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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Robust Low-Cost Cathode for Commercial Applications

Under funding from the NASA Commercial Technology Office, a cathode assembly was designed, developed, fabricated, and tested for use in plasma sources for ground-based materials processing applications. The cathode development activity relied on the large prior NASA investment and successful development of high-current, high-efficiency, long-life hollow cathodes for use on the International Space Station Plasma Contactor System. The hollow cathode was designed and fabricated based on known engineering criteria and manufacturing processes for compatibility with the requirements of the plasma source. The transfer of NASA GRC-developed hollow cathode technology for use as an electron emitter in the commercial plasma source is anticipated to yield a significant increase in process control, while eliminating the present issues of electron emitter lifetime and contamination.

Patterson, Michael J.↗
NASA NTRS2014

Possible Mechanisms for Turbofan Engine Ice Crystal Icing at High Altitude

A thermodynamic model is presented to describe possible mechanisms of ice formation on unheated surfaces inside a turbofan engine compression system from fully glaciated ice crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of ice formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted ice crystals, the ice structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of ice crystals, the ice structure is formed from accumulation of un-melted ice crystals with relatively weak bonding to the surface. The model captures important qualitative trends of the fundamental ice-crystal icing phenomenon reported earlier1,2 from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine ice crystal icing test3 conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of ice formation occurred during the test, and (2) the model has captured some important qualitative trend of turning on (or off) the ice crystal ice formation process in the tested engine low pressure compressor (LPC) targeted area under different icing conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.

Crystal Icing↗
DOE OSTI2023

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, especially where protective candidates can be rapidly identified or developed for emerging biothreats and escape variants. Current cutting-edge technologies for this purpose still rely on pathogen-exposed convalescent volunteers and a large screening effort to find a proverbial needle in a haystack. Computational design of protective antibodies based on pre-existing templates skips those requirements and allows for greater control over the breadth and target epitope, while also co-optimizing for potency and developability or other biophysical characteristics. We approached this problem by building and expanding an in vitro experimental rapid antibody production and characterization pipeline to support development of an autonomous, closed loop, active learning software system based on structural simulation and ground truth experimental data to design and evaluate antibody antigen interactions. Starting from early in the pandemic, we targeted SARS-CoV-2, the causative agent of COVID-19, by re-purposing neutralizing antibodies against SARS-CoV-1 that had been identified in the wake of that outbreak in the early 2000’s. We successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro, where the antibodies were generated externally and tested through conventional binding and neutralization assays internally or with collaborators. As antibodies were identified from the blood of humans infected with SARS-CoV-2, we shifted to collaborate with academic partners to develop improved versions of their human-derived antibodies. This work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, enabled by on demand innovation to our screening pipeline, we computationally designed and experimentally characterized derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Due to tight integration of computational design and experimental evaluation, we were able to identify a pair of designs with potent neutralization of the main targets Omicron BA.1 and BA.1.1; but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23. While earlier design campaigns were substantially outsourced, we have engineered better and faster processes internally to better compliment, calibrate, and speed computational designs. As part of the follow-on GUIDE program, we will stand up a rapid and high-throughput antibody production and characterization facility staffed with the expertise and capabilities to foster our current collaboration across PLS and ENG as well as other partnerships toward computational design of biologics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

STAEBL: Structural tailoring of engine blades, phase 2

The Structural Tailoring of Engine Blades (STAEBL) program was initiated at NASA Lewis Research Center in 1980 to introduce optimal structural tailoring into the design process for aircraft gas turbine engine blades. The standard procedure for blade design is highly iterative with the engineer directly providing most of the decisions that control the design process. The goal of the STAEBL program has been to develop an automated approach to generate structurally optimal blade designs. The program has evolved as a three-phase effort with the developmental work being performed contractually by Pratt & Whitney Aircraft. Phase 1 was intended as a proof of concept in which two fan blades were structurally tailored to meet a full set of structural design constraints while minimizing DOC+I (direct operating cost plus interest) for a representative aircraft. This phase was successfully completed and was reported in reference 1 and 2. Phase 2 has recently been completed and is the basis for this discussion. During this phase, three tasks were accomplished: (1) a nonproprietary structural tailoring computer code was developed; (2) a dedicated approximate finite-element analysis was developed; and (3) an approximate large-deflection analysis was developed to assess local foreign object damage. Phase 3 is just beginning and is designed to incorporated aerodynamic analyses directly into the structural tailoring system in order to relax current geometric constraints.

Hirschbein, M. S.↗
DOE OSTI2020

Unconventional Catalytic Approaches to Ammonia Synthesis

Ammonia is a critically important industrial chemical and is largely responsible for sustaining the growing global population. To provide ammonia to underdeveloped regions and/or regions far from industrial production hubs, modular systems have been targeted and often involve unconventional production methodologies. These novel approaches for ammonia production can tap renewable resources at smaller scales located at the point of use, while decreasing the CO 2 footprint. Plasma-assisted catalysis and electrochemical ammonia synthesis have promise owing to their atmospheric pressure and low-temperature operation conditions and the ability to construct units at scales desired for modularization. Fundamental and applied studies are underway to assess these processes, although many unknowns remain. In this review, we discuss recent developments and opportunities for unconventional ammonia synthesis with a focus on plasma-stimulated systems.

42 ENGINEERING↗
NASA NTRS1992

An intelligent decomposition approach for efficient design of non-hierarchic systems

The design process associated with large engineering systems requires an initial decomposition of the complex systems into subsystem modules which are coupled through transference of output data. The implementation of such a decomposition approach assumes the ability exists to determine what subsystems and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is quite often an extremely complex task which may be beyond human ability to efficiently achieve. Further, in optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the optimal solution. The ability to determine 'weak' versus 'strong' coupling strengths would aid the designer in deciding which couplings could be permanently removed from consideration or which could be temporarily suspended so as to achieve computational savings with minimal loss in solution accuracy. An approach that uses normalized sensitivities to quantify coupling strengths is presented. The approach is applied to a coupled system composed of analysis equations for verification purposes.

Bloebaum, Christina L.↗
NASA NTRS2016

Possible Mechanisms for Turbofan Engine Ice Crystal Icing at High Altitude

A thermodynamic model is presented to describe possible mechanisms of ice formation on unheated surfaces inside a turbofan engine compression system from fully glaciated ice crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of ice formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted ice crystals, the ice structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of ice crystals, the ice structure is formed from accumulation of un-melted ice crystals with relatively weak bonding to the surface. The model captures important qualitative trends of the fundamental ice-crystal icing phenomenon reported earlier (Refs. 1 and 2) from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine ice crystal icing test (Ref. 3) conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of ice formation occurred during the test, and (2) the model has captured some important qualitative trend of turning on (or off) the ice crystal ice formation process in the tested engine low pressure compressor (LPC) targeted area under different icing conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.

Crystal Icing↗
DOE OSTI2021

A microscopic and crystallographic study of proton irradiated alloy 718

Solution annealing and age hardening are important processes for achieving good engineering and chemical properties of alloy 718. The composition of alloy 718 also plays an important role as it can affect both mechanical (γ”- and γ’-phase formation) and irradiation behaviors. Therefore, in this study five different sets of alloy 718 samples with two different chemical compositions were fabricated using different processing conditions and irradiated up to 4 dpa. Based on the effects of irradiation on the microstructural data of γ”- and γ’-phases, irradiation-induced dislocation statistics, and crystallographic data, it can be inferred that the samples processed at high solution annealing temperature (1093°C) behave better under irradiation compared to the samples processed at low solution annealing temperatures (945 and 1065°C).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

Assisted Authoring of Model-Based Systems Engineering Documents

In systems engineering practices system design and analysis have historically been performed using a document-centric approach where stakeholders produce a number of documents that represent their views on a system under development. Given the ad-hoc, disparate, and informal nature of natural language documents, these views become quickly inconsistent. Rigor in engineering work is also lost in the transition from model based engineering design and analysis to engineering documents. Once the documents are delivered, the engineering portion of the work is disconnected. In the Open Model Based Engineering Environment (OpenMBEE), Cross-References (aka transclusions) synthesize data for engineering when the information is not simply hyperlinked, but referenced in place in a document, upgrading a document-based process with model-based engineering technology. Those Cross-References are nowadays partially created manually, putting a burden on the engineer who is authoring the document.This paper presents an approach which can assist the engineer by providing machine-generated suggestions for Cross-References using language processing, graph analysis, and clustering technologies on model data managed by the OpenMBEE infrastructure.

Gomes, Ivan↗
NASA NTRS2020

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autónomo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗
NASA NTRS2020

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autonómo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗
NASA NTRS2000

Giving Bigger Satellites a Boost

Ultramet, Inc. has spurred a new process for producing rocket engine thrust chambers, through SBIR funding and the Glenn Research Center. High-temperature oxidation-resistant thruster materials are being produced in order to achieve high-temperature capability without sacrificing reliability. These thruster materials lead to an estimated three-percent improvement in propulsion system performance. To develop this material, Ultramet used a process called chemical vapor deposition (CVD). CVD involves heating precursors for metals, like iridium and rhenium, to temperatures at which they become gaseous. They are then deposited onto a mandrel, or spindle, layer-by-layer to produce high-density, highly resistant materials from the inside out.

Source record↗
NASA NTRS1986

Lunar materials and processes

The paper surveys current information, describes some important unknowns about lunar materials, and discusses ways to gain more scientific and engineering knowledge concerning the industrial processes that could be used on the moon for the production of products useful in future enterprises in space. Lunar rocks and soils are rich in oxygen, but it is mostly chemically bound in silicates, so that chemical or thermal energy must be supplied to recover it. Iron and titanium are abundant and, in some of their known forms, readily recoverable; aluminum is plentiful but harder to extract. Methods for recovering lunar oxygen and metals fall into three classes: chemical, electrolytic, and dissociative, broadly characterized by their respective process temperatures. Examples of these methods are briefly discussed.

Burke, J. D.↗
NASA NTRS1993

Space Shuttle main engine OPAD: The search for a hardware enhanced plume

The process of applying spectroscopy to the Space Shuttle Main Engine (SSME) for plume diagnostics, as it exists today, originated at Marshall Space Flight Center in Huntsville, Alabama, and its implementation was assured largely through the efforts of Sverdrup AEDC, in Tullahoma, Tennessee. This team continues to lead and guide efforts in the plume diagnostics arena. The process, Optical Plume Anomaly Detection (OPAD), formed the basis for various activities in the development of ground-based systems as well as the development of in-flight plume spectroscopy. OPAD currently provides and will continue to provide valuable information relative to future systems definitions, instrumentation development, code validation, and data diagnostic processing. OPAD is based on the detection of anomalous atomic and molecular species in the SSME plume using two complete, stand-alone optical spectrometers. To-date OPAD has acquired data on 44 test firings of the SSME at the Technology Test Bed (TTB) at MSFC. The purpose of this paper will be to provide an introduction to the OPAD system by discussing the process of obtaining data as well as the methods of examining and interpreting the data. It will encompass such issues as selection of instrumentation correlation of data to nominal engine operation, investigation of SSME component erosion via OPAD spectral data, necessity and benefits of plume seeding, application of artificial intelligence (AI) techniques to data analysis, and the present status of efforts to quantify specie erosion utilizing standard plume and chemistry codes as well as radiative models currently under development.

Powers, W. T.↗
NASA NTRS2004

Probabilistic Study Conducted on Sensor-Based Engine Life Calculation

Turbine engine life management is a very complicated process to ensure the safe operation of an engine subjected to complex usage. The challenge of life management is to find a reasonable compromise between the safe operation and the maximum usage of critical parts to reduce maintenance costs. The commonly used "cycle count" approach does not take the engine operation conditions into account, and it oversimplifies the calculation of the life usage. Because of the shortcomings, many engine components are regularly pulled for maintenance before their usable life is over. And, if an engine has been running regularly under more severe conditions, components might not be taken out of service before they exceed their designed risk of failure. The NASA Glenn Research Center and its industrial and academic partners have been using measurable parameters to improve engine life estimation. This study was based on the Monte Carlo simulation of 5000 typical flights under various operating conditions. First a closed-loop engine model was developed to simulate the engine operation across the mission profile and a thermomechanical fatigue (TMF) damage model was used to calculate the actual damage during takeoff, where the maximum TMF accumulates. Next, a Weibull distribution was used to estimate the implied probability of failure for a given accumulated cycle count. Monte Carlo simulations were then employed to find the profiles of the TMF damage under different operating assumptions including parameter uncertainties. Finally, probabilities of failure for different operating conditions were analyzed to demonstrate the importance of a sensor-based damage calculation in order to better manage the risk of failure and on-wing life.

Guo, Ten-Huei↗
NASA NTRS2017

Mining Twitter Data to Augment NASA GPM Validation

The Twitter data stream is an important new source of real-time and historical global information for potentially augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. There have been other similar uses of Twitter, though mostly related to natural hazards monitoring and management. The validation of satellite precipitation estimates is challenging, because many regions lack data or access to data, especially outside of the U.S. and in remote and developing areas. The time-varying set of "precipitation" tweets can be thought of as an organic network of rain gauges, potentially providing a widespread view of precipitation occurrence. Twitter provides a large source of crowd for crowdsourcing. During a 24-hour period in the middle of the snow storm this past March in the U.S. Northeast, we collected more than 13,000 relevant precipitation tweets with exact geolocation. The overall objective of our project is to determine the extent to which processed tweets can provide additional information that improves the validation of GPM data. Though our current effort focuses on tweets and precipitation, our approach is general and applicable to other social media and other geophysical measurements. Specifically, we have developed an operational infrastructure for processing tweets, in a format suitable for analysis with GPM data; engaged with potential participants, both passive and active, to "enrich" the Twitter stream; and inter-compared "precipitation" tweet data, ground station data, and GPM retrievals. In this presentation, we detail the technical capabilities of our tweet processing infrastructure, including data abstraction, feature extraction, search engine, context-awareness, real-time processing, and high volume (big) data processing; various means for "enriching" the Twitter stream; and results of inter-comparisons. Our project should bring a new kind of visibility to Twitter and engender a new kind of appreciation of the value of Twitter by the science research communities.

validatio↗