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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Kinklike structures in an arcsin real scalar dynamics

Highlights: • Kinklike analyses in a real scalar theory with an arcsin dynamic. • First-order formalism implementation and deformation procedure in an arcsin scalar dynamics. In this paper, we analyze kink-like analytical solutions in a real scalar theory with an arcsin dynamics inspired by the arcsin electrodynamics presented in Kruglov (2015). This analysis is done by means of the first-order formalism. This formalism provides a framework where the equations of motion can be simplified by preserving the linear stability of the theory. In this work, the deformation procedure is implemented with the aim of finding exact solutions in systems with generalized dynamics. Along the paper, we explore how the first-order formalism is implemented in the arcsin kinetics and how such a term influences the kink-like solutions. As a part of the result of our paper, we show that the kink-like solutions are similar to the ones obtained in the standard scalar kinetic theory. We also show that the extra parameter, that controls the non-linearities of the model, plays an essential role in the energy densities and stability potentials. These quantities vary according to this parameter. The goals here are to show how the first-order framework is implemented in this arcsin scenario and to present the analytical kink-like solutions that can be found by means of the first-order framework and deformation method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Doppler effect in rotating systems and Mössbauer rotor experiments

We address once more the problem of the physical interpretation of the Mössbauer effect in a rotating system in the view of the recently discovered extra energy shift (EES) between emitted and absorbed resonant radiation, which emerges in addition to the usual second order Doppler shift for an orbiting absorber. We highlight that both fractional components of the total energy shift have the same sign and correspond to the blueshift of the resonant radiation propagating from the rotational axis to the rotor rim. We indicate a possible way of understanding the origin of the EES in terms of combining metric effects in rotating systems with the quantum mechanical description of resonant nuclei confined in crystal cells by taking into account the recoil-free essence of the Mössbauer effect, where no energy is transmitted to the source (absorber) during the emission (absorption) of resonant radiation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A general strategy and a consolidated mechanism for low-methane hydrogenolysis of polyethylene over ruthenium

Polyethylene (PE) is one of the most environment-threatening plastic waste. Its Ru-catalyzed hydrogenolysis is rapid but produces too much methane. Here, in this study, low-density PE hydrogenolysis is performed at mild conditions and short times over Ru-doped zirconia catalysts (Ru-XZr, X = Ti, Nb, Ce, W, V, Mo, Fe) to determine low-methane catalysts. Methane is produced via direct terminal C-C scission and surface cascade of consecutive C-C scissions, with the latter sensitive to hydrogen availability and dominant in hydrogen-lean conditions. Reactivity studies, characterization and theory reveal that the most effective dopant oxides (W, V, and Mo) are intermediately reducible, as they store and supply extra hydrogen to Ru via reverse hydrogen spillover. This hydrogen readily hydrogenates and desorbs long alkyl surface intermediates that would otherwise produce cascade methane. Our proposed mechanism reconciles the low methane production achieved by increasing the hydrogen pressure or reducing the particle size and exposes the key selectivity descriptors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Assessments of data centers for provision of frequency regulation

There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. Here, when chillers are deactivated, both strategies have a similar regulation capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Orbital engineering of C 3 N monolayer to design efficient synergistic sites electrocatalyst for boosting alkaline hydrogen evolution

Alkaline water electrolyzer (AWE) is one of the promising technologies for hydrogen production at the industrial level. However, energetic inefficiency and low current density impede the development of AWE. Compared with acidic conditions, the Volmer step in alkaline hydrogen evolution reaction (HER) involves extra water dissociation, whose barrier is one of the most vital reasons for the sluggish kinetics of alkaline HER. Herein, choosing C 3 N monolayer as an ideal theoretical model, we design several empty orbitals through intentional metal doping, and further construct synergistic sites on the C 3 N monolayer to accelerate both water dissociation and hydrogen adsorption for alkaline HER. Furthermore, the as-designed Be-doped and Cr-doped C 3 N monolayers exhibit rather low theoretical overpotential of 0.476 eV and 0.216 eV for alkaline HER, respectively, which are even lower than Pt (1 1 1) surface. Moreover, by comparing the water dissociation behaviors on metal-doped C3N monolayer, we find that the empty orbitals with suitable orientation and energy level are useful for promoting the water dissociation process, indicating that we can use orbital engineering strategy to regulate the adsorption strength between adsorbate and surface site. Consequently, it is reasonable to suggest that our orbital engineering strategy would significantly benefit the design of highly efficient alkaline HER electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. Here, this study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m 2 .K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

09 BIOMASS FUELS↗
DOE OSTI2021

Multiscale simulations for multi-continuum Richards equations

In this paper, we study a multiscale method for simulating a dual-continuum unsaturated flow problem within complex heterogeneous fractured porous media. Mathematically, each of the dual continua is modeled by a multiscale Richards equation (for pressure head), and these equations are coupled to one another by transfer terms. On its own, Richards equation is already a nonlinear partial differential equation, and it is exceedingly difficult to solve numerically due to the extra nonlinear dependencies involving the soil water. To deal with multiple scales, our strategy is that starting from a microscopic scale, we upscale the coupled system of dual-continuum Richards equations via homogenization by the two-scale asymptotic expansion, to obtain a homogenized system, at an intermediate scale (level). Based on a hierarchical approach, the homogenization’s effective coefficients are computed through solving the arising cell problems. Furthermore, to tackle the nonlinearity, after time discretization, we use Picard iteration procedure for linearization of the homogenized Richards equations. At each Picard iteration, some degree of multiscale still remains from the intermediate level, so we utilize the generalized multiscale finite element method (GMsFEM) combining with a multi-continuum approach, to upscale the homogenized system to a macroscopic (coarse-grid) level. This scheme involves building uncoupled and coupled multiscale basis functions, which are used not only to construct coarse-grid solution approximation with high accuracy but also (with the coupled multiscale basis) to capture the interactions among continua. These prospects and convergence are demonstrated by several numerical results for the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Microwave catalytic conversion of acetylene for co-production of hydrogen and carbon nanotubes

Natural gas conversion to hydrogen and solid carbon can drastically reduce the carbon footprint. Microwave plasma pyrolysis is an emerging process for chemical industries to directly convert methane (CH 4 ), the major component of natural gas, to hydrogen and carbon, which offers benefits such as fast process dynamics, flexibility, and high product yield. However, the formation of unwanted by-products, like acetylene (C 2 H 2 ), will require extra cost for gas separation. Plasma pyrolysis of CH 4 produces large amount of acetylene at downstream, which is currently used mainly for welding. Here, to avoid gas separation and upgrade acetylene from the downstream of methane plasma reactor, a novel approach toward its transformation to carbon nanotubes (CNT) and pure hydrogen (H 2 ) over Ni-based bimetallic catalyst driven by microwave irradiation has been reported in this work. The dominant gas product was hydrogen. Low concentrations of methane, ethane, and ethylene were observed in the product stream. Catalytic acetylene decomposition was carried out at 400 °C over Al 2 O 3 supported Ni catalyst. The results showed that, at 400 °C, acetylene was dehydrogenated to CNT and hydrogen was the dominant gas in product stream over 10Ni-1Pd-Al 2 O 3 catalyst. Characterizations of spent catalysts was conducted using Raman spectroscopy and transmission electron microscopy (TEM) to investigate the properties of carbon deposited over the catalyst during the catalytic acetylene decomposition. The results highlight that methane can be efficiently converted to hydrogen and CNT through 2-step process, microwave plasma and microwave catalytic conversion of intermediate acetylene, operated in a single reactor system driven by microwave.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Techno-economic evaluation of emission control configurations for AMP/PZ-based post-combustion CO 2 capture

Minimizing the environmental impacts of amine-based post-combustion carbon capture technologies is essential for regulatory compliance and public acceptance. Experimental campaigns at RWE's CO 2 capture pilot plant in Niederaussem using CESAR1 demonstrated that combining existing emission abatement technologies can substantially reduce the concentration of amines and degradation products in the CO 2 -depleted flue gas to below the detection limit of an infrared spectrometer. The campaign confirmed that a proprietary dry bed technology (OEASE aerozone™) or a second water wash can reduce AMP and PZ emissions to below 1 mg/Nm 3 . However, an acid or chemically active wash downstream of the water wash is necessary to reduce NH 3 emissions to very low levels (<2 mg/Nm 3 ). Combining a dry bed with an acid wash significantly reduces both the required acid solution and the resulting acid waste. The techno-economic analysis indicates that implementing emission mitigation technologies provides substantial environmental benefits for the CESAR1 process, with only a marginal increase (<1 €/tCO 2 ) in both the carbon capture cost (CCC) and CO 2 avoidance cost (CAC). The additional capital cost associated with extra column packing is offset by operational cost savings from reduced solvent losses. For stringent emission permits targeting NH 3 , a configuration combining a dry bed upstream of the water wash followed by an acid wash achieves the best balance between emission control and cost efficiency. This configuration results in a Levelized Cost of Electricity (LCOE) of 143 €/MWh, a CCC of 45.4 €/tCO 2 , and a CAC of 88.4 €/tCO 2 .

AMP↗
DOE OSTI2021

Spectroscopic investigations on structural incorporation pathways of FeIII into zeolite frameworks in cement-relevant environments

Fe{sup III}-containing aluminosilicate zeolites are present in cement-relevant and natural environments. Although Fe{sup III} is known to occur in framework tetrahedral sites where it substitutes isomorphically Al{sup III}O{sub 4} or in extra-framework octahedral sites as free Fe(H{sub 2}O){sub 6}{sup 3+}, the structural incorporation process of Fe{sup III} into different sites is little known. We aim to discern feasible pathways of Fe{sup III} incorporation using hydrothermal synthesis methods and synchrotron-based spectroscopic analyses. Results showed that introducing either Fe{sup 3+} or Fe{sub 2}O{sub 3}·xH{sub 2}O initially during zeolite nucleation did not lead to Fe{sup III} incorporation into the zeolites but only Fe{sub 2}O{sub 3}·xH{sub 2}O prevailed in both cases. However, Fe(NO{sub 3}){sub 3}, FeCl{sub 3}, and Fe{sub 2}O{sub 3}·xH{sub 2}O affected the kind of zeolite formed. A feasible pathway to incorporate tetrahedral Fe{sup III} in the zeolite framework was to introduce firstly Fe{sup III} in the cage of faujasite-Y followed by a phase transformation to chabazite. This study facilitates understanding of Fe{sup III} uptake in zeolites and of Fe{sup III} functional sites that can contribute to immobilization of contaminants.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Local structure and Ca/Si ratio in C-S-H gels from hydration of blends of tricalcium silicate and silica fume

At the microscale, C-S-H gels from alite, or neat Portland cements, has a Ca/Si ratio close to 1.80. At the nanoscale, C-S-H is described by a defective tobermorite structure which allows a maximum Ca/Si ratio close to 1.40. There is no agreement in the location of the extra 0.40 mol of Ca(OH){sub 2} at the nanoscale. Atomistic modelling studies reported Ca(OH){sub 2} species within the tobermorite interlayer space. Other works point toward a fine intermixing of defective tobermorite and nanoportlandite. Here, we have prepared a series of alite blended with silica fume and studied the pastes by several techniques including synchrotron pair distribution function (PDF). In the employed conditions, the C-S-H gel formed by the pozzolanic reaction has nearly the same local structure than the primary C-S-H gel. Furthermore, differential PDF points toward Ca(OH){sub 2} excess having a local structure compatible with few-layer thick nanoparticles stretched along the c-axis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Promoting propane dehydrogenation over PtFe bimetallic catalysts by optimizing the state of Fe species

Optimizing the structure of Pt-based bimetallic catalysts is of utmost importance toward improving the propane dehydrogenation performance. It is challenging to precisely synthesize uniform PtFe alloy nanoparticles without excess unalloyed Fe species on the support as these Fe species lead to low propylene selectivity, coke deposition, and poor stability. Herein, we report an effective strategy to optimize the structure of PtFe bimetallic catalysts with minimal coke and high turnover frequency (8.2 s -1 ). For the optimized catalyst, 1Pt3Fe@S-1, most Fe species is in the framework of the zeolite S-1, which significantly suppresses the formation of coke. In addition, the extra-framework Fe and Pt species encapsulated in the channel of zeolite form uniform PtFe alloy nanoparticles, which significantly improves the C 3 H 6 selectivity, catalytic stability, and recycling performance. In conclusion, these findings provide insights into the structure-performance relationship of PtFe bimetallic catalysts and shall be beneficial to future design and optimization of similar catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Using small building blocks to assemble ultra-complex, multifaceted metal-organic frameworks with zeolitic, mesoporous subnetwork

The assembly of ultra-complex structures from simple building units remains a long-term challenge in chemistry. Using small molecular building blocks (MBBs) in a mixed-ligand approach permitted the assembly of unprecedented metal-organic frameworks (MOFs), M-kum-MOF-1 (M = Y, Tb), exhibiting extra-large mesoporous cavities with small access windows. The ultra-complex cage of M-kum-MOF-1 consists of 240 vertices bridged by 432 edges, leading to a 194 faces-containing tile. This tile exhibits more faces than in any periodic structures (zeolites, MOFs, metal-organic polyhedra [MOPs], etc.) known to date. M-kum-MOF-1 not only possess zeolitic features (anionic framework), but they also contain an underlying wse zeolitic topology, which is observed for the first time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Asymptotically compatible reproducing kernel collocation and meshfree integration for the peridynamic Navier equation

Here, we study reproducing kernel (RK) collocation method for peridynamic Navier equation. In the first part, we apply a linear RK approximation to both displacement and dilatation, and then back-substitute dilatation and solve the peridynamic Navier equation in a pure displacement form. The RK collocation scheme converges to the nonlocal limit for a fixed nonlocal interaction length and also to the local limit as nonlocal interactions vanish. The stability is shown by comparing the collocation scheme with the standard Galerkin scheme using Fourier analysis. In the second part, we apply the RK collocation to the quasi-discrete peridynamic Navier equation and show its convergence to the correct local limit when the ratio between the nonlocal length scale and the discretization parameter is fixed. The analysis is carried out on a special family of rectilinear Cartesian grids for the RK collocation method with a designated kernel with finite support. We assume the Lamé parameters satisfy λ ≥ μ to avoid extra assumptions on the nonlocal kernel. Finally, numerical experiments are conducted to validate the theoretical results.

42 ENGINEERING↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2024

Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction

Traditional low-rank approximation is a powerful tool for compressing large data matrices that arise in simulations of partial differential equations (PDEs), but suffers from high computational cost and requires several passes over the PDE data. The compressed data may also lack interpretability thus making it difficult to identify feature patterns from the original data. Here, to address these issues, we present an online randomized algorithm to compute the interpolative decomposition (ID) of large-scale data matrices in situ. Compared to previous randomized IDs that used the QR decomposition to determine the column basis, we adopt a streaming ridge leverage score-based column subset selection algorithm that dynamically selects proper basis columns from the data and thus avoids an extra pass over the data to compute the coefficient matrix of the ID. In particular, we adopt a single-pass error estimator based on the non-adaptive Hutch++ algorithm to provide real-time error approximation for determining the best coefficients. As a result, our approach only needs a single pass over the original data and thus is suitable for large and high-dimensional matrices stored outside of core memory or generated in PDE simulations. A strategy to improve the accuracy of the reconstructed data gradient, when desired, within the ID framework is also presented. We provide numerical experiments on turbulent channel flow and ignition simulations, and on the NSTX Gas Puff Image dataset, comparing our algorithm with the offline ID algorithm to demonstrate its utility in real-world applications.

Column subset selection↗
DOE OSTI2025

Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem

Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Micropolar deep material network

This study extends the Deep Material Network (DMN), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (Cosserat-type) constitutive behavior. This extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. While traditional, direct numerical simulation micropolar models effectively capture size effects by introducing extra local degrees of freedom, they bring significant computational challenges, particularly for multiscale analyses relevant to engineering applications. The micropolar DMN developed in this paper achieves high accuracy while significantly reducing computation time compared to micropolar direct numerical simulations. This advancement enables multiscale analyses and parameter studies that were previously impractical, such as high-cycle fatigue simulations and comprehensive investigations of internal length scale effects notably in size-dependent plastic response and the optimization of lattice structures. By uniting microstructure-sensitive modeling, physics-driven learning, and scalable surrogate modeling, the micropolar DMN paves the way for accelerated material design, large-scale parametric studies, and the reliable incorporation of size-dependent effects across a wide range of engineering applications, including optimization and next-generation composite design.

36 MATERIALS SCIENCE↗