNL dynamics reveals similar complex structures consisting in part of oblique waves collocated with the streak. The origin of these structures is identified by their correspondence to POD modes predicted using a stochastic turbulence model (STM). These predicted POD modes are dominated by the optimally growing structures on the streak, which the STM predicts correctly to be of sinuous oblique wave structure. This close correspondence between the roll-streak structure and the associated fluctuations in DNS, RNL dynamics and the STM implies that the self-sustaining mechanism operating in DNS is essentially the same as that in RNL dynamics, which has been associated previously with optimal perturbation growth on the streak.
arXiv (Cornell University) · 2023-04-12
preprintOpen access1st authorCorrespondingTurbulence in wall-bounded flows is characterized by stable statistics. Although, in many turbulent systems, this stable statistical state corresponds to a stable fixed point of an associated statistical state dynamics (SSD) closed at second order, referred to as S3T, this is not the case for wall turbulence. In wall-turbulence the trajectory of the statistical state is on a transient chaotic attractor in the S3T statistical state space and the time-mean statistical state is neither a stable fixed point of this SSD nor, if it is maintained as an equilibrium, is it stable. Nevertheless, sufficiently small perturbations from the ensemble/time-mean state relax back to the mean statistical state following an effective linear dynamics. In this work, the dynamics of spanwise uniform perturbations to the time-mean flow are studied using a linear inverse model (LIM) to identify the linear operator governing the ensemble stability of the ensemble/time-mean state by obtaining the time-mean stability properties over the transient attractor of the turbulence identified by the S3T SSD. The ensemble/time-mean stability of an unstable equilibrium can be understood by noting that even when every member of an ensemble is unstable the ensemble mean may be stable with perturbations following stable dynamics. While simplifying insight into turbulent flows has been obtained by identifying and studying ensemble mean statistical states, less attention has been accorded to identifying and studying the ensemble mean dynamics. We show that in the case of wall turbulence, even though stable fixed point SSD equilibria are not available to allow the application of traditional perturbation analysis methods to identify the perturbation stability of the mean state, an effective linear stability analysis can be obtained to identify the perturbation dynamics of the ensemble/time-mean statistical state.
Fluctuation covariance-based study of roll-streak dynamics in Poiseuille flow turbulence
arXiv (Cornell University) · 2023
Senior authorCorresponding- Mechanics
- Statistical physics
- Physics
Although the roll-streak (R-S) is fundamentally involved in the dynamics of wall-turbulence, the physical mechanism responsible for its formation and maintenance remains controversial. In this work we investigate the dynamics maintaining the R-S in turbulent Poiseuille flow at R=1650. Spanwise collocation is used to remove spanwise displacement of the streaks and associated flow components, which isolates the streamwise-mean flow R-S component and the second-order statistics of the streamwise-varying fluctuations that are collocated with the R-S. This streamwise-mean/fluctuation partition of the dynamics facilitates exploiting insights gained from the analytic characterization of turbulence in the second-order statistical state dynamics (SSD), referred to as S3T, and its closely associated restricted nonlinear dynamics (RNL) approximation. Symmetry of the statistics about the streak centerline permits separation of the fluctuations into sinuous and varicose components. The Reynolds stress forcing induced by the sinuous and varicose fluctuations acting on the R-S is shown to reinforce low- and high-speed streaks respectively. This targeted reinforcement of streaks by the Reynolds stresses occurs continuously as the fluctuation field is strained by the streamwise-mean streak and not intermittently as would be associated with streak-breakdown events. The Reynolds stresses maintaining the streamwise-mean roll arise primarily from the dominant POD modes of the fluctuations, which can be identified with the time average structure of optimal perturbations growing on the streak. These results are consistent with a universal process of R-S growth and maintenance in turbulent shear flow arising from roll forcing generated by straining turbulent fluctuations, which was identified using the S3T SSD.
2022-09-06
preprintSenior authorUnderstanding the rapid evolution of agricultural pests can inform mitigation efforts and provide comprehensive models for natural systems and examples for the consequences of anthropogenic global change. It is suspected that the practice of migratory beekeeping, in which beehives are shipped great distances to meet pollination demands, increases dispersal of honeybee (Apis melifera) pests and parasites, including the highly virulent mite Varroa destructor. Given it has never been explicitly examined in the United States, here we test this hypothesis by studying the population genetics of Varroa mites sampled from migratory and non-migratory hives across the western United States. Using 3RAD to generate a genome-wide dataset for hundreds of samples, we found very low genetic diversity and no population structure across more than one thousand kilometers. Our findings are consistent with the proposed large and fast mite admixture enabled by migratory pollination. Furthermore, hives that avoid migratory pollination are not insulated from the effects of this admixture, as there is evidence for extremely high rates of gene flow into—and a resulting lack of isolation by distance among—these sedentary populations. Our research suggests the genetic variation of Varroa destructor in the western United States is a result of its recent introduction to the region and shows clear signals of high admixture, likely due to management practices. Moreover, it demonstrates how an evolutionary, genetic perspective is crucial in understanding host-parasite dynamics in agricultural systems and shaping management decisions to protect key species
2022-08-18
preprintOpen accessSenior authorUnderstanding the rapid evolution of agricultural pests can inform mitigation efforts and provide comprehensive models for natural systems and examples for the consequences of anthropogenic global change. It is suspected that the practice of migratory beekeeping, in which beehives are shipped great distances to meet pollination demands, increases dispersal of honeybee (Apis melifera) pests and parasites, including the highly virulent mite Varroa destructor. Given it has never been explicitly examined in the United States, here we test this hypothesis by studying the population genetics of Varroa mites sampled from migratory and non-migratory hives across the western United States. Using 3RAD to generate a genome-wide dataset for hundreds of samples, we found very low genetic diversity and no population structure across more than one thousand kilometers. Our findings are consistent with the proposed large and fast mite admixture enabled by migratory pollination. Furthermore, hives that avoid migratory pollination are not insulated from the effects of this admixture, as there is evidence for extremely high rates of gene flow into—and a resulting lack of isolation by distance among—these sedentary populations. Our research suggests the genetic variation of Varroa destructor in the western United States is a result of its recent introduction to the region and shows clear signals of high admixture, likely due to management practices. Moreover, it demonstrates how an evolutionary, genetic perspective is crucial in understanding host-parasite dynamics in agricultural systems and shaping management decisions to protect key species
arXiv (Cornell University) · 2021-09-06
preprintOpen accessTurbulence structure in the quasi-linear restricted nonlinear (RNL) model is analyzed and compared with DNS of turbulent Poiseuille flow at Reynolds number R=1650. The turbulence structure is obtained by POD analysis of the two components of the flow partition used in formulating the RNL model: the streamwise-mean flow and the associated perturbations. The dominant structures are found to be similar in RNL simulations and DNS despite the neglect of perturbation-perturbation nonlinearity in the RNL formulation. POD analysis of the streamwise-mean flow indicates that the dominant structure in both RNL and DNS is a coherent roll-streak structure in which the roll is collocated with the streak in a manner configured to reinforce the streak by the lift-up process. This mechanism of roll-streak maintenance accords with analytical predictions made using the second order statistical state dynamics (SSD) model, referred to as S3T, which shares with RNL the dynamical restriction of neglecting the perturbation-perturbation nonlinearity. POD analysis of perturbations from the streamwise-mean streak reveals that similar structures characterize these perturbations in both RNL and DNS. The perturbation to the low-speed streak POD are shown to have the form of oblique waves collocated with the streak that can be identified with optimally growing structures on the streak. Given that the mechanism sustaining turbulence in RNL has been analytically characterized, this close correspondence between the streamwise-mean and perturbation structures in RNL and DNS supports the conclusion that the self-sustaining mechanism in DNS is the same as that in RNL.
arXiv (Cornell University) · 2021-09-06
preprintOpen accessTurbulence in the restricted nonlinear (RNL) dynamics is analyzed and compared with DNS of Poiseuille turbulence at $R=1650$. The structures are obtained by POD analysis of the two components of the flow partition used in RNL dynamics: the streamwise-mean flow and fluctuations. POD analysis of the streamwise-mean flow indicates that the dominant POD modes, in both DNS and RNL, are roll-streaks harmonic in the spanwise. However, we conclude that these POD modes do not occur in isolation but rather are Fourier components of a coherent roll-streak structure. POD analysis of the fluctuations in DNS and RNL reveals similar complex structures consisting in part of oblique waves collocated with the streak. The origin of these structures is identified by their correspondence to POD modes predicted using a stochastic turbulence model (STM). These predicted POD modes are dominated by the optimally growing structures on the streak, which the STM predicts correctly to be of sinuous oblique wave structure. This close correspondence between the roll-streak structure and the associated fluctuations in DNS, RNL and the STM implies that the self-sustaining mechanism operating in DNS is essentially the same as that in RNL, which has been previously associated with optimal perturbation growth on the streak.
APS Division of Fluid Dynamics Meeting Abstracts · 2020-01-01
articleSenior author
Recent grants
INSPIRE: Statistical State Dynamics of Turbulent Systems
NSF · $601k · 2012–2017
New Methods in Storm Track Dynamics Theory
NSF · $450k · 2007–2012
New Methods in Storm Track Dynamics Theory
NSF · $469k · 2004–2007
NSF · $507k · 2017–2022
Frequent coauthors
- 162 shared
Petros J. Ioannou
Harvard University
- 38 shared
Navid C. Constantinou
Australian National University
- 24 shared
Joseph G. Fitzgerald
Planetary Science Institute
- 21 shared
Dennice F. Gayme
- 18 shared
Marios-Andreas Nikolaidis
National and Kapodistrian University of Athens
- 16 shared
Nikolaos A. Bakas
University of Ioannina
- 16 shared
Eli Tziperman
Harvard University
- 16 shared
Vaughan Thomas
University College London
Education
- 1982
Phd, Division of Applied Science
Harvard University
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Brian F. Farrell
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup