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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Application of the INSTANT-HPS PN Transport Code to the C5G7 Benchmark Problem

INSTANT is the INL's next generation neutron transport solver to support high-fidelity multi-physics reactor simulation INSTANT is in continuous development to extend its capability Code is designed to take full advantage of middle to large cluster (10-1000 processors) Code is designed to focus on method adaptation while also mesh adaptation will be possible. It utilizes the most modern computing techniques to generate a neutronics tool of full-core transport calculations for reactor analysis and design. It can perform calculations on unstructured 2D/3D triangular, hexagonal and Cartesian geometries. Calculations can be easily extended to more geometries because of the independent mesh framework coded with the model Fortran. This code has a multigroup solver with thermal rebalance and Chebyshev acceleration. It employs second-order PN and Hybrid Finite Element method (PNHFEM) discretization scheme. Three different in-group solvers - preconditioned Conjugate Gradient (CG) method, preconditioned Generalized Minimal Residual Method (GMRES) and Red-Black iteration - have been implemented and parallelized with the spatial domain decomposition in the code. The input is managed with extensible markup language (XML) format. 3D variables including the flux distributions are outputted into VTK files, which can be visualized by tools such as VisIt and ParaView. An extension of the code named INSTANTHPS provides the capability to perform 3D heterogeneous transport calculations within fuel pins. C5G7 is an OECD/NEA benchmark problem created to test the ability of modern deterministic transport methods and codes to treat reactor core problems without spatial homogenization. This benchmark problem had been widely analyzed with various code packages. In this transaction, results of the applying the INSTANT-HPS code to the C5G7 problem are summarized.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.

Austria, Phillipe [ORNL] (ORCID:0000000236223973)↗
DOE OSTI2024

Chemically Amplified, Dry-Develop Poly(aldehyde) Photoresist

The catalytic decomposition of poly(phthalaldehyde) with a photoacid generator can be used as dry-develop photoresist, where the exposed film depolymerizes into small molecules to allow the development of features via controlled vaporization. Higher temperatures enabled shorter dry-development times, but also promoted faster photoacid diffusion that compromised pattern fidelity. Trihexylamine was used as a base quencher to counteract acid diffusion in a phthalaldehyde-propanal co-polymer photoresist. The propanal co-monomer in the polymer improves the vaporization rate because it has a higher vapor pressure than phthalaldehyde. Addition of the base quencher was found to improve the contrast, pattern fidelity, and ease-of-handling of the dry-develop resist in a direct-write UV lithography tool. The dry-development of 4 μ m features was achieved with no appreciable residue. For large area features, a spatially variable exposure method was used to direct the residue away from the exposed area. The gradient exposure method was used to produce 100 μ m features. Plasma etching after dry-development was also used to achieve residue-free dry-developed patterns. These results show the benefits of incorporating base additives into a dry-develop depolymerizable resist system and highlight the need for addressing residue formation.

Materials Science↗
DOE OSTI2021

Preliminary Theoretical Analysis of Mixed Precision Krylov Subspace Methods (Q3 Report)

The third quarter of the project was spent performing theoretical finite precision analysis of Krylov subspace method variants that use mixed precision. Our focus here is on the Conjugate Gradient (CG) method and the Lanczos method. We have performed an analysis of maximum attainable accuracy for the classical CG method in which 3 precisions are used: a working precision ε, a precision ε IP for the inner product computations, and a precision ε MV for the matrix-vector products. Our results show that performing inner product computations in lower precision does not affect the attainable accuracy. Further, we have performed a complete error analysis of the s-step Lanczos algorithm. In this case, we show that the numerical behavior of the algorithm can be significantly improved by using extra precision in a small part of the computation. We summarize the main theorems in the remainder of the document. Other activities include attending biweekly xSDK meetings. The subsequent quarter will be spent finalizing these results into technical reports and/or manuscripts for submission to journals, as well as identifying opportunities for future work.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Trajectory optimization based on differential inclusion

A method for generating finite-dimensional approximations to the solutions of optimal control problems is introduced. By employing a description of the dynamical system in terms of its attainable sets in favor of using differential equations, the controls are completely eliminated from the system model. Besides reducing the dimensionality of the discretized problem compared to state-of-the-art collocation methods, this approach also alleviates the search for initial guesses from where standard gradient search methods are able to converge. The mechanics of the new method are illustrated on a simple double integrator problem. The performance of the new algorithm is demonstrated on a 1-D rocket ascent problem ('Goddard Problem') in presence of a dynamic pressure constraint.

Seywald, Hans↗
NASA NTRS1993

Trajectory optimization based on differential inclusion

A method for generating finite-dimensional approximations to the solutions of optimal control problems is introduced. By employing a description of the dynamical system in terms of its attainable sets in favor of using differential equations, the controls are completely eliminated from the system model. Besides reducing the dimensionality of the discretized problem compared to state-of-the-art collocation methods, this approach also alleviates the search for initial guesses from where standard gradient search methods are able to converge. The mechanics of the new method are illustrated on a simple double integrator problem. The performance of the new algorithm is demonstrated on a I-D rocket ascent problem ('Goddard Problem') in presence of a dynamic pressure constraint.

Seywald, Hans↗
NASA NTRS1993

Trajectory optimization based on differential inclusion

A method for generating finite-dimensional approximations to the solutions of optimal control problems is introduced. By employing a description of the dynamical system in terms of its attainable sets in favor of using differential equations, the controls are completely eliminated from the system model. Besides reducing the dimensionality of the discretized problem compared to state-of-the-art collocation methods, this approach also alleviates the search for initial guesses from where standard gradient search methods are able to converge. The mechanics of the new method are illustrated on a simple double integrator problem. The performance of the new algorithm is demonstrated on a 1-D rocket ascent problem (`Goddard Problem') in presence of a dynamic pressure constraint.

Seywald, Hans↗
DOE OSTI2016

Contour Mapping Based Radiation Source Localization by UAS Swarm

The unmanned swarm of aerial systems (UAS) can be used for remote radiation sensing and search for source location. Recently, the cost of developing UAS platforms has dropped drastically partly due to the increase in their popularity. The radiation sensing using multiple UAS has becomes economically viable. Different algorithms for determining the location of a radiation source using simultaneous measurements taken from drones in formation have been studied including gradient-based methods. Generally in order to accomplish contour mapping, the swarm of drones with on board sensors use gradient estimation to determine the direction of steepest gradient which governs a bulk heading vector for the swarm to follow. However, some algorithms and test methods are useful only in a specific set of circumstances with particular initial conditions. Besides, implementation of drones in swarm formation was generally not tested in the context of radiation source detection. The objective of this research is to advance the state-of-the-art by conducting experiments using multiple UAS and radiative sources in an indoor flight test-bed. The dynamic flight characteristic of the UAS swarm were considered in the search and mapping algorithms. In this paper, the radiation source detection using algorithms pertaining to swarm formation of UAS, gradient estimation, contour mapping, and experimental flight test-bed are discussed. In addition, more effective and practical ways of constructing the contour maps are explored. (authors)

42 ENGINEERING↗
NASA NTRS2002

Comparison of Evolutionary (Genetic) Algorithm and Adjoint Methods for Multi-Objective Viscous Airfoil Optimizations

A comparison between an Evolutionary Algorithm (EA) and an Adjoint-Gradient (AG) Method applied to a two-dimensional Navier-Stokes code for airfoil design is presented. Both approaches use a common function evaluation code, the steady-state explicit part of the code,ARC2D. The parameterization of the design space is a common B-spline approach for an airfoil surface, which together with a common griding approach, restricts the AG and EA to the same design space. Results are presented for a class of viscous transonic airfoils in which the optimization tradeoff between drag minimization as one objective and lift maximization as another, produces the multi-objective design space. Comparisons are made for efficiency, accuracy and design consistency.

Pulliam, T. H.↗
NASA NTRS1973

Aircraft symmetric flight optimization

Review of the development of gradient techniques and their application to aircraft optimal performance computations in the vertical plane of flight. Results obtained using the method of gradients are presented for attitude- and throttle-control programs which extremize the fuel, range, and time performance indices subject to various trajectory and control constraints, including boundedness of engine throttle control. A penalty function treatment of state inequality constraints which generally appear in aircraft performance problems is outlined. Numerical results for maximum-range, minimum-fuel, and minimum-time climb paths for a hypothetical supersonic turbojet interceptor are presented and discussed. In addition, minimum-fuel climb paths subject to various levels of ground overpressure intensity constraint are indicated for a representative supersonic transport. A variant of the Gel'fand-Tsetlin 'method of ravines' is reviewed, and two possibilities for further development of continuous gradient processes are cited - namely, a projection version of conjugate gradients and a curvilinear search.

Falco, M.↗
DOE OSTI2024

Significance of Low‐Velocity Zones on Solute Retention in Rough Fractures

Natural fractures are characterized by high internal heterogeneity. This internal variability is the cause of flow channeling, which in turn leads to contaminant transport taking place primarily along the high-velocity channels. Mass exchange between the high-velocity channels and the low-velocity zones has the potential to enhance contaminant retention, due to solute diffusion into the low-velocity zones and subsequent exposure to additional surface area for diffusion into the bordering rock matrix. Here, we derive a random walk particle tracking method for heterogeneous fractures, which includes an additional term to account for the aperture gradient. The method takes into account advection, diffusion in the fracture and matrix diffusion. The developed numerical framework is applied to assess the effect of low-velocity zones in rough self-affine fractures. The results show that diffusion into low-velocity zones has a visible but modest impact on contaminant retention. The magnitude of this impact does not change considerably, regardless of whether diffusion into the rock matrix is considered in the model, and increases for a decreasing average Péclet number of the fracture.

58 GEOSCIENCES↗
NASA NTRS1993

Radial basis function network learns ceramic processing and predicts related strength and density

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

Cios, Krzysztof J.↗
DOE OSTI2016

Structural and Electronic Effects on the Properties of Fe 2 (dobdc) upon Oxidation with N 2 O

Here, we report electronic, vibrational, and magnetic properties, together with their structural dependences, for the metal–organic framework Fe 2 (dobdc) (dobdc 4 – = 2,5-dioxido-1,4-benzenedicarboxylate) and its derivatives, Fe 2 (O) 2 (dobdc) and Fe 2 (OH) 2 (dobdc)—species arising in the previously proposed mechanism for the oxidation of ethane to ethanol using N 2 O as an oxidant. Magnetic susceptibility measurements reported for Fe 2 (dobdc) in an earlier study and reported in the current study for Fe II 0.26 [Fe III (OH)] 1.74 (dobdc)(DMF) 0.15 (THF) 0.22 , which is more simply referred to as Fe 2 (OH) 2 (dobdc), were used to confirm the computational results. Theory was also compared to experiment for infrared spectra and X-ray powder diffraction structures. Structural and magnetic properties were computed by using Kohn-Sham density functional theory both with periodic boundary conditions and with cluster models. In addition, we studied the effects of different treatments of the exchange interactions on the magnetic coupling parameters by comparing several approaches to the exchange-correlation functional: generalized gradient approximation (GGA), GGA with empirical Coulomb and exchange integrals for 3d electrons (the GGA+U method), nonseparable gradient approximation with empirical Coulomb and exchange integrals for 3d electrons (GAM+U), hybrid GGA, meta-GGA, and hybrid meta- GGA. We found the coupling between the metal centers to be ferromagnetic in the case of Fe 2 (dobdc) and antiferromagnetic in the cases of Fe 2 (O) 2 (dobdc) and Fe 2 (OH) 2 (dobdc). The shift in magnetic coupling behavior correlates with the changing electronic structure of the framework, which derives from both structural and electronic changes that occur upon metal oxidation and addition of the charge-balancing oxo and hydroxo ligands.

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

Magnetic method for stimulating transport in fluids

A method for producing mass and heat transport in fluids, wherein the method does not rely on conventional convection, that is, it does not require gravity, a thermal gradient, or a magnetic field gradient. This method gives rise to a unique class of vigorous, field-controllable flow patterns termed advection lattices. The advection lattices can be used to transport heat and/or mass in any desired direction using only magnetic fields.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

PCG method with Strang’s circulant preconditioner for Hermitian positive definite linear system in Riesz space fractional advection–dispersion equations

In this paper, preconditioned conjugate gradient (PCG) method with Strang’s circulant preconditioner is investigated to solve the Hermitian positive definite linear systems, which is result from the Crank–Nicolson (C-N) finite difference scheme with the weighted and shifted Grünwald difference (WSGD) operators to discretize the Riesz space fractional advection–dispersion equation (RSFADE). We show that the spectrum of the preconditioned matrix is clustered around 1, and the singular values of the preconditioned matrix are uniformly bounded away from zero under a certain condition, respectively; hence the PCG method, when applied to solving the preconditioned system, converges superlinearly. Moreover, the complexity in each iteration of the PCG method is O(Nlog N) via using the fast Fourier transforms, where N is the matrix size. Numerical experiments are included to demonstrate the effectiveness of our approach.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

A comparison of two closely-related approaches to aerodynamic design optimization

Two related methods for aerodynamic design optimization are compared. The methods, called the implicit gradient approach and the variational (or optimal control) approach, both attempt to obtain gradients necessary for numerical optimization at a cost significantly less than that of the usual black-box approach that employs finite difference gradients. While the two methods are seemingly quite different, they are shown to differ (essentially) in that the order of discretizing the continuous problem, and of applying calculus, is interchanged. Under certain circumstances, the two methods turn out to be identical. We explore the relationship between these methods by applying them to a model problem for duct flow that has many features in common with transonic flow over an airfoil. We find that the gradients computed by the variational method can sometimes be sufficiently inaccurate to cause the optimization to fail.

Shubin, G. R.↗
DOE OSTI2014

Comparison of two-dimensional integration methods for shape reconstruction from gradient data

As a requisite and key step in some gradient-based measurement techniques, the reconstruction of the shape, more generally the scalar potential, from the measured gradient data has been studied for many years. Here, in this work, three types of two-dimensional integration methods are compared under various conditions. The merits and drawbacks of each integration method are consequently revealed to provide suggestions in selection of a proper integration method for a particular application.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Gradient-Based Aerodynamic Shape Optimization Using ADI Method for Large-Scale Problems

A gradient-based shape optimization methodology, that is intended for practical three-dimensional aerodynamic applications, has been developed. It is based on the quasi-analytical sensitivities. The flow analysis is rendered by a fully implicit, finite volume formulation of the Euler equations.The aerodynamic sensitivity equation is solved using the alternating-direction-implicit (ADI) algorithm for memory efficiency. A flexible wing geometry model, that is based on surface parameterization and platform schedules, is utilized. The present methodology and its components have been tested via several comparisons. Initially, the flow analysis for for a wing is compared with those obtained using an unfactored, preconditioned conjugate gradient approach (PCG), and an extensively validated CFD code. Then, the sensitivities computed with the present method have been compared with those obtained using the finite-difference and the PCG approaches. Effects of grid refinement and convergence tolerance on the analysis and shape optimization have been explored. Finally the new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4. Despite the expected increase in the computational time, the results indicate that shape optimization, which require large numbers of grid points can be resolved with a gradient-based approach.

Pandya, Mohagna J.↗