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While there are many computational approaches for simulating damage in rock and other materials, few have been ground truth tested with either known experimental data or with blind data sets. Here, in this work, we present a bench-mark laboratory data set for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile materials. The samples were fabricated through additive manufacturing to produce repeatable specimens designed to fail in controlled ways. The failure was induced in the samples using a 3-point bending test to produce different Modes such as Mode I and mixed Modes including I-II, I-III and I-II-III Modes to generate a calibration data set and a blind challenge data set. Data collected included spatial and temporal measurements from traditional digital load–displacement sensors, 2D digital image correlation measurement to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry, and laser profilometry to capture surface roughness. The data sets are available, on a data repository, to the community to advance computational models to improve our ability to predict damage in brittle-ductile materials.
Antimony oxides are important materials for catalysis and flame-retardant applications. The two most common phases, α-Sb 2 O 3 (senarmontite) and β-Sb 2 O 3 (valentinite), have been studied extensively. Specific focus has been placed recently on their lattice dynamics properties and how they relate to the α-β phase transformation and their potential anharmonicity. However, there has not been any direct investigation of anharmonicity in these systems, and a surprising lack of low-temperature structural information has prevented further study. Here, we report the powder neutron diffraction data of both phases of Sb 2 O 3 , as well as structural information. α-Sb 2 O 3 behaved as expected, but β-Sb 2 O 3 revealed a small region of zero thermal expansion along the c axis. Additionally, while the β phase matched well with reported atomic displacement parameters, the α phase displayed a marked deviation. This data will enable further investigations into these systems.
Inertial effects during the process of supercritical CO 2 displacing brine in porous media may not be negligible according to recent studies. Capturing the inertial effects of the physical CO 2 -brine system imposes a requirement on the grid resolution and viscosity to surface tension ratio for pore-scale simulations, which some commonly used simulators may not be able to meet. To fulfill the parameter requirement, we combine the continuum-surface-force based color-gradient lattice Boltzmann (LB) multiphase model and the geometrical wetting model and extend the model to 3D under the multiple-relaxation-time framework. We validate the model via simple benchmarks which show significant improvement over the traditional models. Furthermore, we perform 3D drainage simulations in a heterogeneous micromodel where the simulation result agrees well with experimental data, while our previous work fails to reproduce certain displacement patterns in the experiment due to the use of a traditional LB model that cannot fulfill the parameter requirement. Finally, we perform high-fidelity 3D drainage simulations to study the inertial effects in a Bentheimer sandstone sample. These findings show that stronger inertial effects generally help develop more CO 2 flow pathways for the same capillary number which results in higher CO 2 saturation, consistent with the micromodel results. The phenomena can be found in both low and high capillary number cases, indicating that the inertial effects are not dependent on the mean velocity. In addition, the change of the invasion patterns is not proportional to the change of inertial effects, thus exhibiting threshold behavior.
The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.
Bragg coherent diffraction imaging has the potential to provide significant insight into the structure-properties relationship for crystalline materials by imaging, with nanoscale resolution, three-dimensional strain fields within individual grains and nanoparticles. The capability of present-day synchrotrons to locate and measure a multiplicity of Bragg reflections from a single grain makes it possible to recover the full strain tensor with nanometer resolution. Recent methods for coupling reconstructions from several peaks to determine the strain tensor have been developed and applied to synthetic data, but have not been applied to experimental data. Here, using a coupled genetic reconstruction algorithm, we reconstruct an experimental data set and demonstrate improvements in the ability to resolve vector-valued displacement fields internal to the particle as compared to what is achieved with a noncoupled approach. The coupled approach developed in this work was also validated on simulated data sets. In both simulated and experimental data, reconstructions from our coupled Bragg peak algorithm show improvements over the noncoupled independent reconstruction method of 5% in terms of accuracy and 53% in terms of consistency.
ENDF/B-VIII.0 cross section data is benchmarked on a simple Monte-Carlo model representative of the ex-core geometry of a PWR used for reactor vessel neutron fluence calculations. The benchmarking indicates that the ENDF/B-VIII.0 results show large differences as compared to previous evaluations, which have been extensively compared to measured data. This exercise suggests that ENDF/B-VIII.0 nuclear data is not suitable for ex-core LWR radiation transport applications. Evaluators are aware of the problems with the ENDF/B-VIII.0 evaluation of iron and work is underway to improve the evaluations for an upcoming release.
During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.
As a salient feature of the Asian monsoon system, the East Asian subtropical westerly jet (EASWJ) exerts significant impacts on weather and climate changes in China and even throughout East Asia. In this paper, we applied a new self-adaptive algorithm to detect the EASWJ, identify its boundaries, and then represent its characteristics by defining three indices: the intensity index, meridional displacement index, and width index. Compared to the reanalysis data, we carried out a comprehensive, objective, and quantitative EASWJ evaluation using historical experiments from multiple global climate models (GCMs) in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6). The results show that the multimodel ensemble mean (MME) of both CMIP5 and CMIP6 can simulate the characteristics of winter EASWJ well. While for the other three seasons, the MME of both phase models underestimate the 200-hPa zonal wind (U200) strength in the jet coverage area and overestimate the U200 outside the jet area, such simulation results weaken the meridional shear of the wind field. The EASWJ simulations from the CMIP5 GCMs had no consistent intensity or location characteristic tendencies, and most CMIP5 GCMs tended to simulate relatively wide-coverage jets. In contrast, most CMIP6 GCMs are inclined to simulate significantly weaker, wider, and more-northward jets. Compared to the predecessors in CMIP5, about half of CMIP6 GCMs significantly minimized the jet intensity bias, but remarkable errors were still observed in their jet location and coverage representations. Furthermore, the comparative analysis performed by classifying models based on their evaluated simulation results suggested that the simulated performance of the meridional temperature gradient was important for capturing the EASWJ characteristics. Further in-depth study of the causes of model differences is warranted to improve simulation results.
Strategies that enable ignition of the low cetane alcohol fuels (methanol and ethanol) include intake heating (direct or via hot residual trapping), increased compression ratio (CR), multi-injection strategies, ignition enhancers, and active prechambers. The literature consistently shows alcohol compression ignition (CI) is more efficient than diesel at high loads irrespective of ignition strategy but shows contradictory results at low loads. To understand this, this work combines data from four different engine platforms ranging from a displaced volume of 0.4 to 2.1 L/cyl. using different alcohol CI ignition strategies. Using modeling to support experimental analysis, alcohol-specific efficiency penalties are highlighted to inform alcohol combustion system development. The alcohols’ lower energy density means more fuel must be injected near top dead center to achieve a given load, increasing the relative penalty of sensible/latent heating. Pilot injections help reduce this penalty. Intake heating incurs both a heat transfer penalty and a thermodynamic penalty due to a reduced ratio of specific heats during compression. A strategy that combines elevated CR, large pilot injections, and ignition enhancers can avoid this penalty. Alternatively, a prechamber strategy can achieve this without changing the CR, nor needing ignition enhancers in the fuel. At low loads, diesel burns in a partially premixed mode characterized by high burn rates and low heat losses, reducing alcohol-specific combustion benefits. Alcohol CI on the light-duty platform showed abnormally high heat transfer over diesel compared to other platforms, favoring a more premixed/partially premixed strategy despite a combustion efficiency tradeoff.
High-speed, three-dimensional (3D) scalar-velocity field measurements are demonstrated in a lifted partially-premixed dimethyl-ether/air jet flame using simultaneous laser-induced fluorescence (LIF) of formaldehyde (CH 2 O) and tomographic particle image velocimetry (TPIV). The 3D LIF measurements are performed by raster scanning the laser beam from a 100 kHz pulse-burst laser across the probe volume using an acousto-optic deflector. The volumetric reconstruction of the LIF signal from ten parallel planes provides quasi-instantaneous 3D LIF measurements that are synchronized with 10 kHz TPIV measurements. Here, the temporally resolved CH 2 O-LIF and velocity field data are used to analyze Lagrangian particle trajectories and displacement speeds at the base of the lifted flame. The particle trajectories reveal flow structures that are difficult to observe in an Eulerian reference frame. Positive and negative displacement speeds are observed at the CH 2 O-LIF surfaces at the inner and outer regions of the jet flame with a maximum displacement speed of approximately eight times the laminar flame speed of a stoichiometric dimethyl-ether/air mixture. The observations in present study support formation of lean premixed flames near the flame base whose role in flame stabilization should be investigated in more detail.
A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy. The method to distribute pairs and triplets between processes is general to all potentials. Results are presented for a simulation box of argon, including full box and atom displacement calculations, which are relevant to Monte Carlo simulation. Data on speed-up are presented for up to 120 processes across four nodes. A 4-fold speed-up is observed over five processes, extending to 20-fold over 40 processes and 30-fold over 120 processes.
Crystalline metal–organic frameworks (MOFs) are promising synthetic analogues of photosynthetic light-harvesting complexes (LHCs). The precise assembly of linkers (organic chromophores) around the topology-defined pores offers the evolution of unique photophysical behaviors that are reminiscence of LHCs. These include MOF excited states with photoabsorbed energy that is spatially dispersed over multiple linkers defining the molecular excitons. The multilinker molecular excitons display superradiance–a hallmark of coupled oscillators seen in LHCs–with radiative rate constant (k rad ) exceeding that of a single linker. Our theoretical model and experimental results on three zirconium MOFs, namely, PCN-222(Zn), NU-1000, and SIU-100, with similar topology but varying linkers suggest that the size of such molecular excitons depends on the electronic symmetry of the linker. This multilinker exciton model effectively predicts the energy transfer rate constant; corresponding single-step exciton hopping time, ranging from a few picoseconds in SIU-100 and NU-1000 to a few hundreds of picoseconds in PCN-222(Zn), matches well with the experimental data. The model also predicts the anisotropy of exciton displacement with preferential migration along the crystallographic c-axis. Overall, these findings establish various missing links defining the exciton size and dynamics in MOF-assembled linkers. Furthermore, the understandings will provide design principles, especially, positioning the catalysts or electrode relative to the linker orientation for low-density solar energy conversion systems.
The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.
The observations collected by two scanning lidars deployed on the roof of a 2.8-MW turbine undergoing a series of imposed yaw offsets are analyzed. The wake lateral displacement detected by the rear-facing lidar correlates well with the yaw offset sensed by the forward-facing lidar. We find that the high-frequency part of the yaw offset signal is connected to wake meandering, whereas the low frequency component is a good predictor for wake displacement due to yaw misalignment. Conditionally averaged wake velocity data for different yaw offsets are used as benchmarks for the validation of a linearized Reynolds-averaged Navier-Stokes and an empirical wake model. A mean error as low as 2% and a good prediction of the wake trajectory are achieved, provided that the wake recovery rate matches the observations.
Seismic resonance and surface displacement measurements can be implemented in tandem to improve landslide characterization and progressive failure monitoring. Crack aperture data are frequently used in rock slope stability monitoring and often exhibit recognizable trends prior to failure, such as accelerated crack opening. Alternatively, ambient resonance data offer multiple parameters including modal frequencies, damping, and polarization that can be monitored alongside crack aperture and may respond differently to environmental forcings and complex failure evolution. We analyzed data from continuous ambient vibration monitoring and concomitant crack aperture measurements at the Courthouse Mesa instability, a large toppling sandstone slab in Utah, USA. Three years of data revealed crack aperture increases of 2–4 mm/year with no clearly detectable irreversible changes in modal parameters, including frequency. Annually, frequency and displacement varied by 29% and 19% of the mean, respectively, with average and maximum daily frequency fluctuations of 6.5% and 16%, respectively. These reversible cyclic changes were primarily temperature-driven, but annually, frequency was in-phase with temperature whereas crack aperture lagged temperature changes by ~37 days. Polarization and damping also varied seasonally but were less strongly correlated with temperature. Conceptual 3D finite element modeling demonstrated consistent frequency decreases associated with crack propagation but variable changes in crack aperture measured at a single point; i.e., crack propagation did not always result in increased crack opening but always generated a resonance frequency decrease. Taken together, our data suggest a possible thermal wedging-ratcheting mechanism at the Courthouse Mesa instability, where annual thermoelastic crack closure is impeded by debris infill but the absence of downward crack propagation during the monitoring period is evidenced by no permanent resonance frequency changes. Our study demonstrates that combined seismic resonance and crack aperture data provide an improved description of rock slope instability behavior, supporting refined characterization and monitoring of changes accompanying progressive failure.
The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...
The chemical expansion of thin-film praseodymium-cerium oxide solid solutions (Pr 0.1 Ce 0.9 O 2-δ , PCO10) is investigated at temperatures ranging from 500 °C to 800 °C and oxygen activities down to about 10 -22 . Differential Laser Doppler Vibrometry (D-LDV) in combination with periodic electrochemical pumping of oxygen is used to detect very small displacements of the sample surface. With decreasing pumping frequency, the film approaches chemical equilibrium, which is nearly reached at 700 °C below 0.01 Hz. D-LDV enables direct measurement of film thickness changes as well as the bending of the underlying substrates due electrochemically induced lateral mechanical stress. The substrate bending is found to be more than an order of magnitude larger than the film thickness change, increasing the detection limit by the same factor. The thickness change of the thin film is calculated from the measured displacement of the sample surface and compared with directly measured values. Thin-film literature data available for low oxygen activities up to 650 °C agree with our measurements. In addition, the thickness change of the film is determined from the displacement at different sample positions, which validates previous measurements. Finally, thin film chemical expansion is found to be larger by a factor of about 2 than the corresponding bulk value in agreement with predictions from a mechanical model that the out-of-plane expansion of a constrained film is increased.