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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

Poll, Scott↗
NASA NTRS2017

A Status of U-Class Earth Science Instruments at JPL

With advancements in CubeSat technologies and low-cost launch opportunities, CubeSats could play a role in meeting NASA’s key Earth science measurement objectives, especially in extreme weather and ecosystem processes. In this paper, we discuss the development of “science grade” hyperspectral imager, microwave spectrometer, IR sounder, and Ka-band radar instruments at JPL. They are scheduled to launch in early to late 2018 while the hyperspectral imager is being developed for airborne flights and for space in the future. The limitations in power, mass, and volume imposed by the CubeSat platform required the identification of new technologies in order to miniaturize instruments into a specific form factor. In conclusion, we will summarize strategies to implement small and low-cost instruments and suggest an architecture for enabling a constellation of U-class instruments.

Hyon, Jason J.↗
DOE OSTI2026

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗
DOE OSTI2020

Observation of Electrically Tunable van Hove Singularities in Twisted Bilayer Graphene from NanoARPES

The possibility of triggering correlated phenomena by placing a singularity of the density of states near the Fermi energy remains an intriguing avenue toward engineering the properties of quantum materials. Twisted bilayer graphene is a key material in this regard because the superlattice produced by the rotated graphene layers introduces a van Hove singularity and flat bands near the Fermi energy that cause the emergence of numerous correlated phases, including superconductivity. Direct demonstration of electrostatic control of the superlattice bands over a wide energy range has, so far, been critically missing. This work examines the effect of electrical doping on the electronic band structure of twisted bilayer graphene using a back-gated device architecture for angle-resolved photoemission measurements with a nano-focused light spot. A twist angle of 12.2° is selected such that the superlattice Brillouin zone is sufficiently large to enable identification of van Hove singularities and flat band segments in momentum space. Finally, the doping dependence of these features is extracted over an energy range of 0.4 eV, expanding the combinations of twist angle and doping where they can be placed at the Fermi energy and thereby induce new correlated electronic phases in twisted bilayer graphene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Project Integration Architecture: Implementation of the CORBA-Served Application Infrastructure

The Project Integration Architecture (PIA) has been demonstrated in a single-machine C++ implementation prototype. The architecture is in the process of being migrated to a Common Object Request Broker Architecture (CORBA) implementation. The migration of the Foundation Layer interfaces is fundamentally complete. The implementation of the Application Layer infrastructure for that migration is reported. The Application Layer provides for distributed user identification and authentication, per-user/per-instance access controls, server administration, the formation of mutually-trusting application servers, a server locality protocol, and an ability to search for interface implementations through such trusted server networks.

Jones, William Henry↗
NASA NTRS2005

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Wong, Derek↗
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.

Martin, Rodney Alexander↗
DOE OSTI2025

Grey-Box System Identification of Grid-Forming Inverters

This paper demonstrates the use of grey-box system identification methods for simplifying and understanding the nonlinear power dynamics of grid-forming inverters (GFMs). The power and frequency outputs of complex high-order GFM models are fed into system identification software in order to fit them to a predetermined LTI system and learn system parameters such as (synthetic) inertia and droop constants. The same process is then run for a high-order synchronous generator model, and the outputs are fit to the same set of LTI equations. Simulation of a network of GFM inverters with diverse control architecture is also performed for the same process. The intent is threefold: first, to demonstrate the appropriateness of unified LTI models for describing the power and frequency dynamics of individual resources and connected networks, in order to facilitate analysis of larger heterogeneous networked systems; second, to discover the relationship between internal control parameters of GFMs and their externally observed values; and third, to validate that grey-box data-driven system identification techniques can be a valuable tool to discover the values of important parameters in the absence of explicit vendor models.

analytical models↗
DOE OSTI2023

Expression of blue pigment synthetase a from Streptomyces lavenduale reveals insights on the effects of refactoring biosynthetic megasynthases for heterologous expression in Escherichia coli .

High GC bacteria from the genus Streptomyces harbor expansive secondary metabolism. The expression of biosynthetic proteins and the characterization and identification of biological "parts" for synthetic biology purposes from such pathways are of interest. However, the high GC content of proteins from actinomycetes in addition to the large size and multi-domain architecture of many biosynthetic proteins (such as non-ribosomal peptide synthetases; NRPSs, and polyketide synthases; PKSs often called "megasynthases") often presents issues with full-length translation and folding. Here we evaluate a non-ribosomal peptide synthetase (NRPS) from Streptomyces lavenduale, a multidomain "megasynthase" gene that comes from a high GC (72.5%) genome. While a preliminary step in revealing differences, to our knowledge this presents the first head-to-head comparison of codon-optimized sequences versus a native sequence of proteins of streptomycete origin heterologously expressed in E. coli. We found that any disruption in co-translational folding from codon mismatch that reduces the titer of indigoidine is explainable via the formation of more inclusion bodies as opposed to compromising folding or posttranslational modification in the soluble fraction. In conclusion, this result supports that one could apply any refactoring strategies that improve soluble expression in E. coli without concern that the protein that reaches the soluble fraction is differentially folded.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

A Notional Example of Understanding Human Exploration Traverses on the Lunar Surface

Mr. Gruener received an M.S. in physical science, with an emphasis in planetary geology, from the University of Houston-Clear Lake in 1994. He then began working with NASA JSC.s Solar System Exploration Division on the development of prototype planetary science instruments, the development of a mineral-based substrate for nutrient delivery to plant growth systems in bio-regenerative life support systems, and in support of the Mars Exploration Rover missions in rock and mineral identification. In 2004, Mr. Gruener again participated in a renewed effort to plan and design missions to the Moon, Mars, and beyond. He participated in many exploration planning activities, including NASA.s Exploration Systems Architecture Study (ESAS), Global Exploration Strategy Workshop, Lunar Architecture Team 1 and 2, Constellation Lunar Architecture Team, the Global Point of Departure Lunar Exploration Team, and the NASA Advisory Council (NAC) Workshop on Science Associated with the Lunar Exploration Architecture. Mr. Gruener has also been an active member of the science team supporting NASA.s Desert Research and Technology Studies (RATS).

Gruener, John↗
NASA NTRS2021

Functional Autonomy Challenges in Sampling for an Europa Lander Mission

We present a baseline approach to Functional Autonomyfor the purpose of conducting excavation and samplingbehaviors in a proposed Europa Lander mission. Aspects ofthe problems of site selection, excavation progress tracking,and fault identification are related; with particular emphasison parameters peculiar to an icy moon environment. Firstpass approaches to addressing these challenges are presentedin isolation, while motivating the current development goal ofproducing a general Functional Autonomy architecture thatallows state estimation, fault diagnosis, isolation, & recovery(FDIR), and adaptive behaviors to be formulated in concert.

Backes, Paul↗
DOE OSTI2021

Solid-state batteries and the critical role of interfaces

The Grand Challenge for the next generation of energy storage technologies is no longer the identification of electroactive cathode or anode materials thanks to extensive worldwide synthesis efforts along with theory and modeling like the Materials Project.1 Instead, the critical challenges revolve around assembling materials in the right architecture to achieve maximum performance and cell life at reasonable temperatures and pressures. Nowhere is this more critical than on the next generation of energy storage technologies revolving around all solid-state batteries. These batteries are the ultimate challenge for materials science requiring new ways to assemble multiple dissimilar materials such that: (1) interfaces are optimized to facilitate ion motion across the different compounds while (2) maintaining chemical stability and (3) simultaneously preserving the crystal structures of each phase during (4) large volume changes due to shuttling of lithium, at (5) room temperature and under (6) atmospheric pressure. To address these requirements will require insights and expertise from research fields outside the traditional lithium-ion battery community such as solid oxide fuel cells, synthesis science, barrier layers, interface formers, sintering, and mechanical properties.

25 ENERGY STORAGE↗
DOE OSTI2024

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predictive model for real-time energy disaggregation using long short-term memory

To provide affordable energy-saving solutions for the small and medium-sized manufacturers (SMMs), we propose a unified framework for generating predictive models that support real-time disaggregation of power consumption from combined inputs, enabling automatic machine state identification simultaneously for joint analysis of energy usage patterns. Further, the proposed framework transforms raw power consumption into a time series with look-back and bootstrap capabilities for historical pattern detection, while a learning architecture utilizes the stacked long short-term memory (LSTM) layers as encoders for embedding generation with sequential awareness. Experimental results demonstrate 93.65% minimum accuracy in ideal case of real-time energy usage and machine state prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗
NASA NTRS2000

The A/P axis in echinoderm ontogeny and evolution: evidence from fossils and molecules

Even though echinoderms are members of the Bilateria, the location of their anterior/posterior axis has remained enigmatic. Here we propose a novel solution to the problem employing three lines of evidence: the expression of a posterior class Hox gene in the coeloms of the nascent adult body plan within the larva; the anatomy of certain early fossil echinoderms; and finally the relation between endoskeletal plate morphology and the associated coelomic tissues. All three lines of evidence converge on the same answer, namely that the location of the adult mouth is anterior, and the anterior/posterior axis runs from the mouth through the adult coelomic compartments. This axis then orients the animal such that there is but a single plane of symmetry dividing the animal into left and right halves. We tentatively hypothesize that this plane of symmetry is positioned along the dorsal/ventral axis. These axis identifications lead to the conclusion that the five ambulacra are not primary body axes, but instead are outgrowths from the central anterior/posterior axis. These identifications also shed insight into several other evolutionary mysteries of various echinoderm clades such as the independent evolution of bilateral symmetry in irregular echinoids, but do not elucidate the underlying mechanisms of the adult coelomic architecture.

Non-NASA Center↗
NASA NTRS2007

An Airborne Communications Roadmap for the U.S. Federal Air Marshal Service: Overview and Status

Following the events of September 11, 2001, the responsibilities, operations and numbers of the U.S. Federal Air Marshal Service (FAMS) wer e greatly expanded. With this expansion, new critical research and te chnology needs were identified, including the need for air to ground telecommunications capabilities. To address this need, the FAMS has cr eated a working group to develop, deploy and enhance aviation communi cations with respect to security and law enforcement. This paper presents the working group's progress to date in generating a FAMS air-gro und communications roadmap identifying expected communications servic es, technology maturity, and technology gaps over a timeline. The paper includes a communications preliminary requirements summary and syst em performance characteristics needed to meet identified operational needs. The system engineering process utilized is presented beginning with the identification of users, their operational needs and relevant constraints. The operational needs are translated to desired airbor ne communications services. System technical performance requirements associated with the identified services are summarized. In addition, notional communications architectures addressing the requirements are presented. Finally, future plans to identify and assess potential ca ndidate systems and their associated technical architectures, gaps and barriers to implementation are discussed. The paper addresses the cu rrent, near term (within 5 years) and far term (10 years) timeframes for such an airborne communications system.

Martzaklis, Konstantinos S.↗
DOE OSTI2022

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Blanchard, Andrew E.↗