Matching Items (14)
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- All Subjects: Climate Change
- All Subjects: Particle Image Velocimetry
- Creators: Huang, Huei-Ping
Description
The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections.
ContributorsBaker, Noel C (Author) / Huang, Huei-Ping (Thesis advisor) / Trimble, Steve (Committee member) / Anderson, James (Committee member) / Clarke, Amanda (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2013
Description
Modern day gas turbine designers face the problem of hot mainstream gas ingestion into rotor-stator disk cavities. To counter this ingestion, seals are installed on the rotor and stator disk rims and purge air, bled off from the compressor, is injected into the cavities. It is desirable to reduce the supply of purge air as this decreases the net power output as well as efficiency of the gas turbine. Since the purge air influences the disk cavity flow field and effectively the amount of ingestion, the aim of this work was to study the cavity velocity field experimentally using Particle Image Velocimetry (PIV). Experiments were carried out in a model single-stage axial flow turbine set-up that featured blades as well as vanes, with purge air supplied at the hub of the rotor-stator disk cavity. Along with the rotor and stator rim seals, an inner labyrinth seal was provided which split the disk cavity into a rim cavity and an inner cavity. First, static gage pressure distribution was measured to ensure that nominally steady flow conditions had been achieved. The PIV experiments were then performed to map the velocity field on the radial-tangential plane within the rim cavity at four axial locations. Instantaneous velocity maps obtained by PIV were analyzed sector-by-sector to understand the rim cavity flow field. It was observed that the tangential velocity dominated the cavity flow at low purge air flow rate, its dominance decreasing with increase in the purge air flow rate. Radially inboard of the rim cavity, negative radial velocity near the stator surface and positive radial velocity near the rotor surface indicated the presence of a recirculation region in the cavity whose radial extent increased with increase in the purge air flow rate. Qualitative flow streamline patterns are plotted within the rim cavity for different experimental conditions by combining the PIV map information with ingestion measurements within the cavity as reported in Thiagarajan (2013).
ContributorsPathak, Parag (Author) / Roy, Ramendra P (Thesis advisor) / Calhoun, Ronald (Committee member) / Lee, Taewoo (Committee member) / Arizona State University (Publisher)
Created2013
Description
The numerical climate models have provided scientists, policy makers and the general public, crucial information for climate projections since mid-20th century. An international effort to compare and validate the simulations of all major climate models is organized by the Coupled Model Intercomparison Project (CMIP), which has gone through several phases since 1995 with CMIP5 being the state of the art. In parallel, an organized effort to consolidate all observational data in the past century culminates in the creation of several "reanalysis" datasets that are considered the closest representation of the true observation. This study compared the climate variability and trend in the climate model simulations and observations on the timescales ranging from interannual to centennial. The analysis focused on the dynamic climate quantity of zonal-mean zonal wind and global atmospheric angular momentum (AAM), and incorporated multiple datasets from reanalysis and the most recent CMIP3 and CMIP5 archives. For the observation, the validation of AAM by the length-of-day (LOD) and the intercomparison of AAM revealed a good agreement among reanalyses on the interannual and the decadal-to-interdecadal timescales, respectively. But the most significant discrepancies among them are in the long-term mean and long-term trend. For the simulations, the CMIP5 models produced a significantly smaller bias and a narrower ensemble spread of the climatology and trend in the 20th century for AAM compared to CMIP3, while CMIP3 and CMIP5 simulations consistently produced a positive trend for the 20th and 21st century. Both CMIP3 and CMIP5 models produced a wide range of the magnitudes of decadal and interdecadal variability of wind component of AAM (MR) compared to observation. The ensemble means of CMIP3 and CMIP5 are not statistically distinguishable for either the 20th- or 21st-century runs. The in-house atmospheric general circulation model (AGCM) simulations forced by the sea surface temperature (SST) taken from the CMIP5 simulations as lower boundary conditions were carried out. The zonal wind and MR in the CMIP5 simulations are well simulated in the AGCM simulations. This confirmed SST as an important mediator in regulating the global atmospheric changes due to GHG effect.
ContributorsPaek, Houk (Author) / Huang, Huei-Ping (Thesis advisor) / Adrian, Ronald (Committee member) / Wang, Zhihua (Committee member) / Anderson, James (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced climate changes in the 21st century. The computer simulations performed with those models and archived by the Coupled Model Intercomparison Project - Phase 5 (CMIP5) form the most comprehensive quantitative basis for the prediction of global environmental changes on decadal-to-centennial time scales. While the CMIP5 archives have been widely used for policy making, the inherent biases in the models have not been systematically examined. The main objective of this study is to validate the CMIP5 simulations of the 20th century climate with observations to quantify the biases and uncertainties in state-of-the-art climate models. Specifically, this work focuses on three major features in the atmosphere: the jet streams over the North Pacific and Atlantic Oceans and the low level jet (LLJ) stream over central North America which affects the weather in the United States, and the near-surface wind field over North America which is relevant to energy applications. The errors in the model simulations of those features are systematically quantified and the uncertainties in future predictions are assessed for stakeholders to use in climate applications. Additional atmospheric model simulations are performed to determine the sources of the errors in climate models. The results reject a popular idea that the errors in the sea surface temperature due to an inaccurate ocean circulation contributes to the errors in major atmospheric jet streams.
ContributorsKulkarni, Sujay (Author) / Huang, Huei-Ping (Thesis advisor) / Calhoun, Ronald (Committee member) / Peet, Yulia (Committee member) / Arizona State University (Publisher)
Created2014
Description
Due to decrease in fossil fuel levels, the world is shifting focus towards renewable sources of energy. With an annual average growth rate of 25%, wind is one of the foremost source of harnessing cleaner energy for production of electricity. Wind turbines have been developed to tap power from wind. As a single wind turbine is insufficient, multiple turbines are installed forming a wind farm. Generally, wind farms can have hundreds to thousands of turbines concentrated in a small region. There have been multiple studies centering the influence of weather on such wind farms, but no substantial research focused on how wind farms effect local climate. Technological advances have allowed development of commercial wind turbines with a power output greater than 7.58 MW. This has led to a reduction in required number of turbines and has optimized land usage. Hence, current research considers higher power density compared to previous works that relied on wind farm density of 2 to 4 W/m 2 . Simulations were performed using Weather Research and Forecasting software provided by NCAR. The region of simulation is Southern Oregon, with domains including both onshore and offshore wind farms. Unlike most previous works, where wind farms were considered to be on a flat ground, effects of topography have also been considered here. Study of seasonal effects over wind farms has provided better insight into changes in local wind direction. Analysis of mean velocity difference across wind farms at a height of 10m and 150m gives an understanding of wind velocity profiles. Results presented in this research tends to contradict earlier belief that velocity reduces throughout the farm. Large scale simulations have shown that sometimes, more than 50% of the farm can have an increased wind velocity of up to 1m/s
at an altitude of 10m.
at an altitude of 10m.
ContributorsKadiyala, Yogesh Rao (Author) / Huang, Huei-Ping (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2015
Description
This study performs numerical modeling for the climate of semi-arid regions by running a high-resolution atmospheric model constrained by large-scale climatic boundary conditions, a practice commonly called climate downscaling. These investigations focus especially on precipitation and temperature, quantities that are critical to life in semi-arid regions. Using the Weather Research and Forecast (WRF) model, a non-hydrostatic geophysical fluid dynamical model with a full suite of physical parameterization, a series of numerical sensitivity experiments are conducted to test how the intensity and spatial/temporal distribution of precipitation change with grid resolution, time step size, the resolution of lower boundary topography and surface characteristics. Two regions, Arizona in U.S. and Aral Sea region in Central Asia, are chosen as the test-beds for the numerical experiments: The former for its complex terrain and the latter for the dramatic man-made changes in its lower boundary conditions (the shrinkage of Aral Sea). Sensitivity tests show that the parameterization schemes for rainfall are not resolution-independent, thus a refinement of resolution is no guarantee of a better result. But, simulations (at all resolutions) do capture the inter-annual variability of rainfall over Arizona. Nevertheless, temperature is simulated more accurately with refinement in resolution. Results show that both seasonal mean rainfall and frequency of extreme rainfall events increase with resolution. For Aral Sea, sensitivity tests indicate that while the shrinkage of Aral Sea has a dramatic impact on the precipitation over the confine of (former) Aral Sea itself, its effect on the precipitation over greater Central Asia is not necessarily greater than the inter-annual variability induced by the lateral boundary conditions in the model and large scale warming in the region. The numerical simulations in the study are cross validated with observations to address the realism of the regional climate model. The findings of this sensitivity study are useful for water resource management in semi-arid regions. Such high spatio-temporal resolution gridded-data can be used as an input for hydrological models for regions such as Arizona with complex terrain and sparse observations. Results from simulations of Aral Sea region are expected to contribute to ecosystems management for Central Asia.
ContributorsSharma, Ashish (Author) / Huang, Huei-Ping (Thesis advisor) / Adrian, Ronald (Committee member) / Herrmann, Marcus (Committee member) / Phelan, Patrick E. (Committee member) / Vivoni, Enrique (Committee member) / Arizona State University (Publisher)
Created2012
Description
Over the past three decades, particle image velocimetry (PIV) has been continuously growing to become an informative and robust experimental tool for fluid mechanics research. Compared to the early stage of PIV development, the dynamic range of PIV has been improved by about an order of magnitude (Adrian, 2005; Westerweel et al., 2013). Further improvement requires a breakthrough innovation, which constitutes the main motivation of this dissertation. N-pulse particle image velocimetry-accelerometry (N-pulse PIVA, where N>=3) is a promising technique to this regard. It employs bursts of N pulses to gain advantages in both spatial and temporal resolution. The performance improvement by N-pulse PIVA is studied using particle tracking (i.e. N-pulse PTVA), and it is shown that an enhancement of at least another order of magnitude is achievable. Furthermore, the capability of N-pulse PIVA to measure unsteady acceleration and force is demonstrated in the context of an oscillating cylinder interacting with surrounding fluid. The cylinder motion, the fluid velocity and acceleration, and the fluid force exerted on the cylinder are successfully measured. On the other hand, a key issue of multi-camera registration for the implementation of N-pulse PIVA is addressed with an accuracy of 0.001 pixel. Subsequently, two applications of N-pulse PTVA to complex flows and turbulence are presented. A novel 8-pulse PTVA analysis was developed and validated to accurately resolve particle unsteady drag in post-shock flows. It is found that the particle drag is substantially elevated from the standard drag due to flow unsteadiness, and a new drag correlation incorporating particle Reynolds number and unsteadiness is desired upon removal of the uncertainty arising from non-uniform particle size. Next, the estimation of turbulence statistics utilizes the ensemble average of 4-pulse PTV data within a small domain of an optimally determined size. The estimation of mean velocity, mean velocity gradient and isotropic dissipation rate are presented and discussed by means of synthetic turbulence, as well as a tomographic measurement of turbulent boundary layer. The results indicate the superior capability of the N-pulse PTV based method to extract high-spatial-resolution high-accuracy turbulence statistics.
ContributorsDing, Liuyang (Author) / Adrian, Ronald J (Thesis advisor) / Frakes, David (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Peet, Yulia (Committee member) / Arizona State University (Publisher)
Created2018
Description
Rapid expansion of dense beds of fine, spherical particles subjected to rapid depressurization is studied in a vertical shock tube. As the particle bed is unloaded, a high-speed video camera captures the dramatic evolution of the particle bed structure. Pressure transducers are used to measure the dynamic pressure changes during the particle bed expansion process. Image processing, signal processing, and Particle Image Velocimetry techniques, are used to examine the relationships between particle size, initial bed height, bed expansion rate, and gas velocities.
The gas-particle interface and the particle bed as a whole expand and evolve in stages. First, the bed swells nearly homogeneously for a very brief period of time (< 2ms). Shortly afterward, the interface begins to develop instabilities as it continues to rise, with particles nearest the wall rising more quickly. Meanwhile, the bed fractures into layers and then breaks down further into cellular-like structures. The rate at which the structural evolution occurs is shown to be dependent on particle size. Additionally, the rate of the overall bed expansion is shown to be dependent on particle size and initial bed height.
Taller particle beds and beds composed of smaller-diameter particles are found to be associated with faster bed-expansion rates, as measured by the velocity of the gas-particle interface. However, the expansion wave travels more slowly through these same beds. It was also found that higher gas velocities above the the gas-particle interface measured \textit{via} Particle Image Velocimetry or PIV, were associated with particle beds composed of larger-diameter particles. The gas dilation between the shocktube diaphragm and the particle bed interface is more dramatic when the distance between the gas-particle interface and the diaphragm is decreased-as is the case for taller beds.
To further elucidate the complexities of this multiphase compressible flow, simple OpenFOAM (Weller, 1998) simulations of the shocktube experiment were performed and compared to bed expansion rates, pressure fluctuations, and gas velocities. In all cases, the trends and relationships between bed height, particle diameter, with expansion rates, pressure fluctuations and gas velocities matched well between experiments and simulations. In most cases, the experimentally-measured bed rise rates and the simulated bed rise rates matched reasonably well in early times. The trends and overall values of the pressure fluctuations and gas velocities matched well between the experiments and simulations; shedding light on the effects each parameter has on the overall flow.
The gas-particle interface and the particle bed as a whole expand and evolve in stages. First, the bed swells nearly homogeneously for a very brief period of time (< 2ms). Shortly afterward, the interface begins to develop instabilities as it continues to rise, with particles nearest the wall rising more quickly. Meanwhile, the bed fractures into layers and then breaks down further into cellular-like structures. The rate at which the structural evolution occurs is shown to be dependent on particle size. Additionally, the rate of the overall bed expansion is shown to be dependent on particle size and initial bed height.
Taller particle beds and beds composed of smaller-diameter particles are found to be associated with faster bed-expansion rates, as measured by the velocity of the gas-particle interface. However, the expansion wave travels more slowly through these same beds. It was also found that higher gas velocities above the the gas-particle interface measured \textit{via} Particle Image Velocimetry or PIV, were associated with particle beds composed of larger-diameter particles. The gas dilation between the shocktube diaphragm and the particle bed interface is more dramatic when the distance between the gas-particle interface and the diaphragm is decreased-as is the case for taller beds.
To further elucidate the complexities of this multiphase compressible flow, simple OpenFOAM (Weller, 1998) simulations of the shocktube experiment were performed and compared to bed expansion rates, pressure fluctuations, and gas velocities. In all cases, the trends and relationships between bed height, particle diameter, with expansion rates, pressure fluctuations and gas velocities matched well between experiments and simulations. In most cases, the experimentally-measured bed rise rates and the simulated bed rise rates matched reasonably well in early times. The trends and overall values of the pressure fluctuations and gas velocities matched well between the experiments and simulations; shedding light on the effects each parameter has on the overall flow.
ContributorsZunino, Heather (Author) / Adrian, Ronald J (Thesis advisor) / Clarke, Amanda (Committee member) / Chen, Kangping (Committee member) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2019
Description
The hydrologic cycle in drylands is complex with large spatiotemporal variationsacross scales and is particularly vulnerable to changes in climate and land cover. To
address the challenges posed by hydrologic changes, a synergistic approach that
combines numerical models, ground and remotely sensed observations, and data analysis
is crucial. This dissertation uses innovative detection and modeling techniques to assess
key hydrologic variables in drylands, including irrigated water use, streamflow, and
snowpack conditions, answering following research questions that also have broad
societal implications: (1) What are the individual and combined effects of future climate
and land use change on irrigation water use (IWU) in the Phoenix Metropolitan Area
(PMA)?; (2) How can temporal changes in streamflow and the impacts of flash flooding
be detected in dryland rivers?; and (3) What are the impacts of rainfall-snow partitioning
on future snowpack and streamflow in the Colorado River Basin (CRB)?
Firstly, I conducted a scenario modeling using the Variable Infiltration Capacity
(VIC) model under future climate and land use change scenarios. Results showed that
future IWU will change from -0.5% to +6.8% in the far future (2071-2100) relative to the
historical period (1981-2010). Secondly, I employed CubeSat imagery to map streamflow
presence in the Hassayampa River of Arizona, finding that the imaging capacity of
CubeSats enabled the detection of ephemeral flow events using the surface reflectance of
the near-infrared (NIR) band. Results showed that 12% of reaches were classified as
intermittent, with the remaining as ephemeral. Finally, I implemented a physically-based
rainfall-snow partitioning scheme in the VIC model that estimates snowfall fraction from
the wet-bulb temperature using a sigmoid function. The new scheme predicts more
significant declines in snowfall (-8 to -11%) and streamflow (-14 to -27%) by the end of
the 21st century over the CRB, relative to historical conditions.
Overall, this dissertation demonstrates how innovative technologies can enhance
the understanding of dryland hydrologic changes and inform decision-making of water
resources management. The findings offer important insights for policymakers, water
managers, and researchers who seek to ensure water resources sustainability under the
effects of climate and land use change.
ContributorsWang, Zhaocheng (Author) / Vivoni, Enrique R (Thesis advisor) / White, Dave D (Committee member) / Mascaro, Giuseppe (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2023