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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

TOI-1338: TESS’ First Transiting Circumbinary Planet

We report the detection of the first circumbinary planet (CBP) found by Transiting Exoplanet Survey Satellite (TESS). The target, a known eclipsing binary, was observed in sectors 1 through 12 at 30 minute cadence and in sectors 4 through 12 at 2 minute cadence. It consists of two stars with masses of 1.1 M {sub ⊙} and 0.3 M {sub ⊙} on a slightly eccentric (0.16), 14.6 day orbit, producing prominent primary eclipses and shallow secondary eclipses. The planet has a radius of ∼6.9 R {sub ⊕} and was observed to make three transits across the primary star of roughly equal depths (∼0.2%) but different durations—a common signature of transiting CBPs. Its orbit is nearly circular (e ≈ 0.09) with an orbital period of 95.2 days. The orbital planes of the binary and the planet are aligned to within ∼1°. To obtain a complete solution for the system, we combined the TESS photometry with existing ground-based radial-velocity observations in a numerical photometric-dynamical model. The system demonstrates the discovery potential of TESS for CBPs and provides further understanding of the formation and evolution of planets orbiting close binary stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Conjugation-based genome engineering enables rapid prototyping and bioproduction in non-model bacteria

Abstract Non-model bacteria offer unique metabolic capabilities for sustainable bioproduction, yet their limited genetic accessibility hinders systematic strain development. Here we present conjugation-based serine recombinase-assisted genome engineering (cSAGE), a broad-host-range platform that enables predictable, iterative genomic integration in transformation-resistant bacteria. cSAGE combines conjugative DNA delivery, standardized low-copy vectors, orthogonal recombinases, and modular genetic parts to support rapid pathway assembly and cross-host benchmarking. Using purple nonsulfur bacteria as a testbed, we integrate promoter engineering, multi-payload genome modification, and genome-scale metabolic modeling to empirically evaluate host-dependent pathway performance. Applying this workflow, we identify strain-specific differences in photosynthetic conversion of lignin-derived p -coumarate to the thermoplastic precursor p -vinylphenol. By enabling genome engineering and functional comparison across diverse bacteria using a single plasmid system, cSAGE provides a general framework for non-model strain prototyping and biotransformation discovery.

Guzman, Michael S. [Department of Chemical Enginee↗
NASA NTRS1976

Crop status evaluations and yield predictions

One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

Haun, J. R.↗
NASA NTRS1989

Axisymmetric shell analysis of the Space Shuttle solid rocket booster field joint

The Space Shuttle Challenger (STS 51-L) accident led to an intense investigation of the structural behavior of the solid rocket booster (SRB) tang and clevis field joints. The presence of structural deformations between the clevis inner leg and the tang, substantial enough to prevent the O-ring seals from eliminating hot gas flow through the joints, has emerged as a likely cause of the vehicle failure. This paper presents results of axisymmetric shell analyses that parametrically assess the structural behavior of SRB field joints subjected to quasi-steady-state internal pressure loading for both the original joint flown on mission STS 51-L and the redesigned joint recently flown on the Space Shuttle Discovery. Discussion of axisymmetric shell modeling issues and details is presented and a generic method for simulating contact between adjacent shells of revolution is described. Results are presented that identify the performance trends of the joints for a wide range of joint parameters.

Nemeth, Michael P.↗
NASA NTRS1991

Axisymmetric shell analysis of the space shuttle solid rocket booster field joint

The Space Shuttle Challenger (STS 51-L) accident led to an intense investigation of the structural behavior of the solid rocket booster (SRB) tang and clevis field joints. Results are presented of axisymmetric shell analyses that parametrically assess the structural behavior of SRB field joints subjected to quasi-steady-state internal pressure loading for both the original joint flown on mission STS 51-L and the redesigned joint flown for the first time after the STS 51-L accident on the Space Shuttle Discovery. Discussion of axisymmetric shell modeling issues and details is presented and a generic method for simulating contact between adjacent shells of revolution is described. Results are presented that identify the performance trends of the joints for a wide range of joint parameters. An important finding is that the redesigned joint exhibits significantly smaller O-ring gap changes and much less sensitivity to joint clearances than the original joint. For a wide range of joint parameters, the result presented indicate that the redesigned joint provides a much better pressure seal than the original joint.

Nemeth, Michael P.↗
NASA NTRS1994

A measurement system for large, complex software programs

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

Rone, Kyle Y.↗
NASA NTRS2012

Recent Results from the Lunar Reconnaissance Orbiter Mission and Plans for the Extended Science Phase

The Lunar Reconnaissance Orbiter spacecraft (LRO), launched on June 18, 2009, began with the goal of seeking safe landing sites for future robotic missions or the return of humans to the Moon as part of NASA's Exploration Systems Mission Directorate (ESMD). In addition, LRO's objectives included the search for surface resources and to investigate the Lunar radiation environment. After spacecraft commissioning, the ESMD phase of the mission began on September 15, 2009 and completed on September 15, 2010 when operational responsibility for LRO was transferred to NASA's Science Mission Directorate (SMD). The SMD mission was scheduled for 2 years and completed in September, 2012. The LRO mission has been extended for two years under SMD. The extended mission focuses on a new set of goals related to understanding the geologic history of the Moon, its current state, and what it can tell us about the evolution Of the Solar System. Here we will review the major results from the LRO mission for both exploration and science and discuss plans and objectives going forward including plans for the extended science phase out to 2014. Results from the LRO mission include but are not limited to the development of comprehensive high resolution maps and digital terrain models of the lunar surface; discoveries on the nature of hydrogen distribution, and by extension water, at the lunar poles; measurement of the day and night time temperature of the lunar surface including temperature down below 30 K in permanently shadowed regions (PSRs); direct measurement of Hg, H2, and CO deposits in the PSRs, evidence for recent tectonic activity on the Moon, and high resolution maps of the illumination conditions as the poles. The objectives for the second and extended science phases of the mission under SMD include: 1) understanding the bombardment history of the Moon, 2) interpreting Lunar geologic processes, 3) mapping the global Lunar regolith, 4) identifying volatiles on the Moon, and 5) measuring the Lunar atmosphere and radiation environment.

Vondrak, Richard↗
NASA NTRS2012

Results from the Lunar Reconnaissance Orbiter Mission and Plans for the Extended Science Mission

The Lunar Reconnaissance Orbiter spacecraft (LRO), launched on June 18,2009, began with the goal of seeking safe landing sites for future robotic missions or the return of humans to the Moon as part of NASA's Exploration Systems Mission Directorate (ESMD). In addition, LRO's objectives included the search for surface resources and the measurement of the lunar radiation environment. After spacecraft commissioning, the ESMD phase of the mission began on September 15, 2009 and was completed on September 15, 2010 when operational responsibility for LRO was transferred to NASA's Science Mission Directorate (SMD). The SMD mission was scheduled for 2 years and completed in September of 2012. Under SMD, the Science Mission focused on a new set of goals related to understanding the history of the Moon, its current state, and what it can tell us about the evolution of the Solar System. Having recently marked the completion of the two-year Science Mission, we will review here the major results from the LRO for both exploration and science and discuss plans and objectives for the Extended Science that will last until September, 2014. Some results from the LRO mission are: the development of comprehensive high resolution maps and digital terrain models of the lunar surface; discoveries on the nature of hydrogen distribution, and by extension water, at the lunar poles; measurement of the daytime and nighttime temperature of the lunar surface including temperature down below 30 K in permanently shadowed regions (PSRs); direct measurement of Hg, H2, and CO deposits in the PSRs; evidence for recent tectonic activity on the Moon; and high resolution maps of the illumination conditions at the poles.

Vondrak, Richard R.↗
NASA NTRS2018

Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis

The tropical rainforests are the largest reserves of terrestrial carbon and, therefore, the future of these rainforests is a question that is of immense importance in the geoscience research community. With the recent severe Amazonian droughts in 2005 and 2010 and on-going drought in the Congo region for more than two decades, there is growing concern that these forests could succumb to precipitation reduction, causing extensive carbon release and feedback to the carbon cycle. However, there is no single ecosystem model that quantifies the relationship between vegetation health in these rainforests and climatic factors. Small scale studies have used statistical correlation measure and simple linear regression to model climate-vegetation interactions, but suffer from the lack of comprehensive data representation as well as simplistic assumptions about dependency of the target on the covariates. In this paper we use genetic programming (GP) based symbolic regression for discovering equations that govern the vegetation climate dynamics in the rainforests. Expecting micro-regions within the rainforests to have unique characteristics compared to the overall general characteristics, we use a modified regression-tree based hierarchical partitioning of the space to build individual models for each partition. The discovery of these equations reveal very interesting characteristics about the Amazon and the Congo rainforests. Our method GP-tree shows that the rainforests exhibit tremendous resiliency in the face of extreme climatic events by adapting to changing conditions.

genetic programming↗
NASA NTRS2020

TOI-1338: TESS’ First Transiting Circumbinary Planet

We report the detection of the first circumbinary planet (CBP) found by Transiting Exoplanet Survey Satellite (TESS). The target, a known eclipsing binary, was observed in sectors 1 through 12 at 30 minute cadence and in sectors 4 through 12 at 2 minute cadence. It consists of two stars with masses of 1.1M(ʘ) and 0.3M(ʘ) on a slightly eccentric (0.16), 14.6 day orbit, producing prominent primary eclipses and shallow secondary eclipses. The planet has a radius of ∼6.9R(⊕) and was observed to make three transits across the primary star of roughly equal depths (∼0.2%) but different durations—a common signature of transiting CBPs. Its orbit is nearly circular (e≈0.09) with an orbital period of 95.2 days. The orbital planes of the binary and the planet are aligned to within ∼1°. To obtain a complete solution for the system, we combined the TESS photometry with existing ground-based radialvelocity observations in a numerical photometric-dynamical model. The system demonstrates the discovery potential of TESS for CBPs and provides further understanding of the formation and evolution of planets orbiting close binary stars.

Veselin B. Kostov↗
NASA NTRS2026

List of Commercial and Advanced Developmental Niobium-Based Alloys of the Space Age

This report compiles a list of commercial and developmental niobium-based alloys developed during the Space Age (late 1950s through mid-1970s) for extreme-temperature applications, including rocket engine thrust chambers, hypersonic re-entry thermal protection systems, and space fission reactor loops. Niobium (Nb) was widely pursued because it provided the lowest density (~8.6 g/cc) among the primary refractory metals, a high melting temperature (~2470°C), exceptional low-temperature ductility, good formability, and compatibility with liquid alkali metals. An evaluation of physical metallurgy mechanisms, focusing on solid-solution strengthening via heavy refractory solutes (W, Mo, Ta), dual-purpose reactive solutes (Hf, Zr, Ti), and dispersion strengthening using carbides, nitrides, and oxides is presented. Additionally, the report compares Western and Soviet Union metallurgical approaches, explaining how supply chain factors and manufacturing infrastructure influenced element selection, interstitial chemistry, and alloy identification/naming conventions. Cataloging these historical alloy chemical compositions serves as a foundational reference for modern alloy additive manufacturing, thermodynamic CALPHAD modeling, and machine-learning discovery pipelines for next-generation extreme-environment niobium-based alloys.

Physical Metallurgy↗
DOE OSTI2023

Charge order and superconductivity in a two-band model for infinite-layer nickelates

The recent discovery of superconductivity in infinite-layer nickelates has drawn considerable attention; however, a consensus on the fundamental building blocks and common ingredients necessary to understand and describe their ground states and emergent properties is lacking. A series of experimental and theoretical studies have suggested that an effective two-band Hubbard model with Ni 3d x 2 -y 2 and rare-earth (R) 5d character may describe the low-energy physics. In this report we study the ground state properties of this two-band model on four-leg cylinders using the density-matrix renormalization group (DMRG) technique to better grasp whether such a simple model can embody the essential physics. A key difference compared to single-band Hubbard materials is that the system is self-doped: even at overall half-filling, the R-band acts as an electron reservoir, hole-doping the Ni-layer and fundamentally altering the physics expected from an undoped antiferromagnet. On the four-leg cylinder, the ground state is consistent with a Luttinger liquid, with anti-phase modulations of the charge density in the Ni- and R-layers having corresponding wavevectors that lock together. Light hole doping away from 1/2 filling releases the locking between the Ni and the R charge modulations, as the electron density in the R-band decreases and eventually becomes exhausted at a hole doping concentration that depends sensitively on the effective splitting between the Ni and the R orbitals. The ground state of the doped system is consistent with a Luther-Emery liquid, possessing quasi-long-range superconducting correlations in the Ni layer, similar to the single-band Hubbard model. Our results are consistent with experimental observations and may help to reveal the microscopic mechanism for pairing and other emergent properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗
DOE OSTI2021

Turbulent field fluctuations in gyrokinetic and fluid plasmas

A key uncertainty in the design and development of magnetic confinement fusion energy reactors is predicting edge plasma turbulence. An essential step in overcoming this uncertainty is the validation in accuracy of reduced turbulent transport models. Drift-reduced Braginskii two-fluid theory is one such set of reduced equations that has for decades simulated boundary plasmas in experiment, but significant questions exist regarding its predictive ability. To this end, using a novel physics-informed deep learning framework, we demonstrate the first ever direct quantitative comparisons of turbulent field fluctuations between electrostatic two-fluid theory and electromagnetic gyrokinetic modelling with good overall agreement found in magnetized helical plasmas at low normalized pressure. This framework is readily adaptable to experimental and astrophysical environments, and presents a new technique for the numerical validation and discovery of reduced global plasma turbulence models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Teaching AI when to care about gender

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) concerned with solving language tasks by modeling large amounts of textual data. Some NLP techniques use word embeddings which are semantic models where machine learning (ML) is used to learn to cluster semantically related words by learning about word co-occurrences in the original training text. Unfortunately, these models tend to reflect or even exaggerate biases that are present in the training corpus. Here we describe the Word Embedding Navigator (WEN), which is a tool for exploring word embedding models. We examine a specific potential use case for this tool: interactive discovery and neutralization of gender bias in word embedding models, and compare this human-in-the-loop approach to reducing bias in word embeddings with a debiasing post-processing technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗
DOE OSTI2026

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗