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451 results for “Elasticity”
Elastic Strain Associated with Irradiation-Induced Defects in Self-ion Irradiated Tungsten
<p>Elastic interactions play an important role in controlling irradiation damage evolution, but remain largely unexplored experimentally. Using transmission electron microscopy (TEM) and high-resolution on-axis transmission Kikuchi diffraction (HR-TKD), we correlate the evolution of irradiation-induced damage structures and the associated lattice strains in self-ion irradiated pure tungsten. TEM reveals different dislocation loop structures as a function of sample thickness, suggesting that free surfaces limit the formation of extended defect structures that are found in thicker samples. HR-TKD strain analysis shows the formation of crystallographically-orientated long-range strain fluctuation above 0.01 dpa and a decrease of total elastic energy above 0.1 dpa.</p>
Developing elastic mechanisms: Ultrafast motion and cavitation emerge at the millimeter scale in juvenile snapping shrimp
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Elastic pinch biomechanisms can yield consistent launch speeds regardless of projectile mass
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Indirect actuation reduces flight power requirements in Manduca sexta via elastic energy exchange
<p>In many insects, wing movements are generated indirectly via exoskeletal deformations. Measurements of inertial and aerodynamic power suggest that elastic recovery of energy between wingstrokes might reduce power requirements of flight. We tested three questions. 1) Can the thorax itself provide significant energy return? 2) Does a simple damped elastic model describe the bulk mechanical behavior? and 3) Are different regions of the thorax specialized for elastic energy exchange? We measured deformation mechanics of the hawkmoth <em>Manduca sexta</em> thorax by recording the force required to sinusoidally deform the thorax over a wide frequency range. Elastic energy storage in the thorax is sufficient to minimize power requirements. However, we find that a structural (frequency-independent) damping model, not a viscoelastic model, best describes the thorax's mechanical properties. We next performed complementary experiments on a structurally damped homogeneous hemisphere. In contrast to the hemispherical shell, we find that mechanical coupling between different regions of the thorax improves energy exchange performance, and that local mechanical properties depend on global strain patterns. Specifically, the scutum region provides energy recovery with low dissipation, while the majority of energy loss occurred in the wing hinge region, highlighting the specificity of thorax regions for flight energetics. </p>
Data for: Elastic Application-Level Monitoring for Large Software Landscapes in the Cloud
<p>Application-level monitoring provides valuable, detailed insights into running applications. However, many approaches often only employ a single analysis application. This analysis application may become a performance bottleneck when monitoring several programs resulting in reduced monitoring quality or violated service level agreements of the monitored applications.</p> <p>We present an approach for elastic, distributed application-level monitoring for large software landscapes consisting of several hundreds of applications by utilizing cloud computing. Our approach dynamically inserts and removes worker levels to circumvent overloading the analysis master application without interrupting or pausing the actual live analysis of the monitored data. To evaluate our approach, we conduct an experiment in which we generate load - following a real workload pattern - on web applications in a 24 hour experiment.</p> <p>In our experiment, 160 monitored JPetStore instances generate roughly 20 million analyzed method calls per second in the peak. Furthermore, two worker levels are dynamically started and removed in line with the imposed workload on the monitored applications. The experiment shows that our monitoring approach is capable of live analyzing several millions of monitored method calls per second without overloading the analysis master application.</p> <p>This package provides our supplementary data.</p>
Shape, motion and optical cues to stiffness of elastic objects
<p>Dataset relative to the following publication:</p> <p>Paulun, V.C., Schmidt, F., van Assen, J.J.R., & Fleming, R. W. (2017). Shape, motion and optical cues to stiffness of elastic objects. <em>Journal of Vision, 17(1):20, </em>1-20, doi:10.1167/17.1.20</p> <p>Each folder contains the data and stimulus material relative to one experiment and a text file with comments.</p>
Optimal mechanical interactions direct multicellular network formation on elastic substrates
<p>Cells self-organize into functional, ordered structures during tissue morphogenesis, a process that is evocative of colloidal self-assembly into engineered soft materials. Understanding how intercellular mechanical interactions may drive the formation of ordered and functional multicellular structures is important in developmental biology and tissue engineering. Here, by combining an agent-based model for contractile cells on elastic substrates with endothelial cell culture experiments, we show that substrate deformation–mediated mechanical interactions between cells can cluster and align them into branched networks. Motivated by the structure and function of vasculogenic networks, we predict how measures of network connectivity like percolation probability and fractal dimension as well as local morphological features including junctions, branches, and rings depend on cell contractility and density and on substrate elastic properties including stiffness and compressibility. We predict and confirm with experiments that cell network formation is substrate stiffness dependent, being optimal at intermediate stiffness. We also show the agreement between experimental data and predicted cell cluster types by mapping a combined phase diagram in cell density substrate stiffness. Overall, we show that long-range, mechanical interactions provide an optimal and general strategy for multicellular self-organization, leading to more robust and efficient realizations of space-spanning networks than through just local intercellular interactions.</p>
Data from: Clots reveal anomalous elastic behavior of fiber networks
<p>The adaptive mechanical properties of soft and fibrous biological materials are relevant to their functionality. The emergence of the macroscopic response of these materials to external stress and intrinsic cell traction from local deformations of their structural components is not well understood. Here, we investigate the nonlinear elastic behavior of blood clots by combining microscopy, rheology, and an elastic network model that incorporates the stretching, bending, and buckling of constituent fibrin fibers. By inhibiting fibrin crosslinking in blood clots, we observe an anomalous softening regime in the macroscopic shear response as well as a reduction in platelet-induced clot contractility. Our model explains these observations from two independent macroscopic measurements in a unified manner, through a single mechanical parameter, the bending stiffness of individual fibers. Supported by experimental evidence, our mechanics-based model provides a framework for predicting and comprehending the nonlinear elastic behavior of blood clots and other active biopolymer networks in general.</p>
Teleseismic reverse time migration image dataset of southwest Japan in "Three-dimensional teleseismic elastic reverse-time migration with deconvolution imaging condition and its application to southwest Japan"
<p>This dataset contains the teleseismic elastic reverse time migration results of southwest Japan used in the manuscript entitled "Three-dimensional teleseismic elastic reverse-time migration with deconvolution imaging condition and its application to southwest Japan". submitted to Journal of Geophysical Research Letters.</p>
Temperature-dependent photo-elastic coefficient of silicon at 1550 nm
<p>The associated paper presents a study on the temperature-dependent photo-elastic coefficient in single-crystal silicon with (100) and (110) orientations at a wavelength of 1550 nm. The measurement of the photo-elastic coefficient was performed using a polarimetric scheme across a wide temperature range from 5 K to 300 K. The experimental setup employed high-sensitivity techniques and incorporated automatic beam path correction, ensuring precise and accurate determination of the coefficient's values. The results show excellent agreement with previous measurements at room temperature, specifically yielding a value of dn/dσ = −2.463E-11 1/Pa for the (100) orientation. Interestingly, there is a significant difference in photo-elasticity between the different crystal orientations of approximately 50 %. The photo-elastic coefficient's absolute value increases by approximately 40 % with decreasing temperature down to 5 K. These findings provide valuable insights into the photo-elastic properties of silicon and its behavior under varying mechanical stress, particularly relevant for optomechanical precision experiments like cryogenic gravitational wave detectors and microscale optomechanical quantum sensors.</p>
Room temperature and elevated temperature tensile test and elastic properties data of Al-alloy EN AW-2618A after different aging times and temperatures
<p><span>The dataset contains two types of data: elastic properties (Young's and shear modulus, Poisson's ratio) between room temperature and 250 °C and a set of tensile tests at different aging times, aging temperatures, and test temperatures. </span></p>
Low-Frequency Measurements of the Effective-Stress Coefficient for Elastic Moduli of Mungaroo Sandstone
<p><span>The measurements were performed on <span>n-decane saturated sandstone </span>using a forced-oscillation laboratory apparatus utilizing stress-strain relationship. The dynamic elastic moduli have been measured in two sets of experiments: at constant pore pressures of 0, 1 and 5 MPa and differential pressure (defined as a difference between confining and pore pressures) varied from 3 to 19 MPa; and at </span><span>а</span><span> </span><span>constant confining pressure of 20 MPa and pore pressure varied from 1 to 17 MP. It was shown that the elastic moduli obtained in the measurements are in good agreement with the Gassmann moduli calculated for the range of differential pressures used in our experiments, which corresponds to the effective-stress coefficient equal to unity.</span></p>
Thermodynamic parameters and elasticity data of phase D at high pressures and temperatures
<p>This dataset contains all the original data for figures in the article "Thermoelasticity of phase D and implications for low-velocity anomalies and local discontinuities at the uppermost lower mantle" submitted to American Mineralogist.</p>
Code from: Effect of fluid elasticity on the emergence of oscillations in an active elastic filament
<p>Many microorganisms propel through complex media by deformations of their flagella. The beat is thought to emerge from interactions between forces of the surrounding fluid, passive elastic response from deformations of the flagellum, and active forces from internal molecular motors. The beat varies in response to changes in the fluid rheology, including elasticity, but there is limited data on how systematic changes in elasticity alter the beat. This work analyzes a related problem with fixed-strength driving force: the emergence of the beating of an elastic planar filament driven by a follower force at the tip in a viscoelastic fluid. This analysis examines how the onset of oscillations depends on the strength of the force and viscoelastic parameters. Compared to a Newtonian fluid, it takes more force to induce instability in viscoelastic fluids, and the frequency of the oscillation is higher. The linear analysis predicts that the frequency increases with the fluid relaxation time. Using numerical simulations, the model predictions are compared with experimental data on frequency changes in bi-flagellated alga <em>Chlamydomonas reinhardtii</em>. The model shows the same trends in response to changes in both fluid viscosity and Deborah number and thus provides a possible mechanistic understanding of the experimental observations.</p>
Results Data for "Price Formation Without Fuel Costs: The Interaction of Elastic Demand with Storage Bidding"
<h2>Abstract</h2> <p>Studies on electricity market design for high shares of wind and solar often predict the breakdown of energy-only markets, citing a lack of fuel costs to set prices. Issues include prolonged zero prices, politically unacceptable scarcity prices, price collapses from minor capacity changes, low market value cost recovery, revenue variability across different weather years, and challenges in long-term storage operation. These issues arise from modeling with perfectly inelastic demand. Introducing even a small amount of short-term elasticity (-5%) significantly mitigates these problems. A simplified model with wind, solar, batteries, and hydrogen storage shows that demand elasticity and storage opportunity costs stabilize pricing, smoothing the price duration curve, reducing zero-price hours from 90% to 30%, and ensuring price stability across capacities and weather years. Green hydrogen-derived fuels replace fossil fuels as backup. The long-term model matches the short-term model prices with identical capacities, guiding storage bidding strategies for short-term operations. A model trained on 35 years of weather data and tested on another 35 years demonstrates the energy-only market's potential in future dispatch and investment coordination.</p> <h2>Data Sources</h2> <p>- <strong>Solar and Wind Time Series (1950-2020):</strong> <a href="https://doi.org/10.17864/1947.000321">Bloomfield and Brayshaw (2021)</a><br>- <strong>Techno-Economic Assumptions:</strong><a href="https://github.com/PyPSA/technology-data/tree/v0.8.1"> technology-data (v0.8.1)</a>, <a href="https://ens.dk/en/our-services/technology-catalogues">Danish Energy Agency</a><br>- <strong>Demand Elasticity Assumptions:</strong> <a href="https://doi.org/10.1016/j.eneco.2024.107652">Hirth et al. (2024)</a>, <a href="https://www.ewi.uni-koeln.de/en/publications/on-the-functional-form-of-short-term-electricity-demand-response-insights-from-high-price-years-in-germany-2/">Arnold (2023)</a></p> <h2>Installation</h2> <p>Use <code>conda</code> environment manager:</p> <p><br><code>conda update conda</code><br><code>conda env create -f workflow/envs/environment.fixed.yaml</code><br><code>conda activate price-formation</code></p> <p><strong>Main Dependencies:</strong></p> <ul> <li>pypsa (v0.27.1)</li> <li>linopy (v0.3.8)</li> <li>snakemake (v8.5)</li> <li>gurobi (v11.0.2)</li> </ul> <h2>Run</h2> <p>From the root of the repository:</p> <p><br><code>snakemake -call --use-conda --conda-frontend conda</code></p> <p>Or with a specific scenario configuration file:</p> <p><br><code>snakemake -call --use-conda --conda-frontend conda --configfile config/config.foo.yaml</code></p> <h2>Cluster</h2> <p>On an HPC cluster, run:</p> <p><br><code>snakemake -call --profile slurm --use-conda --conda-frontend conda</code></p> <h2>Compress Results</h2> <p>Use <code>tar</code> to compress results (excluding the report directory):</p> <p><br><code>tar -cJf price-formation-results.tar.xz \</code><br><code> config data figures results resources workflow \</code><br><code> .gitignore .pre-commit-config.yaml .syncignore-receive \</code><br><code> .syncignore-receive CITATION.cff LICENSE matplotlibrc README.md</code></p> <h2>Licenses</h2> <p>The code in this repository is MIT licensed.</p> <p>The data in this repository is CC-BY-4.0 licensed.</p> <h2>Amendments</h2> <p>In <code>v0.2.0</code>, we added the file <code>revision-1-amendments.tar.xz</code>, which includes additional results for sensitivity runs with cross-elastic terms.</p>
Dataset of "Shock recovery with decaying compressive pulses: A shock effect in calcite (CaCO3) around the Hugoniot elastic limit"
<p>The text data supporting the figures on the manuscript. The names of variables are listed on the top column.</p>
Second-strain gradient elasticity parameters for centrosymmetric materials
<p>This is a collection of material parameters sets describing 999, thermodynamically admissible, isotropic, centrosymmetric, elastic materials featuring second-strain gradient elasticity. The notations are according to Mindlin R.D. (1965) Second-gradient theory of strain and surface tension in linear elasticity. Int. J. Solids Structures<br> 1:417-438.</p>
Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 1000 samples
<p>Dataset finite element stress analysis of biaxial specimen with random elastic properties</p> <p>Unzip and execute dataset.py to visualise data samples. PyVista is needed.</p>
Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 100 samples
<p>Dataset finite element stress analysis of biaxial specimen with random elastic properties</p> <p>Unzip and execute dataset.py to visualise data samples. PyVista is needed</p>
Finite-strain Visco-elastic Visco-plastic model identification of PA12 material printed along different directions
<p>The data provide the identification of PA12 bulk material for a finite-strain visco-elastic-visco-plastic (VE-VP) model printed along two directions.</p> <p>Tests were conducted in L. Cobian, M. Rueda-Ruiz, J.P. Fernandez-Blazquez, V. Martinez, F. Galvez, F. Karayagiz, T. Lück, J. Segurado, M.A. Monclus, Micromechanical characterization of the material response in a PA12-SLS fabricated lattice structure and its correlation with bulk behaviour, Polymer Testing 110 (2022) 107556: <a href="https://doi.org/10.1016/j.polymertesting.2022.107556">https://doi.org/10.1016/j.polymertesting.2022.107556</a> (in Open access), see also <a href="http://dx.doi.org/10.5281/zenodo.6136935">http://dx.doi.org/10.5281/zenodo.6136935</a> (in Open access)</p> <p>Material model follows V. D. Nguyen, F. Lani, T. Pardoen, X. Morelle, L. Noels, A large strain hyperelastic viscoelastic-viscoplastic-damage constitutive model based on a multi-mechanism non-local damage continuum for amorphous glassy polymers. International Journal of Solids and Structures 96 (2016): 192-216; <a href="https://dx.doi.org/10.1016/j.ijsolstr.2016.06.008">https://dx.doi.org/10.1016/j.ijsolstr.2016.06.008</a>, Open access: <a href="https://orbi.uliege.be/handle/2268/197898">https://orbi.uliege.be/handle/2268/197898</a>.</p> <p>The model</p> <ul> <li>Is implemented as a cross platform UMAT subroutine that is openly available on <a href="https://gitlab.uliege.be/moammm/moammmpublic/-/tree/master/code/MaterialModels/FiniteStrain/Finite_VEVP">https://gitlab.uliege.be/moammm/moammmpublic/-/tree/master/code/MaterialModels/FiniteStrain/Finite_VEVP</a> (Licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) (<a href="https://creativecommons.org/licenses/by/4.0">https://creativecommons.org/licenses/by/4.0</a>).) and referenced on the project web-site <a href="https://www.moammm.eu/index.php/developed-code/">https://www.moammm.eu/index.php/developed-code/</a>.</li> <li>The model is also implemented at the cm3 laboratory, who provides efficient algorithms for homogenisation implemented in a parallel setting in the open source finite element code base on <a href="http://gmsh.info/">Gmsh</a>. In order to have access to the sources follows <a href="https://www.moammm.eu/index.php/developed-code/">https://www.moammm.eu/index.php/developed-code/</a>.</li> </ul> <p>If you use these data or model, we would be grateful if you could cite the related papers:</p> <ul> <li>L. Cobian, M. Rueda-Ruiz, J.P. Fernandez-Blazquez, V. Martinez, F. Galvez, F. Karayagiz, T. Lück, J. Segurado, M.A. Monclus, Micromechanical characterization of the material response in a PA12-SLS fabricated lattice structure and its correlation with bulk behaviour, Polymer Testing 110 (2022) 107556: https://doi.org/10.1016/j.polymertesting.2022.107556 (in Open access)</li> <li>Data of “. Cobian, M. Rueda-Ruiz, J.P. Fernandez-Blazquez, V. Martinez, F. Galvez, F. Karayagiz, T. Lück, J. Segurado, M.A. Monclus, Micromechanical characterization of the material response in a PA12-SLS fabricated lattice structure and its correlation with bulk behaviour, Polymer Testing 110 (2022) 107556” http://dx.doi.org/10.5281/zenodo.6136935 (in Open access)</li> <li>V. D. Nguyen, F. Lani, T. Pardoen, X. Morelle, L. Noels, A large strain hyperelastic viscoelastic-viscoplastic-damage constitutive model based on a multi-mechanism non-local damage continuum for amorphous glassy polymers. International Journal of Solids and Structures 96 (2016): 192-216; https://dx.doi.org/10.1016/j.ijsolstr.2016.06.008, Open access: https://orbi.uliege.be/handle/2268/197898</li> </ul> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862015</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.