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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optimization to Generate Equations of State for Hydrogen Production

On a high level, the larger project in question, HydroGEN, aims to develop software used for finding equations of state (EOS) to optimize catalyst configuration for H 2 production through water splitting. In particular, this summer project focused on solving the nonlinear equations used in fitting the equations. This problem involved using Python to solve a linear system with nonlinear constraints. In order for this to be achieved, Pyomo was used to build a model and the solver Ipopt, interior point optimizer, was used. Pyomo is a Python-based language developed at Sandia; it is an optimization modeling language. Rather than solving the entire problem at once, a toy problem was created, simplifying the problem down to the most important focus. This problem had a known solution, comparable to the calculated solution to assess accuracy and as progress was made towards finding solutions, complexity was gradually added to the problem. After building and solving the toy problem, it was found that it gave reasonably accurate solutions, better compared to the two existing solvers previously used with this project in terms of functionality. The solver is now ready for implementation into the project’s main software.

08 HYDROGEN↗
DOE OSTI2025

Real time heat load calculation software based on EPICS for Fermilab PIP-II CM tests

Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB 650 CM.

Yoon, S. [Fermilab]↗
DOE OSTI2026

Real time heat load calculation software based on EPICS for Fermilab PIP-II CM tests

Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign, an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real-time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB650 CM.

Yoon, S. [Fermilab]↗
DOE OSTI2021

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Materials Data on Rh3(PbS)2 by Materials Project

Rh3(PbS)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Rh is bonded in a distorted linear geometry to four Pb and two equivalent S atoms. There are two shorter (2.89 Å) and two longer (2.91 Å) Rh–Pb bond lengths. Both Rh–S bond lengths are 2.34 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Rh and two equivalent S atoms to form corner-sharing PbRh6S2 hexagonal bipyramids. Both Pb–S bond lengths are 3.08 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Rh atoms. S is bonded in a 4-coordinate geometry to three equivalent Rh and one Pb atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pd3(PbS)2 by Materials Project

Pd3(PbS)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Pd is bonded in a distorted linear geometry to four Pb and two equivalent S atoms. There are two shorter (2.93 Å) and two longer (3.04 Å) Pd–Pb bond lengths. Both Pd–S bond lengths are 2.36 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Pd and two equivalent S atoms to form corner-sharing PbPd6S2 hexagonal bipyramids. Both Pb–S bond lengths are 3.11 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Pd atoms. S is bonded in a 4-coordinate geometry to three equivalent Pd and one Pb atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Sr3LiTa4(O6F)2 by Materials Project

LiSr3Ta4(O6F)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Li1+ is bonded in a distorted linear geometry to six equivalent O2- and two equivalent F1- atoms. All Li–O bond lengths are 2.76 Å. Both Li–F bond lengths are 1.97 Å. Sr2+ is bonded to six O2- and two equivalent F1- atoms to form distorted SrO6F2 hexagonal bipyramids that share edges with four equivalent SrO6F2 hexagonal bipyramids and edges with six TaO6 octahedra. There are four shorter (2.67 Å) and two longer (2.69 Å) Sr–O bond lengths. Both Sr–F bond lengths are 2.43 Å. There are two inequivalent Ta+4.75+ sites. In the first Ta+4.75+ site, Ta+4.75+ is bonded to six O2- atoms to form TaO6 octahedra that share corners with six TaO6 octahedra and edges with four equivalent SrO6F2 hexagonal bipyramids. The corner-sharing octahedra tilt angles range from 39–45°. There are four shorter (2.01 Å) and two longer (2.02 Å) Ta–O bond lengths. In the second Ta+4.75+ site, Ta+4.75+ is bonded to six equivalent O2- atoms to form TaO6 octahedra that share corners with six equivalent TaO6 octahedra and edges with six equivalent SrO6F2 hexagonal bipyramids. The corner-sharing octahedral tilt angles are 45°. All Ta–O bond lengths are 2.03 Å. There are two inequivalent O2- sites. In the first O2- site, O2- is bonded in a 4-coordinate geometry to two equivalent Sr2+ and two Ta+4.75+ atoms. In the second O2- site, O2- is bonded in a 2-coordinate geometry to one Li1+, one Sr2+, and two equivalent Ta+4.75+ atoms. F1- is bonded to one Li1+ and three equivalent Sr2+ atoms to form distorted corner-sharing FSr3Li tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Pd3(PbSe)2 by Materials Project

Pd3(PbSe)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Pd is bonded in a distorted linear geometry to four Pb and two equivalent Se atoms. There are two shorter (3.03 Å) and two longer (3.04 Å) Pd–Pb bond lengths. Both Pd–Se bond lengths are 2.48 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Pd and two equivalent Se atoms to form corner-sharing PbPd6Se2 hexagonal bipyramids. Both Pb–Se bond lengths are 3.18 Å. In the second Pb site, Pb is bonded in a hexagonal planar geometry to six equivalent Pd atoms. Se is bonded in a 4-coordinate geometry to three equivalent Pd and one Pb atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Rh3(PbSe)2 by Materials Project

Rh3(PbSe)2 crystallizes in the trigonal R-3m space group. The structure is three-dimensional. Rh is bonded in a distorted linear geometry to four Pb and two equivalent Se atoms. There are two shorter (2.91 Å) and two longer (2.98 Å) Rh–Pb bond lengths. Both Rh–Se bond lengths are 2.45 Å. There are two inequivalent Pb sites. In the first Pb site, Pb is bonded to six equivalent Rh and two equivalent Se atoms to form corner-sharing PbRh6Se2 hexagonal bipyramids. Both Pb–Se bond lengths are 3.14 Å. In the second Pb site, Pb is bonded in a 6-coordinate geometry to six equivalent Rh atoms. Se is bonded in a 4-coordinate geometry to three equivalent Rh and one Pb atom.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A greedy Galerkin method to efficiently select sensors for linear dynamical systems

A key challenge in inverse problems is the selection of sensors to gather the most effective data. In this paper, we consider the problem of inferring the initial condition to a linear dynamical system and develop an efficient control-theoretical approach for greedily selecting sensors. Our method employs a Galerkin projection to reduce the size of the inverse problem, resulting in a computationally efficient algorithm for sensor selection. As a byproduct of our algorithm, we obtain a preconditioner for the inverse problem that enables the rapid recovery of the initial condition. Here, we analyze the theoretical performance of our greedy sensor selection algorithm as well as the performance of the associated preconditioner. Finally, we verify our theoretical results on various inverse problems involving partial differential equations.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2024

Stress-hybrid virtual element method on six-noded triangular meshes for compressible and nearly-incompressible linear elasticity

In this paper, we present a first-order Stress-Hybrid Virtual Element Method (SH-VEM) on six-noded triangular meshes for linear plane elasticity. Here, we adopt the Hellinger–Reissner variational principle to construct a weak equilibrium condition and a stress based projection operator. In each element, the stress projection operator is expressed in terms of the nodal displacements, which leads to a displacement based formulation. This stress-hybrid approach assumes a globally continuous displacement field while the stress field is discontinuous across each element. The stress field is initially represented by divergence-free tensor polynomials based on Airy stress functions, but we also present a formulation that uses a penalty term to enforce the element equilibrium conditions, referred to as the Penalty Stress-Hybrid Virtual Element Method (PSH-VEM). Numerical results are presented for PSH-VEM and SH-VEM, and we compare their convergence to the composite triangle FEM and B-bar VEM on benchmark problems in linear elasticity. The SH-VEM converges optimally in the L 2 norm of the displacement, energy seminorm, and the L 2 norm of hydrostatic stress. Furthermore, the results reveal that PSH-VEM converges in most cases at a faster rate than the expected optimal rate, but it requires the selection of a suitably chosen penalty parameter.

42 ENGINEERING↗
DOE OSTI2022

Large-Scale Optimization with Linear Equality Constraints Using Reduced Compact Representation

For optimization problems with linear equality constraints, we prove that the (1,1) block of the inverse KKT matrix remains unchanged when projected onto the nullspace of the constraint matrix. In this work, we develop reduced compact representations of the limited-memory inverse BFGS Hessian to compute search directions efficiently when the constraint Jacobian is sparse. Orthogonal projections are implemented by a sparse QR factorization or a preconditioned LSQR iteration. In numerical experiments two proposed trust-region algorithms improve in computation times, often significantly, compared to previous implementations of related algorithms and compared to IPOPT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Alfvén eigenmode stability in a JET afterglow deuterium plasma and projections to deuterium–tritium plasmas

Abstract The performance of fusion devices relies strongly on the good confinement of energetic particles (EPs). Therefore, the investigation of EP transport by magnetohydrodynamic instabilities is one of the key aspects in the development of plasma scenarios. Alfvénic instabilities in particular can lead to significant losses of alpha particles that are essential for plasma self-heating. A so-called afterglow scheme has been developed to study the destabilization of Alfvén eigenmodes (AEs) by alpha particles and associated EP transport in the JET tokamak. In this work, the linear stability of AEs is discussed for the partial afterglow phase in a JET deuterium plasma discharge and for the full afterglow phase in a projected deuterium–tritium (DT) plasma. Thanks to recent upgrades in the tokamak transport code TRANSP, one can account for the contributions of different EP species to mode stability. Analysis of deuterium plasmas shows that AE growth rates are extremely sensitive to the energy and distribution of fast ions. An increase in fast ion energy can lead to more unstable AEs. In the afterglow phase of projected DT plasmas, it is EPs that mostly drive the AEs. However, the drive by alpha particles is comparable to that by beam ions and their contribution to the net growth rate might be hard to separate. According to the discussed projections, the destabilization of AEs might be ineffective because the background plasma damping significantly exceeds the EP drive. In this case, the development of an alternative plasma scenario that allows us to overcome such damping would be required in future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Materials Data on Pd2O by Materials Project

Pd2O is Cuprite structured and crystallizes in the cubic Pn-3m space group. The structure is three-dimensional. Pd is bonded in a linear geometry to two equivalent O atoms. Both Pd–O bond lengths are 1.97 Å. O is bonded to four equivalent Pd atoms to form corner-sharing OPd4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Zr2O by Materials Project

Zr2O is Cuprite structured and crystallizes in the cubic Pn-3m space group. The structure is three-dimensional. Zr is bonded in a linear geometry to two equivalent O atoms. Both Zr–O bond lengths are 2.11 Å. O is bonded to four equivalent Zr atoms to form corner-sharing OZr4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Ag2O by Materials Project

Ag2O is Cuprite structured and crystallizes in the cubic Pn-3m space group. The structure is three-dimensional. Ag1+ is bonded in a linear geometry to two equivalent O2- atoms. Both Ag–O bond lengths are 2.10 Å. O2- is bonded to four equivalent Ag1+ atoms to form corner-sharing OAg4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on Cu2O by Materials Project

Cu2O is Cuprite structured and crystallizes in the cubic Pn-3m space group. The structure is three-dimensional. Cu1+ is bonded in a linear geometry to two equivalent O2- atoms. Both Cu–O bond lengths are 1.86 Å. O2- is bonded to four equivalent Cu1+ atoms to form corner-sharing OCu4 tetrahedra.

36 MATERIALS SCIENCE↗