The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f9860d07890>'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/xml/xml.py", line 67, in _generate_tables
with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 967, in xopen
return open(main_hop, mode, *args, **kwargs)
FileNotFoundError: [Errno 2] No such file or directory: '<datasets.utils.file_utils.FilesIterable object at 0x7f9860d07890>'Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PIGLET Test Cases
PIGLET is a MATLAB based framework for the reconstruction of turbulent flow fields from particle tracking data. This dataset contains test cases to demonstrate and test PIGLET. The test cases include:
prism- experimental Shake-The-Box particle tracking measurements in the wake of a square prism at $Re_H \approx 7850$hit- synthetic data of homogeneous isotropic turbulence at $Re_\lambda \approx 125$channel- synthetic data of turbulent channel flow at $Re_\tau \approx 180$DAChallenge- a copy of the turbulent duct test case from the 2nd Data Assimilation Challenge
Square Prism Wake
This dataset contains measurements of the wake of a $H=50\textrm{mm}$ square prism at a freestream velocity of $U_\infty = 0.150~\text{m/s}$ corresponding to $\Re_H \approx 7850$ in the University of Southampton's Recirculating Water Tunnel. This flow lacks fundamental statistical symmetries of homogeneity and isotropy, making it a useful test case for PIGLET.
Polyamide tracers ($55\mu\text{m}$ diameter) were recored using a four-camera LaVision Minishaker 2M PTV system and LED-pulse illumination at $121.2 \text{Hz}$. 120 bursts of 25 frames each were recored at 3.5s intervals, covering a downstream region 105 to 445 mm from the prism at a resolution of 0.165 mm/vx with a seeding concentration of 0.0056ppp. Particle trajectories were reconstructed in DaViS 10 using the Shake-The-Box algorithm. A full description of the dataset and the methodology used are available at https://doi.org/10.1103/zvm4-wtkq.
Homogeneous Isotropic Turbulence
This case is derived from direct numerical simulation of turbulence in a $512^3$ periodic box of side length $2\pi$ at $R_\lambda \approx 122$. Initially, the turbulence was externally forced to reach a statistically stationary state. Then, the forcing was turned off and the trajectories of $2^{22}$ tracer particles were integrated using a fourth-order Adams-Bashforth method and cubic spline velocity interpolation for $1.0\tau_\eta$.
The DNS data was was partitioned into $64$ sub-volumes of side-length $\pi/2$.
Data was downsampled to 4096, 16384, or 65536 particles per sub-volume, corresponding to datasets bigbox32x, bigbox8x and bigbox2x.
Velocity data sampled on tracer trajectories are used to generate a synthetic four-pulse LPT measurement using a $2:1:2$ timing scheme with $\Delta t = 0.15\tau_\eta$ between the second and third pulses.
Over this timestep, the mean square displacement is $0.85\eta$ ($\approx 0.4%$ of the domain).
Additive white Gaussian noise was added to these trajectories to model position uncertainty, corresponding to a moderate measurement noise level $\sigma_u/u' = 0.01$ (the standard uncertainty in the particle position is $\sigma_x = 2.2324 \times 10^{-4}$).
Finally, a second order polynomial fit is applied to each trajectory to measure the (noisy) tracer position, velocity and acceleration.
Turbulent Channel Flow
This case is derived from direct numerical simulations of turbulent channel flow in a $4\pi \times 2 \times 2\pi$ domain, periodic in the streamwise and spanwise directions, at $\Re_\tau \approx 180$ using spectralDNS. The channel half height is $h=1$ and the skin friction velocity is $u_\tau = 0.064$. spectralDNS implements a standard spectral-Galerkin method discretised onto $192 \times 128 \times 192$ intervals using Fourier basis functions for the streamwise and spanwise directions and Chebyshev polynomials in the wall-normal direction. Second-order accurate integration in time is performed using the Crank-Nicolson method for the linear terms and an Adams-Bashforth method for the non-linear terms with a constant time step $5\times10^{-3}$ corresponding to a Courant-Friedrichs-Lewy number of $0.076$. The simulation is initialised from laminar conditions with a small perturbation added to trigger transition to turbulence and is initially allowed to evolve to a fully turbulent state with a dynamically adjusted driving force to maintain the bulk velocity $U_b = 1$. After $t U_b / h = 60$ convective flow through times, the forcing is turned off and the flow is driven by a uniform pressure gradient. After a further $210$ convective flow through times to establish stationarity, $2^{22}$ tracer particles are uniformly seeded throughout the domain and their trajectories are integrated using a second-order Heun scheme. The tracer velocity is interpolated using a fourth order barycentric Lagrange interpolation scheme.
The dataset contains a sampling of 910 tracers in 72 sub-volumes ($\pi/6 \times 1 \times 2\pi/3$) drawn from the bottom half of the channel flow after it has reached a stationary state. Trajectories are selected so that all tracks are entirely within the measurement domain. A normally distributed position error is added to trajectories, corresponding to a velocity measurement noise of $\sigma = 0.01U_b$.
2nd Data Assimilation Challenge
This is a copy of the turbulent duct flow dataset from the 2nd Data Assimilation Challenge.
- Downloads last month
- 11