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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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15 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The use of minimal spanning trees in particle physics

Minimal spanning trees (MSTs) have been used in cosmology and astronomy to distinguish distributions of points in a multi-dimensional space. They are essentially unknown in particle physics, however. We briefly define MSTs and illustrate their properties through a series of examples. We show how they might be applied to study a typical event sample from a collider experiment and conclude that MSTs may prove useful in distinguishing different classes of events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Geometric Estimation of Multivariate Dependency

This paper proposes a geometric estimator of dependency between a pair of multivariate random variables. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate samples. This estimator converges to a quantity that we call the geometric mutual information (GMI), which is equivalent to the Henze–Penrose divergence. between the joint distribution of the multivariate samples and the product of the marginals. The GMI has many of the same properties as standard MI but can be estimated from empirical data without density estimation; making it scalable to large datasets. The proposed empirical estimator of GMI is simple to implement, involving the construction of an minimal spanning tree (MST) spanning over both the original data and a randomly permuted version of this data. We establish asymptotic convergence of the estimator and convergence rates of the bias and variance for smooth multivariate density functions belonging to a Hölder class. We demonstrate the advantages of our proposed geometric dependency estimator in a series of experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Convergence Rates for Empirical Estimation of Binary Classification Bounds

Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information theory. Many bounds on the Bayes binary classification error rate depend on information divergences between the pair of class distributions. Recently, the Henze–Penrose (HP) divergence has been proposed for bounding classification error probability. We consider the problem of empirically estimating the HP-divergence from random samples. We derive a bound on the convergence rate for the Friedman–Rafsky (FR) estimator of the HP-divergence, which is related to a multivariate runs statistic for testing between two distributions. The FR estimator is derived from a multicolored Euclidean minimal spanning tree (MST) that spans the merged samples. We obtain a concentration inequality for the Friedman–Rafsky estimator of the Henze–Penrose divergence. We validate our results experimentally and illustrate their application to real datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Evaluation of low-exergy heating and cooling systems and topology optimization for deep energy savings at the urban district level

District energy systems have the potential to achieve deep energy savings by leveraging the density and diversity of loads in urban districts. However, planning and adoption of district thermal energy systems is hindered by the analytical burden and high infrastructure costs. It is hypothesized that network topology optimization would enable wider adoption of advanced (ambient temperature) district thermal energy systems, resulting in energy savings. In this study, energy modeling is used to compare the energy performance of “conventional” and “advanced” district thermal energy systems at the urban district level, and a partial exhaustive search is used to evaluate a heuristic for the topology optimization problem. For the prototypical district considered, advanced district thermal energy systems mated with low-exergy building heating and cooling systems achieved a source energy use intensity that was 49% lower than that of conventional systems. The minimal spanning tree heuristic was demonstrated to be effective for the network topology optimization problem in the context of a prototypical district, and contributes to mitigating the problem’s computational complexity. The work presented in this paper demonstrates the potential of advanced district thermal energy systems to achieve deep energy savings, and advances to addressing barriers to their adoption through topology optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Spectroscopic assessment of Wise-based young stellar object selection near λ and σ Orionis

We have conducted a sensitive search down to the hydrogen burning limit for unextincted stars over ~200 square degrees around Lambda Orionis and 20 square degrees around Sigma Orionis using the methodology of Koenig and Leisawitz. From WISE and 2MASS data we identify 544 and 418 candidate young stellar objects (YSOs) in the vicinity of λ and σ respectively. Based on our followup spectroscopy for some candidates and the existing literature for others, we found that ~80% of the K14-selected candidates are probable or likely members of the Orion star-forming region. The yield from the photometric selection criteria shows that WISE sources with K{sub S}-w3>1.5 mag and K{sub S} between 10 and 12 mag are most likely to show spectroscopic signs of youth, while WISE sources with K{sub S}-w3 > 4 mag and K{sub S}>12 were often active galactic nuclei when followed up spectroscopically. The population of candidate YSOs traces known areas of active star formation, with a few new “hot spots” of activity near Lynds 1588 and 1589 and a more dispersed population of YSOs in the northern half of the H ii region bubble around σ and ϵ Ori. A minimal spanning tree analysis of the two regions to identify stellar groupings finds that roughly two-thirds of the YSO candidates in each region belong to groups of 5 or more members. The population of stars selected by WISE outside the MST groupings also contains spectroscopically verified YSOs, with a local stellar density as low as 0.5 stars per square degree.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Massive gravity wrapped in the cosmic web

We study how the filamentary pattern of the cosmic web changes if the true gravity deviates from general relativity (GR) on a large scale. The f(R) gravity, whose strength is controlled to satisfy the current observational constraints on the cluster scale, is adopted as our fiducial model and a large, high-resolution N-body simulation is utilized for this study. By applying the minimal spanning tree algorithm to the halo catalogs from the simulation at various epochs, we identify the main stems of the rich superclusters located in the most prominent filamentary section of the cosmic web and determine their spatial extents per member cluster to be the degree of their straightness. It is found that the f(R) gravity has the effect of significantly bending the superclusters and that the effect becomes stronger as the universe evolves. Even in the case where the deviation from GR is too small to be detectable by any other observables, the degree of the supercluster straightness exhibits a conspicuous difference between the f(R) and the GR models. Our results also imply that the supercluster straightness could be a useful discriminator of f(R) gravity from the coupled dark energy since it is shown to evolve differently between the two models. As a final conclusion, the degree of the straightness of the rich superclusters should provide a powerful cosmological test of large scale gravity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

YOUNG STELLAR OBJECTS IN THE MASSIVE STAR-FORMING REGION W49

We present the initial results of our investigation of the star-forming complex W49, one of the youngest and most luminous massive star-forming regions in our Galaxy. We used Spitzer/Infrared Array Camera (IRAC) data to investigate massive star formation with the primary objective of locating a representative set of protostars and the clusters of young stars that are forming around them. We present our source catalog with the mosaics from the IRAC data. In this study we used a combination of IRAC, MIPS, Two Micron All Sky Survey, and UKIRT Deep Infrared Sky Survey (UKIDSS) data to identify and classify the young stellar objects (YSOs). We identified 232 Class 0/I YSOs, 907 Class II YSOs, and 74 transition disk candidate objects using color–color and color–magnitude diagrams. In addition, to understand the evolution of star formation in W49, we analyzed the distribution of YSOs in the region to identify clusters using a minimal spanning tree method. The fraction of YSOs that belong to clusters with ≥7 members is found to be 52% for a cutoff distance of 96″, and the ratio of Class II/I objects is 2.1. We compared the W49 region to the G305 and G333 star-forming regions and concluded that W49 has the richest population, with seven subclusters of YSOs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Young Stellar Objects in the Massive Star-forming Regions W51 and W43

We present the results of our investigation of the star-forming complexes W51 and W43, two of the brightest in the first Galactic quadrant. In order to determine the young stellar object (YSO) populations in W51 and W43 we used color–magnitude relations based on Spitzer mid-infrared and 2MASS/UKIDSS near-infrared data. We identified 302 Class I YSOs and 1178 Class II/transition disk candidates in W51, and 917 Class I YSOs and 5187 Class II/transition disk candidates in W43. We also identified tens of groups of YSOs in both regions using the Minimal Spanning Tree (MST) method. We found similar cluster densities in both regions, even though Spitzer was not able to probe the densest part of W43. By using the Class II/I ratios, we traced the relative ages within the regions and, based on the morphology of the clusters, we argue that several sites of star formation are independent of one another in terms of their ages and physical conditions. We used spectral energy distribution-fitting to identify the massive YSO (MYSO) candidates since they play a vital role in the star formation process, and then examined them to see if they are related to any massive star formation tracers such as UCH ii regions, masers, or dense fragments. We identified 17 MYSO candidates in W51, and 14 in W43, respectively, and found that groups of YSOs hosting MYSO candidates are positionally associated with H ii regions in W51, though we do not see any MYSO candidates associated with previously identified massive dense fragments in W43.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Evaluation of Topology Optimization to Achieve Energy Savings at the Urban District Level: Preprint

Advanced district thermal energy systems have the potential to achieve significant energy savings and facilitate the integration of renewable thermal resources and waste heat, contributing to reductions in carbon emissions. Such systems, also known as fifth generation district heating and cooling (5GDHC) systems, circulate water at temperatures close to ambient, and leverage electrically-driven water-source heat pumps located at connected buildings to further temper the water. However, barriers exist to the adoption of 5GDHC systems, including the factorial growth in potential network configurations as a function of the number of considered buildings. Topology optimization, which seeks to answer the questions, “Which is the best subset of buildings, if any, to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?” can accelerate the adoption of 5GDHC systems. This study is part of an effort to develop a topology optimization framework for district thermal energy systems. In this study, a heuristic for one aspect of the topology optimization problem---the use of the minimal spanning tree network to connect a given set of buildings at the least life cycle cost---is validated.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2025

Efficient sparse state preparation via quantum walks

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work, we develop an algorithm that converts single-edge and self-loop dynamic CTQWs to the gate model of computation. We use this mapping to introduce an efficient sparse quantum state preparation framework based on dynamic CTQWs. Our approach utilizes combinatorics techniques such as minimal hitting sets, minimum spanning trees, and shortest Hamiltonian paths to reduce the number of controlled gates required to prepare sparse states. We show that our framework encompasses the current state of the art ancilla-free sparse state preparation method by reformulating this method as a CTQW. This CTQW-based framework offers an alternative to the uniformly controlled rotation method used by Qiskit by requiring fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

dynamic continuous time quantum walks↗
DOE OSTI2019

A Graph Theory Method for Identification of a Minimum Breakpoint Set for Directional Relay Coordination

The energy grid becomes more complex with increasing penetration of renewable resources, distributed energy storage, distributed generators, and more diverse loads such as electric vehicle charging stations. The presence of distributed energy resources (DERs) requires directional protection due to the added potential for energy to flow in both directions down the line. Additionally, contingency requirements for critical loads within a microgrid may result in looped or meshed systems. Computation speeds of iterative methods required to coordinate loops are improved by starting with a minimum breakpoint set (MBPS) of relays. A breakpoint set (BPS) is a set of breakers such that, when opened, breaks all loops in a mesh grid creating a radial system. A MBPS is a BPS that consists of the minimum possible number of relays required to accomplish this goal. In this paper, a method is proposed in which a minimum spanning tree is computed to indirectly break all loops in the system, and a set difference is used to identify the MBPS. The proposed method is found to minimize the cardinality of the BPS to achieve a MBPS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2024

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗