Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dimensionality Reduction”

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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluating the Toxicity Reduction With Computed Tomographic Ventilation Functional Avoidance Radiation Therapy

Purpose: Computed tomographic (CT) ventilation imaging is a new modality that uses 4-dimensional (4D) CT information to calculate lung ventilation. Although retrospective studies have reported on the reduction in dose to functional lung, no work to our knowledge has been published in which the dosimetric improvements have been translated to a reduction in the probability of pulmonary toxicity. Our work estimates the reduction in toxicity for CT ventilation–based functional avoidance planning. Methods and Materials: Seventy previously treated lung cancer patients who underwent 4DCT imaging were used for the study. CT ventilation maps were calculated with 4DCT deformable image registration and a density change–based algorithm. Pneumonitis was graded on the basis of imaging and clinical presentation. Maximum likelihood methods were used to generate normal tissue complication probability (NTCP) models predicting grade 2 or higher (2+) and grade 3+ pneumonitis as a function of dose (V5 Gy, V10 Gy, V20 Gy, V30 Gy, and mean dose) to functional lung. For 30 patients a functional plan was generated with the goal of reducing dose to the functional lung while meeting Radiation Therapy Oncology Group 0617 constraints. The NTCP models were applied to the functional plans and the clinically used plans to calculate toxicity reduction. Results: By the use of functional avoidance planning, absolute reductions in grade 2+ NTCP of 6.3%, 7.8%, and 4.8% were achieved based on the mean fV20 Gy, fV30 Gy, and mean dose to functional lung metrics, respectively. Absolute grade 3+ NTCP reductions of 3.6%, 4.8%, and 2.4% were achieved with fV20 Gy, fV30 Gy, and mean dose to functional lung. Maximum absolute reductions of 52.3% and 16.4% were seen for grade 2+ and grade 3+ pneumonitis for individual patients. Conclusion: Our study quantifies the possible toxicity reduction from CT ventilation–based functional avoidance planning. Reductions in grades 2+ and 3+ pneumonitis were 7.1% and 4.7% based on mean dose-function metrics, with reductions as high as 52.3% for individual patients. Our work provides seminal data for determining the potential toxicity benefit from incorporating CT ventilation into thoracic treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1993

An Eulerian/Lagrangian coupling procedure for three-dimensional vortical flows

A coupled Eulerian/Lagrangian method is presented for the reduction of numerical diffusion observed in solutions of 3D vortical flows using standard Eulerian finite-volume time-marching procedures. A Lagrangian particle tracking method, added to the Eulerian time-marching procedure, provides a correction of the Eulerian solution. In turn, the Eulerian solution is used to integrate the Lagrangian state-vector along the particles trajectories. While the Eulerian solution ensures the conservation of mass and sets the pressure field, the particle markers describe accurately the convection properties and enhance the vorticity and entropy capturing capabilities of the Eulerian solver. The Eulerian/Lagrangian coupling strategies are discussed and the combined scheme is tested on a constant stagnation pressure flow in a 90 deg bend and on a swirling pipe flow. As the numerical diffusion is reduced when using the Lagrangian correction, a vorticity gradient augmentation is identified as a basic problem of this inviscid calculation.

Felici, Helene M.↗
NASA NTRS1986

Efficient solution methods for the Navier-Stokes equations

Implicit finite difference schemes for solving two-dimensional and three-dimensional Euler and thin layer Navier-Stokes equations are addressed. The methods are demonstrated in fully vectorized codes for a Cray type architecture. The Beam and Warming implicit approximate factorization algorithm in generalized coordinates is used. The methods are either time accurate or accelerated non-time accurate steady state schemes. Acceleration and efficiency modifications such as matrix reduction, diagonalization, and flux split schemes are presented. Two dimensional inviscid and viscous calculations (e.g., airfoils with a deflected spoiler, circulation control airfoils, and unsteady buffeting) and of three dimensional viscous elliptical bodies, exhausting boattails, and generic oblique wing computations are discussed.

Pulliam, T. H.↗
DOE OSTI2024

Atomic-scale identification of active sites of oxygen reduction nanocatalysts

Heterogeneous nanocatalysts play a crucial role in both the chemical and energy industries. Despite substantial advancements in theoretical, computational and experimental studies, identifying their active sites remains a major challenge. Here we utilize atomic electron tomography to determine the three-dimensional atomic structure of PtNi and Mo-doped PtNi nanocatalysts for the electrochemical oxygen reduction reaction. We then employ the experimental atomic structures as input to first-principles-trained machine learning to identify the active sites of the nanocatalysts. Through the analysis of the structure–activity relationships, we formulate an equation termed the local environment descriptor, which balances the strain and ligand effects to provide physical and chemical insights into active sites in the oxygen reduction reaction. The ability to determine the three-dimensional atomic structure and chemical composition of realistic nanoparticles, combined with machine learning, could transform our fundamental understanding of the active sites of catalysts and guide the rational design of optimal nanocatalysts.

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

Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference

This work introduces a method for learning low-dimensional models from data of high-dimensional black-box dynamical systems. The novelty is that the learned models are exactly the reduced models that are traditionally constructed with classical projection-based model reduction techniques. Thus, the proposed approach learns models that are guaranteed to have the well-studied properties of reduced models known from model reduction, without requiring full knowledge of the governing equations and without requiring the operators of the high-dimensional systems. The key ingredient is a new data sampling scheme to obtain re-projected trajectories of high-dimensional systems that correspond to Markovian dynamics in low-dimensional subspaces. The exact recovery of reduced models from these re-projected trajectories is guaranteed pre-asymptotically under certain conditions for finite amounts of data and for a large class of systems with polynomial nonlinear terms. Numerical results demonstrate that the low-dimensional models learned with the proposed approach match reduced models from traditional model reduction up to numerical errors in practice. In conclusion, the numerical results further indicate that low-dimensional models fitted to re-projected trajectories are predictive even in situations where models fitted to trajectories without re-projection are inaccurate and unstable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Nonlinear electron-magnetohydrodynamic simulations of three dimensional current shear instability

This paper deals with detailed nonlinear electron-magnetohydrodynamic simulations of a three dimensional current shear driven instability in slab geometry. The simulations show the development of the instability in the current shear layer in the linear regime leading to the generation of electromagnetic turbulence in the nonlinear regime. The electromagnetic turbulence is first generated in the unstable shear layer and then spreads into the stable regions. The turbulence spectrum shows a new kind of anisotropy in which power transfer towards shorter scales occurs preferentially in the direction perpendicular to the electron flow. Results of the present three dimensional simulations of the current shear instability are compared with those of our earlier two dimensional simulations of sausage instability. It is found that the flattening of the mean velocity profile and thus reduction in the electron current due to generation of electromagnetic turbulence in the three dimensional case is more effective as compared to that in the two dimensional case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Operator inference for non-intrusive model reduction with quadratic manifolds

This paper proposes a novel approach for learning a data-driven quadratic manifold from high-dimensional data, then employing this quadratic manifold to derive efficient physics-based reduced-order models. The key ingredient of the approach is a polynomial mapping between high-dimensional states and a low-dimensional embedding. This mapping consists of two parts: a representation in a linear subspace (computed in this work using the proper orthogonal decomposition) and a quadratic component. The approach can be viewed as a form of data-driven closure modeling, since the quadratic component introduces directions into the approximation that lie in the orthogonal complement of the linear subspace, but without introducing any additional degrees of freedom to the low-dimensional representation. Combining the quadratic manifold approximation with the operator inference method for projection-based model reduction leads to a scalable non-intrusive approach for learning reduced-order models of dynamical systems. Further, applying the new approach to transport-dominated systems of partial differential equations illustrates the gains in efficiency that can be achieved over approximation in a linear subspace.

42 ENGINEERING↗
DOE OSTI2021

Generalized global symmetries of T[ M ] theories. Part I

We study reductions of 6d theories on a d-dimensional manifold Md, focusing on the interplay between symmetries, anomalies, and dynamics of the resulting (6 – d)-dimensional theory T[M d ]. We refine and generalize the notion of “polarization” to polarization on Md, which serves to fix the spectrum of local and extended operators in T[M d ]. Another important feature of theories T[M d ] is that they often possess higher-group symmetries, such as 2-group and 3-group symmetries. We study the origin of such symmetries as well as physical implications including symmetry breaking and symmetry enhancement in the renormalization group flow. To better probe the IR physics, we also investigate the ’t Hooft anomaly of 5d Chern-Simons matter theories. The present paper focuses on developing the general framework as well as the special case of d = 0 and 1, while an upcoming paper will discuss the case of d = 2, 3 and 4.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

X-ray tomography studies on porosity and particle size distribution in cast in-situ Al-Cu-TiB{sub 2} semi-solid forged composites

X-ray computed tomography (XCT) was used to characterise the internal microstructure and clustering behaviour of TiB{sub 2} particles in in-situ processed Al-Cu metal matrix composites prepared by casting method. Forging was used in semi-solid state to reduce the porosity and to uniformly disperse TiB{sub 2} particles in the composite. Quantification of porosity and clustering of TiB{sub 2} particles was evaluated for different forging reductions (30% and 50% reductions) and compared with an as-cast sample using XCT. Results show that the porosity content was decreased by about 40% due to semi-solid forging as compared to the as-cast condition. Further, XCT results show that the 30% forging reduction resulted in greater uniformity in distribution of TiB{sub 2} particles within the composite compared to as-cast and the 50% forge reduction in semi-solid state. These results show that the application of forging in semi-solid state enhances particle distribution and reduces porosity formation in cast in-situ Al-Cu-TiB{sub 2} metal matrix composites. - Highlights: •XCT was used to visualise 3D internal structure of Al-Cu-TiB{sub 2} MMCs. •Al-Cu-TiB{sub 2} MMC was prepared by casting using flux assisted synthesis method. •TiB{sub 2} particles and porosity size distribution were evaluated. •Results show that forging in semi-solid condition decreases the porosity content and improve the particle dispersion in MMCs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Surface Processes Control the Fate of Reactive Oxidants Generated by Electrochemical Activation of Hydrogen Peroxide on Stainless-Steel Electrodes

Low-cost stainless-steel electrodes can activate hydrogen peroxide (H 2 O 2 ) by converting it into a hydroxyl radical ( • OH) and other reactive oxidants. At an applied potential of +0.020 V, the stainless-steel electrode produced • OH with a yield that was over an order of magnitude higher than that reported for other systems that employ iron oxides as catalysts under circumneutral pH conditions. Decreasing the applied potential at pH 8 and 9 enhanced the rate of H 2 O 2 loss by shifting the process to a reaction mechanism that resulted in the formation of an Fe(IV) species. Significant metal leaching was only observed under acidic pH conditions (i.e., at pH <6), with the release of dissolved Fe and Cr occurring as the thickness of the passivation layer decreased. Despite the relatively high yield of • OH production under circumneutral pH conditions, most of the oxidants were scavenged by the electrode surface when contaminant concentrations comparable to those expected in drinking water sources were tested. The stainless-steel electrode efficiently removed trace organic contaminants from an authentic surface water sample without contaminating the water with Fe and Cr. With further development, stainless-steel electrodes could provide a cost-effective alternative to other H 2 O 2 activation processes, such as those by ultraviolet light.

42 ENGINEERING↗
DOE OSTI2015

The polarized Debye sheath effect on Kadomtsev-Petviashvili electrostatic structures in strongly coupled dusty plasma

We give a theoretical investigation on the dynamics of nonlinear electrostatic waves in a strongly coupled dusty plasma with strong electrostatic interaction between dust grains in the presence of the polarization force (i.e., the force due to the polarized Debye sheath). Adopting a reductive perturbation method, we derived a three-dimensional Kadomtsev-Petviashvili equation that describes the evolution of weakly nonlinear electrostatic localized waves. The energy integral equation is used to study the existence domains of the localized structures. The analysis provides the localized structure existence region, in terms of the effects of strong interaction between the dust particles and polarization force.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Renormalization of states and quasiparticles in many-body downfolding

We explore the principles of many-body Hamiltonian complexity reduction via downfolding on an effective low-dimensional representation. We show that the renormalization factor provides a unique measure of the quality of the compression as it directly represents the projection between the approximate stationary state of the many-body Hamiltonian and the full many-body wavefunction. Hence, the renormalization factor is a measure of fidelity between the effective (reduced-rank) description and the full many-body treatment for arbitrary (i.e., ground and excited) states. When the entire problem is mapped on a system of interacting quasiparticles [Romanova et al., npj Comput. Mater. 9, 126 (2023)], the effective Hamiltonians can faithfully reproduce the physics only when a clear energy scale separation exists between the subsystems and their environment. We also demonstrate that it is necessary to include quasiparticle renormalization at distinct energy scales, capturing the distinct interaction between subsystems and their surrounding environments. Numerical results from simple, exactly solvable models highlight the limitations and strengths of this approach, particularly for ground and low-lying excited states. This work lays the groundwork for applying dynamical downfolding techniques to problems concerned with (quantum) interfaces.

Green-functions technique↗
DOE OSTI2020

Spatially separating redox centers on 2D carbon nitride with cobalt single atom for photocatalytic H 2 O 2 production

Redox cocatalysts play crucial roles in photosynthetic reactions, yet simultaneous loading of oxidative and reductive cocatalysts often leads to enhanced charge recombination that is detrimental to photosynthesis. This study introduces an approach to simultaneously load two redox cocatalysts, atomically dispersed cobalt for improving oxidation activity and anthraquinone for improving reduction selectivity, onto graphitic carbon nitride (C 3 N 4 ) nanosheets for photocatalytic H 2 O 2 production. Spatial separation of oxidative and reductive cocatalysts was achieved on a two-dimensional (2D) photocatalyst, by coordinating cobalt single atom above the void center of C 3 N 4 and anchoring anthraquinone at the edges of C 3 N 4 nanosheets. Such spatial separation, experimentally confirmed and computationally simulated, was found to be critical for enhancing surface charge separation and achieving efficient H 2 O 2 production. This center/edge strategy for spatial separation of cocatalysts may be applied on other 2D photocatalysts that are increasingly studied in photosynthetic reactions.

2D photocatalyst↗
NASA NTRS1985

Aerodynamic interaction between vortical wakes and the viscous flow about a circular cylinder

In the design analysis of conventional aircraft configurations, the prediction of the strong interaction between vortical wakes and the viscous flow field about bodies is of considerable importance. Interactions between vortical wakes and aircraft components are even more common on rotorcraft and configurations with lifting surfaces forward of the wing. An accurate analysis of the vortex-wake interaction with aircraft components is needed for the optimization of the payload and the reduction of vibratory loads. However, the three-dimensional flow field beneath the rotor disk and the interaction of the rotor wake with solid bodies in the flow field are highly complex. The present paper has the objective to provide a basis for the considered interactions by studying a simpler problem. This problem involves the two-dimensional interaction of external wakes with the viscous flow about a circular cylinder.

Stremel, P. M.↗
NASA NTRS1992

Numerical simulation of unsteady flow in a hypersonic shock tunnel facility

This paper describes the computational work performed on the simulation of a 16-in shock-tunnel facility. The numerical problems encountered during the computation of these flows are discussed along with the validity of some approximations used, notably concerning the reduction of the problem into problems of smaller dimensionality. Quasi-1D simulations can be used to help design experiments, or to better understanding the characteristics of the facility. An application to the design of a nonintrusive diagnostic is shown. The multidimensional flow transients computed include the shock reflection at the end of the driven tube, the shock propagation down the nozzle, and the breaking of the main diaphragm.

Cambier, Jean-Luc↗
DOE OSTI2023

Fluid dynamic and thermal performance of a slotted cylinder at low Reynolds number

The fluid dynamic and thermal performance of a circular cylinder with a slot parallel to the flow is numerically investigated. The study utilized the semi-implicit finite volume multi-material algorithm MPM-ICE, a component of the Uintah framework. The normalized slot width s/D ranges from 0.1 - 0.3, introducing an additional heat transfer surface area between ~ 10 and ~ 50%, and a mass reduction between ~ 13 and ~ 38% in the cylinder. We assumed two-dimensional incompressible flow and simulated a Reynolds number Re D between 100 and 1000. The slotted cylinders are found to have a total drag force reduction up to ~ 45%, compared to a solid cylinder despite the additional viscous drag force in the slot. Convection heat transfer is enhanced up to ~ 70%. Further, the slotted cylinder performance index, defined as the ratio of the heat rate to the drag force, increases up to maximum of ~ 3, indicating better overall thermal fluid performance. An entropy analysis showed the best performance index occurs at the highest Re D . Correlations for drag coefficient and Nusselt number are proposed along with an entropy optimization method.

42 ENGINEERING↗
NASA NTRSDate not supplied

Deep Neural Network Based Unsteady Flamelet Progress Variable Approach in a Supersonic Combustor

Higher dimensional flamelet manifolds are essential in capturing the coupled effects of pressure gradients and unsteady chemical kinetics observed in supersonic combustion applications. Previous studies have validated the feasibility of using deep neural networks as an alternative to computation-ally intensive multidimensional flamelet table storage and lookup. This approach has demonstrated a significant reduction in memory footprint and enabled the use of larger dimensional tabulated manifolds for supersonic combustion in canonical problems. In this study, the Unsteady Flamelet Progress Variable (UFPV)-ANN model implemented in the VULCAN-CFD code is validated by the Burrows-Kurkov supersonic mixing/combustion configuration. The well characterized experimental problem consists of hydrogen injection into a supersonic vitiated crossflow that results in a lifted flame structure. The initial model consists of a 4-dimensional table where the independent variables Z, C, Xst, P are tabulated using an unsteady flamelet code with boundary conditions corresponding to the vitiated air conditions. The results show the development of a lifted flame structure and over-all acceptable agreement with finite-rate chemistry (FRC) simulation and the experimental data. Moreover, direct mapping between the independent variables and the flamelet table is replaced by a deep neural network for significant memory reduction. The results indicate that the UFPV-ANN approach can retrieve the same solution as the memory intensive lookup table approach.

Flamelet↗