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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Artificial Immune System Approach for Airborne Vehicle Maneuvering

A method and system for control of a first aircraft relative to a second aircraft. A desired location and desired orientation are estimated for the first aircraft, relative to the second aircraft, at a subsequent time, t=t2, subsequent to the present time, t=t1, where the second aircraft continues its present velocity during a subsequent time interval, t1.ltoreq.t.ltoreq.t2, or takes evasive action. Action command sequences are examined, and an optimal sequence is chosen to bring the first aircraft to the desired location and desired orientation relative to the second aircraft at time t=t2. The method applies to control of combat aircraft and/or of aircraft in a congested airspace.

Kaneshige, John T.↗
NASA NTRS2017

NiTi Alloys: New Materials that enable Shockproof, Corrosion Immune Bearings

Though steel is the dominant material of choice for mechanical components (bearings and gears) it has intrinsic limitations related to corrosion and plastic deformation. In contrast, dimensionally stable nickel-rich Ni-Ti alloys, such as Nitinol 60, are intrinsically rustproof and can withstand high contact loads without damage (denting). Over the last decade, focused RD to exploit these alloys for new applications has revealed the science behind NiTi's remarkable properties. In this presentation, the state-of-the-art of nickel-rich NiTi alloys will be introduced along with a discussion of how NASA is adopting this new technology inside the space station water recycling system as a pathfinder for more down-to-earth tribological challenges.

bearings↗
NASA NTRSDate not supplied

Spaceflight-Induced Changes in Microbial Virulence and the Impact to the Host Immune Response

Over the past 50 years, microorganisms have displayed unexpected responses relevant to infectious disease when grown in spaceflight and spaceflight analogues, including changes in final cell concentration, biofilm production, stress resistance, antibiotic sensitivity, gene expression, and virulence. •Seminal studies demonstrated that the foodborne pathogen, Salmonella enterica serovar Typhimurium, increased its virulence and pathogenesis-related characteristics in response to both spaceflight and spaceflight analogue culture. Since those experiments, alterations in the pathogenesis-related characteristics of other pathogens have been documented in response to growth in these environments4,5,6, and a recent study has demonstrated an increase in virulence of Serratia marcescens cultured during spaceflight7. However, our overall knowledge of which microorganisms will alter their virulence in response to spaceflight and spaceflight analogue culture remains very limited

C. M. Ott↗
NASA NTRSDate not supplied

Development of Machine Learning-Derived Microbiological and Immune Signatures: Applications in Adaptive Risk Assessment of Infectious Disease During Spaceflight

Infectious diseases represent an urgent risk for spaceflight with consequences ranging from loss in crew performance to crew incapacitation or loss of life should an outbreak occur. The resident environmental microbiome on the International Space Station has been monitored through routine surveillance over almost twenty years, beginning with culture-based microbial detection which has advanced to molecular methods in recent years. This has created a wealth of data that we have begun mining to define the microbial ecology of the ISS. Summarized here is our analysis of data from the historical microbial population defined by culture-based monitoring from the past two decades, organized by their likelihood to cause disease into clinical categories. As expected, many residents of the normal microflora in environments where people work and live were detected. However, some known pathogens were also detected. As the spaceflight environment can predispose humans to infection, crew health records were used to source additional data for the set to uncover clinical relevance. Data mining was performed on crew health records to capture adverse health events that may be related to infectious disease. Machine learning, specifically Random Forest analysis, was used to analyze the microbial and crew health datasets. The symptom categories were not explained by the ranked bacteria, due to lack of sufficient data for some categories and due to poor ranking of the pathogens for others. Poor ranking of the bacteria could be due to the clinical symptoms being linked to other disease-causing factors, such as allergy or viral infection. These findings suggest a lack of relationship between bacteria detected on surfaces in the ISS and historical health events experienced by astronauts.

Kristyn Hoffman↗