Data production on past and future NASA missions

Jasper, Lee; Xaypraseuth, Peter

doi:10.1109/aero.2017.7943918

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If AE or GUW monitoring effectively yields data at rates of 1 GBit/second or more, the data storage necessary becomes impressive. Again, data storage demands for the deep space network provide a nice example [117] for comparison.…”

Section: Durability Of Electronic Data Acquisition Equipment For Ae and Guwmentioning

confidence: 99%

Structural Health and Condition Monitoring with Acoustic Emission and Guided Ultrasonic Waves: What about Long-Term Durability of Sensors, Sensor Coupling and Measurement Chain?

Brunner

2021

Applied Sciences

View full text Add to dashboard Cite

Acoustic Emission (AE) and Guided Ultrasonic Waves (GUWs) are non-destructive testing (NDT) methods in several industrial sectors for, e.g., proof testing and periodic inspection of pressure vessels, storage tanks, pipes or pipelines and leak or corrosion detection. In materials research, AE and GUW are useful for characterizing damage accumulation and microscopic damage mechanisms. AE and GUW also show potential for long-term Structural Health and Condition Monitoring (SHM and CM). With increasing computational power, even online monitoring of industrial manufacturing processes has become feasible. Combined with Artificial Intelligence (AI) for analysis this may soon allow for efficient, automated online process control. AI also plays a role in predictive maintenance and cost optimization. Long-term SHM, CM and process control require sensor integration together with data acquisition equipment and possibly data analysis. This raises the question of the long-term durability of all components of the measurement system. So far, only scant quantitative data are available. This paper presents and discusses selected aspects of the long-term durability of sensor behavior, sensor coupling and measurement hardware and software. The aim is to identify research and development needs for reliable, cost-effective, long-term SHM and CM with AE and GUW under combined mechanical and environmental service loads.

show abstract

Section: Durability Of Electronic Data Acquisition Equipment For Ae and Guwmentioning

confidence: 99%

Structural Health and Condition Monitoring with Acoustic Emission and Guided Ultrasonic Waves: What about Long-Term Durability of Sensors, Sensor Coupling and Measurement Chain?

Brunner

2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The failure of any one activity in the sequence costs additional time as the agent pauses and waits for new instructions. For many missions, downlink bandwidth accommodates a tiny fraction of the potential data ( Jasper and Xaypraseuth, 2017). More flexible autonomy will be important to overcome these limits and enable critical emerging astrobiology investigations for outer planet exploration (Lorenz and Cabrol, 2018), high-volume instruments (Thompson et al, 2013(Thompson et al, , 2015aBekker et al, 2014), and wide-area adaptive sensing (Fink et al, 2005;McGuire et al, 2014;Woods et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Spatial Spectroscopic Models for Remote Exploration

et al. 2018

View full text Add to dashboard Cite

Ancient hydrothermal systems are a high-priority target for a future Mars sample return mission because they contain energy sources for microbes and can preserve organic materials (Farmer, 2000 ; MEPAG Next Decade Science Analysis Group, 2008 ; McLennan et al., 2012 ; Michalski et al., 2017 ). Characterizing these large, heterogeneous systems with a remote explorer is difficult due to communications bandwidth and latency; such a mission will require significant advances in spacecraft autonomy. Science autonomy uses intelligent sensor platforms that analyze data in real-time, setting measurement and downlink priorities to provide the best information toward investigation goals. Such automation must relate abstract science hypotheses to the measurable quantities available to the robot. This study captures these relationships by formalizing traditional "science traceability matrices" into probabilistic models. This permits experimental design techniques to optimize future measurements and maximize information value toward the investigation objectives, directing remote explorers that respond appropriately to new data. Such models are a rich new language for commanding informed robotic decision making in physically grounded terms. We apply these models to quantify the information content of different rover traverses providing profiling spectroscopy of Cuprite Hills, Nevada. We also develop two methods of representing spatial correlations using human-defined maps and remote sensing data. Model unit classifications are broadly consistent with prior maps of the site's alteration mineralogy, indicating that the model has successfully represented critical spatial and mineralogical relationships at Cuprite. Key Words: Autonomous science-Imaging spectroscopy-Alteration mineralogy-Field geology-Cuprite-AVIRIS-NG-Robotic exploration. Astrobiology 18, 934-954.

show abstract

Volcano geodesy using InSAR in 2020: the past and next decades

Poland

Zebker

2022

Bull Volcanol

View full text Add to dashboard Cite

Data production on past and future NASA missions

Cited by 3 publications

References 6 publications

Structural Health and Condition Monitoring with Acoustic Emission and Guided Ultrasonic Waves: What about Long-Term Durability of Sensors, Sensor Coupling and Measurement Chain?

Structural Health and Condition Monitoring with Acoustic Emission and Guided Ultrasonic Waves: What about Long-Term Durability of Sensors, Sensor Coupling and Measurement Chain?

Spatial Spectroscopic Models for Remote Exploration

Volcano geodesy using InSAR in 2020: the past and next decades

Contact Info

Product

Resources

About