Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Comparative Study”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Charge Hopping Dynamics along a Disordered Chain in Quantum Environments: Comparative Study of Different Rate Kernels

This work presents a computational study of charge hopping dynamics along a one-dimensional chain with Gaussian site energy disorder and linearly coupled quantum bath. Time dependent square displacements are calculated directly from numerical solutions of Pauli master equations, for five different rate kernels: exact Fermi golden rule (FGR) rate expression, stationary phase interpolation (SPI) approximation, semiclassical (SC) approximation, classical Marcus rate expression, and Miller-Abrahams expression. All results demonstrate diffusive behavior in the steady state limit. The results based on the FGR rate expression show that the charge transport in the quantum bath can be much more sensitive to the disorder than the prediction from the classical Marcus expression. While the SPI approximation captures this general trend reasonably well, the SC approximation tends to be unreliable at both quantitative and qualitative levels and becomes even worse than the classical Marcus expression under certain conditions. Furthermore, these results offer useful guidance in the choice of approximate rate kernels for larger-scale simulations and also demonstrate significant but fragile positive effects of quantum environments on the charge hopping dynamics.

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

A Comparative Study on the Effect of Zr, Sn, and Ti on the Crystallization Behavior of Nepheline Glass

In alkali aluminosilicate glasses, additions of 4+ cations like Zr and Ti are often added to promote crystallization. In this study, Zr, Ti, or Sn are progressively substituted for Si in nepheline (NaAlSiO4) glass to determine their impact on the crystallization behavior. For glasses homogeneous on quenching, up to NaAlZr0.075Si0.925O4, NaAlSn0.100Si0.900O4, and NaAlTi0.300Si0.700O4, respectively, crystallization temperatures were investigated by thermal analysis. A subset of compositions was subjected to additional thermal analysis, varying heating rate and particle size, to investigate the subtleties of crystallization behavior. Subsequent heat treatment of glass powders was performed to maximize crystallization, and glass-ceramic microstructure was assessed by optical microscopy and electron microprobe, while crystalline phases were determined by X-ray diffraction. In all cases the major crystalline phase was orthorhombic carnegieite, which accommodated Ti in its structure but not Zr or Sn, and excess 4+ cations formed MO2, i.e., brookite, baddeleyite, and cassiterite, respectively.

Nienhuis-Marcial, Emily T.↗
DOE OSTI2021

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗
DOE OSTI2018

A comparative study on the oxidation of two-dimensional Ti 3 C 2 MXene structures in different environments

The oxidation of two-dimensional Ti 3 C 2 MXene structures has been recognized as a promising method for the formation of hybrid structures of carbon supported nanotitania. Here, we studied the oxidation of Ti 3 C 2 MXene structures using reactive force field (ReaxFF) based molecular dynamics simulations. To investigate the effect of oxidizing agent, we used three different environments including dry air (oxygen molecules), wet air (oxygen and water molecules) and hydrogen peroxide (H 2 O 2 molecules). Oxidation simulations were performed at different temperatures of 1000, 1500, 2000, 2500 and 3000 K. We found that by controlling the temperature, carbon supported titania can be formed by diffusion of Ti atoms to the surface of MXene structures during the oxidation. These results were confirmed by the increase in the average bond orders of C–C and Ti–O and decrease in the average bond orders of Ti–C. Moreover, it was revealed that by increasing the temperature, the oxidation rate increases, and the rate depends on the oxidant according to the following order: H 2 O 2 > wet air > dry air. This was validated by heating the MXene in wet air and dry air followed by examining the products using X-ray diffraction and Raman spectroscopy. To investigate the effect of the presence of the oxidant, the MXene structure was also heated under vacuum, and it was found that in this case the MXene structure was converted to cubic TiC. Furthermore, it was indicated that during the heating process of the MXene structure in a vacuum, the average bond orders for C–C, Ti–C and Ti–O do not change significantly due to the lack of oxidants in the environment, leaving room for only topotactic transformation of atoms during the heating. In conclusion, the formation of the TiC structure by heating the MXene in an inert environment was confirmed experimentally as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization

We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of a star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models cannot be selected arbitrarily. If the free parameters are properly defined, the reverse CG procedure also yields an accurate effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces the many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Rotationally invariant slave-boson and density matrix embedding theory: Unified framework and comparative study on the one-dimensional and two-dimensional Hubbard model [Rotationally invariant slave-boson and density matrix embedding theory: A unified framework and a comparative study on the 1D and 2D Hubbard Model]

We present detailed benchmark ground-state calculations of the one- and two-dimensional Hubbard model utilizing the cluster extensions of the rotationally invariant slave-boson mean-field theory and the density matrix embedding theory. Our analysis shows that the overall accuracy and the performance of these two methods are very similar. Furthermore, we propose a unified computational framework that allows us to implement both of these techniques on the same footing. In conclusion, this provides us with a different line of interpretation and paves the ways for developing systematically distinct generalizations of these complementary approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Comparative study of GeO{sub 2}/Ge and SiO{sub 2}/Si structures on anomalous charging of oxide films upon water adsorption revealed by ambient-pressure X-ray photoelectron spectroscopy

The energy difference between the oxide and bulk peaks in X-ray photoelectron spectroscopy (XPS) spectra was investigated for both GeO{sub 2}/Ge and SiO{sub 2}/Si structures with thickness-controlled water films. This was achieved by obtaining XPS spectra at various values of relative humidity (RH) of up to ∼15%. The increase in the energy shift is more significant for thermal GeO{sub 2} on Ge than for thermal SiO{sub 2} on Si above ∼10{sup −4}% RH, which is due to the larger amount of water molecules that infiltrate into the GeO{sub 2} film to form hydroxyls. Analyzing the origins of this energy shift, we propose that the positive charging of a partially hydroxylated GeO{sub 2} film, which is unrelated to X-ray irradiation, causes the larger energy shift for GeO{sub 2}/Ge than for SiO{sub 2}/Si. A possible microscopic mechanism of this intrinsic positive charging is the emission of electrons from adsorbed water species in the suboxide layer of the GeO{sub 2} film to the Ge bulk, leaving immobile cations or positively charged states in the oxide. This may be related to the reported negative shift of flat band voltages in metal-oxide-semiconductor diodes with an air-exposed GeO{sub 2} layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A Comparative Study of the COG Thermal Libraries II

This paper reports the results of a comparative study of the various libraries making up the COG thermal database and is a follow up to an earlier study, “A Comparative Study of the COG Thermal Libraries”.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A comparative study of velocity increment generation between the rigid body and flexible models of MMET

The motorized momentum exchange tether (MMET) is capable of generating useful velocity increments through spin–orbit coupling. This study presents a comparative study of the velocity increments between the rigid body and flexible models of MMET. The equations of motions of both models in the time domain are transformed into a function of true anomaly. The equations of motion are integrated, and the responses in terms of the velocity increment of the rigid body and flexible models are compared and analysed. Results show that the initial conditions, eccentricity, and flexibility of the tether have significant effects on the velocity increments of the tether.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Comparative study on the overall energy performance between photovoltaic and Low-E insulated glass units

In this report a novel semi-transparent building integrated photovoltaic (BIPV) laminate was developed and introduced in this paper. It was produced by cutting standard mono-crystalline silicon solar cells into small strips and then making electrical connections between each strip before laminating the cells between two layers of glass. The overall energy performance and energy saving potential of the BIPV insulated glass unit (IGU) under real world conditions were identified through a side by side comparative study. Compared to the reference IGU, the BIPV IGU had lower solar heat gain coefficient (SHGC) but much higher U-factor. The average HVAC electricity saving of the BIPV IGU was about 10% relative to the reference IGU. Daylighting measurement and analysis were carried out to evaluate the trade-offs associated with the BIPV IGU between daylight, glare, and lighting energy use. The results indicated that the BIPV IGU is better than the reference IGU in reducing discomfort glare. However, if the most conservative viewpoint near the window is used for the assessment, a lower transmittance BIPV IGU is required to bring the overall discomfort levels below the perceptible level. Lastly, the net energy saving potential associated with the novel BIPV IGU was identified based on the power, thermal and daylighting performance. On average, the BIPV IGU saved 16.8% of the total electricity use of the room. Further studies and improvement on the energy conversion efficiency of solar cells, the optimal transmittance as well as the thermal properties would make this technology more energy-efficient and affordable.

14 SOLAR ENERGY↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
DOE OSTI2023

A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks

This study focuses on the comparative study of deep learning (DL) models for pore space and discrete fracture networks (DFNs) segmentation in synthetic fractured digital rocks, specifically targeting low-permeability rock formations, such as shale and tight sandstones. Accurate characterization of pore space and DFNs is critical for subsequent property analysis and fluid flow modeling. Four DL models, SegNet, U-Net, U-Net-wide, and nested U-Net (i.e., U-Net++), were trained, validated, and tested using synthetic datasets, including input and label image pairs with varying properties. The model performance was assessed regarding pixel-wise metrics, including the F1 score and pixel-wise difference maps. In addition, the physics-based metrics were considered for further analysis, including sample porosity and absolute permeability. Particularly, We first simulated the permeability of porous media containing only pore space and then simulated the permeability of porous media with DFNs added. The difference between these two values is used to quantify the connectivity of segmented DFNs, which is an important parameter for low-permeability rocks. The pixel-wise metrics showed that the nested U-Net model outperformed the rest of the DL models in pore space and DFNs segmentation, with the SegNet model exhibiting the second-best performance. Particularly, nested U-Net enhanced segmentation accuracy for challenging boundary pixels affected by partial volume effects. The U-Net-wide model achieved improved accuracy compared to the U-Net model, which indicated the influence of parameter numbers. Similarly, nested U-Net has the closest match to the ground truth of physics-based metrics, including the porosity of pore space and DFNs, and the permeability difference quantifying the connectivity of DFNs. The findings highlight the effectiveness of DL models, especially the U-Net++ model with nested architecture and redesigned skip connections, in accurately segmenting pore spaces and DFNs, which are crucial for pore-scale fluid flow and transport simulation in low-permeability rocks.

Wang, Hongsheng↗
DOE OSTI2019

Comparative Study of the Effect of Magnetic Nanoparticle CoFe{sub 2}O{sub 4} on Fluctuation-Induced Conductivity of Y-123 and Y-358 Superconductors

In this study, a comparative investigation of the electrical conductivity fluctuations in nano-CoFe{sub 2}O{sub 4} added to Y{sub 3}Ba{sub 5}Cu{sub 8}O{sub 18±x} (Y-358) and YBa{sub 2}Cu{sub 3}O{sub 7−d} (Y-123) products is performed. All products were made using the solid-state reaction process. X-ray powder diffraction (XRD) analyses confirmed the formation of different phases. Scanning electron microscope (SEM) analysis shows the reduction of grain size with increasing the quantity of nano-CoFe{sub 2}O{sub 4} particles for both the Y-123 and Y-358 samples. The decrease of grain size is more accentuated in the case of the Y-358 samples compared with the Y-123 ones. The data of conductivity fluctuations are examined in terms of the derivative of the electrical resistivity with respect to temperature and the logarithmic derivative of the conductivity with regard to temperature. The results illustrate the existence of a transition with two stages; intragrain and intergrain. It is demonstrated that the addition of CoFe{sub 2}O{sub 4} nanoparticles affects the electrical conductivity fluctuations, the values of the critical exponents, and the fluctuation dimensionality in YBCO systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM

Accurate identification of material parameters is crucial for predictive modeling in computational mechanics. Here, the two primary approaches in the experimental mechanics community for calibration from full-field digital image correlation data are known as finite element model updating (FEMU) and the virtual fields method (VFM). In VFM, the objective function is a squared mismatch between internal and external virtual work or power. In FEMU, the objective function quantifies the weighted mismatch between model predictions and corresponding experimentally measured quantities of interest. It is minimized by iteratively updating the parameters of an FE model. While FEMU is seen as more flexible, VFM is commonly used instead of FEMU due to its considerably greater computational expense. However, comparisons between the two methods usually involve approximations of gradients or sensitivities with finite difference schemes, thereby making direct assessments difficult. Hence, in this study, we compare VFM and FEMU in the context of numerically-exact sensitivities obtained through local sensitivity analyses and the application of automatic differentiation software. To this end, we conduct a series of test cases to assess both methods under practical challenges using a finite strain elastoplasticity model.

Automatic differentiation↗