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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Conceptual Design of a Communication-Based Deep Space Navigation Network

As the need grows for increased autonomy and position knowledge accuracy to support missions beyond Earth orbit, engineers must push and develop more advanced navigation sensors and systems that operate independent of Earth-based analysis and processing. Several spacecraft are approaching this problem using inter-spacecraft radiometric tracking and onboard autonomous optical navigation methods. This paper proposes an alternative implementation to aid in spacecraft position fixing. The proposed method Network-Based Navigation technique takes advantage of the communication data being sent between spacecraft and between spacecraft and ground control to embed navigation information. The navigation system uses these packets to provide navigation estimates to an onboard navigation filter to augment traditional ground-based radiometric tracking techniques. As opposed to using digital signal measurements to capture inherent information of the transmitted signal itself, this method relies on the embedded navigation packet headers to calculate a navigation estimate. This method is heavily dependent on clock accuracy and the initial results show the promising performance of a notional system.

Anzalone, Evan J.↗
NASA NTRS2013

Shock Position Control for Mode Transition in a Turbine Based Combined Cycle Engine Inlet Model

A dual flow-path inlet for a turbine based combined cycle (TBCC) propulsion system is to be tested in order to evaluate methodologies for performing a controlled inlet mode transition. Prior to experimental testing, simulation models are used to test, debug, and validate potential control algorithms which are designed to maintain shock position during inlet disturbances. One simulation package being used for testing is the High Mach Transient Engine Cycle Code simulation, known as HiTECC. This paper discusses the development of a mode transition schedule for the HiTECC simulation that is analogous to the development of inlet performance maps. Inlet performance maps, derived through experimental means, describe the performance and operability of the inlet as the splitter closes, switching power production from the turbine engine to the Dual Mode Scram Jet. With knowledge of the operability and performance tradeoffs, a closed loop system can be designed to optimize the performance of the inlet. This paper demonstrates the design of the closed loop control system and benefit with the implementation of a Proportional-Integral controller, an H-Infinity based controller, and a disturbance observer based controller; all of which avoid inlet unstart during a mode transition with a simulated disturbance that would lead to inlet unstart without closed loop control.

Csank, Jeffrey T.↗
NASA NTRS2013

Exploring Mission Concepts with the JPL Innovation Foundry A-Team

The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts called the A-Team. The A-Team combines innovative collaborative methods with subject matter expertise and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an A-Team study. Methods are grouped by Concept Maturity Level (CML), from 1 through 3, including idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for each CML are presented, and the key team roles are described from two points of view: innovative methods and technical expertise. A-Team roles for providing innovative methods include the facilitator, study lead, and assistant study lead. A-Team roles for providing technical expertise include the architect, lead systems engineer, and integration engineer. In addition to these key roles, each A-Team study is uniquely staffed to match the study topic and scope including subject matter experts, scientists, technologists, flight and instrument systems engineers, and program managers as needed. Advanced analysis and collaborative engineering tools (e.g. cost, science traceability, mission design, knowledge capture, study and analysis support infrastructure) are also under development for use in A-Team studies and will be discussed briefly. The A-Team facilities provide a constructive environment for innovative ideas from all aspects of mission formulation to eliminate isolated studies and come together early in the development cycle when they can provide the biggest impact. This paper provides an overview of the A-Team, its study processes, roles, methods, tools and facilities.

Team Eureka↗
NASA NTRS2016

Extended Bright Bodies - Flight and Ground Software Challenges on the Cassini Mission at Saturn

Extended bright bodies in the Saturn environment such as Saturn's rings, the planet itself, and Saturn's satellites near the Cassini spacecraft may interfere with the star tracker's ability to find stars. These interferences can create faulty spacecraft attitude knowledge, which would decrease the pointing accuracy or even trip a fault protection response on board the spacecraft. The effects of the extended bright body interference were observed in December of 2000 when Cassini flew by Jupiter. Based on this flight experience and expected star tracker behavior at Saturn, the Cassini AACS operations team defined flight rules to suspend the star tracker during predicted interference windows. The flight rules are also implemented in the existing ground software called Kinematic Predictor Tool to create star identification suspend commands to be uplinked to the spacecraft for future predicted interferences. This paper discusses the details of how extended bright bodies impact Cassini's acquisition of attitude knowledge, how the observed data helped the ground engineers in developing flight rules, and how automated methods are used in the flight and ground software to ensure the spacecraft is continuously operated within these flight rules. This paper also discusses how these established procedures will continue to be used to overcome new bright body challenges that Cassini will encounter during its dips inside the rings of Saturn for its final orbits of a remarkable 20-year mission at Saturn.

Sung, Tina S.↗
DOE OSTI2013

The Walk Forward of Sun-Grown Green-Thing Energy

Representing the Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio), this document is one of the entries in the Ten Hundred and One Word Challenge and was awarded "Best Tagline." As part of the challenge, the 46 Energy Frontier Research Centers were invited to represent their science in images, cartoons, photos, words and original paintings, but any descriptions or words could only use the 1000 most commonly used words in the English language, with the addition of one word important to each of the EFRCs and the mission of DOE: energy. The mission of C3Bio at Purdue University is to integrate fundamental knowledge and enable technologies for catalytic conversion of engineered biomass to advanced biofuels and value-added products.

09 BIOMASS FUELS↗
DOE OSTI2019

Global Benefits: the LBNF/DUNE Project

LBNF/DUNE is an international mega-science project hosted by the Department of Energy’s Fermilab. http://www.fnal.gov/dune It will send a beam of tiny particles called neutrinos 1,300 kilometers straight through the earth from Fermilab to the Sanford Underground Research Facility. It will help solve some of the deepest mysteries of the universe and boost innovation while training young people around the world in science, engineering and computing. Scientists and engineers at universities and laboratories are working hand-in-hand with companies to design electronics, build hardware and develop computer programs for the project. LBNF and DUNE will create jobs as well as demand for materials, products and services. Students in dozens of countries around the world will start their careers in science and engineering with this project, and then transfer their knowledge into industry, medicine, computer science and many other fields.

43 PARTICLE ACCELERATORS↗
NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗
DOE OSTI2024

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Ford/BASF/UM Activities in Support of the Hydrogen Storage Engineering Center of Excellence

Widespread adoption of hydrogen as a vehicular fuel depends critically on the development of low-cost, on-board hydrogen storage technologies capable of achieving high energy densities and fast kinetics for hydrogen uptake and release. As present-day technologies -- which rely on physical storage methods such as compressed hydrogen -- are incapable of attaining established Department of Energy (DOE) targets, development of materials-based approaches for storing hydrogen have garnered increasing attention. Material-based storage technologies have potential to store hydrogen beyond twice the density of liquid hydrogen. To hasten development of these ‘hydride’ materials, the DOE previously established three centers of excellence for materials storage R&D associated with the key classes of materials: metal hydrides, chemical hydrogen, and adsorbents. While these centers made progress in identifying new storage materials, the challenges associated with the engineering of the system around a candidate storage material are in need of further advancement. In 2009 the DOE established the Hydrogen Storage Engineering Center of Excellence with the objective of developing innovative engineering concepts for materials-based hydrogen storage systems. As a partner in the Hydrogen Storage Engineering Center of Excellence, the Ford-UM-BASF team conducted a multi-faceted research program that addresses key engineering challenges associated with the development of materials-based hydrogen storage systems. First, we developed a novel framework that allowed for a material-based hydrogen storage system to be modeled and operated within a virtual fuel cell vehicle. This effort resulted in the ability to assess dynamic operating parameters and interactions between the storage system and fuel cell power plant, including the evaluation of performance throughout various drive cycles. Second, we engaged in cost modeling of various incarnations of the storage systems. This analysis revealed cost gaps and opportunities that identified a storage system that was lower cost than a 700 bar compressed system. Finally, we led the HSECoE efforts devoted to characterizing and enhancing metal organic framework (MOF) storage materials. This report serves as a final documentation of the Ford-UM-BASF project contributions to the HSECoE during the 6-year timeframe of the Center. The activities of the HSECoE have impacted the broader goals of the DOE-EERE and USDRIVE, leading to improved understanding in the engineering of materials-based hydrogen storage systems. This knowledge is a prerequisite to the development of a commercially-viable hydrogen storage system.

08 HYDROGEN↗
DOE OSTI2024

Technical Language Processing of Nuclear Power Plants Equipment Reliability Data

Operating nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) element data that contain information about the status of components, assets, and systems. Some of this information is in textual form where the occurrence of abnormal events or maintenance activities are described. Analyses of NPP textual data via natural language processing (NLP) methods have expanded in the last decade, and only recently the true potential of such analyses has emerged. So far, applications of NLP methods have been mostly limited to classification and prediction in order to identify the nature of the given textual element (e.g., safety or non-safety relevant). In this paper, we target a more complex problem: the automatic generation of knowledge based on a textual element in order to assist system engineers in assessing an asset’s historical health performance. The goal is to assist system engineers in the identification of anomalous behaviors, cause–effect relations between events, and their potential consequences, and to support decision-making such as the planning and scheduling of maintenance activities. “Knowledge extraction” is a very broad concept whose definition may vary depending on the application context. In our particular context, it refers to the process of examining an ER textual element to identify the systems or assets it mentions and the type of event it describes (e.g., component failure or maintenance activity). In addition, we wish to identify details such as measured quantities and temporal or cause–effect relations between events. This paper describes how ER textual data elements are first preprocessed to handle typos, acronyms, and abbreviations, then machine learning (ML) and rule-based algorithms are employed to identify physical entities (e.g., systems, assets, and components) and specific phenomena (e.g., failure or degradation). A few applications relevant from an NPP ER point of view are presented as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Heterostructure engineering in electrode materials for sodium-ion batteries: Recent progress and perspectives

Sodium-ion batteries (SIBs) have stepped into the spotlight as a promising alternative to lithium-ion batteries for large-scale energy storage systems. However, SIB electrode materials, in general, have inferior performance than their lithium counterparts because Na + is larger and heavier than Li + . Heterostructure engineering is a promising strategy to overcome this intrinsic limitation and achieve practical SIBs. We provide a brief review of recent progress in heterostructure engineering of electrode materials and research on how the phase interface influences Na + storage and transport properties. Efficient strategies for the design and fabrication of heterostructures (in situ methods) are discussed, with a focus on the heterostructure formation mechanism. The heterostructure's influence on Na + storage and transport properties arises primarily from local distortions of the structure and chemomechanical coupling at the phase interface, which may accelerate ion/electron diffusion, create additional active sites, and bolster structural stability. Finally, we offer our perspectives on the existing challenges, knowledge gaps, and opportunities for the advancement of heterostructure engineering as a means to develop practical, high-performance sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2014

Programmed Nanomaterial Assemblies in Large Scales: Applications of Synthetic and Genetically- Engineered Peptides to Bridge Nano-Assemblies and Macro-Assemblies

Work is reported in these areas: Large-scale & reconfigurable 3D structures of precise nanoparticle assemblies in self-assembled collagen peptide grids; Binary QD-Au NP 3D superlattices assembled with collagen-like peptides and energy transfer between QD and Au NP in 3D peptide frameworks; Catalytic peptides discovered by new hydrogel-based combinatorial phage display approach and their enzyme-mimicking 2D assembly; New autonomous motors of metal-organic frameworks (MOFs) powered by reorganization of self-assembled peptides at interfaces; Biomimetic assembly of proteins into microcapsules on oil-in-water droplets with structural reinforcement via biomolecular recognition-based cross-linking of surface peptides; and Biomimetic fabrication of strong freestanding genetically-engineered collagen peptide films reinforced by quantum dot joints. We gained the broad knowledge about biomimetic material assembly from nanoscale to microscale ranges by coassembling peptides and NPs via biomolecular recognition. We discovered: Genetically-engineered collagen-like peptides can be self-assembled with Au NPs to generate 3D superlattices in large volumes (> μm{sup 3}); The assembly of the 3D peptide-Au NP superstructures is dynamic and the interparticle distance changes with assembly time as the reconfiguration of structure is triggered by pH change; QDs/NPs can be assembled with the peptide frameworks to generate 3D superlattices and these QDs/NPs can be electronically coupled for the efficient energy transfer; The controlled assembly of catalytic peptides mimicking the catalytic pocket of enzymes can catalyze chemical reactions with high selectivity; and, For the bacteria-mimicking swimmer fabrication, peptide-MOF superlattices can power translational and propellant motions by the reconfiguration of peptide assembly at the MOF-liquid interface.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on “omics” driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in “omics” technologies, compare the pros and cons of the different “omics” technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of “omics” technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of “omics” technologies to agricultural and food biotechnology, and review the impact of “omics” on current COVID-19 research.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Spacecraft Thermal Control Coatings References

The successful thermal design of spacecraft depends in part on a knowledge of the solar absorption and hemispherical emittance of the thermal control coatings used in and on the spacecraft. Goddard Space Flight Center has had since its beginning a group whose mission has been to provide thermal/optical properties data of thermal control coatings to thermal engineers. This handbook represents a summary of the data and knowledge accumulated over many years at GSFC.

Kauder, Lonny↗
NASA NTRS2014

U.S. Spacesuit Knowledge Capture Accomplishments in Fiscal Years 2012 and 2013

The NASA U.S. spacesuit knowledge capture (KC) program has been in operations since the beginning 2008. The program was designed to augment engineers and others with information about spacesuits in a historical way. A multitude of seminars have captured spacesuit history and knowledge over the last six years of the programs existence. Subject matter experts have provided lectures and were interviewed to help bring the spacesuit to life so that lessons learned will never be lost. As well, the program concentrated in reaching out to the public and industry by making the recorded events part of the public domain through the NASA technical library via You Tube media. The U.S. spacesuit KC topics have included lessons learned from some of the most prominent spacesuit experts and spacesuit users including current and former astronauts. The events have enriched the spacesuit legacy knowledge from Gemini, Apollo, Skylab, Space Shuttle and International Space Station Programs. As well, expert engineers and scientists have shared their challenges and successes to be remembered. The last few years have been some of the most successful years of the KC program program's life with numerous recordings and releases to the public. It is evidenced by the thousands that have view the recordings online. This paper reviews the events accomplished and archived over Fiscal Years 2012 and 2013 and highlights a few of the most memorable ones. This paper also communicates ways to access the events that are available internally to NASA as well as in the public domain.

Chullen, Cinda↗
DOE OSTI2021

Advanced Engine and Fuel Technologies FY2020 Annual Progress Report

In support of the Vehicle Technology Office’s goal for future U.S. economic growth, the Advanced Engine and Fuel Technologies Program focuses early-stage research and development on improving the understanding of combustion processes, fuel properties, and emissions control technologies, generating knowledge and insight necessary for industry to develop the next generation of engines and fuels for the efficient, cost-effective, and secure transportation of people and goods across America.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

Lessons Learned on University Education Programs of Chemical Engineering Principles for Nuclear Plant Operations - 13588

University education aims to supply qualified human resources for industries. In complex large scale engineering systems such as nuclear power plants, the importance of qualified human resources cannot be underestimated. The corresponding education program should involve many topics systematically. Recently a nuclear engineering program has been initiated in Dongguk University, South Korea. The current education program focuses on undergraduate level nuclear engineering students. Our main objective is to provide industries fresh engineers with the understanding on the interconnection of local parts and the entire systems of nuclear power plants and the associated systems. From the experience there is a huge opportunity for chemical engineering disciple in the context of giving macroscopic overview on nuclear power plant and waste treatment management by strengthening the analyzing capability of fundamental situations. (authors)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1988

Portable inference engine: An extended CLIPS for real-time production systems

The present C-Language Integrated Production System (CLIPS) architecture has not been optimized to deal with the constraints of real-time production systems. Matching in CLIPS is based on the Rete Net algorithm, whose assumption of working memory stability might fail to be satisfied in a system subject to real-time dataflow. Further, the CLIPS forward-chaining control mechanism with a predefined conflict resultion strategy may not effectively focus the system's attention on situation-dependent current priorties, or appropriately address different kinds of knowledge which might appear in a given application. Portable Inference Engine (PIE) is a production system architecture based on CLIPS which attempts to create a more general tool while addressing the problems of real-time expert systems. Features of the PIE design include a modular knowledge base, a modified Rete Net algorithm, a bi-directional control strategy, and multiple user-defined conflict resolution strategies. Problems associated with real-time applications are analyzed and an explanation is given for how the PIE architecture addresses these problems.

Le, Thach↗