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Results for “Support Vector Machines”

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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361 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

An Investigation of State-Space Model Fidelity for SSME Data

In previous studies, a variety of unsupervised anomaly detection techniques for anomaly detection were applied to SSME (Space Shuttle Main Engine) data. The observed results indicated that the identification of certain anomalies were specific to the algorithmic method under consideration. This is the reason why one of the follow-on goals of these previous investigations was to build an architecture to support the best capabilities of all algorithms. We appeal to that goal here by investigating a cascade, serial architecture for the best performing and most suitable candidates from previous studies. As a precursor to a formal ROC (Receiver Operating Characteristic) curve analysis for validation of resulting anomaly detection algorithms, our primary focus here is to investigate the model fidelity as measured by variants of the AIC (Akaike Information Criterion) for state-space based models. We show that placing constraints on a state-space model during or after the training of the model introduces a modest level of suboptimality. Furthermore, we compare the fidelity of all candidate models including those embodying the cascade, serial architecture. We make recommendations on the most suitable candidates for application to subsequent anomaly detection studies as measured by AIC-based criteria.

Space Shuttles↗
DOE OSTI2026

End-To-End Decentralized Transmission Line Protection in IBR-Dominated Weak Grids Using Interpretable Data-Driven Methods

Traditional transmission line protection relies on predictable synchronous-based fault signatures, which frequently fail under the non-standard, current-limited fault characteristics of Inverter-Based Resources (IBRs). This study investigates how to achieve secure, communication-free fault isolation in IBR-dominated weak grids without relying on opaque, computationally heavy "black-box" machine learning algorithms. To address this, we propose a novel, standalone, and inherently interpretable data-driven protection framework. Unlike centralized methods requiring multi-terminal communication, this decentralized approach relies solely on local measurements using a hierarchical linear-kernel Support Vector Machine (SVM). The methodology decomposes the protection task into four sequential stages that mimic traditional protection elements: fault detection and fault direction identification, fault type classification, zone classification, and location estimation. This multi-stage architecture allows for specialized feature engineering at each stage, combining high computational efficiency with logic traceability. The framework's end-to-end performance was validated via C-code and PSCAD/EMTDC co-simulation, utilizing a real-world utility network and an OEM black-box IBR model. The proposed relay achieves 97.2% overall accuracy and provides a reliable trip decision within a 2.5-cycle window. The results confirm 100% accuracy in fundamental fault detection, reliable zone selectivity across low to moderate fault resistances, and robust security against non-fault transients, proving its immediate viability for integration into commercial numerical relays.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Robust Biaxial Anisotropy and Switchable Néel Vectors in LaFeO 3 Epitaxial Films

Antiferromagnets with highly stable but switchable Néel vectors are desired for antiferromagnetic spintronics with ultrafast speed and terahertz frequencies. Electrical switching of antiferromagnetic insulators has been demonstrated using binary antiferromagnets, while large families of complex antiferromagnets such as perovskites are largely unexplored. Here, we show that epitaxial LaFeO 3 thin films on SrTiO 3 (001) exhibit clear, robust biaxial anisotropy with a spin-flop field of a few tesla. Angular-dependent spin-Hall magnetoresistance (SMR) characterizations of Pt/LaFeO 3 bilayers with the current channel along SrTiO 3 [100] and [110] reveal distinct, intriguing shapes and field dependence. Simulations using a macrospin model accurately describe the main behavior and fine features of the SMR data from which key antiferromagnetic parameters are extracted. Furthermore, remanent SMR measurement confirms the high fidelity of the Néel vector along either easy axis of the biaxial anisotropy, indicating that epitaxial films of LaFeO 3 and potentially other perovskite antiferromagnets offer an attractive platform for antiferromagnetic spintronics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Design of an AI Trash Sorting Machine for Use on the Moon and Mars

As NASA prepares for Mars colonization, resource conservation will be critical for survival. Artificial Intelligence (AI) powered waste sorting technologies, already emerging on Earth, offer promising solutions for recycling and material recovery. These systems use advanced sensors and machine learning algorithms to identify and separate materials with remarkable accuracy. On Mars, where every item has significant value, efficient recycling will be essential to reduce resupply needs and support closed-loop life support systems. This paper explores how terrestrial AI-based trash sorting technologies can be adapted for Martian conditions, focusing on challenges such as the harsh surface environment, minimizing system mass, power, volume, and estimating waste composition. Addressing these issues will be key to enabling sustainable operations on the Red Planet.

AI↗
DOE OSTI2026

Heavy long-lived dark vector via a gluonic portal

We study a dark gauge boson Z′ that exclusively couples to the QCD gluons through higher dimensional operators. These operators are generated from integrating out of heavy ultraviolet resonances carrying both QCD and dark gauge charges. With SU(3)C gauge invariance, charge and parity symmetries preserved, we find that the leading effective operators are restricted to have the form of Z′GGG and Z′Z′GG at dimension-eight, which can naturally render the Z′ particle long-lived, and serve as a viable dark matter candidate. We investigate the phenomenology of these operators with both collider experiments and cosmological observation, without and with the assumption that this dark gauge boson plays the role of the dominant dark matter component. For an unstable Z′, we show that depending on its lifetime, it can be probed by various observables up to ultraviolet physics scale around 10 9 GeV. For Z′ being dark matter, we find that $m_{Z'}$ ≳ 1 TeV is consistent with the thermal freeze-out scenario. In contrast, in the freeze-in scenario, the extremely small couplings leave the relevant parameter space largely unconstrained by current experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

A Unified Scaling Framework for Comparative Analysis of Major Electrical Machine Topologies

This paper presents a unified framework for comparing major electrical machine topologies under identical output and thermal constraints, with emphasis on supply-chain-aware selection among rare-earth-intensive, reduced-rare-earth, and rare-earth-free solutions. Using power factor and air-gap flux density as the principal descriptors, the framework links topology choice to relative size, copper demand, magnet dependence, cost sensitivity, and inertia. To support robust early-stage screening, the deterministic scaling model is combined with uncertainty representation, Monte Carlo scenario propagation, and hesitationaware ranking. The results show that rare-earth-rich machines remain compact and dense, whereas reduced-rare-earth and rare-earth-free alternatives become more attractive under specific material-risk and cost scenarios.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
NASA NTRSDate not supplied

Turbo-Design: Open-Source Radial Equilibrium Turbomachinery Solver: Part I - Turbines

Advances in 3D Geometrical Designs and Cooling have played a significant role in improving the efficiency of turbomachinery. However, these advancements must be effectively translated back to the modeler. Machine learning can facilitate this transition. Specifically, machine learning–based loss models can bridge the gap between 3D and 1D designs, enabling modelers not only to predict velocity triangles but also to extract additional geometric features. Currently, the design tools used at NASA have not been updated to support such integration—until now. TurboDesign is an open-source, Python-based framework that replaces TD2 (LEW-11029-1) and AXOD2 (LEW-16323-1), both of which are radial equilibrium solvers for axial turbines. The goal of this update is to enable the integration of machine learning loss models into radial equilibrium equations. Additionally, TurboDesign is designed to support radial machines. This paper presents the governing equations, the assumptions underlying the code, the integration of legacy loss models, an example of machine learning model integration, and a validation comparison with CFD. All code, tutorials, and documentation are available at: https://www.github.com/nasa/turbo-design

Radial Equilibrium↗
NASA NTRS2026

A Review of Superconducting Electric Machines with On-Board Cryocoolers

This paper reviews the evolution and emerging direction of superconducting electric machines that employ onboard cryocoolers integrated directly into the rotor, eliminating the need for cryogenic fluid coupling and, in some cases, rotary seals. Traditional low-temperature superconducting (LTS) machines relied on external cryogenic systems and liquid helium transfer couplers, which introduced excessive complexity, poor reliability, and significant parasitic energy losses. The advent of high-temperature superconductors (HTS) has enabled compact, closed-cycle cryocoolers that support self-contained, fluid-free refrigeration architectures suitable for rotating applications. This paper examines the key technological challenges associated with on-board cryocooler integration and reviews three representative efforts by KAIST, NASA, and Hinetics, each illustrating distinct strategies and milestones toward practical implementation. KAIST demonstrated early proof-of-concept for rotating machines with on-board cryocoolers, NASA developed a shaft-integrated Stirling-type pulse tube cryocooler for a 1.4 MW hybrid-electric motor, and Hinetics achieved full-scale validation of a self-contained HTS rotor incorporating a commercial Stirling cryocooler and spoke-suspension torque tube. Collectively, these achievements confirm the technical feasibility of on-board cryogenic refrigeration and highlight steady progress toward compact and efficient superconducting rotating systems across various applications. Embedding cryocoolers directly within the rotor enables practical, efficient, and commercially viable superconducting propulsion technologies.

Cryogenics↗
DOE OSTI2025

PAH101: A GW+BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals

Abstract The excited-state properties of molecular crystals are important for applications in organic electronic devices. TheGWapproximation and Bethe-Salpeter equation (GW+BSE) is the state-of-the-art method for calculating the excited-state properties of crystalline solids with periodic boundary conditions. We present the PAH101 dataset ofGW+BSE calculations for 101 molecular crystals of polycyclic aromatic hydrocarbons (PAHs) with up to ~500 atoms in the unit cell. To the best of our knowledge, this is the firstGW+BSE dataset for molecular crystals. The data records include theGWquasiparticle band structure, the fundamental band gap, the static dielectric constant, the first singlet exciton energy (optical gap), the first triplet exciton energy, the dielectric function, and optical absorption spectra for light polarized along the three lattice vectors. The dataset can be used to (i) discover materials with desired electronic/optical properties, (ii) identify correlations between DFT andGW+BSE quantities, and (iii) train machine learned models to help in materials discovery efforts.

Science & Technology - Other Topics↗
NASA NTRS2014

Analytical Model for Steady Flow through a Finite Channel with One Porous Wall with Arbitrary Variable Suction or Injection

This paper presents an exact solution of two-dimensional laminar flow through a finite length channel with one porous wall. It improves upon previous solutions by (1) satisfying the no-slip boundary condition at the channel dead end, (2) adding a turbulent term to the porous wall boundary condition, (3) allowing for arbitrary variable suction or injection across the porous wall, and (4) model validation against new cryogenic liquid hydrogen and oxygen experimental data. Of particular interest in the current work is the modeling of cryogenic propellant flow through a porous liquid acquisition device (LAD) screen and channel inside a propellant tank. First, a detailed review of the literature is presented for previously attempted solutions to channel flow with one porous wall. Next, the governing equations, boundary conditions, and model assumptions are used to derive the analytical flow solution and present general model results for pressure and velocity fields within the channel. Then, the model solution is compared with horizontal LAD channel flow data in liquid oxygen as well as vertical LAD channel flow data in an inverted outflow configuration in liquid hydrogen. Model results are used to update the static cryogenic bubble point pressure model with a dynamic bubble point term which factors in enhanced convection and cooling at the screen during propellant outflow. Convective heat transfer at the LAD screen during outflow is also quantified by comparing model and data. The new analytical flow solution with the dynamic bubble point model is shown to compare well with available cryogenic experimental data

Navier Stokes Equations↗
NASA NTRS2026

Advanced Materials Testing Plan for the Space Suit Portable Life Support System

The Space Suit Portable Life Support System (PLSS) has a tight mass requirement to meet while also meeting other requirements for supporting a crewmember in space, on the Moon, or on Mars. To meet these requirements, atypical materials must be considered to close the mass budget allocations. However, many of these materials and processes are relatively new and untested. Therefore, initial analysis and testing of some new and advanced processes have been conducted following a roadmap presented last year. This material testing has focused primarily on thermoplastics, both additively manufactured and machined, to assess plating and fastening operations that will be required. These processes will provide additional strength and shielding capability typically only achieved with metallics. This testing has also helped to define a forward plan to certify these materials and processes for critical spaceflight applications. This report will review testing plated thermoplastics both for strength and thermal properties. It will also review fastener and fastening options and look at insert and fastener testing. It will also review state-of-the-art methods being considered elsewhere and some additional testing being conducted. Using the testing results researched here, there will be recommendations on applications for each of these types of methods going forward.

Ryan Ogilvie↗
NASA NTRS2026

Advanced Materials Testing Plan for the Space Suit Portable Life Support System

The Space Suit Portable Life Support System (PLSS) has a tight mass requirement to meet while also meeting other requirements for supporting a crewmember in space, on the Moon, or on Mars. To meet these requirements, atypical materials must be considered to close the mass budget allocations. However, many of these materials and processes are relatively new and untested. Therefore, initial analysis and testing of some new and advanced processes have been conducted following a roadmap presented last year. This material testing has focused primarily on thermoplastics, both additively manufactured and machined, to assess plating and fastening operations that will be required. These processes will provide additional strength and shielding capability typically only achieved with metallics. This testing has also helped to define a forward plan to certify these materials and processes for critical spaceflight applications. This report will review testing plated thermoplastics both for strength and thermal properties. It will also review fastener and fastening options and look at insert and fastener testing. It will also review state-of-the-art methods being considered elsewhere and some additional testing being conducted. Using the testing results researched here, there will be recommendations on applications for each of these types of methods going forward.

Ryan Ogilvie↗
DOE OSTI2022

Variational Quantum Circuits to Prepare Low Energy Symmetry States

We explore how to build quantum circuits that compute the lowest energy state corresponding to a given Hamiltonian within a symmetry subspace by explicitly encoding it into the circuit. We create an explicit unitary and a variationally trained unitary that maps any vector output by ansatz A(α → ) from a defined subspace to a vector in the symmetry space. The parameters are trained varitionally to minimize the energy, thus keeping the output within the labelled symmetry value. The method was tested for a spin XXZ Hamiltonian using rotation and reflection symmetry and H 2 Hamiltonian within S z = 0 subspace using S 2 symmetry. We have found the variationally trained unitary gives good results with very low depth circuits and can thus be used to prepare symmetry states within near term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗
DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗