Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Fidelity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multi-fidelity Uncertainty Quantification for Homogenization Problems in Structure-Property Relationships from Crystal Plasticity Finite Elements

Crystal plasticity finite element method (CPFEM) has been an integrated computational materials engineering (ICME) workhorse to study materials behaviors and structure-property relationships for the last few decades. These relations are mappings from the microstructure space to the materials properties space. Due to the stochastic and random nature of microstructures, there is always some uncertainty associated with materials properties, for example, in homogenized stress-strain curves. For critical applications with strong reliability needs, it is often desirable to quantify the microstructure-induced uncertainty in the context of structure-property relationships. However, this uncertainty quantification (UQ) problem often incurs a large computational cost because many statistically equivalent representative volume elements (SERVEs) are needed. In this article, we apply a multi-level Monte Carlo (MLMC) method to CPFEM to study the uncertainty in stress-strain curves, given an ensemble of SERVEs at multiple mesh resolutions. By using the information at coarse meshes, we show that it is possible to approximate the response at fine meshes with a much reduced computational cost. We focus on problems where the model output is multi-dimensional, which requires us to track multiple quantities of interest (QoIs) at the same time. In conclusion, our numerical results show that MLMC can accelerate UQ tasks around 2.23x, compared to the classical Monte Carlo (MC) method, which is widely known as ensemble average in the CPFEM literature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toward efficient elastocaloric systems: Predicting material thermal properties with high fidelity

A critical need to accurately model thermal behaviors of materials that exhibit strong elastocaloric effects, including predicting the effects themselves at varying stresses and temperatures, has been addressed using a simple and versatile physics-based approach. The key factor leading to the high precision is approximating the underlying elastic phase transition as a smooth modification of lattice entropy between coexisting phases. Once the phase transformation entropy is modeled to match experimentally measured strain as a function of temperature and applied stress, estimating the heat capacity, entropy, and isothermal entropy and adiabatic temperature changes in temperature-stress coordinates becomes straightforward. This approach provides insight into how thermal properties of elastocaloric materials vary through the transition based on strain measurements that are simple to perform and interpret. In addition to aiding in the rapid evaluation of new and existing elastocaloric materials, this advance is expected to prove invaluable for accurate heat transfer modeling aimed at designing efficient regenerative elastocaloric cooling devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven learning of nonlocal physics from high-fidelity synthetic data

A key challenge to nonlocal models is the analytical complexity of deriving them from first principles, and frequently their use is justified a posteriori. Here, we extract nonlocal models from data, circumventing these challenges and providing data-driven justification for the resulting model form. Extracting data-driven surrogates is a major challenge for machine learning (ML) approaches, due to nonlinearities and lack of convexity — it is particularly challenging to extract surrogates which are provably well-posed and numerically stable. Our scheme not only yields a convex optimization problem, but also allows extraction of nonlocal models whose kernels may be partially negative while maintaining well-posedness even in small-data regimes. To achieve this, based on established nonlocal theory, we embed in our algorithm sufficient conditions on the non-positive part of the kernel that guarantee well-posedness of the learnt operator. These conditions are imposed as inequality constraints to meet the requisite conditions of the nonlocal theory. We demonstrate this workflow for a range of applications, including reproduction of manufactured nonlocal kernels; numerical homogenization of Darcy flow associated with a heterogeneous periodic microstructure; nonlocal approximation to high-order local transport phenomena; and approximation of globally supported fractional diffusion operators by truncated kernels.

42 ENGINEERING↗
DOE OSTI2021

High-Fidelity Simulations of Gravity Currents Using a High-Order Finite-Difference Spectral Vanishing Viscosity Approach

This numerical work investigates the potential of a high-order finite-difference spectral vanishing viscosity approach to simulate gravity currents at high Reynolds numbers. The method introduces targeted numerical dissipation at small scales through altering the discretisation of the second derivatives of the viscous terms in the incompressible Navier-Stokes equations to mimic the spectral vanishing viscosity (SVV) operator, originally designed for the regularisation of spectral element method (SEM) solutions of pure advection problems. Using a sixth-order accurate finite-difference scheme, the adoption of the SVV method is straightforward and comes with a negligible additional computational cost. In order to assess the ability of this high-order finite-difference spectral vanishing viscosity approach, we performed large-eddy simulations (LES) of a gravity current in a channelised lock-exchange set-up with our SVV model and with the well-known explicit static and dynamic Smagorinsky sub-grid scale (SGS) models. The obtained data are compared with a direct numerical simulation (DNS) based on more than 800 million mesh nodes, and with experimental measurements. A framework for the energy budget is introduced to investigate the behaviour of the gravity current. First, it is found that the DNS is in good agreement with the experimental data for the evolution of the front location and velocity field as well as for the stirring and mixing inside the gravity current. Secondly, the LES performed with less than 0.4% of the total number of mesh nodes compared to the DNS, can reproduce the main features of the gravity currents, with the SVV model yielding slightly more accurate results. It is also found that the dynamic Smagorinsky model performs better than its static version. For the present study, the static and dynamic Smagorinsky models are 1.8 and 2.5 times more expensive than the SVV model, because the latter does not require the calculation of explicit SGS terms in the Navier-Stokes equations nor spatial filtering operations.

direct numerical simulation↗
DOE OSTI2025

Parallel diffusion operator for magnetized plasmas with improved spectral fidelity

Diffusive transport processes in magnetized plasmas are highly anisotropic, with fast parallel transport along the magnetic field lines sometimes faster than perpendicular transport by orders of magnitude. This constitutes a major challenge for describing non-grid-aligned magnetic structures in Eulerian (grid-based) simulations. Here, the present paper describes and validates a new method for parallel diffusion in magnetized plasmas based on the anti-symmetry representation [Halpern and Waltz, Phys. Plasmas 25, 060703 (2018)]. In the anti-symmetry formalism, diffusion manifests as a flow operator involving the logarithmic derivative of the transported quantity. Qualitative plane wave analysis shows that the new operator naturally yields better discrete spectral resolution compared to its conventional counterpart. Numerical simulations comparing the new method against existing finite difference methods are carried out, showing significant improvement. In particular, we find that combining anti-symmetry with finite differences in diagonally staggered grids essentially eliminates the so-called “artificial numerical diffusion” that affects conventional finite difference and finite volume methods.

Anisotropic diffusion↗
DOE OSTI2021

Active learning strategy for high fidelity short-term data-driven building energy forecasting

The quality of a data-driven model is heavily dependent on the quality of data. Data from building operation often have data bias problems, which means that the data sample is collected in a way that some members of the intended data population are less likely to be included than others. Data-driven energy forecasting models built on such data hence are biased and could lead to large forecasting errors. Active learning—an effective method to defying data bias—is rarely studied or applied in the area of data-driven building energy forecasting modeling. This paper attempts to fill this gap and explores the application of active learning in data-driven building energy forecasting. The developed strategy in this paper efficiently generate informative training data within a time budget and uses block design to passively consider weather disturbances. The developed active learning strategy is applied and evaluated in both virtual and real-building testbeds against traditional data-driven methods. Via these virtual and real-building evaluation cases, we have demonstrated that the data bias problem typically exists in building operation data is resolved by applying the developed active learning strategy. Furthermore, building energy forecasting models trained from data generated from the active learning strategy have shown improved performances in both model accuracy and model extendibility perspectives. The effectiveness of the block design module is also validated to effectively consider the impact of weather conditions on active learning design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Insights into the failure mode of the Chelyabinsk meteor from high-fidelity simulation

In 2013, an asteroid with a diameter of approximate 20 m broke up in the atmosphere above the Russian city of Chelyabinsk producing what is known as an airburst event. The event was recorded on video from multiple angles and a 500-kg fragment was recovered from Lake Chebarkul shortly thereafter. These aspects, coupled with the asteroid’s large size, distinguish the Chelyabinsk event as unique. In this study, we use the smoothed particle hydrodynamics method to examine the breakup mode of a Chelyabinsk-sized monolithic asteroid and probe whether a monolithic structure is consistent with observations from the Chelyabinsk event. We model the object as a homogeneous sphere with properties consistent with Chelyabinsk meteorites. We use planar-2D simulations to test the sensitivity of results to variations in the material model and to qualitatively inspect the cause of crack nucleation and fragmentation. We then compare results from a 3D simulation to observations from the event. Our 3D simulation predicts a burst height within 3 km of the observed peak luminosity suggesting the responsible asteroid may have been monolithic.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparative investigations of multi-fidelity modeling on performance of electrostatically-actuated cracked micro-beams

Silicon is a commonly used material for the fabrication of beams for use in micro-electrical-mechanical systems (MEMS). Although silicon is a brittle material, it has been shown to accumulate fatigue damage at the micro-scale. Understanding the effect this has on the overall device performance is critical to the design of reliable devices. Analytical methods for modeling damage provide expedient results but are limited by broad modeling assumptions. Numerical models account for more detailed physical phenomena but can be computationally intensive. In this work, two different crack scenarios are modeled using both analytical techniques and 3D computational simulations. First, the effects of a single surface crack on the static deflection and natural frequency of an electrostatically actuated micro-beam are formulated and compared. Then, a new method for approximating damage associated with realistic distributed crack networks is formulated for use in an analytical model and numerical simulations. A method for utilizing experimentally derived crack statistics to inform the analytical and numerical distributed crack models is developed. Good agreement between the analytical and numerical models is obtained for both crack scenarios. Altogether, these models can be used to effectively simulate a variety of damage and fatigue behaviors in silicon-based MEMS devices.

42 ENGINEERING↗
DOE OSTI2022

Experimentally validated high-fidelity simulations of a liquid jet in supersonic crossflow

Here, utilizing recent advancements in computational schemes for compressible, multiphase flows, this work features a parametric study of a pure liquid jet in supersonic crossflow that involves simulating the atomization process for four values of momentum-flux ratio. These simulations are validated against experimental results measured with high-speed X-ray imaging, which confirm the accuracy of the numerical approach. Also, the effect of numerical resolution on some flow behavior is investigated, revealing convergence of the jet shape and surface instability wavelength. Analysis of the resulting sprays includes statistical descriptions of the liquid distribution, liquid structures created through breakup, interfacial instabilities, and dominant flow features. As the flowrate increases, the spray penetrates further, it becomes more disperse, and less liquid impacts the wall, but the droplet size distribution changes little. The wavelength of instabilities on the windward side of the jet diverges from measured trends in subsonic crossflows. In a visualization of the time-averaged flow, counter-rotating vortices are observed along the jet core and in the wake, affecting the process of primary atomization and early droplet trajectories.

42 ENGINEERING↗