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Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

BRIC-23 GeneLab Process Verification Test: Bacillus subtilis transcriptomic, proteomic, and metabolomic data

Microbes interact with humans in complex ways and understanding how they respond to the spaceflight environment is important to the success of future manned spaceflight missions. The BRIC-23 mission was designed to measure the response of Bacillus subtilis and Staphylococcus aureus to the spaceflight environment. This experiment aimed to produce high quality omics data from B. subtilis and S. aureus grown aboard the International Space Station (ISS) to allow comparison to matched ground controls. There were two primary objectives for this experiment: (1) Demonstrate all post-flight processes and operations required for successful completion of GeneLab Reference Missions conducted on ISS, and (2) Generate high quality GeneLab Reference Mission omics data sets for two prokaryotic model organisms, Bacillus subtilis and Staphylococcus aureus. Freezing Control Experiment: The BRIC hardware has significant thermal inertia, thus the freezing rate of samples placed at -80 C is quite slow. This could affect RNA-sequencing, proteomic and metabolic data sets. In an effort to understand how slow freezing could affect these data sets, a control experiment was designed in which B. subtilis and S. aureus were grown in petri plates and either slow frozen to -80 C at a rate matching the BRIC-23 spaceflight samples or processed immediately to harvest RNA and protein. S. aureus omics data is deposited in GLDS-145.

Rotor health monitoring combining spin tests and data-driven anomaly detection methods

Health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost, and durable products. In an effort to address technical issues concerning health monitoring, this article considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating turbine engine-like-disk to detect the disk faults and assess its structural integrity. The experimental results composed at a range of rotational speeds from tests conducted at the NASA Glenn Research Center’s Rotordynamics Laboratory are evaluated and integrated into multiple data-driven anomaly detection techniques to identify faults and anomalies in the disk. In summary, this study presents a select evaluation of online health monitoring of a rotating disk using high caliber capacitive sensors and demonstrates the capability of the in-house spin system.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Propulsion Health Monitoring of a Turbine Engine Disk using Spin Test Data

On line detection techniques to monitor the health of rotating engine components are becoming increasingly attractive options to aircraft engine companies in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenging feature to easily implement, especially, in the presence of scattered loading conditions, crack size, component geometry and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini cracks before any catastrophic event occurs. These techniques go further to evaluate materials' discontinuities and other anomalies that have grown to the level of critical defects which can lead to failure. Generally, health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications [1-5]. These efforts are focused on developing high temperature, wireless, low cost and durable products.Therefore, in an effort to address the technical issues concerning health monitoring of a rotor disk, this paper considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating engine-like-disk-to predict the disk faults and assess its structural integrity. The experimental results collected at a range of rotational speeds from tests conducted at the NASA Glenn Research Center's Rotordynamics Laboratory will be evaluated using multiple data-driven anomaly detection techniques [6-9] to identify anomalies in the disk. This study is expected to present a select evaluation of online health monitoring of a rotating disk using these high caliber sensors and test the capability of the in-house spin system.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.

Collaborative Testing of Turbulence Models: Incompressible Flow Cases from 1980-81 Data Library

This grouping contains the incompressible-flow cases from the 1980-81 Data Library.