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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A new method to compute periodic orbits in general symplectic maps

The search of high-order periodic orbits has been typically restricted to problems with symmetries that help to reduce the dimension of the search space. Well-known examples include reversible maps with symmetry lines. The present work proposes a new method to compute high-order periodic orbits in twist maps without the use of symmetries. The method is a combination of the parameterization method in Fourier space and a Newton–Gauss multiple shooting scheme. The parameterization method has been successfully used in the past to compute quasi-periodic invariant circles. However, this is the first time that this method is used in the context of periodic orbits. Numerical examples are presented showing the accuracy and efficiency of the proposed method. Furthermore, the method is also applied to verify the renormalization prediction of the residues’ convergence at criticality (extensively studied in reversible maps) in the relatively unexplored case of maps without symmetries.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Computational diagnostics for flame acceleration and transition to detonation in a hydrogen/air mixture

A new computational diagnostic method for pressure-induced compressibility is proposed by projecting its local contribution to the chemical explosive mode (CEM) in the chemical explosive mode analysis (CEMA) framework. The new method is validated for the study of detonation development during the deflagration-to-detonation transition (DDT) process. The flame characteristics are identified through the quantification of individual CEM contributions of chemical reaction, diffusion, and pressure-induced compressibility. Numerical simulations are performed to investigate the DDT processes in a stoichiometric hydrogen-air mixture. A Godunov algorithm, fifth-order in space, and third-order in time are used to solve the fully compressible Navier-Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model (CDM) described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The new diagnostic method is first applied to onedimensional (1D) canonical flame configurations followed by two-dimensional (2D) simulations of DDT in an obstructed channel where different detonation initiation scenarios are examined using the new CEMA projection formulation. Detailed examinations of the idealized configuration of detonation initiation through shock focusing mechanism at a flame front are also studied using the new formulation. A comparison of the currently proposed CEMA projection and the original formulation by the authors suggests that including the pressure-induced compressibility is essential for the use of CEMA in DDT process. The results also show that the new formulation of CEMA projection can successively capture the detonation initiation through either a gradient mechanism or a direct initiation mechanism, and therefore can be used as an effective local analytical tool for the computational diagnostics of detonation initiation in a DDT process. It was found that detonation development is characterized by a strong contribution of chemistry role to the CEM which is pivotal to the initiation of detonation. The role of compressibility is found enhanced at the edge of the detonation front where diffusion was found to have minimal effects on detonation development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Reviewing computational studies of defect formation and behaviors in carbon fiber structural units

Solid-state carbon materials, such as graphite and graphene, are at the forefront of materials research because of their unique electronic, vibrational, and mechanical properties, leading to a broad range of potential and realized applications. One key application is their role as basic structural units of carbon fiber (CF), a lightweight alternative to steel. In CF, a delicate relationship exists between ultimate material strength and the atomic-scale density of defects contained at the inter- and intra-subunit levels. Computational studies provide insight into the stability of various types of defects that can form in these systems and connect with experimental observables such as bandgap and spectroscopic measurements. Therefore, the literature contains many computational studies that focus on changes induced by defects, including vacancies and Dienes transformations (Stone-Wales and Thrower defects). However, wide-ranging methods and cell sizes have been used, and property-specific information is often lacking. Furthermore, this review summarizes key literature findings, paying particular attention to changes in the electronic, vibrational, and mechanical properties induced by defects in graphitic materials relevant to CF.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computationally efficient optimization models for preliminary distillation column design and separation energy targeting

We propose versatile shortcut distillation column and separation energy targeting models that are well-suited for superstructure-based process synthesis. The models are based on a novel reformulation of the Underwood equations to address systems where the components that are present in the feed can vary due to zero flow rates of some components. Also, we propose valid constraints, resulting in a significant enhancement of the computational performance of the models. Furthermore, the proposed distillation column model can automatically identify adequate key components and the energy requirement of a desired separation task, while considering a wide range of types of separations including non-sharp/sloppy splits. Also, the proposed separation energy targeting model can be used to estimate an energy requirement target for the separation of a mixture without finding detail network configurations. Due to their versatility and computational efficiency, the proposed models can be readily used for and expand the scope of superstructure-based process synthesis approaches.

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

Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?

Human population growth and accelerated climate change necessitate agricultural improvements using designer crop ideotypes (idealized plants that can grow in niche environments). Diverse and highly skilled research groups must integrate efforts to bridge the gaps needed to achieve international goals toward sustainable agriculture. Given the scale of global agricultural needs and the breadth of multiple types of omics data needed to optimize these efforts, explainable artificial intelligence (AI with a decipherable decision making process that provides a meaningful explanation to humans) and exascale computing (computers that can perform 1018 floating-point operations per second, or exaflops) are crucial. Accurate phenotyping and daily-resolution climatype associations are equally important for refining ideotype production to specific environments at various levels of granularity. In this article, we review advances toward tackling technological hurdles to solve multiple United Nations Sustainable Development Goals and discuss a vision to overcome gaps between research and policy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A computational investigation of high-flux, plate-and-frame membrane modules for industrial carbon capture

In this work, we study the application of membrane-based separation systems for carbon capture, considering plate-and-frame membrane modules. The successful deployment of membrane CO 2 capture system relies on high-performing membranes as well as effective membrane modules that can fully exploit the developed membranes. A plate-and-frame membrane module is especially attractive for CO 2 capture from industrial flue gas due to its lower pressure drop compared to its counterparts such as spiral wound modules and hollow fiber modules. To design better plate-and-frame modules, we investigate their basic unit - a single membrane stack through a combination of computational modeling and experimental investigations. The modeling approach is based on Computational Fluid Dynamics (CFD) to represent a multiphysics problem, including the fluid flow and diffusion processes within a membrane module. We use experimental data collected under different operating conditions to validate the CFD model. Numerical results suggest a good agreement between experiments and model outputs for the CO 2 recovery, CO 2 mole fraction in the retentate and permeate, and stage-cut. The CFD model is able to predict accurately the flow behavior, providing valuable insights on the effects of fluid dynamics on mass transfer of CO 2 . We also carry out a sensitivity analysis to identify the effect of key parameters on the CO 2 recovery and the CO 2 purity of the outlet streams.

CFD simulation↗
DOE OSTI2021

Computation-guided discovery of coating materials to stabilize the interface between lithium garnet solid electrolyte and high-energy cathodes for all-solid-state lithium batteries

All-solid-state batteries with a lithium metal anode, enabled by lithium garnet solid electrolytes such as Li 7 La 3 Zr 2 O 12 (LLZO), are a promising next-generation energy-storage technology. The further development of all-solid-state battery requires the integration of high-energy cathodes such as LiNi 1-x-y Mn x Co y O 2 (NMC) with the garnet solid electrolyte with stable and low-resistance interfaces, which requires a coating layer to stabilize the interface during high-temperature sintering and electrochemical cycling. In order to guide the future development of interfacial coatings, we perform high-throughput thermodynamic analyses based on first-principles computation to investigate the stability of LLZO garnet and high-energy NMC cathodes with a wide range of materials chemistries. Here our study reveals the factors governing the materials stability with LLZO garnet and NMC cathodes, and identifies the mechanisms of good coating layers stable with LLZO and NMC. In addition to classifying known coating layers, our study provides detailed guiding charts and multiple new materials systems as promising coatings for stabilizing LLZO—NMC interfaces to enable high-energy-density garnet-based all-solid-state batteries. Our demonstrated computation scheme and high-throughput analyses are generally applicable to investigate and screen coating materials for stabilizing interfaces in energy-related applications.

25 ENERGY STORAGE↗
DOE OSTI2023

A computational parametric study of ducted fuel injection implementation in a heavy-duty diesel engine

Experiments have shown that ducted fuel injection (DFI) effectively reduces soot emissions from direct-injection diesel engines. Although many computational studies have evaluated DFI’s spray development and soot reduction mechanisms in constant volume chambers, only limited computational work on internal combustion engines exists. The DFI duct assembly changes the engine’s in-cylinder flow, spray, and combustion development. Therefore, current production engine designs might not be optimal for achieving the best engine performance with DFI. Here, this work conducted an extensive numerical study to evaluate how parameter changes affect DFI performance. The parameters include swirl ratio, piston geometry, compression ratio (CR), number of injector orifices, split injection strategy, and exhaust gas recirculation (EGR) in a heavy-duty diesel engine utilizing DFI. The combustion and soot emission data from the Sandia compression ignition optical research engine were used for model validation. Simulations showed that an increased swirl ratio resulted in more intense jet flame-piston interaction, slowing down the combustion heat release during the late combustion stage and leading to lower indicated thermal efficiency (ITE) due to higher exhaust losses. A piston-bowl design with a reentrant inner piston edge yielded the highest thermal efficiency, due to the reduced cylinder head heat transfer loss. Additional injector orifices led to higher efficiency owing to a more advanced combustion phasing. Nevertheless, the maximum pressure rise rate (MPRR) and oxides of nitrogen (NO x ) emissions also increased with the number of injector orifices due to more rapid heat release and higher combustion temperature. Implementation of a split injection strategy combined with a higher EGR rate effectively inhibited the excessive MPRR and NO x formation. In general, the study concluded that DFI is not sensitive to most parameter changes but will benefit from future parameter optimization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Zeolite-templated carbons as effective sorbents to remove methylsiloxanes and derivatives: A computational screening

Though widely used in our daily lives, volatile methylsiloxanes and derivatives are emerging contaminants and becoming a high-priority environment and public health concern. Developing effective sorbent materials can remove siloxanes in a cost-effective manner. Herein, by means of Grand Canonical Monte Carlo (GCMC) simulations, we evaluated the potentials of the recently proposed 68 stable zeolite-templated carbons (ZTCs) for the removal of four linear methylsiloxanes and derivatives as well as two cyclic methylsiloxanes by the calculated average loading and average adsorption energy values. Four ZTCs, namely ISV, FAU1, FAU3, and H8326836, were identified with the top 50% adsorption performance toward all the six targeted contaminants, which outperform activated carbons. Further first principles computations revealed that steric hindrance, electrostatic interactions (further enhanced by charge transfer), and CH-π interactions account for the outstanding adsorption performance of these ZTCs. This work provides a quick procedure to computationally screen promising ZTCs for siloxane removal, and help guide future experimental and theoretical investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation

Here, the impact of hydrogen charge states on the stability and transport characteristics of hydrogen interstitials in alumina polymorphs is evaluated by multiscale computational methods including density functional theory (DFT), ab initio molecular dynamics (AIMD) and machine learned force fields. Thermodynamic calculations show that the protonic H i +1 interstitial is the most stable defect species for most values of the electronic bandgap in both and amorphous alumina (Al 2 O 3 ). Further, active learned Gaussian approximation potentials (GAP) were developed using AIMD data to study temperature dependent long time proton diffusion in alumina. Diffusivity calculations from GAP-MD simulations are found to be comparable with of the AIMD data, while being ~340 times faster and scalable to larger systems. Comparisons with diffusivity values for other interstitial charge states (H i 0 and H i -1 ) and published experimental literature indicate that H i +1 diffusion is the likely mechanism of hydrogen transport. A good agreement is obtained between H i +1 diffusivity calculated in α-Al 2 O 3 from DFT: 5.05 10 -3 exp(-0.81 eV/k B /T) cm 2 /s and reported experiment: 9.7X10 -4 exp(-0.83 eV/k B /T) cm 2 /s. Computationally and experimentally calculated energy barriers (0.81 and 0.83 eV respectively) only differ by 2.5%. Similarly, the pre-exponential diffusion coefficients only differ by 0.5 orders of magnitude. Moreover, the diffusivity of H i +1 in amorphous Al 2 O 3 in the 1000–2000 K range is calculated to be 2.53X10 -2 exp(-0.89 eV/k B /T), just one order of magnitude higher than the corresponding value in α-Al 2 O 3 . This suggests that local structural disorder does not significantly affect the energy landscape and diffusion behavior of H i +1 in Al 2 O 3 . Overall, these results show promise for the application of alumina polymorphs as hydrogen permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Regular sensitivity computation avoiding chaotic effects in particle-in-cell plasma methods

Particle-in-cell (PIC) simulation methods are attractive for representing species distribution functions in plasmas. However, as a model, they introduce uncertain parameters, and for quantifying their prediction uncertainty it is useful to be able to assess the sensitivity of a quantity-of-interest (QoI) to these parameters. Such sensitivity information is likewise useful for optimization. However, computing sensitivity for PIC methods is challenging due to the chaotic particle dynamics, and sensitivity techniques remain underdeveloped compared to those for Eulerian discretizations. This challenge is examined from a dual particle–continuum perspective that motivates a new sensitivity discretization. Two routes to sensitivity computation are presented and compared: a direct fully-Lagrangian particle-exact approach provides sensitivities of each particle trajectory, and a new particle-pdf discretization, which is formulated from a continuum perspective but discretized by particles to take the advantages of the same type of Lagrangian particle description leveraged by PIC methods. Since the sensitivity particles in this approach are only indirectly linked to the plasma-PIC particles, they can be positioned and weighted independently for efficiency and accuracy. The corresponding numerical algorithms are presented here in mathematical detail. The advantage of the particle-pdf approach in avoiding the spurious chaotic sensitivity of the particle-exact approach is demonstrated for Debye shielding and sheath configurations. In essence, the continuum perspective makes implicit the distinctness of the particles, which circumvents the Lyapunov instability of the N -body PIC system. The cost of the particle-pdf approach is comparable to the baseline PIC simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Accelerating eigenvalue computation for nuclear structure calculations via perturbative corrections

Subspace projection methods utilizing perturbative corrections have been proposed for computing the lowest few eigenvalues and corresponding eigenvectors of large Hamiltonian matrices. In this paper, we build upon these methods and introduce the term Subspace Projection with Perturbative Corrections (SPPC) method to refer to this approach. We tailor the SPPC for nuclear many-body Hamiltonians represented in a truncated configuration interaction subspace, i.e., the no-core shell model (NCSM). We use the hierarchical structure of the NCSM Hamiltonian to partition the Hamiltonian as the sum of two matrices. The first matrix corresponds to the Hamiltonian represented in a small configuration space, whereas the second is viewed as the perturbation to the first matrix. Eigenvalues and eigenvectors of the first matrix can be computed efficiently. Because of the split, perturbative corrections to the eigenvectors of the first matrix can be obtained efficiently from the solutions of a sequence of linear systems of equations defined in the small configuration space. These correction vectors can be combined with the approximate eigenvectors of the first matrix to construct a subspace from which more accurate approximations of the desired eigenpairs can be obtained. We show by numerical examples that the SPPC method can be more efficient than conventional iterative methods for solving large-scale eigenvalue problems such as the Lanczos, block Lanczos and the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The method can also be combined with other methods to avoid convergence stagnation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as Monte Carlo weighting. In this work we present a staged approach to the generation of expected distributions of observables in order to overcome these challenges. By combining multiple integration and smoothing techniques which address limited statistics from simulation it arrives at reliable analysis results using modest computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays

Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Experimental and computational investigation of the influence of iso -butanol on autoignition of n -decane and n -heptane in non-premixed flows

Experimental and computational investigation is carried out to elucidate the influence of iso-butanol on critical conditions of autoignition of n-decane and n-heptane. The counterflow configuration is employed. In this configuration an axisymmetric stream of air is directed over the surface of an evaporating pool of a liquid fuel. A stagnation plane is established. The temperature of the air is increased until autoignition is achieved in the mixing layer in the vicinity of the stagnation plane. The temperature of the air stream at autoignition, T ig , is measured at various values of the strain rate, which is defined as the axial gradient of the axial component of the flow velocity at the stagnation plane. Fuels tested are n-decane, n-heptane, iso-butanol and various mixtures of n-decane/iso-butanol and n-heptane/iso-butanol. Kinetic modeling is carried out using the recently updated version of the comprehensive CRECK chemical-kinetic mechanism. Critical conditions of autoignition are predicted for all fuels and fuel mixtures and the results are compared with the measurements. Computations show that low-temperature chemistry plays a significant role in promoting autoignition of n-decane and n-heptane, and the influence of low-temperature chemistry decreases with increasing strain rates because there is insufficient residence for the low-temperature reactions to take place. Experimental data and numerical simulations show that addition of even small amounts of iso-butanol to n-decane or n-heptane increases the value of T ig at low strain rates indicating that iso-butanol strongly inhibits the low-temperature chemistry of n-decane and n-heptane. Furthermore, the simulations show that when iso-butanol is present in the liquid fuel, only a small amount of n-decane is available in the gas phase and its low concentration cannot effectively sustain the low temperature degenerate branching oxidation process. Here, predicted flame structures show that the peak values of mole fraction of ketohydroperoxide are significantly reduced when iso-butanol is added to n-decane indicating that the kinetic pathway to low temperature ignition is blocked. This observation is confirmed from sensitivity analysis.

42 ENGINEERING↗
DOE OSTI2020

Insights into grain boundary energy structure-property relationships by examining computed [100] disorientation axis grain boundaries in Nickel

A study of 346 computed [100] disorientation axis grain boundaries provides insight into grain boundary energy structure-property relationships. The grain boundaries come from 6 coincidence site lattice misorientations at regularly spaced disorientation angles, and cover the full range of boundary plane orientations. The computed energy has clear trends in disorientation angle and boundary plane orientation. Here, the data are used to reexamine the 'special' attribute frequently applied to low Σ coincidence site lattice misorientations and low-angle boundaries and to assess the accuracy of a face-centered cubic grain boundary energy function.

36 MATERIALS SCIENCE↗