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  1. Free, publicly-accessible full text available June 1, 2024
  2. null (Ed.)
  3. Foulds, J.R. ; Pan, S. (Ed.)
  4. null (Ed.)
  5. While bending strains result from any web being wound at a radius of curvature into a roll, these bending strains are largest for the thicker homogeneous webs and laminates. Many webs are viscoelastic on some time scale and bending stresses will lead to creep. When the web material is unwound and cut into discrete samples, a residual curvature will remain. This curvature, called curl, is the inability for the web to lie flat at no tension. Curl is an undesirable web defect that causes loss of productivity in a subsequent web process. The goal of this research is to develop numerical and experimental tools by which process engineers can explore and mitigate machine direction curl in homogenous webs. Two numerical methods that allow the prediction of curl in a web are developed, a winding software based on bending recovery theory and the implementation of dynamic simulations of winding. One experimental method directly measures the curl online by taking advantage of the anticlastic bending resulting from the curl. All methods applied to a common isotropic LDPE web correlate well with each other and present an opportunity for process engineers to mitigate curl and its negative consequences at low time cost. 
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  6. Free, publicly-accessible full text available June 1, 2024
  7. Abstract The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype. 
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