Search NASA⌕ Search

SEARCH · Search NASA

Results for “ELASTIC PROPERTY”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗
NASA NTRS1981

Postseismic rebound due to creep of the lower lithosphere and asthenosphere

Postseismic surface deformations are attributed to the inelastic flow of the subcrustal regions of the Earth following an earthquake. A multilayer representation of the Earth's rheological properties is used in conjunction with a finite element computational scheme to calculate time dependent displacements and strains subsequent to a strike slip earthquake. The deviatoric stress strain relations for the uppermost layer is assumed elastic. Lower layers are assumed to be, in order of increasing depth, a standard, linear, three element, viscoelastic solid; a linear viscoelastic fluid; and another elastic solid. Physically these layers correspond to the upper lithosphere, lower lithosphere, asthenosphere, and lower mantle, respectively. Elastic dilatational properties are assumed throughout. Appreciable postseismic displacements, possibly approaching meters, for large earthquakes, arise from viscoelastic relaxation following sudden coseismic slip. Furthermore, compared to the simpler case of an elastic lithosphere over a viscoelastic asthenosphere and the near fault postseismic shear, strain is increased, by a factor of two or more in some cases, by the presence of a viscoelastic lower lithosphere. Also, the duration of postseismic straining is increased by the relatively slow relaxation of this layer.

Cohen, S. C.↗
NASA NTRS2016

Mechanical Model Development for Composite Structural Supercapacitors

Novel composite structural supercapacitor concepts have recently been developed as a means both to store electrical charge and to provide modest mechanical load carrying capability. Double-layer composite supercapacitors are often fabricated by impregnating a woven carbon fiber fabric, which serves as the electrodes, with a structural polymer electrolyte. Polypropylene or a glass fabric is often used as the separator material. Recent research has been primarily limited to evaluating these composites experimentally. In this study, mechanical models based on the Multiscale Generalized Method of Cells (MSGMC) were developed and used to calculate the shear and tensile properties and response of two composite structural supercapacitors from the literature. The modeling approach was first validated against traditional composite laminate data. MSGMC models for composite supercapacitors were developed, and accurate elastic shear/tensile properties were obtained. It is envisioned that further development of the models presented in this work will facilitate the design of composite components for aerospace and automotive applications and can be used to screen candidate constituent materials for inclusion in future composite structural supercapacitor concepts.

Micromechanics↗
NASA NTRSDate not supplied

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗
DOE OSTI2025

Sound Speeds of Solids from Ultrasonic Pulse Receiver Measurements

A common method of determining elastic material properties is utilizing an ultrasonic pulse receiver. This is a non-destructive test (NDT) causing no plastic deformation of the material. It requires a pulse generator, oscilloscope, and two transducers to measure the sound velocity of a material. Both longitudinal and shear sound velocities may be obtained by utilizing the appropriate transducer. Acoustic nondestructive testing methods are often used in manufacturing certification processes and for material defect detection in industry. These methods can also be utilized to directly measure the elastic moduli of a material without damaging the material. Overall, it is a low-cost experiment with minimal preparation, and is easy to use.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale repeating unit cell model of a single spherulite containing four disparate length scales was developed to predict the thermoelastic behavior of semicrystalline thermoplastic materials for composite aerospace applications. The continuum level scales were fully coupled and modeled using the generalized method of cells and the high fidelity generalized method of cells micromechanics theories. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents in the multiscale continuum models. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, showing good agreement with the available experimental data from the open literature. Moreover, it is shown that predicted properties are fairly insensitive to the fidelity of the micromechanics model used at the highest continuum scale or the assumed shape of the spherulite.

thermoplastics↗
NASA NTRS1998

Material Properties and Defects Characterization Using LLW Data

Leaky Lamb Wave (LLW) propagation in composite materials has been studied extensively since it was first observed in 1982. The wave is induced using a pitch-catch arrangement and the plate wave modes are detected by identifying minima in the reflected spectra to obtain the dispersion data.

Composites↗
NASA NTRS1994

Prediction of natural frequency variability due to uncertainty in material properties

Composite materials are widely used in various types of modern engineering structures. Traditional studies on composite structures have been based on the assumption that the material properties of the composites are characterized by a priori known elastic moduli, and no uncertainties of these moduli have been considered. However, the composite materials are invariably subject to a certain amount of scatter in their measured elastic moduli. To a large extent, the properties of composite materials are dependent on the fabrication process. But even the composite materials manufactured by the same process demonstrate differences in their elastic properties. This paper proposes a new, non-probabilistic method to predict the variability in the natural frequencies of the composite cylindrical shell, resulting from the unavoidable scatter in elastic moduli. The available measurements of elastic moduli are fitted by the four-dimensional uncertainty ellipsoid. The upper and lower bounds of the natural frequency are derived. With these bounds, designers will have a better understanding of the real dynamic behavior of the structure.

Li, Y. W.↗
DOE OSTI2025

Tailoring Nitinol for elastocaloric application

This study focuses on tailoring commercial Nitinol, the most commonly used elastocaloric material, for near-room-temperature cooling applications. Short heat treatments near 500 °C were used to fine-tune the material’s transition temperature, resulting in austenite finish temperatures ranging from 6.0 to 25.5°C and altered superelastic and elastocaloric properties. Plateau stresses decreased while temperature changes rose from 21.5°C up to 27.9°C at 6% strain. Significant variability in the Nitinol response when testing below its austenite finish temperature was observed. In conclusion, the effect of mechanical cycling on transition temperatures was also evaluated, demonstrating an increase for all the samples.

Efficiency↗
DOE OSTI2025

Extending the capillary wave model to include the effect of bending rigidity: X-ray reflectivity and diffuse scattering

The surface roughness of a thin film at a liquid interface exhibits contributions of thermally excited fluctuations. This thermal roughness depends on temperature (𝑇), surface tension (𝛾), and elastic material properties, specifically the bending modulus (𝜅) of the film. A nonzero 𝜅 suppresses the thermal roughness at small length scales compared to an interface with zero 𝜅, as expressed by the power spectral density of the thermal roughness. The description of the x-ray scattering of the standard capillary wave model (CWM), which is valid for zero 𝜅, is extended to include the effect of 𝜅. The extended CWM (eCWM) provides a single analytical form for both the specular x-ray reflectivity (XRR) and the diffuse scattering around the specular reflection, and recovers the expression of the CWM at its zero 𝜅 limit. This theoretical approach enables the use of single-shot grazing incidence x-ray off-specular scattering (GIXOS) measurements for characterizing the structure of thin films on a liquid surface. The eCWM analysis approach decouples the thermal roughness factor from the surface scattering signal, providing direct access to the intrinsic surface-normal structure of the film and its bending modulus. Moreover, the eCWM facilitates the calculation of reflectivity at any desired resolution (pseudo-XRR approach). The transformation into pseudo-XRR provides the benefit of using widely available XRR software to perform GIXOS analysis. The extended range of the vertical scattering vector (𝑄 𝑧 ) available with the GIXOS pseudo-XRR approach allows for a higher spatial resolution than with conventional XRR. Experimental results are presented for various lipid systems, showing strong agreement between conventional specular XRR and pseudo-XRR methods. This agreement validates the proposed approach and highlights its utility for analyzing soft, thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dissimilar Material Joining via Interlocking Metasurfaces

Background The integration of dissimilar materials poses a significant challenge in engineering, necessitating innovative solutions for robust and reliable joining. Interlocking metasurfaces (ILMs) are a new joining technology comprising arrays of autogenous features patterned across two surfaces that interlock to form robust structural joints. Objective Here, this study elucidates the factors influencing the tensile performance of ILM joints formed between dissimilar materials. Methods We employed parametric optimization to identify optimal unit cell geometries for maximal yield strength based on the hypothesis that the elastic tensile properties of the materials are the primary determinants of tensile performance. Experimental validation was performed by mechanically testing the theorized optimal ILM geometry and a range of ILM geometries to capture the overall behavior trends of joints between two additively manufactured polymers, VeroPureWhite (VW) and RGDA8430-DM (8430). Results Experimental validation of optimized designs revealed that additional factors, e.g. flexural strength and localized plasticity, also strongly influenced the tensile performance of T-slot ILMs joining dissimilar materials. The proposed optimal design remained the best performer. Conclusions This study demonstrates the viability of ILMs as a joining method for dissimilar materials. ILMs can join dissimilar materials with no loss in joint yield strength compared to joints composed solely of the weaker of the two constitutive materials. ILMs demonstrated their potential as a versatile and effective joining technology in diverse engineering applications.

Elbrecht, Benjamin James [Sandia National Laborato↗
DOE OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗