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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 991 records · Page 55

Carbon Fiber Reinforced Polyolefin Body Panels

This project addresses an automotive industry desire for a cost-effective, lightweight material for body panels that offers mass reduction compared to steel and aluminum body panels, and a cost savings compared to incumbent polymer body panels. Inexpensive polypropylene (PP) combined with <10 weight % reclaimed/recycled carbon fiber (rCF) have the potential to meet both performance and affordability targets for lightweight, paintable vertical body panels. This project supports DOE and IACMI technical goals of reducing production cost of CF composites >25% in 5 years on a path to >50% in 10 years and demonstrating technologies for >80% recyclability or reuse of fiber reinforced composites in 5 years on a path to >95% in 10 years. Alternative body panel materials must meet all fit and surface finish requirements, and match the appearance of metal body panels adjacent to them. The PP/rCF materials must maintain exterior dimensional requirements with a low co-efficient of thermal expansion, excellent paintability, and mechanical performance. Thermoplastic injection molding offers significant reduction in tooling costs as injection molding dies are typically less than half the cost of stamping dies. This project utilized rCF compounded with special formulations of PPs to produce automotive components that meet requirements for fit, finish, mechanical performance, and paintability while offering significant mass savings over incumbent metal panels. It will also offer a cost savings versus other composite solutions. Fenders were molded at the IACMI – Corktown facility using an existing fender tool. Ford Motor Company was the industry lead for this project and provided project management, testing, painting and adhesion testing, and developed the cost-model/business case. Ford engaged and aggregated cost share with Borealis who provided materials, technical support for process trials, and participated in coordination meetings. Vehicles Technology Area staff in Corktown assisted in project management, process trials, molded fenders, and benchmarked physical characteristics. Over 450 plaques were molded with two different gating systems to look at processing conditions and specimens were excised for mechanical testing. Plaques were also used for paint trials, surface analysis, and dimensional analysis. Subsequently, over 200 fenders were molded at IACMI – Corktown. These fenders were used for paint trials, surface analysis, and dimensional analysis. The PP/rCF systems met all of the requirements except for paint appearance. Additional development of paint primer and top coat is necessary to fulfill automotive OEM paint surface requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A methodology for generating reduced-order models for large-scale buildings using the Krylov subspace method

Developing a computationally efficient but accurate building energy simulation (BES) model is important for many purposes. Model order reduction (MOR) methods are attractive and much more reliable than identification approaches, since it directly extract a lower-dimensional model from a detailed physics-based model without any pre-simulations. However, because of computational and data storage requirements, there are challenges of applying these methods to a large-scale building. To overcome the problem, this work introduces the Krylov subspace method to the building science field. Technical issues of applying the method to building applications are addressed and a suitable algorithm that overcomes those challenges is presented. Furthermore, to demonstrate the reliability of the algorithm, comparisons between the resulted reduced-order model (ROM) and a high-fidelity model from a commercial BES software for a 60-zone case study building are provided. The ROM was a factor of 100 faster than the high fidelity model but with high accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of phase-change technique to thin sections with heating on both surfaces

A numerical digital computer program was developed to calculate the heat-transfer coefficients for both sides of a one-dimensional finite slab subject to the boundary conditions ascribed to the phase-change coating heat-transfer technique. In a typical tunnel test situation where a thin wing was exposed to heating on both sides, the data reduction procedures for a semi-infinite slab gave heat-transfer coefficients as much as 375 percent too high on the side with the lowest heating. The results from the one-dimensional finite-slab procedure are presented in the form of correction factors to the solution for a semi-infinite slab in terms of parameters normally used with the phase-change heat-transfer technique. These correlations are not restricted to slab thickness or thermophysical properties and are easily used to obtain accurate data on thin model sections.

Hunt, J. L.↗

Aerodynamic design for improved maneuverability by the use of three-dimensional transonic theory

This study has examined the level of transonic maneuver performance that can be achieved by the use of three-dimensional transonic theory. The FLO-27 code of Jameson and Caughey (1977) was used to lower maneuver drag by the reduction of shock strength on the wing upper surface. A design procedure was used to provide a set of guidelines for the iterative application of FLO-27 during the wing design process. The fighter configuration utilized had a leading-edge sweep of 45 deg and an aspect ratio of 3.28. Tests were conducted at Mach numbers from 0.60 to 0.95 and angles of attack from -5 to 18 deg. The accurate prediction of wing shock systems required the inclusion of fuselage effects in the theory. The FLO-27 code gave a reasonable estimate of the experimental wing pressure distributions at transonic maneuver conditions in the region of the wing where the flow was attached. For Mach numbers between 0.60 and 0.95 and lift coefficients near 0.9, a wing designed by the use of FLO-27 showed substantially lower drag than an empirically developed, supercritical maneuver wing and a maneuver wing designed primarily by two-dimensional transonic theory. For some maneuver conditions, the drag of the two-dimensional design was somewhat lower.

Mann, M. J.↗

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ 2 -norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A space for lattice representation and clustering

Algorithms for quantifying the differences between two lattices are used for Bravais lattice determination, database lookup for unit cells to select candidates for molecular replacement, and recently for clustering to group together images from serial crystallography. It is particularly desirable for the differences between lattices to be computed as a perturbation-stable metric, i.e. as distances that satisfy the triangle inequality, so that standard tree-based nearest-neighbor algorithms can be used, and for which small changes in the lattices involved produce small changes in the distances computed. A perturbation-stable metric space related to the reduction algorithm of Selling and to the Bravais lattice determination methods of Delone is described. Two ways of representing the space, as six-dimensional real vectors or equivalently as three-dimensional complex vectors, are presented and applications of these metrics are discussed. (Note: in his later publications, Boris Delaunay used the Russian version of his surname, Delone.)

36 MATERIALS SCIENCE↗

Cost-Effective Additive Manufacturing of Ambient Pressure-Dried Silica Aerogel

The conventional manufacturing processes for aerogel insulation materials mostly rely on the supercritical drying, which suffers from issues of massive energy consumption, high-cost equipment, and prolonged processing time. Considering the large market demand for the aerogel insulation material in the next decade, a cost-effective and scalable fabrication technique is highly desired. In this paper, a direct ink writing (DIW) method is used to three-dimensionally fabricate the silica aerogel insulation material, followed by room-temperature and ambient pressure drying. Compared with the supercritical drying and freeze-drying techniques, the reported method significantly reduces the fabrication time and costs. The cost-effective DIW technique offers the capability to print complex hollow internal structures, coupled with the porous aerogel structure, it is found to be beneficial for the thermal insulation property. In this work, the addition of fiber to the ink assures the durability of the fabricated product, without sacrificing the thermal insulation performance. The foam ink preparation methods and the printability are demonstrated in this paper, along with the printing of complex three-dimensional geometries. The thermal insulation performance of the printed objects is characterized, and the mechanical properties were also examined. The proposed approach is found to have a 56% reduction in the processing time. The printed silica aerogels exhibit a low thermal conductivity of 0.053 W m –1 K –1 .

36 MATERIALS SCIENCE↗

Linear stability of magnetized massive protoplanetary disks

Magnetorotational instability (MRI) and gravitational instability (GI) are the two principle routes to turbulent angular momentum transport in accretion disks. Protoplanetary disks (PPDs) may develop both. This paper aims to reinvigorate interest in the study of magnetized massive PPDs, starting from the basic issue of stability. The local linear stability of a self-gravitating, uniformly magnetized, differentially rotating, three-dimensional stratified disk subject to axisymmetric perturbations is calculated numerically. The formulation includes resistivity. It is found that the reduction in the disk thickness by self-gravity (SG) can decrease MRI growth rates; the MRI becomes global in the vertical direction, and MRI modes with small radial length scales are stabilized. The maximum vertical field strength that permits the MRI in a strongly self-gravitating polytropic disk with polytropic index Γ = 1 is estimated to be B{sub z,max}≃c{sub s0}Ω√(μ{sub 0}/16πG), where c{sub s0} is the midplane sound speed and Ω is the local angular velocity. In massive disks with layered resistivity, the MRI is not well localized to regions where the Elsasser number exceeds unity. For MRI modes with radial length scales on the order of the disk thickness, SG can enhance density perturbations, an effect that becomes significant in the presence of a strong toroidal field, and which depends on the symmetry of the underlying MRI mode. In gravitationally unstable disks where GI and MRI growth rates are comparable, the character of unstable modes can transition smoothly between MRI and GI. Implications for nonlinear simulations are discussed briefly.

79 ASTRONOMY AND ASTROPHYSICS↗

Minimising the effect of nanoparticle deformation in intermittent contact amplitude modulation atomic force microscopy measurements

The results of systematic height measurements of polystyrene (PS) nanoparticles using intermittent contact amplitude modulation atomic force microscopy (IC-AM-AFM) are presented. The experimental findings demonstrate that PS nanoparticles deform during AFM imaging, as indicated by a reduction in the measured particle height. This deformation depends on the IC-AM-AFM imaging parameters, material composition, and dimensional properties of the nanoparticles. A model for nanoparticle deformation occurring during IC-AM-AFM imaging is developed as a function of the peak force which can be calculated for a particular set of experimental conditions. The undeformed nanoparticle height can be estimated from the model by extrapolation to zero peak force. A procedure is proposed to quantify and minimise nanoparticle deformation during IC-AM-AFM imaging, based on appropriate adjustments of the experimental control parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Physics-Informed Active Learning With Simultaneous Weak-Form Latent Space Dynamics Identification

The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy data. Here, to enhance robustness against noise, we incorporate the weak-form estimation of nonlinear dynamics (WENDy) into gLaSDI. In the proposed weak-form gLaSDI (WgLaSDI) framework, an autoencoder and WENDy are trained simultaneously to discover intrinsic nonlinear latent-space dynamics of high-dimensional data. Compared with the standard sparse identification of nonlinear dynamics (SINDy) employed in gLaSDI, WENDy enables variance reduction and robust latent space discovery, therefore leading to more accurate and efficient reduced-order modeling. Furthermore, the greedy physics-informed active learning in WgLaSDI enables adaptive sampling of optimal training data on the fly for enhanced modeling accuracy. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including viscous and inviscid Burgers' equations, time-dependent radial advection, and the Vlasov equation for plasma physics. With data that contains 5%–10% Gaussian white noise, WgLaSDI outperforms gLaSDI by orders of magnitude, achieving 1%–7% relative errors. Compared with the high-fidelity models, WgLaSDI achieves 121 to 1779x speed-up.

97 MATHEMATICS AND COMPUTING↗

Effect of Slotted Anode on Gas Bubble Behaviors in Aluminum Reduction Cell

In the aluminum reduction cells, gas bubbles are generated at the bottom of the anode which eventually reduces the effective current contact area and the system efficiency. To encourage the removal of gas bubbles, slotted anode has been proposed and increasingly adopted by some industrial aluminum reduction cells. Nonetheless, the exact gas bubble removal mechanisms are yet to be fully understood. A three-dimensional (3D) transient, multiphase flow mathematical model coupled with magnetohydrodynamics has been developed to investigate the effect of slotted anode on the gas bubble movement. The Eulerian volume of fluid approach is applied to track the electrolyte (bath)–molten aluminum (metal) interface. Meanwhile, the Lagrangian discrete particle model is employed to handle the dynamics of gas bubbles with considerations of the buoyancy force, drag force, virtual mass force, and pressure gradient force. The gas bubble coalescence process is also taken into account based on the O’Rourke’s algorithm. The two-way coupling between discrete bubbles and fluids is achieved by the inter-phase momentum exchange. Numerical predictions are validated against the anode current variation in an industrial test. Comparing the results using slotted anode with the traditional one, the time-averaged gas bubble removal rate increases from 36 to 63 pct; confirming that the slotted anode provides more escaping ways and shortens the trajectories for gas bubbles. Furthermore, the slotted anode also reduces gas bubble’s residence time and the probability of coalescence. Moreover, the bubble layer thickness in aluminum cell with slotted anode is reduced about 3.5 mm (17.4 pct), so the resistance can be cut down for the sake of energy saving and the metal surface fluctuation amplitude is significantly reduced for the stable operation due to the slighter perturbation with smaller bubbles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. Here, we propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reductions than diseased models. In all cases, our workflow coupling Dakota’s MLMF estimators with the SimVascular cardiovascular modeling framework makes uncertainty quantification feasible for constrained computational budgets.

59 BASIC BIOLOGICAL SCIENCES↗

A physics-informed multi-agents model to predict thermo-oxidative/hydrolytic aging of elastomers

This paper introduces a novel physics-informed multi-agents constitutive model to propose prediction in quasi-static constitutive behavior of cross-linked elastomer and the loss of mechanical performance during environmental aging. The presented model is used to simulate the effect of single-mechanism chemical aging (i.e. thermal-inducedor hydrolytic aging) on the behavior of the material in this hybrid framework. Those environmental single-mechanism damages change the polymer matrix over time due to massive chain scission, chain formations, and changing the arrangement of molecules in the polymer matrix. Here we propose a data-driven super-constrained machine-learned engine to represent damage in the polymer matrix and capture the changes in material behavior, including its inelastic features such as Mullins effect and permanent set in the course of aging. We have simplified the 3D stress–strain tensor mapping problem into a small number of super-constrained 1D mapping problems by means of a sequential order reduction. An assembly of multiple replicated conditional neural-network learning-agents (L-agents) is trained to systematically simplify the high-dimensional mapping problem into multiple 1D problems, each represented by a different type of agent. Our hybrid framework is designed to capture the effect of deformation history, aging time, and aging temperature. The model is validated with respect to a comprehensive set of experiments specifically designed to benchmark model capabilities and also against available data in the literature. Thermodynamic consistency and frame independency have been verified. Besides acceptable predictive abilities, a significant reduction of computational cost to predict behavior at multiple states of deformation is the most significant feature of this model.

42 ENGINEERING↗

Membrane tension feedback on shape and motility of eukaryotic cells

In the framework of a phase field model of a single cell crawling on a substrate, we investigate how the properties of the cell membrane affect the shape and motility of the cell. Since the membrane influences the cell dynamics on multiple levels and provides a nontrivial feedback, we consider the following fundamental interactions: (i) the reduction of the actin polymerization rate by membrane tension; (ii) area conservation of the cell’s two-dimensional cross-section vs. conservation of the circumference (i.e. membrane inextensibility); and (iii) the contribution from the membrane’s bending energy to the shape and integrity of the cell. As in experiments, we investigate two pertinent observables — the cell’s velocity and its aspect ratio. We find that the most important effect is the feedback of membrane tension on the actin polymerization. Bending rigidity has only minor effects, visible mostly in dynamic reshaping events, as exemplified by collisions of the cell with an obstacle.

Winkler, Benjamin↗

Bit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)

Abstract. Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits of consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25–80 and 5–65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1–5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1–2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.

58 GEOSCIENCES↗

Structural optimization of turbine blade firtrees

On the basis of the present optimization equation for the structural capacity of a turbine blade attachment firtree, the optimum of the lobe circular fillet radius in the blade and in the turbine disk is determined. In order to further diminish peak stress in firtree design, an elliptical fillet radius is selected in place of the circular one. Two-dimensional stress analysis results for a three-lobe firtree with elliptical radius shows a 14-percent stress reduction in the blade necks (where cracking has been experienced) over the current, four-lobe firtree design.

Lee, R. L.↗

Combined magnetic vector-scalar potential finite element computation of 3D magnetic field and performance of modified Lundell alternators in Space Station applications

A method of combined use of magnetic vector potential (MVP) based finite element (FE) formulations and magnetic scalar potential (MSP) based FE formulations for computation of three-dimensional (3D) magnetostatic fields is developed. This combined MVP-MSP 3D-FE method leads to considerable reduction by nearly a factor of 3 in the number of unknowns in comparison to the number of unknowns which must be computed in global MVP based FE solutions. This method allows one to incorporate portions of iron cores sandwiched in between coils (conductors) in current-carrying regions. Thus, it greatly simplifies the geometries of current carrying regions (in comparison with the exclusive MSP based methods) in electric machinery applications. A unique feature of this approach is that the global MSP solution is single valued in nature, that is, no branch cut is needed. This is again a superiority over the exclusive MSP based methods. A Newton-Raphson procedure with a concept of an adaptive relaxation factor was developed and successfully used in solving the 3D-FE problem with magnetic material anisotropy and nonlinearity. Accordingly, this combined MVP-MSP 3D-FE method is most suited for solution of large scale global type magnetic field computations in rotating electric machinery with very complex magnetic circuit geometries, as well as nonlinear and anisotropic material properties.

Wang, Ren H.↗