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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗
DOE OSTI2025

CFD modeling and simulation for corrosive wear of refractory in molten slag

The development of high-wear resistant refractories having minimal production costs is facilitated by characterizing the wear mechanisms associated with their corrosive wear. Static cup testing is a commonly used method for comparing the corrosion resistance performance of two or more refractory materials. Although the static cup test conditions are not as severe as dynamic tests, this study shows that the thermal gradient present within the system during heating and cooling stages serves to generate movement of the slag leading to mechanical wear. The thermal gradient within the refractory, and between the slag and the refractory, occurs during the ramp stage of the test and lasts until the soaking stage is reached bringing the system to a thermal equilibrium. Using computational fluid dynamics (CFD) capabilities embedded within ANSYS software, this study modelled and quantified the convection currents within the slag and associated shear stresses generated on the refractory walls due to the thermal gradient. A traditional ladle furnace was employed as a case study to verify the results of the studied CFD model. The corrosion rate of the refractory lining was found to depend on the mass transfer coefficient of the refractory dissolution into the slag, and a velocity term which governs the extent of corrosion at any given location. This velocity term is a function of slag viscosity, as well as the concentration gradient and/or temperature gradient at the triple points. In this study, wall shear stress was used as a reliable proxy for identifying high-velocity regions prone to excessive corrosive wear. Elevated wall shear stress near the slag/air and slag/molten steel interfaces align with observed corrosion grooves, which reflects the intensified corrosive wear at these locations.

Ramteke, Rajat Rajat Durgesh Ramteke [University o↗
NASA NTRS1988

Generation of dynamo magnetic fields in protoplanetary and other astrophysical accretion disks

A computational method for treating the generation of dynamo magnetic fields in astrophysical disks is presented. The numerical difficulty of handling the boundary condition at infinity in the cylindrical disk geometry is overcome by embedding the disk in a spherical computational space and matching the solutions to analytically tractable spherical functions in the surrounding space. The lowest lying dynamo normal modes for a 'thick' astrophysical disk are calculated. The generated modes found are all oscillatory and spatially localized. Tha potential implications of the results for the properties of dynamo magnetic fields in real astrophysical disks are discussed.

Stepinski, T. F.↗
DOE OSTI2025

A constrained-transport embedded boundary method for compressible resistive magnetohydrodynamics

Motivated by the increased interest in pulsed-power magneto-inertial fusion devices in recent years, we present a method for implementing an arbitrarily shaped embedded boundary on a Cartesian mesh while solving the equations of compressible resistive magnetohydrodynamics. The method is built around a finite volume formulation of the equations in which a Riemann solver is used to compute fluxes on the faces between grid cells, and a face-centered constrained transport formulation of the induction equation. The small time step problem associated with the cut cells is avoided by always computing fluxes on the faces and edges of the Cartesian mesh. We extend the method to model a moving interface between two materials with different properties using a ghost-fluid approach, and show some preliminary results including shock-wave-driven and magnetically-driven dynamical compressions of magnetohydrostatic equilibria. In conclusion, we present a thorough verification of the method and show that it converges at second order in the absence of discontinuities, and at first order with a discontinuity in material properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

Method to predict external store carriage loads at transonic speeds

A computational method for prediction of external store carriage loads at transonic speeds is described. The geometric flexibility required for treatment of isolated and underwing, pylon mounted stores is achieved by computing solutions on a five level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body conforming grid improves the accuracy of the computed store body flow field. A nonlinear finite difference relaxation scheme, developed specifically for modified transonic small disturbance flow equations, enhances numerical stability and accuracy. As a result, more accurate treatment of low aspect ratio, highly swept and tapered wing planforms is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, force and moment correlation show good agreement for several test cases.

Rosen, Bruce S.↗
NASA NTRS2005

Data management in the mission data system

As spacecraft evolve from simple embedded devices to become more sophisticated computing platforms with complex behaviors it is increasingly necessary to model and manage the flow of data, and to provide uniform models for managing data that promote adaptability, yet pay heed to the physical limitations of the embedded and space environments.

mission data system (MDS)↗
NASA NTRS2017

Computationally Efficient Beam Elements for Accurate Stresses in Sandwich Laminates and Laminated Composites with Delaminations

Laminated composites are prone to delamination failure due to the lack of reinforcement through the thickness. Therefore, during the design process the initiation and propagation of delaminations should be accounted for as early as possible. This paper presents computationally efficient nine degree-of-freedom (dof) and eight-dof shear locking-free beam elements using the mixed form of the refined zigzag theory (RZT(sup(m))). The corresponding nine-dof and eight-dof elements use the anisoparametric and constrained anisoparametric interpolation schemes, respectively, to eliminate shear locking in slender beams. The advantage of the present element over previous RZT beam elements is that no post-processing is required to accurately model the transverse shear stress while maintaining the computational efficiency of a low-order beam element. Comparisons with high-fidelity finite element models and three-dimensional elasticity solutions show that the elements can robustly and accurately predict the displacement field, axial stress and transverse shear stress through the thickness of a sandwich beam or a composite laminate with an embedded delamination. In fact, the accuracy and computational efficiency of predicting stresses in laminates with embedded delaminations make the present elements attractive choices for RZT-based delamination initiation and propagation methodologies available in the literature.

R. M. J. Groh↗
DOE OSTI2024

Active learning approach to simulations of strongly correlated matter with the ghost Gutzwiller approximation

Quantum embedding (QE) methods such as the ghost Gutzwiller approximation (gGA) offer a powerful approach to simulating strongly correlated systems, but come with the computational bottleneck of computing the ground state of an auxiliary embedding Hamiltonian (EH) iteratively. In this work, we introduce an active learning (AL) framework integrated within the gGA to address this challenge. The methodology is applied to the single-band Hubbard model and results in a significant reduction in the number of instances where the EH must be solved. Through a principal component analysis (PCA), we find that the EH parameters form a low-dimensional structure that is largely independent of the geometric specifics of the systems, especially in the strongly correlated regime. Our AL strategy enables us to discover this low-dimensionality structure on the fly, while leveraging it for reducing the computational cost of gGA, laying the groundwork for more efficient simulations of complex strongly correlated materials. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2023

VecPAC: A Vectorizable and Precision-Aware CGRA

This paper proposes VecPAC -- a vectorizable and precision-aware coarse-grained reconfigurable array (CGRA) design. VecPAC integrates CGRA tiles with scalar functional units and specialized tiles with vector functional units that can trade off the number of vector lanes for the accuracy of the computation. We discuss the architecture design and present the related compilation framework. The experimental evaluation on a set of applications from three different domains (embedded, machine learning, and high-performance computing) shows that the hybrid design of VecPAC outperforms CGRAs with only scalar functional units by 1.48x, while providing higher scalability.

Tan, Cheng↗
DOE OSTI2026

Quantum computing approach for building surface sunlit in urban-scale energy modeling

Solar shadow calculations are needed in building energy modeling and performance simulation of PV systems installed on roofs or facades of buildings. We present a quantum computing approach for calculation of building surface sunlit fractions by recasting solar visibility as a binary optimization problem solved by quantum annealing. Each triangulated surface centroid is encoded as a binary qubit indicating sunlit or shaded status. Geometric visibility constraints are derived from the Möller-Trumbore intersection algorithm and converted into a constrained quadratic binary model compatible with contemporary quantum annealers. The coefficients were embedded to D-Wave quantum computer. To demonstrate feasibility, we conducted a case study in San Francisco for a target building with 52 triangles and roughly 2700 nearby triangles within 50 m evaluated at representative winter and summer solar positions. The results demonstrated that quantum annealing can reliably calculate and distinguish sunlit from shaded surfaces. Quantum samples achieved average accuracy exceeding 92.4 %, with the aggregate surface-level agreement approaching 99.9 %. The outputs of quantum computers agreed closely with classical algorithms, indicating practical feasibility and promising scalability. Finally, the hourly sunlit fractions of building surfaces can be obtained for urban energy modelling. This is the first study to apply quantum computing to the solar shadow and building surface sunlit calculation. It introduces a new paradigm that differs fundamentally from traditional approaches.

Deng, Zhipeng↗
DOE OSTI2021

Dual-atom active sites embedded in two-dimensional C 2 N for efficient CO 2 electroreduction: A computational study

Double-atom catalysts (DACs) have emerged as an enhanced platform of single-atom catalyst for promoting electrocatalytic CO 2 reduction reaction (CO 2 RR). Herein, we present a density-functional theory study on CO 2 RR performance of seven C 2 N-supported homo- and heteronuclear DACs, denoted as M 2 @C 2 N. Our results demonstrate that there exists substantial synergistic effect of dual-metal-atom N 2 M 2 N 2 active site and C 2 N matrix on O&#x2550 C &#x2550O bond activation. The dual-atom M 2 sites are able to drive CO 2 RR beyond C 1 products with low limiting potential (U L ). Specifically, C 2 H 4 formation is preferred on FeM@C 2 N (M = Fe, Co, Ni, Cu) versus CH 4 formation on CuM@C 2 N (M = Co, Ni, Cu). Furthermore, *CO+*CO co-binding strength can serve as a descriptor for CO 2 RR activity for making C 2 products such that the moderate binding results in the lowest U L . Remarkably, C-affinity matters most to C—C bond coupling and C 2 H 4 formation while both C- and O-affinity control CH 4 formation. Furthermore, our results provide theoretical insight into rational design of DACs for efficient CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Benchmarking embedded chain breaking in quantum annealing*

Quantum annealing solves combinatorial optimization problems by finding the energetic ground states of an embedded Hamiltonian. However, quantum annealing dynamics under the embedded Hamiltonian may violate the principles of adiabatic evolution and generate excitations that correspond to errors in the computed solution. Here we empirically benchmark the probability of chain breaks and identify sweet spots for solving a suite of embedded Hamiltonians. We further correlate the physical location of chain breaks in the quantum annealing hardware with the underlying embedding technique and use these localized rates in a tailored post-processing strategies. Our results demonstrate how to use characterization of the quantum annealing hardware to tune the embedded Hamiltonian and remove computational errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing

Models have historically represented fractured porous media with continuum descriptions that characterize the media using bulk parameters. The impact of small-scale features is not captured in these models, although they may be controlling the performance of subsurface applications. Pore-scale models can simulate processes in small-scale features by representing the pore space geometry explicitly but are computationally expensive for large domains. The alternative multiscale approach entails the combination of pore-scale and continuum-scale descriptions in a single framework. We use Chombo-Crunch, a computational capability that discretizes complex geometries with an adaptive, embedded boundary method to contrast these two approaches. Chombo-Crunch takes advantage of recent computational performance and memory bandwidth improvements resulting from the emergence of exascale computing resources. These combined improvements enable the efficient simulation of reactive transport in fractured media with a high degree of fidelity and the ability to capture the control small-scale processes exert on the overall medium evolution.

42 ENGINEERING↗
DOE OSTI2026

Same Data, Different Audiences: Using Personas to Scope a Supercomputing Job Queue Visualization

Domain-specific visualizations sometimes focus on narrow, albeit important, tasks for one group of users. This focus limits the utility of a visualization to other groups working with the same data. While tasks elicited from other groups can present a design pitfall if not disambiguated, they also present a design opportunity—namely, the development of visualizations that support multiple groups. This development choice presents a trade-off of broadening the scope but limiting support for the more narrow tasks of any one group, which in some cases can enhance the overall utility of the visualization. We investigate this scenario through a design study where we develop Guidepost, a notebook-embedded visualization of data that helps scientists assess compute wait times, machine learning researchers understand prediction accuracy, and system maintainers analyze usage trends. We adapt the use of personas for visualization design from existing literature in the HCI and design domains, applying them to categorize tasks based on their uniqueness across stakeholder personas. Under this model, tasks shared between all groups should be supported by interactive visualizations and tasks unique to each group can be deferred to scripting with notebook-embedded visualization design. We evaluate our visualization through real-world case studies and a task-focused evaluation with nine participants. We observe that together, Guidepost's visual encodings, interactions, and export capabilities support the tasks of our differing personas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Towards utility-scale electronic structure with sample-based quantum bootstrap embedding

One of the main applications for which quantum computers are hoped to find utility is in simulating ground state energies and other observables of molecular chemical systems. The recently proposed sample-based diagonalization method is a readily implementable method for this task on current-day hardware using short circuit depths and has been demonstrated on as many as 85 qubits in recent studies. In this work, we combine the recently proposed quantum bootstrap embedding (QBE) method with sampled-based diagonalization (QBE-SQD) and present the first benchmarking study of the QBE method on real quantum hardware, ibm_pittsburgh, a Heron r3 processor with 156 qubits. Our test system is a hydrogen ring with 8 hydrogen atoms in the cc-pVDZ basis. We show that for this system, QBE-SQD using an active space of (8e, 19o) per fragment with a 43 qubit footprint produces a ground state energy accuracy which exceeds that of an SQD calculation with an (8e, 30o) active space with a 67 qubit footprint when using a comparable number of Slater determinants. This demonstrates that the use of quantum bootstrap embedding techniques is a promising path towards extending the capabilities of state-of-the-art quantum eigensolvers on near-term devices.

Bierman, Joel [North Carolina State University, Ra↗
NASA NTRS2001

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Trevino, Luis↗
NASA NTRS1988

External store carriage loads prediction at transonic speeds

A computational method for prediction of external store carriage loads at transonic speeds is described. The geometric flexibility required for treatment of isolated and underwing, pylon-mounted stores is achieved by computing solutions on a five-level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body-conforming grid improves the accuracy of the computed store body flow field. A nonlinear finite difference relaxation scheme, developed specifically for modified transonic small disturbance flow equations, enhances numerical stability and accuracy. As a result, more accurate treatment of low aspect ratio, highly swept and tapered wing planforms is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, force and moment correlations show good agreement for several test cases.

Rosen, Bruce S.↗