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Results for “multi-component expansion”

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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8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A General Framework for Progressive Data Compression and Retrieval

In scientific simulations, observations, and experiments, the transfer of data to and from disk and across networks has become a major bottleneck for data analysis and visualization. Compression techniques have been employed to tackle this challenge, but traditional lossy methods often demand conservative error tolerances to meet the numerical accuracy requirements of both anticipated and unknown data analysis tasks. Progressive data compression and retrieval has emerged as a promising solution, where each analysis task dictates its own accuracy needs. However, few analysis algorithms inherently support progressive data processing, and adapting compression techniques, file formats, client/server frameworks, and APIs to support progressivity can be challenging. Here, this paper presents a framework that enables progressive-precision data queries for any data compressor or numerical representation. Our strategy hinges on a multi-component representation that successively reduces the error between the original and compressed field, allowing each field in the progressive sequence to be expressed as a partial sum of components. We have implemented this approach with four established scientific data compressors and assessed its effectiveness using real-world data sets from the SDRBench collection. The results show that our framework competes in accuracy with the standalone compressors it is based upon. Additionally, (de)compression time is proportional to the number of components requested by the user. Finally, our framework allows for fully lossless compression using lossy compressors when a sufficient number of components are employed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A generalized and adaptable tensor-contraction-based cluster expansion formalism for multicomponent solids

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has served as the standard workaround to improve computational efficiency. However, the standard CE technique is difficult to extend to exotic and/or low-symmetry lattices, often implemented via iteration over particular cluster types, which must be enumerated per lattice structure. In this work, we introduce the tensor cluster expansion (TCE), implemented in the open-source code tce-lib, which maps correlation functions to mixed tensor contractions, eliminating the need to iterate over cluster types and additionally making the calculation of correlation functions well-suited for massively parallel architectures like GPUs. We show that local interaction energies are an immediate consequence of the TCE formalism, yielding nearly $\mathcal{O}$(1) energy difference calculations. We then use this formalism to fit CE models for the TaW and CoNiCrFeMn systems, and use these models to respectively compute the enthalpy of mixing curve and Cowley short-range order parameters, showing excellent agreement with ground truth data.

Cluster expansion↗
DOE OSTI2025

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Hubble Space Telescope Observations of Oxygen-rich Supernova Remnants in the Magellanic Clouds. III. WFPC2 Imaging of the Young, Crab-like Supernova Remnant SNRO540-69.3

Hubble Space Telescope images with the Wide Field Planetary Camera 2 of the young, oxygen-rich, Crab-like supernova remnant SNR0540-69.3 in the Large Magellanic Cloud (LMC) reveal details of the emission distribution and the relationship between the expanding ejecta and synchrotron nebula. The emission distributions appear very similar to those seen in the Crab nebula, with the ejecta located in a thin envelope surrounding the synchrotron nebula. The [O III] emission is more extended than other tracers, forming a faint "skin" around the denser filaments and synchrotron nebula, as also observed in the Crab. The [O III] exhibits somewhat different kinematic structure in long-slit spectra, including a more extended high-velocity emission halo not seen in images. Yet even the fastest expansion speeds in SNR 0540 s halo are slow when compared to most other young supernova remnants, though the Crab nebula has similar slow expansion speeds. We show a striking correspondence between the morphology of the synchrotron nebula observed in an optical continuum filter with that recently resolved in Chandra X-ray images. We argue that the multi-component kinematics and filamentary morphology of the optical emission-line features likely result from magnetic Rayleigh-Taylor instabilities that form as the synchrotron nebula expands and sweeps up ejecta, as seen in the Crab nebula. Our images and spectra help to refine our understanding of SNR 0540 in several more detailed respects: they confirm the identification of H(alpha)+[N II] in the red spectrum, they show that the systemic velocity of SNR 0540 is not significantly different from that of the LMC, and they hint at a lower Ne abundance than the Crab (potentially indicating a more massive progenitor star).

Morse, Jon A.↗
NASA NTRS2004

Containerless Measurement of Thermophysical Properties of Ti-Zr-Ni Alloys

The surface tension, viscosity, density, and thermal expansion of Ti-Zr-Ni alloys were measured for a number of compositions by electrostatic levitation methods. Containerless methods greatly reduce heterogeneous nucleation, increasing access to the undercooled liquid regime at finite cooling rates. The density and thermal expansion are measured optically, while the surface tension and viscosity are measured by the oscillating drop method. The measured alloys include compositions which form a metastable quasicrystal phase from the undercooled liquid, and alloys close to the composition of several multi-component bulk metallic glass-forming alloys. Measurements of surface tension show behavior typical of transition metals at high temperature, but a sudden decrease in the deeply undercooled liquid for alloys near the quasicrystal-forming composition range, but not for compositions which form the solid-solution phase first.

Hyers, Robert↗
DOE OSTI2023

Accurate calculation of many-body energies in water clusters using a classical geometry-dependent induction model

We incorporate geometry-dependent distributed multipole and polarizability surfaces into an induction model that is used to describe the 3- and 4-body terms of the interaction between water molecules. The expansion is carried out up to hexadecapole with the multipoles distributed on the atom sites. Dipole-dipole, dipole-quadrupole, and quadrupole-quadrupole distributed polarizabilities are used to represent the response of the multipoles to an electric field. We compare the model against two large databases consisting of 43,844 3-body terms and 3,603 4-body terms obtained from high level ab initio calculations previously used to fit the MB-pol and q-AQUA interaction potentials. The classical induction model with no adjustable parameters reproduces the ab-initio 3- and 4-body terms contained in these teo Databases with a Root-Mean-Square-Error (RMSE) of 0.104/0.058 and a Mean-Absolute-Error (MAE) of 0.054/0.026 kcal/mol, respectively, results that are on a par with those obtained 1 by fitting the same data using tens of thousands of Permutationally Invariant Polynomials (PIPs). This demonstrates the accuracy of this physically motivated model in describing the 3- and 4-body terms in the interactions between water molecules with no adjustable parameters. The triple-dipole-dispersion energy was included in the 3-body energy and was found to be small but not quite negligible. The model represents a practical, efficient and transferable approach for obtaining accurate non-additive interactions for multi-component systems without the need of performing tens of thousands of high level electronic structure calculations and fitting them with tens of thousands of PIPs.

molecular analysis water, aqueous↗
NASA NTRS1981

Component mode synthesis of large rotor systems

A scheme is presented for calculating the vibrations of large multi-component flexible rotor systems based on the component mode synthesis method. It is shown that, by a modal expansion of the elastic interconnecting elements, the system modal equation can be conveniently constructed from the undamped eigen representations of the component subsystems. The capability of the component mode method is demonstrated in two examples: a transient simulation of a two-spool gas turbine engine equipped with a squeeze-film damper; and an unbalance response analysis of the Space Shuttle Main Engine oxygen turbopump in which the dynamics of the rotor and the housing are both considered.

Li, D. F.↗