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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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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Clock Synchronization Characterization of the Washington DC Metropolitan Area Quantum Network (DC-QNet)

Quantum networking protocols relying on interference and precise time-of-flight measurements require high-precision clock synchronization. This study describes the design, implementation, and characterization of two optical time transfer methods in a metropolitan-scale quantum networking research testbed. With active electronic stabilization, sub-picosecond time deviation (TDEV) was achieved at integration times between 1 s and 10 5 s over 53 km of deployed fiber. Over the same integration periods, 10-picosecond level TDEV was observed using the White Rabbit-Precision Time Protocol (WR-PTP) over 128 km. Measurement methods are described to understand the sources of environmental fluctuations on clock synchronization towards the development of in-situ compensation methods. Path delay gradients, chromatic dispersion, polarization drift, and optical power variations all contributed to clock synchronization errors. The results from this study will inform future work in the development of link noise management methods essential for enabling experimental research in developing practical quantum networking protocols.

PIKTime↗
DOE OSTI2011

Ab initio molecular dynamics simulation of pressure-induced phase transformation in BeO

Ab initio molecular dynamics (MD) method has been used to study high pressure-induced phase transformation in BeO based on the local density approximation (LDA) and the generalized gradient approximation (GGA). Both methods show that the wurtzite (WZ) and zinc blende (ZB) BeO transforms to the rocksalt (RS) structure smoothly at high pressure. The transition pressures obtained from the LDA method are about 40 GPa larger than the GGA result for both WZ → RS and ZB → RS phase transformations, and the phase transformation mechanisms revealed by the LDA and GGA methods are different. For WZ → RS phase transformations both mechanisms obtained from the LDA and GGA methods are not comparable to the previous ab initio MD simulations of WZ BeO at 700 GPa based on the GGA method. It is suggested that the phase transformation mechanisms of BeO revealed by the ab initio MD simulations are affected remarkably by the exchange–correlation functional employed and the way of applying pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Implementation and Exploration of Parameterizations of Large-Scale Dynamics in NCAR's Single Column Atmosphere Model SCAM6

A single column model with parameterized large-scale (LS) dynamics is used to better understand the response of steady-state tropical precipitation to relative sea surface temperature under various representations of radiation, convection, and circulation. The large-scale dynamics are parametrized via the weak temperature gradient (WTG), damped gravity wave (DGW), and spectral weak temperature gradient (Spectral WTG) method in NCAR's Single Column Atmosphere Model (SCAM6). Radiative cooling is either specified or interactive, and the convective parameterization is run using two different values of a parameter that controls the degree of convective inhibition. Results are interpreted in the context of the Global Atmospheric System Studies -Weak Temperature Gradient (GASS-WTG) Intercomparison project. Using the same parameter settings and simulation configuration as in the GASS-WTG Intercomparison project, SCAM6 under the WTG and DGW methods produces erratic results, suggestive of numerical instability. However, when key parameters are changed to weaken the large-scale circulation's damping of tropospheric temperature variations, SCAM6 performs comparably to single column models in the GASS-WTG Intercomparison project. The Spectral WTG method is less sensitive to changes in convection and radiation than are the other two methods, performing qualitatively similarly across all configurations considered. Under all three methods, circulation strength, represented in 1D by grid-scale vertical velocity, is decreased when barriers to convection are reduced. This effect is most extreme under specified radiative cooling, and is shown to come from increased static stability in the column's reference radiative-convective equilibrium profile. This argument can be extended to interactive radiation cases as well, though perhaps less conclusively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Comparison of Machine Learning Methods for Frequency Nadir Estimation in Power Systems: Preprint

An increasing penetration level of inverter-based renewable energy resources changes the inertia of power systems, posing challenges for maintaining the desired system frequency stability. An accurate frequency nadir estimation is crucial for power system operators to prepare preventive actions against large frequency excursions. In this paper, five machine learning methods - linear regression, gradient boosting, support vector regression, an artificial neural network, and XGBoost - are applied to two different sets of preprocess data for the prediction of the frequency nadir in the Western Electricity Coordinating Council 240-bus system with high renewable penetration levels. The training and testing data sets are collected by extensive generation scheduling simulations on the Multi-timescale Integrated Dynamic and Scheduling (MIDAS) toolbox. Numerical results show that all five machine learning methods can achieve high performance accuracy for power system nadir frequency estimation. Among them, the gradient boosting and the XGBoost are clear winners by providing the best prediction accuracy.

data driven↗
DOE OSTI2022

A Comparison of Machine Learning Methods for Frequency Nadir Estimation in Power Systems

An increasing penetration level of inverter-based renewable energy resources changes the inertia of power systems, posing challenges for maintaining the desired system frequency stability. An accurate frequency nadir estimation is crucial for power system operators to prepare preventive actions against large frequency excursions. In this paper, five machine learning methods - linear regression, gradient boosting, support vector regression, an artificial neural network, and XGBoost - are applied to two different datasets, i.e., 1) the unit generation dataset and 2) the system total inertia and headroom dataset, for the prediction of the frequency nadir. The training and testing datasets are generated through extensive generation scheduling simulations using Multi-timescale Integrated Dynamic and Scheduling (MI-DAS) toolbox on the Western Electricity Coordinating Council 240-bus system with high renewable penetration levels. Numerical results show that all five machine learning methods perform well in predicting the nadir frequency of the system. Among them, the gradient boosting and the XGBoost are clear winners yielding the best prediction accuracy in terms of four evaluation metrics.

data driven↗
NASA NTRS2006

Reentry-Vehicle Shape Optimization Using a Cartesian Adjoint Method and CAD Geometry

A DJOINT solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (e.g., geometric parameters that control the shape). Classic aerodynamic applications of gradient-based optimization include the design of cruise configurations for transonic and supersonic flow, as well as the design of high-lift systems. are perhaps the most promising approach for addressing the issues of flow solution automation for aerodynamic design problems. In these methods, the discretization of the wetted surface is decoupled from that of the volume mesh. This not only enables fast and robust mesh generation for geometry of arbitrary complexity, but also facilitates access to geometry modeling and manipulation using parametric computer-aided design (CAD). In previous work on Cartesian adjoint solvers, Melvin et al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the two-dimensional Euler equations using a ghost-cell method to enforce the wall boundary conditions. In Refs. 18 and 19, we presented an accurate and efficient algorithm for the solution of the adjoint Euler equations discretized on Cartesian meshes with embedded, cut-cell boundaries. Novel aspects of the algorithm were the computation of surface shape sensitivities for triangulations based on parametric-CAD models and the linearization of the coupling between the surface triangulation and the cut-cells. The accuracy of the gradient computation was verified using several three-dimensional test cases, which included design variables such as the free stream parameters and the planform shape of an isolated wing. The objective of the present work is to extend our adjoint formulation to problems involving general shape changes. Factors under consideration include the computation of mesh sensitivities that provide a reliable approximation of the objective function gradient, as well as the computation of surface shape sensitivities based on a direct-CAD interface. We present detailed gradient verification studies and then focus on a shape optimization problem for an Apollo-like reentry vehicle. The goal of the optimization is to enhance the lift-to-drag ratio of the capsule by modifying the shape of its heat-shield in conjunction with a center-of-gravity (c.g.) offset. This multipoint and multi-objective optimization problem is used to demonstrate the overall effectiveness of the Cartesian adjoint method for addressing the issues of complex aerodynamic design.

Nemec, Marian↗
NASA NTRS1959

A Simple Method for Determining Heat Transfer, Skin Friction, and Boundary-Layer Thickness for Hypersonic Laminar Boundary-Layer Flows in a Pressure Gradient

A procedure based on the method of similar solutions is presented by which the skin friction, heat transfer, and boundary-layer thickness in a laminar hypersonic flow with pressure gradient may be rapidly evaluated if the pressure distribution is known. This solution, which at present is. restricted to power-law variations of pressure with surface distance, is presented for a wide range of exponents in the power law corresponding to both favorable and adverse pressure gradients. This theory has been compared to results from heat-transfer experiments on blunt-nose flat plates and a hemisphere cylinder at free-stream Mach numbers of 4 and 6.8. The flat-plate experiments included tests made at a Mach number of 6.8 over a range of angle of attack of +/- 10 deg. Reasonable agreement of the experimental and theoretical heat-transfer coefficients has been obtained as well as good correlation of the experimental results over the entire range of angle of attack studied. A similar comparison of theory with experiment was not feasible for boundary-layer-thickness data; however, the hypersonic similarity theory was found to account satisfactorily for the variation in boundary-layer thickness due to local pressure distribution for several sets of measurements.

Bertram, Mitchel H.↗
DOE OSTI2014

TH-A-19A-12: A GPU-Accelerated and Monte Carlo-Based Intensity Modulated Proton Therapy Optimization System

Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast in-house graphics processing unit (GPU) based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2016

Strain-Based Damage Determination Using Finite Element Analysis for Structural Health Management

A damage determination method is presented that relies on in-service strain sensor measurements. The method employs a gradient-based optimization procedure combined with the finite element method for solution to the forward problem. It is demonstrated that strains, measured at a limited number of sensors, can be used to accurately determine the location, size, and orientation of damage. Numerical examples are presented to demonstrate the general procedure. This work is motivated by the need to provide structural health management systems with a real-time damage characterization. The damage cases investigated herein are characteristic of point-source damage, which can attain critical size during flight. The procedure described can be used to provide prognosis tools with the current damage configuration.

Hochhalter, Jacob D.↗
NASA NTRS1992

A finite element: Boundary integral method for electromagnetic scattering

A method that combines the finite element and boundary integral techniques for the numerical solution of electromagnetic scattering problems is presented. The finite element method is well known for requiring a low order storage and for its capability to model inhomogeneous structures. Of particular emphasis in this work is the reduction of the storage requirement by terminating the finite element mesh on a boundary in a fashion which renders the boundary integrals in convolutional form. The fast Fourier transform is then used to evaluate these integrals in a conjugate gradient solver, without a need to generate the actual matrix. This method has a marked advantage over traditional integral equation approaches with respect to the storage requirement of highly inhomogeneous structures. Rectangular, circular, and ogival mesh termination boundaries are examined for two-dimensional scattering. In the case of axially symmetric structures, the boundary integral matrix storage is reduced by exploiting matrix symmetries and solving the resulting system via the conjugate gradient method. In each case several results are presented for various scatterers aimed at validating the method and providing an assessment of its capabilities. Important in methods incorporating boundary integral equations is the issue of internal resonance. A method is implemented for their removal, and is shown to be effective in the two-dimensional and three-dimensional applications.

Collins, J. D.↗
NASA NTRS2017

A Requirements-Driven Optimization Method for Acoustic Liners Using Analytic Derivatives

More than ever, there is flexibility and freedom in acoustic liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. In a previous paper on this subject, a method deriving the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground was described. A simple code-wrapping approach was used to evaluate a community noise objective function for an external optimizer. Gradients were evaluated using a finite difference formula. The subject of this paper is an application of analytic derivatives that supply precise gradients to an optimization process. Analytic derivatives improve the efficiency and accuracy of gradient-based optimization methods and allow consideration of more design variables. In addition, the benefit of variable impedance liners is explored using a multi-objective optimization.

Aircraft Noise↗
DOE OSTI2020

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Despite the great achievements of the modern deep neural networks (DNNs), the vulnerability/robustness of state-of-the-art DNNs raises security concerns in many application domains requiring high reliability. Various adversarial attacks are proposed to sabotage the learning performance of DNN models. Among those, the black-box adversarial attack methods have received special attentions owing to their practicality and simplicity. Black-box attacks usually prefer less queries in order to maintain stealthy and low costs. However, most of the current black-box attack methods adopt the first-order gradient descent method, which may come with certain deficiencies such as relatively slow convergence and high sensitivity to hyper-parameter settings. In this paper, we propose a zeroth-order natural gradient descent (ZO-NGD) method to design the adversarial attacks, which incorporates the zeroth-order gradient estimation technique catering to the black-box attack scenario and the second-order natural gradient descent to achieve higher query efficiency. The empirical evaluations on image classification datasets demonstrate that ZO-NGD can obtain significantly lower model query complexities compared with state-of-the-art attack methods.

Zhao, Pu↗
NASA NTRSDate not supplied

Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft With Analytic Gradients

Demands on aircraft design methods in recent years have begun to require increasingly higher amounts of coupling between disciplines and have also begun to require optimization in order to satisfy competing objectives involving large numbers of parameters that define unconventional configurations. These expanding requirements have amplified a need for new and improved aircraft design, analysis, and optimization codes that are capable of performing coupled design exploiting analytic gradients where possible. Aviary is a multidisciplinary design optimization and analysis framework which allows for tightly coupled simultaneous aircraft and subsystem design using analytic gradients. Aviary has employed the methods of two legacy aircraft analysis tools to provide native analytically differentiated calculations for five different disciplines, and it also has the ability to couple in external discipline analysis tools, whether or not those tools can provide analytic gradients. Preliminary examples and modeling efforts have shown Aviary’s ability to effectively model novel concepts and explore large and non-intuitive design spaces. Finally, a multi-level user interface in Aviary creates an easy entry point for users with any level of multidisciplinary design, analysis, and optimization experience.

multidisciplinary↗
DOE OSTI2024

Apparatus and methods for sample analysis with multi-gradient microfluidics

A device for analyzing biological samples comprises first, second, third, and fourth layers. The first layer comprises a sample chamber in which a sample is positioned. The second layer comprises first, second, and third channels. A third, porous layer is positioned between the first layer and the second layer. A fourth layer composed of a substantially liquid-impermeable material is positioned between the second layer and the third layer. The fourth layer includes first and second pass-through channels that are aligned with the first and second channel, respectively. Fluids that flow in the first and second channels pass through the pass-through channels and diffuse into the sample chamber, establishing a chemical concentration gradient therein. A gas in the sample chamber can diffuse through the third and fourth layers and interact with a fluid flowing in the third channel, establishing a gas concentration gradient in the sample chamber.

Kim, Peter Wonhee↗
DOE OSTI2012

Refractive index gradient measurement across the thickness of a dielectric film by the prism coupling method

A method is proposed for measuring the refractive index gradient n(z) in nonuniformly thick dielectric films. The method is based on the excitation of waveguide modes in a film using the prism coupling technique and on the calculation of n(z) and film thickness H{sub f} with the help of the angular positions of the TE or TM modes. The method can be used for an arbitrary shape of the index modulation over the film thickness in the limit of a small gradient [{Delta} n(z)/n(z) || 1]. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Structural, electronic and elastic properties of REIr{sub 2} (RE=La and Ce) Laves phase compounds

REIr{sub 2} (RE = La and Ce) Laves phase intermetallic compounds were investigated with respect to their structural, electronic and elastic properties using full potential linearized augmented plane wave (FP-LAPW) method within generalized gradient approximation (GGA) as implemented in WIEN2k code. The ground state properties such as lattice constants (a{sub 0}), bulk modulus (B), pressure derivative of bulk modulus (B′) and density of state at Fermi level N(E{sub F}) have been obtained by optimization method. The electronic structure (BS, TDOS and PDOS) reveals that these Laves phase compounds are metallic in nature. The calculated elastic constants indicate that these compounds are mechanically stable at ambient pressure and found to be ductile in nature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Journey Over Destination: Differentiable Sensor Placement Enhances Generalization [Poster]

The challenge of reconstructing spatial fields that change over time from limited sensor data has been a focal point for many research studies. Various machine learning methods have been used in attempts to address this complex issue, including convolutional neural networks. All of the proposed methods share a common requirement that the user needs to manually determine the sensor positions. This requirement remains a limiting factor in the ongoing quest for efficient learning and accurate field reconstruction. This study aims to present a method that enables a model to optimize sensor positions via backpropagation, thereby facilitating the model’s exploration of the spatial domain and enhancing sensor positioning effectively. Indexing naturally incorporates discrete decisions. This operation is nondifferentiable which is a requirement for the application of gradient-based optimization methods. We showcased its effectiveness by training an attention-based neural network, which achieved top-tier performance on two separate datasets. To our knowledge, this represents the first fully end-to-end differentiable workflow for enhancing sensor placement within a neural network model.

58 GEOSCIENCES↗