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Experimental Investigations Into the Fluid Dynamics and Forcing Underlying Cross-Flow Turbine Operation
Experimental Investigations Into the Fluid Dynamics and Forcing Underlying Cross-Flow Turb...
Experimental Investigations Into the Fluid Dynamics and Forcing Underlying Cross-Flow Turbine Operation

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20250211152644
ISBN  
9798384097211
DDC  
620
저자명  
Snortland, Abigale.
서명/저자  
Experimental Investigations Into the Fluid Dynamics and Forcing Underlying Cross-Flow Turbine Operation
발행사항  
[Sl] : University of Washington, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
154 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
주기사항  
Includes supplementary digital materials.
주기사항  
Advisor: Polagye, Brian;Williams, Owen.
학위논문주기  
Thesis (Ph.D.)--University of Washington, 2024.
초록/해제  
요약Within the wind and marine energy sectors, axial-flow (i.e., horizontal axis) turbines are a well-established and well-understood approach to converting the kinetic energy in a moving fluid to electricity. Recent cross-flow (i.e., vertical axis) turbine research has yielded substantial performance gains through the exploitation of unsteady fluid dynamics for individual turbines and mutually beneficial interactions between closely-spaced turbines in arrays. However, an understanding of the dynamics underlying cross-flow turbine operation remains incomplete due to the presence of fluid phenomena that are difficult to model, including dynamic stall, flow curvature effects, and the influence of the turbine on the surrounding flow, called induction. This thesis considers the intricate relationship between the flow physics and performance of cross-flow turbines and augments understanding of their fundamental operation. First, cross-flow turbine performance and flow fields exhibit cycle-to-cycle variations, though this is often implicitly neglected through time- and phase-averaging. This variability could potentially arise from a variety of mechanisms -- inflow fluctuations, the stochastic nature of dynamic stall, and cycle-to-cycle hysteresis -- each of which have different implications for our understanding of cross-flow turbine dynamics. In this work, the extent and sources of cycle-to-cycle variability, for both the flow fields and performance, are explored experimentally under two, contrasting operational conditions. Flow fields, obtained through two-dimensional planar particle image velocimetry (PIV) inside the turbine swept area, are correlated simultaneously with measured performance using an unsupervised hierarchical clustering pipeline. A principal component analysis (PCA) pre-processor is employed that allows for clustering based on all the dynamics present in the high-dimensional flow-field data in an interpretable, low-dimensional subspace that is weighted by contribution to overall velocity variance. We find that the flow-field clusters and their associated performance are correlated primarily with inflow fluctuations, despite relatively low turbulence intensity. These inflow fluctuations drive variations in the timing of the dynamic stall process, while hysteresis between cycles is found to be negligible. Clustering reveals persistent ties between performance and flow-field variability during the upstream portion of the turbine rotation. The approach employed here provides a more comprehensive picture of cross-flow turbine flow fields and performance than aggregate, statistical representations.Second, cross-flow turbine blades encounter a relatively undisturbed inflow for the first half of each rotational cycle (``upstream sweep'') and then pass through their own wake for the latter half (``downstream sweep''). While most research on cross-flow turbine optimization focuses on the power-generating upstream sweep, we use single-bladed turbine experiments to show that the downstream sweep strongly affects time-averaged performance. Specifically, we find that power generation from the upstream sweep continues to increase beyond the optimal tip-speed ratio. In contrast, the power consumption from the downstream sweep begins to increase approximately linearly beyond the optimal tip-speed ratio due, in part, to an increasingly unfavorable orientation of lift and drag relative to the rotation direction. Downstream power degradation increases faster than upstream power generation, indicating the downstream sweep strongly influences the optimal tip-speed ratio. In addition, PIV data is obtained inside the turbine swept area at three tip-speed ratios. This illuminates the mechanisms underpinning the observed performance degradation in the downstream sweep and motivates an analytical model for a limiting case with high induction or an infinite tip-speed ratio. Performance results are shown to be consistent across 55 unique combinations of chord-to-radius ratio, preset pitch angle, and Reynolds number, underscoring the general significance of the downstream sweep to cross-flow turbine performance. Third, while investigating trends in terms of turbine-level forces and torques is important, it does not tell the full story of cross-flow turbine operation. Identification of blade-level forces and torques allows for specific investigations into how effectively fluid forcing on the blade drives rotation and can aid in blade structural design. Further, the determination of blade-level forces allows more robust comparison to computational fluid dynamic simulations. Here, we present a methodology for extracting blade-level forces and moments from experimental measurements at the axis of rotation for a single-bladed turbine. The method is based on knowledge of the flow physics and its validity is assessed via comparison with equivalent blade-only large-eddy simulations. By applying this method, we identify the fluid force components contributing to cross-flow turbine power production and forcing, illuminating the significance of the commonly ignored pitching moment. Failing to consider this term leads to an over-prediction of cross-flow turbine performance.Overall, these three works contribute new methods, fundamental knowledge, and data to the field of cross-flow turbine research and together they constitute a set of well-characterized benchmark cases useful for informing future works that consider different turbine geometries, kinematics, or non-ideal inflows. Further these works provide useful insight applicable to improving reduced-order models and turbine structural design.
일반주제명  
Fluid mechanics
일반주제명  
Applied physics
일반주제명  
Energy
일반주제명  
Mechanical engineering
키워드  
Aerodynamics
키워드  
Cross-flow turbines
키워드  
Dynamic stall
키워드  
Marine renewable energy
키워드  
Particle image velocimetry
키워드  
Vertical axis wind turbines
기타저자  
University of Washington Mechanical Engineering
기본자료저록  
Dissertations Abstracts International. 86-03B.
전자적 위치 및 접속  
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MARC

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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a620
■1001  ▼aSnortland,  Abigale.
■24510▼aExperimental  Investigations  Into  the  Fluid  Dynamics  and  Forcing  Underlying  Cross-Flow  Turbine  Operation
■260    ▼a[Sl]▼bUniversity  of  Washington▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a154  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-03,  Section:  B.
■500    ▼aIncludes  supplementary  digital  materials.
■500    ▼aAdvisor:  Polagye,  Brian;Williams,  Owen.
■5021  ▼aThesis  (Ph.D.)--University  of  Washington,  2024.
■520    ▼aWithin  the  wind  and  marine  energy  sectors,  axial-flow  (i.e.,  horizontal  axis)  turbines  are  a  well-established  and  well-understood  approach  to  converting  the  kinetic  energy  in  a  moving  fluid  to  electricity.  Recent  cross-flow  (i.e.,  vertical  axis)  turbine  research  has  yielded  substantial  performance  gains  through  the  exploitation  of  unsteady  fluid  dynamics  for  individual  turbines  and  mutually  beneficial  interactions  between  closely-spaced  turbines  in  arrays.  However,  an  understanding  of  the  dynamics  underlying  cross-flow  turbine  operation  remains  incomplete  due  to  the  presence  of  fluid  phenomena  that  are  difficult  to  model,  including  dynamic  stall,  flow  curvature  effects,  and  the  influence  of  the  turbine  on  the  surrounding  flow,  called  induction.  This  thesis  considers  the  intricate  relationship  between  the  flow  physics  and  performance  of  cross-flow  turbines  and  augments  understanding  of  their  fundamental  operation.  First,  cross-flow  turbine  performance  and  flow  fields  exhibit  cycle-to-cycle  variations,  though  this  is  often  implicitly  neglected  through  time-  and  phase-averaging.  This  variability  could  potentially  arise  from  a  variety  of  mechanisms  --  inflow  fluctuations,  the  stochastic  nature  of  dynamic  stall,  and  cycle-to-cycle  hysteresis  --  each  of  which  have  different  implications  for  our  understanding  of  cross-flow  turbine  dynamics.  In  this  work,  the  extent  and  sources  of  cycle-to-cycle  variability,  for  both  the  flow  fields  and  performance,  are  explored  experimentally  under  two,  contrasting  operational  conditions.  Flow  fields,  obtained  through  two-dimensional  planar  particle  image  velocimetry  (PIV)  inside  the  turbine  swept  area,  are  correlated  simultaneously  with  measured  performance  using  an  unsupervised  hierarchical  clustering  pipeline.  A  principal  component  analysis  (PCA)  pre-processor  is  employed  that  allows  for  clustering  based  on  all  the  dynamics  present  in  the  high-dimensional  flow-field  data  in  an  interpretable,  low-dimensional  subspace  that  is  weighted  by  contribution  to  overall  velocity  variance.  We  find  that  the  flow-field  clusters  and  their  associated  performance  are  correlated  primarily  with  inflow  fluctuations,  despite  relatively  low  turbulence  intensity.  These  inflow  fluctuations  drive  variations  in  the  timing  of  the  dynamic  stall  process,  while  hysteresis  between  cycles  is  found  to  be  negligible.  Clustering  reveals  persistent  ties  between  performance  and  flow-field  variability  during  the  upstream  portion  of  the  turbine  rotation.  The  approach  employed  here  provides  a  more  comprehensive  picture  of  cross-flow  turbine  flow  fields  and  performance  than  aggregate,  statistical  representations.Second,  cross-flow  turbine  blades  encounter  a  relatively  undisturbed  inflow  for  the  first  half  of  each  rotational  cycle  (``upstream  sweep'')  and  then  pass  through  their  own  wake  for  the  latter  half  (``downstream  sweep'').  While  most  research  on  cross-flow  turbine  optimization  focuses  on  the  power-generating  upstream  sweep,  we  use  single-bladed  turbine  experiments  to  show  that  the  downstream  sweep  strongly  affects  time-averaged  performance.  Specifically,  we  find  that  power  generation  from  the  upstream  sweep  continues  to  increase  beyond  the  optimal  tip-speed  ratio.  In  contrast,  the  power  consumption  from  the  downstream  sweep  begins  to  increase  approximately  linearly  beyond  the  optimal  tip-speed  ratio  due,  in  part,  to  an  increasingly  unfavorable  orientation  of  lift  and  drag  relative  to  the  rotation  direction.  Downstream  power  degradation  increases  faster  than  upstream  power  generation,  indicating  the  downstream  sweep  strongly  influences  the  optimal  tip-speed  ratio.  In  addition,  PIV  data  is  obtained  inside  the  turbine  swept  area  at  three  tip-speed  ratios.  This  illuminates  the  mechanisms  underpinning  the  observed  performance  degradation  in  the  downstream  sweep  and  motivates  an  analytical  model  for  a  limiting  case  with  high  induction  or  an  infinite  tip-speed  ratio.  Performance  results  are  shown  to  be  consistent  across  55  unique  combinations  of  chord-to-radius  ratio,  preset  pitch  angle,  and  Reynolds  number,  underscoring  the  general  significance  of  the  downstream  sweep  to  cross-flow  turbine  performance.  Third,  while  investigating  trends  in  terms  of  turbine-level  forces  and  torques  is  important,  it  does  not  tell  the  full  story  of  cross-flow  turbine  operation.  Identification  of  blade-level  forces  and  torques  allows  for  specific  investigations  into  how  effectively  fluid  forcing  on  the  blade  drives  rotation  and  can  aid  in  blade  structural  design.  Further,  the  determination  of  blade-level  forces  allows  more  robust  comparison  to  computational  fluid  dynamic  simulations.  Here,  we  present  a  methodology  for  extracting  blade-level  forces  and  moments  from  experimental  measurements  at  the  axis  of  rotation  for  a  single-bladed  turbine.  The  method  is  based  on  knowledge  of  the  flow  physics  and  its  validity  is  assessed  via  comparison  with  equivalent  blade-only  large-eddy  simulations.  By  applying  this  method,  we  identify  the  fluid  force  components  contributing  to  cross-flow  turbine  power  production  and  forcing,  illuminating  the  significance  of  the  commonly  ignored  pitching  moment.  Failing  to  consider  this  term  leads  to  an  over-prediction  of  cross-flow  turbine  performance.Overall,  these  three  works  contribute  new  methods,  fundamental  knowledge,  and  data  to  the  field  of  cross-flow  turbine  research  and  together  they  constitute  a  set  of  well-characterized  benchmark  cases  useful  for  informing  future  works  that  consider  different  turbine  geometries,  kinematics,  or  non-ideal  inflows.  Further  these  works  provide  useful  insight  applicable  to  improving  reduced-order  models  and  turbine  structural  design.
■590    ▼aSchool  code:  0250.
■650  4▼aFluid  mechanics
■650  4▼aApplied  physics
■650  4▼aEnergy
■650  4▼aMechanical  engineering
■653    ▼aAerodynamics
■653    ▼aCross-flow  turbines
■653    ▼aDynamic  stall
■653    ▼aMarine  renewable  energy
■653    ▼aParticle  image  velocimetry
■653    ▼aVertical  axis  wind  turbines
■690    ▼a0204
■690    ▼a0548
■690    ▼a0215
■690    ▼a0791
■71020▼aUniversity  of  Washington▼bMechanical  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-03B.
■790    ▼a0250
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163249▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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