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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.

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At least 361 records · Page 20

A phase-field model for hydraulic fracture nucleation and propagation in porous media

Many geo-engineering applications, for example, enhanced geothermal systems, rely on hydraulic fracturing to enhance the permeability of natural formations and allow for sufficient fluid circulation. Over the past few decades, the phase-field method has grown in popularity as a valid approach to modeling hydraulic fracturing because of the ease of handling complex fracture propagation geometries. However, existing phase-field methods cannot appropriately capture nucleation of hydraulic fractures because their formulations are solely energy-based and do not explicitly take into account the strength of the material. Thus, in this work, we propose a novel phase-field formulation for hydraulic fracturing with the main goal of modeling fracture nucleation in porous media, for example, rocks. Built on the variational formulation of previous phase-field methods, the proposed model incorporates the material strength envelope for hydraulic fracture nucleation through two important steps: (i) an external driving force term, included in the damage evolution equation, that accounts for the material strength; (ii) a properly designed damage function that defines the fluid pressure contribution on the crack driving force. In conclusion, the comparison of numerical results for two-dimensional test cases with existing analytical solutions demonstrates that the proposed phase-field model can accurately model both nucleation and propagation of hydraulic fractures. Additionally, we present the simulation of hydraulic fracturing in a three-dimensional domain with various stress conditions to demonstrate the applicability of the method to realistic scenarios.

15 GEOTHERMAL ENERGY↗

Multilevel graph embedding

The goal of the present paper is the design of embeddings of a general sparse graph into a set of points in $\mathbb{R}^d$ for appropriate d ≥ 2. The embeddings that we are looking at here aim to keep vertices that are grouped in communities together and keep the rest apart. To achieve this property, we utilize coarsening that respects possible community structures of the given graph. We employ a hierarchical multilevel coarsening approach that identifies communities (strongly connected groups of vertices) at every level. The multilevel strategy allows any given (presumably expensive) graph embedding algorithm to be made into a more scalable (and faster) algorithm. We demonstrate the presented approach on a number of given embedding algorithms and large-scale graphs and achieve speed-up over the methods in a recent paper.

97 MATHEMATICS AND COMPUTING↗

Numerical solution of singular Lyapunov equations

We consider the numerical solution of large scale singular (continuous-time) Lyapunov equations of the form AX + XA T + BB T = 0, where A is semistable, that is, its spectrum is contained in the left half plane, with the exception of a few semisimple eigenvalues at zero. We also consider the case of a few semisimple eigenvalues on the imaginary axis. We assume that we know these few eigenvalues (zero or imaginary), and that we have or can compute the corresponding invariant subspaces. We use this information to build an appropriate newly proposed subspace on which to project the Lyapunov equations, and then compute a low-rank approximation to the least squares solution. Selected illustrative numerical examples are provided.

97 MATHEMATICS AND COMPUTING↗

Weighted relaxation for multigrid reduction in time

Current trends in computer architectures now mean that faster computation speed must come primarily from increased concurrency, not faster clock speeds, which are stagnating. Thus, this situation creates bottlenecks for serial algorithms, including the well-known bottleneck for sequential time-integration, where each individual time-value (i.e., time-step) is computed sequentially. One approach to alleviate this and achieve parallelism in time is with multigrid. Here, in this work, we consider multigrid-reduction-in-time (MGRIT), a multilevel method applied to the time dimension that computes multiple time-steps in parallel. Like all multigrid methods, MGRIT relies on the complementary relationship between relaxation on a fine-grid and a correction from the coarse grid to solve the problem. All current MGRIT implementations are based on unweighted-Jacobi relaxation; here we introduce the concept of weighted relaxation to MGRIT. We derive new convergence bounds for weighted relaxation, and use this analysis to guide the selection of relaxation weights. Numerical results then demonstrate that by choosing appropriate non-unitary relaxation weights, one can achieve faster convergence rates and lower iteration counts for MGRIT when compared with unweighted relaxation. In most cases, weighted relaxation yields a 10%–20% saving in iterations, which is significant when using large high-performance computers. For A-stable integration schemes, results also illustrate that under-relaxation can restore convergence in some cases where unweighted relaxation is not convergent.

97 MATHEMATICS AND COMPUTING↗

Approximation of periodic Green's operator in real space using numerical integration and its use in fast Fourier transform-based micromechanical models

In this work, we propose an expression for the periodic first derivative of Green's function in real space. The proposed expression allows an alternative way of computing the periodic Green's operator based on periodically summing the free-space Green's operator in terms of an appropriate quadrature rule. We provide computational examples, which show the accuracy of the proposed approach, together with reduced spurious oscillations in the solution fields.

42 ENGINEERING↗

Calibration of elastoplastic constitutive model parameters from full-field data with automatic differentiation-based sensitivities

Here, we present a framework for calibration of parameters in elastoplastic constitutive models that is based on the use of automatic differentiation (AD). The model calibration problem is posed as a partial differential equation-constrained optimization problem where a finite element (FE) model of the coupled equilibrium equation and constitutive model evolution equations serves as the constraint. The objective function quantifies the mismatch between the displacement predicted by the FE model and full-field digital image correlation data, and the optimization problem is solved using gradient-based optimization algorithms. Forward and adjoint sensitivities are used to compute the gradient at considerably less cost than its calculation from finite difference approximations. Through the use of AD, we need only to write the constraints in terms of AD objects, where all of the derivatives required for the forward and inverse problems are obtained by appropriately seeding and evaluating these quantities. We present three numerical examples that verify the correctness of the gradient, demonstrate the AD approach's parallel computation capabilities via application to a large-scale FE model, and highlight the formulation's ease of extensibility to other classes of constitutive models.

42 ENGINEERING↗

A micromorphic filter for determining stress and deformation measures from direct numerical simulations of lower length scale behavior

A micromorphic filter is presented for the extraction of stress and deformation measures from underlying direct numerical simulation (DNS) of microstructural mechanical response. The filter is consistent with the micromorphic continuum theory of Eringen and Suhubi (1964), and allows the interrogation of a DNS to generate higher order constitutive models. The filter adopts aspects of the overlap coupling techniques for atomistic-continuum scale-bridging in order to update the nodal degrees of freedom of the finite-element-based filter. Here, two methods for the extraction of quantities of interest from the underlying DNS are presented. The first is a least squares fitting technique which is appropriate for finite-element-style macro-scale domains, and the second is a variationally based approach which generalizes the method to any macro-scale domain which has a variational form. No restrictions on the form of the micro-scale simulation are inherent to the approach, provided that the required quantities (stress, position, etc.) can be provided. The filter is applied to a simple homogeneous medium undergoing homogeneous deformation to demonstrate the recovery of a classical continuum response, what we call the null case. We then apply the framework to the same homogeneous medium with a central and edge penny-shaped crack to show micromorphic effects. We demonstrate that varying the size of the filter causes the micromorphic behaviors to arise and then dissipate as the filter becomes smaller than the crack's length scale. Additionally we show the effect of filter size on a chiral element network along with a plate perforated with evenly spaced and perturbed holes through the thickness. The micromorphic effects are shown to be present for the chiral elements under any loading but become most pronounced when a single element is located within each averaging domain. Micromorphic effects become pronounced for the plate upon the onset of localization.

97 MATHEMATICS AND COMPUTING↗

Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction

In this work, a novel approach is introduced for accelerating the solution of structural dynamics problems in the presence of localised phenomena, such as cracks. For this category of problems, conventional projection-based Model Order Reduction (MOR) methods are either limited with respect to the range of system configurations that can be represented or require frequent solutions of the Full Order Model (FOM) to update the low-dimensional spaces, in which solutions are represented. In the proposed approach, low-dimensional spaces, constructed for the healthy structure, are enriched with appropriately selected columns of the flexibility matrix of the system. It can be shown that these spaces contain the solution to the original problem for the static case, while their dimension is much smaller. In order to allow their online construction for arbitrary localised features, the full flexibility matrix of the system should be available. To this end, a hierarchical representation is used for the matrices involved, allowing to compute the flexibility matrix efficiently and with reduced memory requirements. The resulting method offers significant speedups, without sacrificing the flexibility and accuracy of the full order model. The performance and limitations of the approach are studied through a series of examples in structural dynamics.

fracture mechanics↗

A layered solid finite element formulation with interlaminar enhanced displacements for the modeling of laminated composite structures

Accurate modeling of layered composite structures often requires the use of detailed finite element models which can sufficiently resolve the kinematics and material behavior within each layer of the composite. However, individually discretizing each material layer into finite elements presents a prohibitive computational expensive given the large number of thin layers comprising some laminated composites. To address these challenges, an 8-node layered solid hexahedral finite element is formulated with the aim of striking an appropriate balance between efficiency and fidelity. The element is discretized into an arbitrary number of distinct material layers, and employs reduced in-plane integration within each layer. The chosen reduced integration scheme is supplemented by a novel physical stabilization approach which includes layerwise enhancements to mitigate various forms of locking phenomena. The proposed framework additionally supports the inclusion of interlaminar enhanced displacements to better represent the kinematics of general layered composite materials. Finally, the described element formulation has been implemented in the ParaDyn finite element code, and its efficacy for modeling laminated composite structures is demonstrated on a variety of verification problems.

42 ENGINEERING↗

A least-squares finite element method based on the Helmholtz decomposition for hyperbolic balance laws

In this paper, a least-squares finite element method for scalar nonlinear hyperbolic balance laws is proposed and studied. The approach is based on a formulation that utilizes an appropriate Helmholtz decomposition of the flux vector and is related to the standard notion of a weak solution. This relationship, together with a corresponding connection to negative-norm least-squares, is described in detail. As a consequence, an important numerical conservation theorem is obtained, similar to the famous Lax–Wendroff theorem. The numerical conservation properties of the method in this paper do not fall precisely in the framework introduced by Lax and Wendroff, but they are similar in spirit as they guarantee that when L 2 convergence holds, the resulting approximations approach a weak solution to the hyperbolic problem. The least-squares functional is continuous and coercive in an H -1 -type norm, but not L 2 -coercive. Nevertheless, the L 2 convergence properties of the method are discussed. Convergence can be obtained either by an explicit regularization of the functional, that provides control of the L 2 norm, or by properly choosing the finite element spaces, providing implicit control of the L 2 norm. Numerical results for the inviscid Burgers equation with discontinuous source terms are shown, demonstrating the L 2 convergence of the obtained approximations to the physically admissible solution. The numerical method utilizes a least-squares functional, minimized on finite element spaces, and a Gauss–Newton technique with nested iteration. Finally, we believe that the linear systems encountered with this formulation are amenable to multigrid techniques and combining the method with adaptive mesh refinement would make this approach an efficient tool for solving balance laws (this is the focus of a future study).

97 MATHEMATICS AND COMPUTING↗

Effect of recycled fibers and shredded intermediates variation on the mechanical properties and energy absorption of fiber‐reinforced composite panels

Abstract The global composite industry generates large quantities of waste which mostly ends up in landfills due to a lack of established end‐use applications for multiple waste streams. The scrap from end‐of‐life (EoL) includes manufacturing waste such as dry chopped fiber tows, loose fibers, shredded fibers from fabric textile operations, cured/semi‐cured prepregs, and fully cured composite structure waste from aircraft, automobiles, wind blades, boats, and pressure vessels. In this work, different composite waste streams were reduced to shredded intermediates, followed by simple blending, and subjected to wet compression molding to produce composite panels. The panels/plaques were tested for mechanical properties (flexure and impact), fiber‐matrix wet‐out, and property bounds. It was found that wet‐compression molding was a viable and scale‐able approach to produce recycled panels from EoL composites shredded scrap. Furthermore, full‐scale size panels for use in truck bodies and intermodal shipping container flooring were manufactured and their impact resistance was tested using a drop weight impact test. They were tested both for high‐ and low‐velocity load. In the case of high‐velocity load, the average impact load was 14,673 N; the average absorbed energy was 101.6 J; the average elastic energy was 11.7 J and the impact resistance was 1065 J/m. In the case of the low‐velocity drop weight impact test, it was found that the average impact load was 7877.358 N; the average absorbed energy was 9.718 J; the average elastic energy was 9.14 J, and the impact resistance was 184.1 J/m. The shredded composite was shown to be a candidate material for the manufacture of truck bodies and intermodal containers’ flooring panels. Highlights By using shredded intermediates from different composite waste streams, it is possible to manufacture composite panels. Wet–compression process is an appropriate technique for manufacturing recycled fiber composite panels. Regardless of the source of scrap, the mechanical properties of the produced composite panels were improved. The recycling process technology can be transformed to commercial scale to produce full‐size transportation flooring panels. A product pathway is established in consideration of lower cost and improved recyclability.

Vaidya, Uday↗

Rheological behavior of neat and carbon fiber-reinforced poly(ether ketone ketone) for extrusion deposition additive manufacturing

To develop new materials for extrusion additive manufacturing (AM) systems, a fundamental understanding of rheological properties is essential to correlate the effect of processing on material structure and its properties. In this work, the rheological properties of five different grades of neat and carbon fiber (CF)-reinforced poly(ether ketone ketone) are reported. Rheological properties are essential to understand the effect of reinforcing fibers and AM process parameters such as time, temperature, environment, and shear rate on flow behavior during processing. Small-amplitude oscillatory shear tests and steady shear tests indicated neat grades to exhibit less increase in viscosity over time when processed in air than the CF-filled grades. The filled grades showed greater shear thinning and lower sensitivity to temperature. Altogether, this rheological analysis provides a broad framework for determining appropriate processing conditions for extrusion deposition AM of such high-temperature polymer systems.

36 MATERIALS SCIENCE↗

Synthesis and acoustic properties study of castor‐oil‐based polyurethane foams with the addition of graphene‐oxide‐modified straw fibers

Abstract Polyurethane foam (PUF) can absorb sound by air friction and structural vibrations of cell walls. It is widely used as acoustic material in the automotive industry. According to existing studies, graphene oxide (GO) can improve the acoustic properties of PUF. However, GO tends to coalesce inside PUF. In this paper, straw fibers were modified with different concentrations of GO solution to embed GO on the surface of plant fibers. The GO was dispersed in the PUF using straw fibers. In addition, some studies show that the wrinkled morphology of the GO surface is believed to play a mechanical interlocking role in improving interfacial bonding, thus enhancing the stress transfer between the plant fibers and the polyurethane (PU) matrix and improving the mechanical properties of the PU composites. The acoustic and mechanical properties of the modified PU materials were observed by treating plant fibers with appropriate amounts of GO solution. The experimental study shows that the sample modified with 1 g L −1 GO solution reaches a maximum average sound absorption coefficient of 0.5838 when the straw fiber content reaches 0.5 g, and the sample modified with 2 g L −1 GO solution reaches a maximum transmission loss of 10.5333 when the straw fiber content reaches 1 g. © 2022 Society of Industrial Chemistry.

Yang, Keyao↗

Estimating and parameterizing mismatch power loss in bifacial photovoltaic systems

Nonuniform irradiance on the rear side of bifacial photovoltaic (PV) systems can cause additional mismatch loss, which may not be appropriately captured in PV energy production estimates and software. We evaluated several scenarios including horizontal single-axis tracking (HSAT) over natural ground-cover and rooftop-mounted systems over high albedo reflective roofs. We found mismatch losses of up to 1.5% annual loss for very close-mounted (0.15 m) rooftop systems, but losses for HSAT systems and high-ground-clearance rooftop systems were lower (<0.5%). A simplified empirical relationship was found that links the spatial variation of irradiance (specifically, the mean absolute difference of irradiance) to the resulting mismatch loss factor, with an R 2 better than .99. Furthermore, this approximate relationship was experimentally validated on mismatched PV modules, and it provides a basis for rapidly estimating bifacial mismatch loss factors for use in hourly PV performance simulations such as PVSyst or SAM. Additional parameters investigated include (a) climate dependence and module orientation, which were not found to have a strong impact on bifacial mismatch losses and (b) PV module fill factor and bifaciality ratio, which did have a strong linear impact on mismatch losses.

14 SOLAR ENERGY↗

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗

Coefficient of Thermal Expansion during Ratchet Growth of TATB Compactions

Triamino trinitrobenzene (TATB) is an insensitive high explosive, meaning that it is quite immune from accidental detonation and only performs in appropriately engineered configurations. While this is advantageous for applications, the TATB crystal is graphitic and possesses significant thermal and mechanical anisotropy. Compactions of TATB crystals, with or without binder, have been shown to have oriented TATB crystals that relate to the pressing geometry and process, and this TATB texture necessarily imparts microscale and macroscale anisotropy to the compaction. By a mechanism not fully understood, thermal cycling results in irreversible volume expansion (also called ratchet growth) of the compaction likely by creating stress points on the microscale. Changes in density caused by thermal cycling can certainly effect the explosive performance. Our past characterization of the ratchet growth phenomenon has focused on the magnitude of the irreversible strain as measured before and after a thermal cycle. Finally, in the work presented here, we analyze the evolving thermal expansion behavior during the ascending and descending temperature ramps, providing further insight into the material changes taking place during the ratchet growth phenomenon.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗

Data‐Efficient Generation of Synthetic Microstructures of Polymer‐Bonded Energetic Material With Fine‐Tuned Stable Diffusion

Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.

Dreambooth↗