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DOE OSTI2015

Comparison of measured and computed radial trajectories of plasma focus devices UMDPF1 and UMDPF0

In published literature, there has been scant data on radial trajectory of the plasma focus and no comparison of computed with measured radial trajectory. This paper provides the first such comparative study. We compute the trajectories of the inward-moving radial shock and magnetic piston of UMDPF1 plasma focus and compare these with measured data taken from a streak photograph. The comparison shows agreement with the measured radial trajectory in terms of average speeds and general shape of trajectory. This paper also presents the measured trajectory of the radially compressing piston in another machine, the UMDPF0 plasma focus, confirming that the computed radial trajectory also shows similar general agreement. Features of divergence between the computed and measured trajectories, towards the end of the radial compression, are discussed. From the measured radial trajectories, an inference is made that the neutron yield mechanism could not be thermonuclear. A second inference is made regarding the speeds of axial post-pinch shocks, which are recently considered as a useful tool for damage testing of fusion-related wall materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

An accurate bilinear cavern model for compressed air energy storage

Compressed air energy storage is suitable for large-scale electrical energy storage, which is important for integrating renewable energy sources into electric power systems. A typical compressed air energy storage plant consists of compressors, expanders, caverns, and a motor/generator set. Current cavern models used for compressed air energy storage are either accurate but highly nonlinear or linear but inaccurate. The application of highly nonlinear cavern models in power system optimization problems renders them computationally challenging to solve. In this regard, an accurate bilinear cavern model for compressed air energy storage is proposed. The charging and discharging processes in a cavern are divided into several real/virtual states. The first law of thermodynamics and ideal gas law are then utilized to derive a cavern model, i.e., a model for the variation of temperature and pressure in these processes. Thereafter, the heat transfer between the air in the cavern and the cavern wall is considered and integrated into the cavern model. By subsequently eliminating several negligible terms, the cavern model reduces to a bilinear model. The accuracy of the bilinear cavern model is verified via comparison with both an accurate nonlinear model and two sets of field-measured data. The bilinear cavern model can be easily linearized and is then suitable for integration into optimization problems considering compressed air energy storage. This is verified via comparatively solving a self-scheduling problem of compressed air energy storage using different cavern models.

25 ENERGY STORAGE↗

DOE OSTI2017

The Formation of Magnetic Depletions and Flux Annihilation Due to Reconnection in the Heliosheath

The misalignment of the solar rotation axis and the magnetic axis of the Sun produces a periodic reversal of the Parker spiral magnetic field and the sectored solar wind. The compression of the sectors is expected to lead to reconnection in the heliosheath (HS). We present particle-in-cell simulations of the sectored HS that reflect the plasma environment along the Voyager 1 and 2 trajectories, specifically including unequal positive and negative azimuthal magnetic flux as seen in the Voyager data. Reconnection proceeds on individual current sheets until islands on adjacent current layers merge. At late time, bands of the dominant flux survive, separated by bands of deep magnetic field depletion. The ambient plasma pressure supports the strong magnetic pressure variation so that pressure is anticorrelated with magnetic field strength. There is little variation in the magnetic field direction across the boundaries of the magnetic depressions. At irregular intervals within the magnetic depressions are long-lived pairs of magnetic islands where the magnetic field direction reverses so that spacecraft data would reveal sharp magnetic field depressions with only occasional crossings with jumps in magnetic field direction. This is typical of the magnetic field data from the Voyager spacecraft. Voyager 2 data reveal that fluctuations in the density and magnetic field strength are anticorrelated in the sector zone, as expected from reconnection, but not in unipolar regions. The consequence of the annihilation of subdominant flux is a sharp reduction in the number of sectors and a loss in magnetic flux, as documented from the Voyager 1 magnetic field and flow data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Performance Enhancement of the Transcritical CO2 Cycle with a Near-Isothermal Liquid Piston Compression by an Ejector

This study investigates the use of an ejector in a transcritical CO2 cycle employing a near-isothermal liquid piston compressor, with the objective of mitigating refrigerant degassing in mineral oil. While the liquid piston compressor demonstrated high isothermal efficiency (˜90%), overall cycle performance was limited by CO2 degassing during chamber pressure fluctuations. A thermodynamic model was developed to compare baseline and ejector-assisted cycles, incorporating solubility correlations, entrainment ratio characteristics, and a degassing correction factor. Results indicate that the ejector increased suction pressure and reduced CO2–oil solubility variation, which improved refrigerant intake and reduced degassing losses. Despite these benefits, the ejector-assisted cycle showed a lower coefficient of performance (COP) than the baseline. Possible contributing factors include the limited marginal benefit of pressure reduction in a highly efficient isothermal compressor, reduced effectiveness of the separator due to the use of a suction-line heat exchanger in both cycles, and uncertainties in the solubility data under transient conditions. These findings suggest that degassing mitigation is essential for realizing the potential of liquid piston compression, but ejector integration alone is unlikely to enhance COP. Future work should focus on ejector optimization, improved oil–refrigerant management, introducing less-soluble working liquids, and experimental validation under realistic operating conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Structure Formation of Hexagonal Diamond: Ab Initio Calculations

The formation of structure of hexagonal diamond from graphite and cubic diamond is simulated with the density functional theory. Orthorhombic AB graphite transforms into hexagonal diamond under uniaxial compression at pressures above 61 GPa. The pressure should be higher than 57 GPa to form hexagonal diamond from AA graphite. Another possible way to obtain hexagonal diamond is uniaxial compression of cubic diamond under pressures from 300 to 380 GPa. The theoretical calculations were used to interpret the diffraction data obtained after X-ray diffraction and electron microscopic analysis of natural and synthetic diamond-like materials. We found that there are no crystals with ideal cubic and hexagonal structures in diamond-like carbon materials, and their structure is characterized by random packing of molecular layers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

DES Y1 results: Splitting growth and geometry to test $\Lambda$CDM

We analyze Dark Energy Survey (DES) data to constrain a cosmological model where a subset of parameters—focusing on Ωm—are split into versions associated with structure growth (e.g., Ωmgrow) and expansion history (e.g., Ωmgeo). Once the parameters have been specified for the ΛCDM cosmological model, which includes general relativity as a theory of gravity, it uniquely predicts the evolution of both geometry (distances) and the growth of structure over cosmic time. Any inconsistency between measurements of geometry and growth could therefore indicate a breakdown of that model. Our growth-geometry split approach therefore serves both as a (largely) model-independent test for beyond-ΛCDM physics, and as a means to characterize how DES observables provide cosmological information. We analyze the same multiprobe DES data as [Phys. Rev. Lett. 122, 171301 (2019)PRLTAO0031-900710.1103/PhysRevLett.122.171301] : DES Year 1 (Y1) galaxy clustering and weak lensing, which are sensitive to both growth and geometry, as well as Y1 BAO and Y3 supernovae, which probe geometry. We additionally include external geometric information from BOSS DR12 BAO and a compressed Planck 2015 likelihood, and external growth information from BOSS DR12 RSD. We find no significant disagreement with Ωmgrow=Ωmgeo. When DES and external data are analyzed separately, degeneracies with neutrino mass and intrinsic alignments limit our ability to measure Ωmgrow, but combining DES with external data allows us to constrain both growth and geometric quantities. We also consider a parametrization where we split both Ωm and w, but find that even our most constraining data combination is unable to separately constrain Ωmgrow and wgrow. Relative to ΛCDM, splitting growth and geometry weakens bounds on σ8 but does not alter constraints on h.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Woven ceramic matrix composite surrogate model based on physics-informed recurrent neural network

A recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear constitutive behavior of woven ceramic matrix composites (CMCs) driven by matrix damage at multiple length scales. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the multiscale generalized method of cells (MSGMC) approach coupled with a matrix damage model. This coupling permits simulating the nonlinear behavior of woven CMCs based on constituent response at the micro-, meso-, and macroscales. The multiscale repeating unit cell is loaded under non-monotonic conditions including multiple load / unload cycles and tension / compression. The fiber volume fraction as well as the intra- and intertow void volume fractions are also varied in the generation of training data. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input strain sequence and fiber and void volume fractions, the resulting stress versus strain response while satisfying physical constraints such as positive semi-definiteness of the tangent stiffness matrix and linear elastic unloading. Further, the trained surrogate model effectively matches the stress versus strain response and successfully predicts the tangent modulus throughout the loading regime. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex architectures, nonlinear multiaxial material response, and under non-monotonic loading conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Aspen ploidy level and cover maps from NEON Airborne Observation Platform, 2018, Crested Butte, Colorado

Maps of aspen ploidy (diploid or triploid) developed using National Ecological Observatory Network (NEON) Airborne Observation Platform visible to shortwave infrared imaging spectroscopy data that were acquired over the Upper East River, Colorado in 2018. Maps of aspen distribution, as well as other land cover types that were used to screen for aspen dominated pixels are also provided. Each image file is provided as a GeoTiff with internal tiling and LZW compression. For use of ploidy maps, it is necessary to mask out non-aspen and shaded pixels. Shaded pixels are provided in an associated data package. For full details, please see associated publication and methods description. This dataset is associated with the publication in Ecological Applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Sound speed measurements in shock-compressed cemented Tungsten carbides at pressures up to 100 GPa

To gain insights into thermodynamic states attained during shock compression of cemented tungsten carbide with 3.7 wt.% cobalt binder, we present results of longitudinal sound (release wave) speed measurements and their analysis at peak stresses up to 100 GPa (volumetric compression ratio ~ 15%). The sound speeds are determined using front-surface impact and release-wave overtake plate impact experimental configurations using laser interferometry. The measured sound speed data along with estimates for bulk sound speeds obtained using the fourth-order Birch-Murnaghan EoS and thermodynamics are used to determine the longitudinal moduli and shear moduli of shocked tungsten carbide at the various peak compression states attained in the experiments. Here, the longitudinal sound speeds were found to increase linearly with volume compression ratio from 6.97 ± 0.010 km/s at ambient conditions to 8.26 ± 0.156 km/s at a volume compression ratio of ~ 15%. The corresponding longitudinal elastic moduli also increase nearly linearly with the volume compression ratio but remain consistently lower than their theoretical predictions based on continuum models with no damage. Also, the sensitivity of shear moduli to pressure, as predicted by the Steinberg-Guinan model, is reduced substantially and the shear moduli of cemented WC with 3.7 wt.% Co remains nearly constant at ~ 310 GPa at the various peak compression stress states investigated in the present study.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Pressure core analysis of geomechanical and fluid flow properties of seals associated with gas hydrate-bearing reservoirs in the Krishna-Godavari Basin, offshore India

Physical properties of the sediment directly overlying a gas hydrate reservoir provide important controls on the effectiveness of depressurizing that reservoir to extract methane from gas hydrate as an energy resource. The permeability of overlying sediment determines if a gas hydrate reservoir’s upper contact will provide an effective seal that enables efficient reservoir depressurization. Compressibility, stiffness and strength indicate how overlying sediment will deform as the in situ stress changes during production, providing engineering data for well designs. Assessing these properties requires minimally-disturbed sediment. India’s National Gas Hydrates Program Expedition 2 (NGHP-02) provided an opportunity to study these seal sediment properties, reducing disturbance from gas exsolution and bubble growth by collecting a pressure core from the seal sediment just above the primary gas hydrate reservoir at Site NGHP-02-08 in Area C of the Krishna-Godavari Basin. The effective stress chamber (ESC) and the direct shear chamber (DSC) devices in the suite of Pressure Core Characterization Tools (PCCTs) were used to measure permeability, compressibility, stiffness and shear strength at the in situ vertical stress. Geotechnical properties of the predominantly fine-grained seal layer at in situ vertical stress are in typical clay sediment ranges, with low measured permeability (0.02 mD), high compressibility (C c = 0.26 – 0.33) and low shear strength (404 kPa). Though pressure and temperature were maintained throughout the collection and measurement process to stabilize gas hydrate, the lack of effective stress in the pressure core storage chamber and the chamber pressurization with methane-free water caused core expansion and gas hydrate in a thin coarser-grained layer to dissolve. The PCCTs can reapply in situ stress with incremental loading steps during a consolidation test to account for sediment compaction. Lastly, gas hydrate dissolution can be limited by storing cores just above freezing temperatures, and by using solid spacers to reduce the storage chamber’s free volume.

09 BIOMASS FUELS↗

DOE OSTI2026

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗

DOE OSTI2018

Coupled strain-induced alpha to omega phase transformation and plastic flow in zirconium under high pressure torsion in a rotational diamond anvil cell

Strain-induced α → ω phase transformation (PT) in the zirconium (Zr) sample under compression and plastic shear in a rotational diamond anvil cell (RDAC) is investigated using the finite element method (FEM). The fields of the volume fraction of the ω phase, all components of the stress tensor, and plastic strain are presented. Before torsion, PT barely occurs. During torsion under a fixed applied force, PT initiates at the center of the sample, where the pressure first reaches the minimum pressure for strain-induced α → ω PT, p d ε , and propagates from the center to the periphery and from the symmetry plane to the contact surface. Salient increase of the shear friction stress and pressure at the center of a sample, so-called pressure self-multiplication effect observed experimentally for some other materials, is predicted here for Zr. It is caused by much higher yield strength of the phase in comparison with the phase. Except at the very center of a sample, the total contact friction stress is equal to the yield strength in shear of the mixture of phases and the plastic sliding occurs there. Due to the reduction in sample thickness and radial material flow during torsion, the ω phase can be observed in the region where pressure is lower than p d ε , which may lead to misinterpretation of the experimental data for p d ε . For the same applied force, torsion drastically promotes PT in comparison with the compression without torsion. However, the PT process in RDAC is far from optimal: (a) due to the pressure self-multiplication effect, the pressure in the transformed region is much higher than that required for PT; (b) the region in which PT occurs is limited by the pressure p d ε and cannot be expanded by increasing a shear under a fixed force; and (c) the significant reduction in thickness during torsion reduces the total mass of the high-pressure phase. These drawbacks can be overcome by placing a sample within a strong gasket with an optimized geometry. It is shown that, due to strong pressure heterogeneity, characterization of α → ω and α → β PTs based on the averaged pressure contains large errors. Furthermore, the obtained results, in addition to providing an improved understanding of the strain-induced PTs, may be beneficial for the optimum design of experiments and the extraction of material parameters, as well as optimization and control of PTs by varying the geometry and loading conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. Here, the study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.

42 ENGINEERING↗

DOE OSTI2014

Mammographic compression after breast conserving therapy: Controlling pressure instead of force

Purpose: X-ray mammography is the primary tool for early detection of breast cancer and for follow-up after breast conserving therapy (BCT). BCT-treated breasts are smaller, less elastic, and more sensitive to pain. Instead of the current force-controlled approach of applying the same force to each breast, pressure-controlled protocols aim to improve standardization in terms of physiology by taking breast contact area and inelasticity into account. The purpose of this study is to estimate the potential for pressure protocols to reduce discomfort and pain, particularly the number of severe pain complaints for BCT-treated breasts. Methods: A prospective observational study including 58 women having one BCT-treated breast and one untreated nonsymptomatic breast, following our hospital's 18 decanewton (daN) compression protocol was performed. Breast thickness, applied force, contact area, mean pressure, breast volume, and inelasticity (mean E-modulus) were statistically compared between the within-women breast pairs, and data were used as predictors for severe pain, i.e., scores 7 and higher on an 11-point Numerical Rating Scale. Curve-fitting models were used to estimate how pressure-controlled protocols affect breast thickness, compression force, and pain experience. Results: BCT-treated breasts had on average 27% smaller contact areas, 30% lower elasticity, and 30% higher pain scores than untreated breasts (allp < 0.001). Contact area was the strongest predictor for severe pain (p < 0.01). Since BCT-treatment is associated with an average 0.36 dm{sup 2} decrease in contact area, as well as increased pain sensitivity, BCT-breasts had on average 5.3 times higher odds for severe pain than untreated breasts. Model estimations for a pressure-controlled protocol with a 10 kPa target pressure, which is below normal arterial pressure, suggest an average 26% (range 10%–36%) reduction in pain score, and an average 77% (range 46%–95%) reduction of the odds for severe pain. The estimated increase in thickness is +6.4% for BCT breasts. Conclusions: After BCT, women have hardly any choice in avoiding an annual follow-up mammogram. Model estimations show that a 10 kPa pressure-controlled protocol has the potential to reduce pain and severe pain particularly for these women. The results highly motivate conducting further research in larger subject groups.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

3D Experimental Measurement of Lattice Strain and Fracture Behavior of Sand Particles Using Synchrotron X-Ray Diffraction and Tomography

3D synchrotron X-ray diffraction (3DXRD) and synchrotron micro-computed tomography (SMT) techniques were used to measure and monitor the lattice strain evolution and fracture behavior of natural Ottawa sand particles subjected to 1D compression loading. The particle-averaged lattice strain within sand particles was measured using 3DXRD and then was used to calculate the corresponding lattice stress tensor. In addition, the evolution and mode of fracture of sand particles was investigated using high-resolution 3D SMT images. The results of diffraction data analyses revealed that the major principal component of the lattice strain or stress tensor increased in most of the particles as the global applied compressive load increased until the onset of fracture. Particle fracture and subsequent rearrangements caused significant variation and fluctuations in measured lattice strain/stress values from one particle to another and from one load step to the next one. SMT image analysis at the particle-scale showed that cracks in fractured sand particles generally initiate and propagate along the plane that connects the two contact points. Fractured particles initially split into two or three major fragments followed by disintegration into multiple smaller fragments in some cases. In conclusion, microscale analysis of fractured particles showed that particle position, morphology, the number and location of contact points play a major role in the occurrence of particle fracture in confined comminution of the sand assembly.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Mechanical response of lithium fluoride under off-principal dynamic shock-ramp loading

Single crystal lithium fluoride (LiF), oriented [100], was shock loaded and subsequently shocklessly compressed in two experiments at the Z Machine. We employed velocimetry measurements in order to obtain an impactor velocity, shock transit times, and in-situ particle velocities for LiF samples up to ~1.8 mm thick. We also performed a dual thickness Lagrangian analysis on the in-situ velocimetry data to obtain the mechanical response along the loading path of these experiments. Finally, we observed an elastic response on one experiment during initial shockless compression from 100 GPa before yielding. The relatively large thickness differences utilized for the dual sample analyses (up to ~1.8 mm) combined with a relative timing accuracy of ~0.2 ns resulted in an uncertainty of less than 1% on density and stress at ~200 GPa peak loading on one experiment and <4% on peak loading at ~330 GPa for another. The stress-density analyses from these experiments compare favorably with recent equation of state models for LiF.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Narrowing down the possible explanations of cosmic acceleration with geometric probes

Recent re-calibration of the Type Ia supernova (SNe Ia) magnitude-redshift relation combined with cosmic microwave background (CMB) and baryon acoustic oscillation (BAO) data have provided excellent constraints on the standard cosmological model. Here, we examine particular classes of alternative cosmologies, motivated by various physical mechanisms, e.g. scalar fields, modified gravity and phase transitions to test their consistency with observations of SNe Ia and the ratio of the angular diameter distances from the CMB and BAO. Using a model selection criterion for a relative comparison of the models (the Bayes Factor), we find moderate to strong evidence that the data prefer flat ΛCDM over models invoking a thawing behaviour of the quintessence scalar field. However, some exotic models like the growing neutrino mass cosmology and vacuum metamorphosis still present acceptable evidence values. The bimetric gravity model with only the linear interaction term as well as a simplified Galileon model can be ruled out by the combination of SNe Ia and CMB/BAO datasets whereas the model with linear and quadratic interaction terms has a comparable evidence value to standard ΛCDM. Thawing models are found to have significantly poorer evidence compared to flat ΛCDM cosmology under the assumption that the CMB compressed likelihood provides an adequate description for these non-standard cosmologies. We also present estimates for constraints from future data and find that geometric probes from oncoming surveys can put severe limits on non-standard cosmological models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Calibrating constitutive models with full‐field data via physics informed neural networks

Abstract The calibration of solid constitutive models with full‐field experimental data is a long‐standing challenge, especially in materials that undergo large deformations. In this paper, we propose a physics‐informed deep‐learning framework for the discovery of hyperelastic constitutive model parameterizations given full‐field surface displacement data and global force‐displacement data. Contrary to the majority of recent literature in this field, we work with the weak form of the governing equations rather than the strong form to impose physical constraints upon the neural network predictions. The approach presented in this paper is computationally efficient, suitable for irregular geometric domains, and readily ingests displacement data without the need for interpolation onto a computational grid. A selection of canonical hyperelastic material models suitable for different material classes is considered including the Neo–Hookean, Gent, and Blatz–Ko constitutive models as exemplars for general non‐linear elastic behaviour, elastomer behaviour with finite strain lock‐up, and compressible foam behaviour, respectively. We demonstrate that physics informed machine learning is an enabling technology and may shift the paradigm of how full‐field experimental data are utilized to calibrate constitutive models under finite deformations.

Hamel, Craig M.↗