SEARCH · Engineering Papers

Results for “numerical errors”

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.

SourceResearch connectionFrom yearThrough year

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

At least 721 records · Page 40

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Computational screening of fly ash zeolite sorbents for boric acid removal

In the United States, many impoundments at coal-fired power plants contain elevated contaminants like arsenic, boron, barium, and selenium. Zeolites synthesized from fly ash show promise as sorbents for these contaminants. However, optimizing sorption capacity is challenging due to numerous possible topologies, silicon to aluminum (Si/Al) ratios, and cation types. In this study, molecular simulations are used to design cationic zeolites for boric acid adsorption. Force field models based on quantum mechanical calculations (PBE + D2) for Na-, Ca-, Mn-, and Fe-exchanged chabazite and LTA are presented. The new D2FF force fields reproduce DFT energies with about half the error of UFF. Zeolite performance depends on Si/Al ratio and cation type, with low Si/Al ratio chabazite (CHA) and phillipsite (PHI) zeolite frameworks exchanged with Ca 2+ or Na + /Ca 2+ mixtures showing the highest adsorption. In conclusion, these findings suggest tailored fly ash-derived zeolites could provide effective boron removal from leachate ponds.

CCR impoundment↗

DOE OSTI2025

Enhanced shear stabilization of turbulence in NSTX

In studying a particular non-stationary NSTX L-mode plasma, we observed unexpectedly high levels of flux—first with quasilinear (TGLF) modeling and subsequently with nonlinear gyrokinetic simulations. Upon more detailed analysis, a novel confinement regime was discovered in which a modest increase in E x B shear (beyond baseline experimental estimates) rapidly reduced turbulent transport to levels consistent with power balance. This modest increase is plausible given the errors inherent to the estimation of shearing rates, and the added complexity of the non-stationary (time-dependent) power balance. Remarkably, an additional small increase in shear yields the familiar ion-neoclassical transport level with what appears to be the onset of high-k electron transport only. Although analyses using the TGLF-SAT2 model successfully capture numerous parametric dependencies of this plasma, TGLF does not reproduce the rapid E x B stabilization seen in CGYRO. We believe the results presented should help to better characterize the nonlinear physics of spherical tokamak confinement regimes, provide useful ST datasets for reduced model development, and motivate more accurate experimental diagnosis of E x B shearing rates.

Atomic and molecular collisions↗

DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation

This paper proposes a hybrid data and model-based anomaly detection scheme to secure the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders are set up at the edge device level and they use local DER operational data as inputs. The abnormal statuses are detected by analyzing reconstruction errors. In parallel, modelbased state estimation (SE) is set up at the central level and it uses system-wide models and measurements as data inputs. The anomalies are identified by analyzing measurement residuals. The hybrid scheme preserves the benefits of both data-driven and model-based analyses and thus improves the robustness and the accuracy of anomaly detection. Numerical tests based on the model of a real distribution feeder in Southern California highlight the proposed scheme's effectiveness and benefits.

anomaly detection↗

DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗

DOE OSTI2023

SKS Polarization Anomalies Due to the Coriolis Force

The Earth’s Coriolis force has been well–known to impact surface waves and normal modes, which is essential to accurately interpret these waves. However, the Coriolis force on body waves has been assumed to be negligible and mostly ignored. It has been previously shown that the Coriolis force impacts polarizations of shear waves, whereas the wavefronts remain unaffected. We expand on the potential influences of Earth’s Coriolis force on shear–wave polarization measurements by conducting 3D numerical simulations for elastic waves generated by earthquake and explosive sources in a radially symmetric, and 3D mantle and crustal models. The Coriolis force can produce polarization anomalies of mantle shear waves up to 7° and core phases, such as SKS and SKKS, up to 4°. Uncorrected shear–wave polarizations due to the Coriolis force can cause an additional source of error (5°–10° in fast direction, and 0.2–0.3 s delay time depending on the method and seismic phase), inaccurate interpretation of station misalignments, and imprecise estimates of the core–mantle boundary topography. We show how to correct for the Coriolis force on teleseismic shear waves using 1D ray tracing for well–isolated phases. Here, we recommend the use of full waveform simulations to accurately account for earthquake sources parameters, poorly isolated phases that could include interfering phase arrivals within the measurement time window, and the effect of the Coriolis force on the polarizations of shear waves.

58 GEOSCIENCES↗

DOE OSTI2020

Benchmarking Adaptive Variational Quantum Eigensolvers

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is indirectly assessed by the value of the associated energy. Novel adaptive derivative-assembled pseudo-trotter (ADAPT) ansatz approaches and recent formal advances now establish a clear connection between the theory of quantum chemistry and the quantum state ansatz used to solve the electronic structure problem. Here we benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves for a few selected diatomic molecules, namely H 2 , NaH, and KH. Using numerical simulation, we find both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods. Another relevant finding is that gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers. The results also identify small errors in the prepared state fidelity which show an increasing trend with molecular size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The Effect of Spectral Resolution of Light Sources on Photopic and a-opic Quantities

There is a growing interest in including light source spectrum in advanced lighting software tools and simulations. Given that traditional lighting software tools have been used primarily for calculating photometric quantities, their simplifying assumptions may not be suitable for calculating other a-opic quantities. Commonly used simulation tools use three values to represent the three primary colors (red, green, and blue), but others have expanded the number of bands (i.e., the spectral resolution) to 9, 27, or 81 in an attempt to more accurately represent variations in light source spectrum and downstream spectrally-derived quantities. It remains unclear, however, to what extent spectral resolution affects calculated quantities. To address this gap, a numerical analysis was completed using a large spectral power distribution database (n = 1,302 light sources). Calculated illuminance, a-opic irradiance, luminous efficacy of radiation (LER), melanopic efficacy of radiation (MER), and melanopic to photopic (M/P) ratio were compared for spectral resolutions of 3 and 9 bands compared to a baseline of 81 bands. Across all examined lighting quantities, considerable errors—a mean absolute percent error of 18.4%—were found when using 3 band calculations. These were reduced to 4% for 9 band calculations. The errors varied by metric and light source type. The results suggest that the use of 9 bands can more accurately characterize performance of different light source types across a range of metrics compared to using 3 bands.

Abboushi, Belal K.↗

DOE OSTI2022

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

Abstract Johnson-Cook constitutive model is a commonly used material model for machining simulations. The model includes five parameters that capture the initial yield stress, strain-hardening, strain-rate hardening, and thermal softening behavior of the material. These parameters are difficult to determine using experiments since the conditions observed during machining (such as high strain-rates of the order of $$10^5$$ 10 5 /sec - $$10^6$$ 10 6 /sec) are challenging to recreate in the laboratory. To address this problem, several researchers have recently proposed inverse approaches where a combination of experiments and analytical models are used to predict the Johnson-Cook parameters. The errors between the measured cutting forces, chip thicknesses and temperatures and those predicted by analytical models are minimized and the parameters are determined. In this work, it is shown that only two of the five Johnson-Cook parameters can be determined uniquely using inverse approaches. Two different algorithms, namely, Adaptive Memory Programming for Global Optimization (AMPGO) and Particle Swarm Optimization (PSO), are used for this purpose. The extended Oxley’s model is used as the analytical tool for optimization. For determining a parameter’s value, a large range for each parameter is provided as an input to the algorithms. The algorithms converge to several different sets of values for the five Johnson-Cook parameters when all the five parameters are considered as unknown in the optimization algorithm. All of these sets, however, yield the same chip shape and cutting forces in FEM simulations. Further analyses show that only the strain-rate and thermal softening parameters can be determined uniquely and the three parameters present in the strain-hardening term of the Johnson-Cook model cannot be determined uniquely using the inverse method. A combined experimental and numerical approach is proposed to eliminate this determine all parameters uniquely.

42 ENGINEERING↗

DOE OSTI2023

CO and [C ii] line emission of molecular clouds: the impact of stellar feedback and non-equilibrium chemistry

We analyse synthetic 12 CO, 13 CO, and [C ii] emission maps of molecular cloud (MC) simulations from the SILCC-Zoom project. We present radiation, magnetohydrodynamic zoom-in simulations of individual clouds, both with and without radiative stellar feedback, forming in a turbulent multiphase interstellar medium following on-the-fly the evolution of e.g. H 2 , CO, and C + . We introduce a novel post-processing routine based on cloudy which accounts for higher ionization states of carbon due to stellar radiation in H ii regions. Synthetic emission maps of [C ii] in and around feedback bubbles show that the bubbles are largely devoid of [C ii], as recently found in observations, which we attribute to the further ionization of C+ into C 2+ . For both 12 CO and 13 CO, the cloud-averaged luminosity ratio, $L_\rm {CO}/L_\rm {[C\, \small {II}]}$, can neither be used as a reliable measure of the H 2 mass fraction nor of the evolutionary stage of the clouds. We note a relation between the $I_\rm {CO}/I_\rm {[C\, \small {II}]}$ intensity ratio and the H 2 mass fraction for individual pixels of our synthetic maps. The scatter, however, is too large to reliably infer the H 2 mass fraction. Finally, the assumption of chemical equilibrium overestimates H2 and CO masses by up to 150 and 50 per cent, respectively, and $L_\rm {CO}$ by up to 60 per cent. The masses of H and C + would be underestimated by 65 and 30 per cent, respectively, and $L_\rm {[C\, \small {II}]}$ by up to 35 per cent. Hence, the assumption of chemical equilibrium in MC simulations introduces intrinsic errors of a factor of 2 in chemical abundances, luminosities, and luminosity ratios.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated flow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a low-dimensional linear subspace poorly approximates the solution. To address cases such as these, we have developed a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM (NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space dimension than the LS-ROMs. Our method takes advantage of the existing numerical methods that are used to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction technique in the context of the NM-ROM. Numerical results show that neural networks can learn a more efficient latent space representation on advection-dominated data from 1D and 2D Burgers' equations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are achieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique. Lastly, a posteriori error bounds for the NM-ROMs are derived that take account of the hyper-reduced operators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A moment-conserving discontinuous Galerkin representation of the relativistic Maxwellian distribution

Kinetic simulations of relativistic gases and plasmas are critical for understanding diverse astrophysical and terrestrial systems, but the accurate construction of the relativistic Maxwellian, the Maxwell–Jüttner distribution, on a discrete simulation grid is challenging. Difficulties arise from the finite velocity bounds of the domain, which may not capture the entire distribution function, as well as errors introduced by projecting the function onto a discrete grid. Here, we present a novel scheme for iteratively correcting the moments of the projected distribution applicable to all grid-based discretizations of the relativistic kinetic equation. In addition, we describe how to compute the needed nonlinear quantities, such as Lorentz boost factors, in a discontinuous Galerkin scheme through a combination of numerical quadrature and weak operations. The resulting method accurately captures the distribution function and ensures that the moments match the desired values to machine precision.

astrophysical plasmas↗

DOE OSTI2021

Finite-temperature vibrational full configuration interaction

Thermodynamic functions of an ideal molecular gas due to its anharmonic vibrations are evaluated in a wide range of temperature (T) by the vibrational full-configuration-interaction (FCI) method using a quartic force field and a finite number (N) of harmonic-oscillator basis functions along each normal mode. The thermodynamic functions considered are the grand potential (Ω), internal energy (U), and entropy (S). They are compared with those obtained from the Bose–Einstein theory with or without truncation of the harmonic-oscillator basis functions after quantum number N–1. The comparison reveals that the finite-basis-set errors in Ω and U are, respectively, k B Tln(k B T/Nℏω) and k B T per mode in the high-T limit, obscuring anharmonic effects when k B T > ℏω, where ω is the lowest mode frequency. Here, the benchmark data for several low-order perturbation corrections to Ω, U, and S are also obtained as the numerical derivatives of their FCI values with respect to dimensionless perturbation strength, and the domain of T and N in which these data are reliable (for the N → ∞ limits) is discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

HPC-driven computational reproducibility in numerical relativity codes: a use case study with IllinoisGRMHD

Abstract Reproducibility of results is a cornerstone of the scientific method. Scientific computing encounters two challenges when aiming for this goal. Firstly, reproducibility should not depend on details of the runtime environment, such as the compiler version or computing environment, so results are verifiable by third-parties. Secondly, different versions of software code executed in the same runtime environment should produceconsistent numerical results for physical quantities. In this manuscript, we test the feasibility of reproducing scientific results obtained using theIllinoisGRMHDcode that is part of an open-source community software for simulation in relativistic astrophysics, theEinstein Toolkit. We verify that numerical results of simulating a single isolated neutron star withIllinoisGRMHDcan be reproduced, and compare them to results reported by the code authors in 2015. We use two different supercomputers: Expanse at SDSC, and Stampede2 at TACC. By compiling the source code archived along with the paper on both Expanse and Stampede2, we find thatIllinoisGRMHDreproduces results published in its announcement paper up to errors comparable to round-off level changes in initial data parameters. We also verify that a current version ofIllinoisGRMHDreproduces these results once we account for bug fixes which have occurred since the original publication.

Astronomy & Astrophysics↗

DOE OSTI2022

Extension of the PINN diffusion model to k-eigenvalue problems

This paper extends our recent work on the Physics-Informed Neural Networks (PINN) approach for the fixed source diffusion models and applies it to the diffusion theory based k-eigenvalue problems. To make the PINN equitable for the eigenvalue problems, we introduce a novel integral regularization term to the loss function in the framework, and allow the direct inference of the principal eigenvalue and the associated eigenfunction. The regularization term enforces a pre-defined value on the integration of the model predictions, and this value can be directly related to a physical property of the system. We also introduce an additional learnable parameter to approximate the principal eigenvalue. As a proof of principle, we solve the one-group two-dimensional k-eigenvalue neutron diffusion equation in this work. We then provide two numerical examples to demonstrate the applicability of the PINN approach. In each example, we solve the k-eigenvalue diffusion equation in a multi-region configuration constrained with a set of Robin boundary conditions for generality. We use a FEM solution based on the power-iteration method to verify the results of the PINN solution. The results showed relative percentage error in the predicted eigenvalue of about 0.77% and about 1.2% for example 1 and example 2, respectively. The mean absolute error in the predicted flux for example 1 is ∼ 0.002 and for example 2 is ∼ 0.0024. These results indicate some preliminary successes of the PINN application to k-eigenvalue problems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Nonlinear manifold-based reduced order model

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations, in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated flow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a low-dimensional linear subspace poorly approximates the solution. To address cases such as these, we have developed a fast and accurate physicsinformed neural network ROM, namely nonlinear manifold ROM (NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space dimension than the LSROMs. Our method takes advantage of the existing numerical methods that are used to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction technique in the context of the NM-ROM. Numerical results show that neural networks can learn a more efficient latent space representation on advection-dominated data from 1D and 2D Burgers’ equations. A speedup of up to 2.6 for 1D Burgers’ and a speedup of 11.7 for 2D Burgers’ equations are achieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique. Finally, a posteriori error bounds for the NM-ROMs are derived that take account of the hyper-reduced operators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Longitudinal Phase Space Tomography for the Booster Synchrotron

Efforts in the study of the longitudinal behavior of charged particles in the Fermilab Booster can be catalyzed with an image of the two-dimensional phase space distribution. In the past, tomography has been extensively employed in the reconstruction of the phase space in accelerators such as the Recycler at Fermilab and the Proton Synchrotron Booster at CERN. However, such a capability had yet to realize for the Fermilab Booster synchrotron. In this work, the first successful tomographic phase space reconstruction of a low-energy Booster bunch is presented along with validation metrics. A numerical turn-by-turn model of the longitudinal particle dynamics in the Booster has been implemented, which utilizes a fast, map-based particle transport algorithm. Using a sinogram generated from the Wall Current Monitor, the iterative reconstruction algorithm recovers a discretized image of the original phase space distribution at variable resolution. The reconstruction result shows low root-mean-square error and a rapid convergence toward the solution, providing strong evidence of accuracy. Future and ongoing work includes modeling high-energy bunches above transition and using tomography to infer certain machine parameters such as synchronous phase, peak gap voltage, and synchronous energy in addition to the phase space distribution.

Ebeid, Safi [Unlisted]↗

DOE OSTI2026

Longitudinal Phase Space Tomography for the Booster Synchrotron (Abstract Only)

Ebeid, Safi [Unlisted, US]↗

DOE OSTI2026

Dissipation Enables Strongly Detuning-Dependent Interference in Pulsed Dynamical Decoupling

One of the defining features of pulsed dynamical decoupling is its suppression of a driven qubit's sensitivity to static detuning errors between the drive field and qubit resonance. In this paper, we show that dissipation, in the form of excited-state decay, can change this behavior entirely, producing an interference signal with a strong detuning dependence. This signal arises from decay during driven evolution and relies on coherence retained by the qubit after such a decay event. We develop analytical and numerical models that capture the underlying mechanism and observe this same dissipation-induced detuning dependence experimentally in both a free-space strontium atom interferometer and a superconducting transmon qubit system. We also use this dissipation-induced detuning dependence as the basis for a new spectroscopic technique called Dissipative Carr-Purcell Spectroscopy (DCPS) and compare it with a traditional Ramsey sequence. Our results establish a regime of pulsed dynamical decoupling in which dissipation reshapes, rather than merely degrades, coherent control, and we expect these dynamics to be relevant to a wide range of quantum systems.

DeRose, Kenneth [Northwestern U.; Fermilab] (ORCID↗