Data-driven In-situ Characterization of Microscale Properties of Composite Materials
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This project dealt with the development on new methodologies and algorithms for the multi-spectrum electromagnetic characterization of large scale nonmetallic airborne vehicles and structures. A robust, low memory, and accurate methodology was developed which is particularly suited for modern machine architectures. This is a hybrid finite element method that combines two well known numerical solution approaches. That of the finite element method for modeling volumes and the boundary integral method which yields exact boundary conditions for terminating the finite element mesh. In addition, a variety of high frequency results were generated (such as diffraction coefficients for impedance surfaces and material layers) and a class of boundary conditions were developed which hold promise for more efficient simulations. During the course of this project, nearly 25 detailed research reports were generated along with an equal number of journal papers. The reports, papers, and journal articles are listed in the appendices along with their abstracts.
NASA has recognized the need for better characterization of composite materials to support advances in aeronautics and the next generation of space exploration vehicles. An area of related research is the evaluation of impact induced delaminations. Presented is a non-contact method of measuring the ply depth of impact delamination damage in a composite through use of a Scanning Laser Doppler Vibrometer (SLDV), multi-frequency wavenumber analysis, and a wavenumber-ply correlation algorithm. A single acquisition of a chirp excited lamb wavefield in an impacted composite is post-processed into a numerous single frequency excitation wavefields through a deconvolution process. A spatially windowed wavenumber analysis then extracts local wavenumbers from the wavefield, which are then correlated to theoretical dispersion curves for ply depth determination. SLDV based methods to characterize as-manufactured composite variation using wavefield analysis will also be discussed.
The return to the Moon has ignited the need to characterize the lunar regolith using fast, reliable in-situ methods. Characterizing the physical properties of the rocks and soils can be very difficult because of the many complex parameters that influence the measurements. In particular, soil electrical property measurements are influenced by temperature, mineral type, grain size, porosity, and soil conductivity. Determining the dielectric constant of lunar materials may be very important in providing quick characterization of surface deposits, especially for the Moon. A close examination of the lunar regolith samples collected by the Apollo astronauts indicates that the rocks and soils on the Moon are dominated by silicates and oxides. In this presentation, we will show that determining the dielectric constant measurements can provide a simple, quick detection method for minerals that contain titanium, iron, and water. Their presence is manifest by an unusually large imaginary permittivity.
The chemical composition of Venus’ clouds has attracted considerable attention since the first atmospheric probes entered the planet in the early 1980s. We know from these early studies that cloud aerosols consist of micron and submicron droplets of sulfuric acid (~85%) and water (~15%), but outstanding questions still exist regarding their trace chemical composition, especially the identity of the unknown UV absorber(s) and the possible presence of organic material (Spacek & Benner, 2021). Veritas and DaVinci will launch at the end of the decade to advance our understanding of Venus’ surface and atmosphere, however these missions are not designed to sample and analyze cloud aerosols at trace levels. Raman spectroscopy is an ideal candidate for characterizing aerosols and has a track record in studies of Earth’s atmosphere. Raman provides broad chemical screening of organic and inorganic molecules within seconds, and Raman instrumentation can be miniaturized to meet the stringent size, weight, and power (SWaP) constraints of an atmospheric probe while retaining sensitivity and specificity that allow spectral fingerprinting of compounds and functional groups. Raman alone is insufficient to characterize trace constituents however, as limits of detection are typically in the 10s to 100s of ppm at best for planetary Raman spectrometers. Surface-Enhanced Raman Spectroscopy (SERS), a method that utilizes nanoscale materials interacting with a sample to enhance weak Raman signals by orders of magnitude when probed by a laser, has the potential to drastically improve the sensitivity of a Raman instrument while adding little-to-no SWaP nor complexity to a scientific payload. We aim to de-risk SERS technology for rapid infusion in future planetary science missions by developing custom SERS substrates tailored towards Venus atmospheric exploration. We have developed SERS substrates consisting of nanotextured silver films and tested them on potential Venus-relevant organic compounds, with preliminary results indicating sub-ppm sensitivity. Additionally, we have planned tests to investigate durability, longevity, and other key characteristics that impact SERS substrate performance to prepare SERS technology for flight.
Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.
Inhomogeneities in the spatial distribution of second phase particles in engineering materials are known to affect certain mechanical properties. Progress in this area has been hampered by the lack of a convenient method for quantitative description of the spatial distribution of the second phase. This study intends to develop a broadly applicable method for the quantitative analysis and description of the spatial distribution of second phase particles. The method was designed to operate on a desktop computer. The Dirichlet tessellation technique (geometrical method for dividing an area containing an array of points into a set of polygons uniquely associated with the individual particles) was selected as the basis of an analysis technique implemented on a PC. This technique is being applied to the production of Al sheet by PM processing methods; vacuum hot pressing, forging, and rolling. The effect of varying hot working parameters on the spatial distribution of aluminum oxide particles in consolidated sheet is being studied. Changes in distributions of properties such as through-thickness near-neighbor distance correlate with hot-working reduction.
X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be time-consuming. While adaptive sampling methods exist for efficiently collecting spectroscopic data, they often lack domain-specific knowledge about the structure of XANES spectra. Here we demonstrate a knowledge-injected Bayesian optimization approach for adaptive XANES data collection that incorporates understanding of spectral features like absorption edges and pre-edge peaks. We show this method accurately reconstructs the absorption edge of XANES spectra using only 15–20% of the measurement points typically needed for conventional sampling, while maintaining the ability to determine the x-ray energy of the sharp peak after the absorption edge with errors less than 0.03 eV, the absorption edge with errors less than 0.1 eV; and overall root-mean-square errors less than 0.005 compared to traditionally sampled spectra. Our experiments on battery materials and catalysts demonstrate the method’s effectiveness for both static and dynamic XANES measurements, improving data collection efficiency and enabling better time resolution for tracking chemical changes. This approach advances the degree of automation in XANES experiments, reducing the common errors of under- or over-sampling points near the absorption edge and enabling dynamic experiments that require high temporal resolution or limited measurement time.
Molecular-level characterization of polymeric matrix resin in cured graphite-reinforced composite materials now determined through analysis of diffuse reflectance (DR) with Fourier Transform Infrared (FTIR) spectroscopy. Improved analytical method based on diffuse reflectance. DR/ FTIR technique successfully applied to analysis of several different composites and adhesives impossible to analyze by conventional methods.
This paper discusses the concepts of a next-generation in situ science program, named Sample Acquisition, Analysis, and Preservation (SAAP), established by NASA to develop critical technologies for remote identification, acquisition, processing, analysis, and preservation of materials for the in situ science, engineering characterization, and earth return. Special attention is given to the SAAP architecture, system design, remote sensing system, sample acquisition system, and methods for sample analysis. A diagram of the SAAP preliminary system conceptual design is included.
The experimental techniques and associated data analysis methods used to measure the resistance to interlaminar fracture, or 'fracture toughness', of polymer matrix composite materials are described. A review in the use of energy techniques to characterize fracture behavior in elastic solids is given. An overview is presented of the types of approaches employed in the design of delamination-resistant composite materials.
A series of tests was run to characterize the through-the-thickness tensile strength for a variety of composites that included 2D and 3D braids, 2D and 3D weaves, and prepreg tapes. A new test method based on a curved beam was evaluated. The through-the-thickness deformations were characterized using moire interferometry. Failures were significantly different between the 2D and 3D materials. The 2D materials delaminated between layers due to out-of-plane tensile stresses. The strength of the 2D textile composites did not increase relative to the tapes. The 3D materials failed due to the formation of radial cracks caused by high circumferential stresses along the inner radius. A circumferential crack similar to the 2D materials produced the final failure. Final failure in the 3D materials occurred at a lower bending moment than in other materials. The early failures were caused by radial crack formation rather than low through-the-thickness strength.
Comparisons of complete genome sequences allow the most objective and comprehensive descriptions possible of a lineage's evolution. This communication uses the completed genomes from four major euryarchaeal taxa to define a genomic signature for the Euryarchaeota and, by extension, the Archaea as a whole. The signature is defined in terms of the set of protein-encoding genes found in at least two diverse members of the euryarchaeal taxa that function uniquely within the Archaea; most signature proteins have no recognizable bacterial or eukaryal homologs. By this definition, 351 clusters of signature proteins have been identified. Functions of most proteins in this signature set are currently unknown. At least 70% of the clusters that contain proteins from all the euryarchaeal genomes also have crenarchaeal homologs. This conservative set, which appears refractory to horizontal gene transfer to the Bacteria or the Eukarya, would seem to reflect the significant innovations that were unique and fundamental to the archaeal "design fabric." Genomic protein signature analysis methods may be extended to characterize the evolution of any phylogenetically defined lineage. The complete set of protein clusters for the archaeal genomic signature is presented as supplementary material (see the PNAS web site, www.pnas.org).
Material recession and charring are two major processes determining the performance of ablative heat shield materials. Even in ground testing, the characterization of these two mechanisms relies on measurements of material thickness before and after testing, thus providing only information integrated over the test time. For recession measurements, optical methods such as imaging the sample surface during testing are under investigation but require high alignment and instrument effort, therefore being not established as a standard measurement method. For char depth measurements, the most common method so far consists in investigation of sectioned samples after testing or in the case of Stardust where core extractions were performed to determine char information. In flight, no reliable recession measurements are available, except total recession after recovering the heat shield on ground. Developments of mechanical recession sensors have been started but require substantial on board instrumentation adding mass and complexity. In this work, preliminary experiments to evaluate the feasibility of remote sensing of material recession and possibly char depth through optically observing the emission signatures of seeding materials in the post shock plasma is investigated. It is shown that this method can provide time resolved recession measurements without the necessity of accurate alignment procedures of the optical set-up and without any instrumentation on board of a spacecraft. Furthermore, recession data can be obtained without recovering flight hardware which would be a huge benefit for inexpensive heat shield material testing on board of small re-entry probes, e.g. on new micro-satellite re-entry probes as a possible future application of Cubesats or RBR
The unidirectional carbon pultruded rod running through the tops of the stringers is a key design feature of the Pultruded Rod Efficient Unitized Structure (PRSEUS) concept as applied to aircraft fuselage structure. Reported herein are the test methods and results from a test campaign in which the strength of the rod/overwrap interface of various PRSEUS stringer configurations were characterized. The different stringer configurations included different materials and stacking sequences for the stringer overwrap and whether or not an additional layer of adhesive was included between the rod and the overwrap.
The present talk will provide an overview of the work performed during the Advanced Composites Project (ACP) on the development, and verification and validation of the Floating Node Method (FNM) as well as the Virtual Crack Closure Technique (VCCT) and cohesive zone modeling (CZM). The FNM is a finite element-based technique to represent crack networks. The complex nature of matrix crack-delamination interactions observed in unidirectional (UD) tape laminates suggests that a methodology such as the FNM method may be required to be able to accurately simulate damage progression in these laminates. Simulating crack onset and growth within the context of the FNM relies on techniques such as VCCT and CZM. The talk is organized to provide, via select examples, an overview of the breadth of the Verification & Validation (V&V) exercises performed during the ACP, and how these challenged the state-of-the art and guided further developments in discrete crack modeling, while helping to establish confidence in the progress made and map the challenges ahead. The performance of the VCCT and CZM individually, and in combination with the FNM can be assessed through verification exercises. These exercises typically consist of a comparison of simulation results to known numerical or analytical solutions. Verification is key to identify implementation issues and limitations that, otherwise, may remain undetected and cloud any subsequent validation efforts. Indeed, a subset of these numerical exercises led to further developments of the VCCT and the FNM method as will be illustrated. Before embarking on the subsequent validation of the framework, it is critical to have adequate characterization data. However, the testing campaign conducted revealed material responses that challenged the state-of-the-art and required further developments. The developments in CZM technology associated with the modeling of the responses of hybrid interfaces (fabric/UD) will be given as an example. Finally, the talk will conclude with a summary of the validation exercises performed under quasi-static and fatigue loadings, highlighting some of the key achievements, outstanding challenges and lessons learned.
The development of high-wear resistant refractories having minimal production costs is facilitated by characterizing the wear mechanisms associated with their corrosive wear. Static cup testing is a commonly used method for comparing the corrosion resistance performance of two or more refractory materials. Although the static cup test conditions are not as severe as dynamic tests, this study shows that the thermal gradient present within the system during heating and cooling stages serves to generate movement of the slag leading to mechanical wear. The thermal gradient within the refractory, and between the slag and the refractory, occurs during the ramp stage of the test and lasts until the soaking stage is reached bringing the system to a thermal equilibrium. Using computational fluid dynamics (CFD) capabilities embedded within ANSYS software, this study modelled and quantified the convection currents within the slag and associated shear stresses generated on the refractory walls due to the thermal gradient. A traditional ladle furnace was employed as a case study to verify the results of the studied CFD model. The corrosion rate of the refractory lining was found to depend on the mass transfer coefficient of the refractory dissolution into the slag, and a velocity term which governs the extent of corrosion at any given location. This velocity term is a function of slag viscosity, as well as the concentration gradient and/or temperature gradient at the triple points. In this study, wall shear stress was used as a reliable proxy for identifying high-velocity regions prone to excessive corrosive wear. Elevated wall shear stress near the slag/air and slag/molten steel interfaces align with observed corrosion grooves, which reflects the intensified corrosive wear at these locations.
Abstract Biopolymers and bioinspired materials contribute to the construction of intricate hierarchical structures that exhibit advanced properties. The remarkable toughness and damage tolerance of such multilevel materials are conferred through the hierarchical assembly of their multiscale (i.e., atomistic to macroscale) components and architectures. Here, the functionality and mechanisms of biopolymers and bio‐inspired materials at multilength scales are explored and summarized, focusing on biopolymer nanofibril configurations, biocompatible synthetic biopolymers, and bio‐inspired composites. Their modeling methods with theoretical basis at multiple lengths and time scales are reviewed for biopolymer applications. Additionally, the exploration of artificial intelligence‐powered methodologies is emphasized to realize improvements in these biopolymers from functionality, biodegradability, and sustainability to their characterization, fabrication process, and superior designs. Ultimately, a promising future for these versatile materials in the manufacturing of advanced materials across wider applications and greater lifecycle impacts is foreseen.