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At least 325 records · Page 18

What Can We Learn from One Billion Ground System Log Messages?

Shortage of log-based data in a ground system they have traditionally been the under achievers in a satellite ground system. This is due to several factors: Once log messages scroll out of view on the TTC event console window they are soon forgotten. Application and system log files are scattered across directories within a system, across a multitude of servers, and across one or more databases making access cumbersome. Typical tools to perform log file content searching are generally crude and typically only employed as part of trouble-shooting exercises.As we move towards satellite constellations and fleets and add even more status information, the number of messages keeps growing. One mission now estimates that they could generate 3,000,000 messages per day 1 billion per year - for the life of their mission. What to do with those 1 billion messages? That is the challenge. With the recent technological advances in the management of large data sets, text-based processing, and data analytics, there are now capabilities that we can provide to the ground system engineers and satellite operators to address what we postulate are missed opportunities. Advanced real-time log analysis can allow us to be less reactionary in favor of being more proactive. Analytics goals include the ability to: Identify root cause of unexpected events, failures or error conditions enabled by correlating disparate data. Detect security breaches attempts before they are successful. Help admins ensure IT resources continue running optimally. Identify trends and patterns that may indicate impending failures or error conditions for valuable assets before they happen. Compare satellites in a fleet or constellation in terms of number of alarms, number of command sent to them, etc.. Answer questions like "Are the operations support needs increasing over the past year?" or "Have we seen this combination of alarm conditions before?" But really, once the tools are readily available the users will start realizing what can be done with their new powers. In this presentation we will show the results of analyzing millions of actual mission operations log messages, how the results can be displayed to the user, and how new products now available as open source can be applied to the challenges of large scale time-tagged text-based mission operations messages. Flight operations team members believe that this is a powerful new option for how they assess overall system and space asset health. Technical descriptions of the design, tools, and storage will be provided. One billion messages? Bring'em on!

Orsborne, Sharon↗

Verifying Autonomous Air Traffic Algorithms in the Presence of Sensor Error and Flight Perturbations

We offer a method to verify algorithms for air traffic control in the presence of sensor errors and flight perturbations. Since errors and perturbations are described by stochastic processes, verification by analytical methods is difficult. We turn to Monte Carlo simulation, but there are two major obstacles. Since air traffic algorithms are safety-critical, the algorithm must be established at a very high confidence level which requires an enormous number of trials. Another is that a simulation attempts to show that an algorithm correctly handles a hazard that might appear, but there is a lack of information about the frequency of occurrence of hazards in the airspace. This paper offers a solution to these and other obstacles. It recognizes there may be a number of algorithms that address different hazards, and the results of the different simulations must be combined to satisfy a global reliability requirement at a high confidence level. To demonstrate the feasibility of the approach, we apply it to an example, an initial effort in collision avoidance.

verification↗

Accelerating SNP Development with Radiation Source Approximations for Far-Field Environment Modeling

The successful development and deployment of space nuclear power and propulsion technology requires a high-fidelity, efficient means of modeling ex-core radiation fields. Monte Carlo particle transport codes provide enable the highest level of fidelity in radiation field modeling but are inefficient for modeling ex-core radiation without modification. This paper details the development of an approach to ex-core radiation field modeling that maintains the fidelity of a Monte Carlo transport approach without sacrificing computational efficiency. This approach is based on recent improvements to an existing Monte Carlo transport acceleration technique known as surface source banking. As the transport of many particles is required to ensure adequate uncertainty in far field transport, analytical reconstruction techniques are employed to represent surface source banks as sampleable series of distributions in particle phase from which an arbitrarily large number of particles can be generated and simulated. All steps of this approach are incorporated into an AMA model to test both the underlying mathematics of the analytical source reconstruction process, as well as the relevance of the technique as a whole towards SNP applications. These tests demonstrated that this approach is capable of accelerating far-field radiation modeling in SNP-relevant scenarios by factors of at least nine over purely eigenvalue-based scenarios without significantly sacrificing simulation accuracy.

Surface Source Banking↗

Assessment of Near-Angle Scatter on Exo-Earth Coronagraphy

Near-Angle Scatter (NAS) of the host star’s light into the coronagraph dark hole may limit the ability of a potential Habitable Worlds Observatory (HWO) to detect and characterize an Earth-like planet around a Sun-like star. This paper summarizes a 5-year investigation of the impact of NAS on high-contrast coronagraphy. Science requirements were flowed down to a draft flux ratio noise ratio (FRN) error budget with allocations for NAS. The modeled sources of NAS include correlated (low and mid-spatial) surface structure, uncorrelated surface microroughness and coating structure, particulate contamination, micrometeoroid impacts and polarization leakage. The paper develops specifications for these sources of scattered light that meet their FRN error budget allocations, distinguishing between scatter that can and cannot be modulated. The development process utilizes an analytical expression that predicts scatter throughput into the dark hole based on BRDF/BSDF. Using this relationship, Photon Engineering performed a FRED® straylight analysis of the HWO EAC-1 (Exploratory Analytical Case #1) coronagraph to parametrically study predicted scattered light contrast in the dark hole. The model revealed that primary mirror microroughness or contamination is not a significant source of scattered light; the most critical surfaces are the smallest and those located closest to the coronagraph focal plane mask. The assessment found that uncorrelated microstructure, contamination, and micrometeoroid impacts require more investigation and potential significant sources of unmodulated scattered light, and highlights that slow thermal wavefront drift is an order of magnitude more impactful than fast mechanical jitter.

coronagraphy↗

An Integrated Platform for Mission Performance: Goddard Space Flight Center's Meta Information System

Successful management of NASA Goddard Space Flight Centers portfolio of mission projects (i.e. spacecraft, spacecraft instruments / subsystems, and ground systems) depends upon numerous processes, data and information resources coming together throughout the life-cycle of the projects to enable sound decision-making, risk reduction, conformance with requirements and continual improvement. In the summer of 2012, GSFC SMA management recognized that the set of legacy data systems used to support the SMA mission and responsibilities at GSFC were not effective, integrated nor on par with best practices. Accordingly, GSFC SMA management launched a project to transform the GSFC electronic management system to create and deploy an integrated, state-of-the-market information system for process performance, data management and analytics that is currently operating in support of GSFC overall mission performance. The information system, known as Meta, provides controlled, process-based applications, integrated data management, and analytics for a robust set of integrated applications. Since the inception of the project, a lean, award-winning SMA project team has thus far designed, configured and managed the system to serve as an integrated platform for 18 applications that support key processes for GSFC and the Science Mission Directorate at NASA headquarters, such as internal Management System assessments, Supplier Assessments, Supplier Research & Analysis, Problem Reporting for in-house mission projects, On-orbit Anomaly Reporting for GSFC-operated spacecraft, GSFC Project Life-Cycle Reviews, Risk Management and Reporting, and SMA Project Team Reporting. The system has experienced steady growth in utilization with 1,917 users (NASA employees and support contractor personnel) and 44 gigabytes of data and related files managed by the system as of the end of April 2018. Overall, Meta has achieved increasing levels of process management and real-time data / information integration to enable improved process performance, richer analytics and informed decision-making. This paper will present and examine the need, goals, approach and design driving the management and operation of the Meta information system and its ongoing growth as an integrated platform for advancing NASA mission performance.

Integration↗

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

This letter presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. Here, the robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.

42 ENGINEERING↗

Rapid Sensing to Facilitate Purification of Rare Earth Element-Containing Process Streams Produced Through Membrane-Assisted Solvent Extraction

The development of an economically competitive domestic supply of rare earth elements and yttrium (REY) is necessary for our nation’s economic growth and national security. The achievement of a secure domestic supply of REY requires not only the development of effective processes for recovery of REY from naturally occurring materials and/or recycled products, but also the development of downstream processes for the ultimate production of high-REY content solids. An impediment to the development of such processes is the scarcity of analytical methods that provide rapid determination of the process stream compositions. In this work, a membrane-based extraction process was used to selectively recover REYs from a dilute solution in the presence of much higher concentrations of Ca and Al. In tandem, the use of a portable spectrometer equipped with an immobilized zinc adeninate benzene tricarboxylate metal-organic framework sensing material makes possible the rapid detection of the presence of ppm concentrations of Tb and Eu in both weakly acidic and strongly acidic process streams within minutes. A solvent extraction processing time of 15-60 min maximized REY selectivity over gangue ions while achieving up to 80% REY and minimal gangue ion recovery. Taken together, these experiments highlight not only an innovative method for REY purification but also the importance of inexpensive, portable characterization methods for near real-time analysis of REY content.

Membrane-assisted solvent extraction↗

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows

In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities by scheduling data analytics close to the data source. Hybrid in-situ processing splits data analytics into two stages: the data processing that runs in-situ aims to extract regions of interest, which are then transferred to staging services for further in-transit analytics. To facilitate this type of hybrid in-situ processing, the data staging service needs to support complex intermediate data representations generated/consumed by the in-situ tasks. Unstructured (or irregular) mesh is one such derived data representation that is typically used and bridges simulation data and analytics. However, how staging services efficiently support unstructured mesh transfer and processing remains to be explored. This paper investigates design options for transferring and processing unstructured mesh data using staging services. Using polygonal mesh data as an example, we show that hybrid in-situ workflows with staging-based unstructured mesh processing can effectively support hybrid in-situ workflows, and can significantly decrease data movement overheads.

data-driven↗

Raman Spectroscopy Based On-Line, Real-Time Monitoring to Reduce Composition Uncertainties: Enhanced sensitivity through optimization of Raman Parameters

Optical spectroscopy-based on-line monitoring of Hanford processing streams can enable real-time characterization of chemical composition of process streams and batches, ultimately enabling and enhancing process control. It can provide immediate feedback on process conditions and has the potential to reduce the needed number of grab sample collections, thereby reducing times and costs associated with laboratory processing. Here we discuss the utilization of Raman spectroscopy to quantify multiple target analytes that are common within Hanford tanks and waste processing streams. Analytes include: nitrate, nitrite, carbonate, chromate, sulfate, phosphate, hydroxide, oxalate, ammonia, and aluminate. Most notably in this work, Raman applications to low-concentration streams are explored and optimized. Raman instrument specifications are compared; specifically, the impact of utilizing three different Raman excitation wavelengths, 405, 532, and 671 nm, is discussed. Also, Raman data collection parameters such as collection time and spectral averaging are measured and discussed. Finally, optical libraries of chemical targets were collected using optimized collection parameters and chemometric models were built to automate quantification of chemical targets. These models were validated through application to simulants and real Hanford process samples. Chemometric models performed well on both training and validation sets, suggesting these approaches can be successfully applied to on-line and real-time monitoring of low concentration Hanford processing streams. The use of the combine Raman wave lengths with the enhanced chemometric models for the low concentration streams significantly improved the chemical detection levels and significantly reduced uncertainties of those measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deriving Earth Science Data Analytics Requirements

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

data analytics↗

Application of modern surface analytical tools in the investigation of surface deterioration processes

Surface profilometry and scanning electron microscopy were utilized to study changes in the surface of polymers when eroded. The X-ray photoelectron spectroscopy (XPS) and depth profile analysis indicate the corrosion of metal and ceramic surfaces and reveal the diffusion of certain species into the surface to produce a change in mechanical properties. Ion implantation, nitriding and plating and their effects on the surface are characterized. Auger spectroscopy analysis identified morphological properties of coatings applied to surfaces by sputter deposition.

Buckley, D. H.↗

Development of an analytical transient evacuation model for the fairing jettison process

A general, lumped-parameter, control volume equation is developed to describe the rapid loss of pressure associated with a launch vehicle fairing jettison event in its initial phase. Beginning with a general mass conservation statement, a sonic constraint is applied to the expanding gap between receding fairing halves to produce a statement for transient density. This is related to fairing pressure by assuming the expansion may be described by a polytropic process. A generic, single-step, lateral fairing half separation case is created and explored for illustrative purposes.

Fairing depressurization↗

Development of an analytical transient evacuation model for the fairing jettison process

A general, lumped-parameter, control volume equation is developed to describe the rapid loss of pressure associated with a launch vehicle fairing jettison event in its initial phase. Beginning with a general mass conservation statement, a sonic constraint is applied to the expanding gap between receding fairing halves to produce a statement for transient density. This is related to fairing pressure by assuming the expansion may be described by a polytropic process. A generic, single-step, lateral fairing half separation case is created and explored for illustrative purposes.

fairing depressurization↗

Development of an Analytical Transient Evacuation Model for the Fairing Jettison Process

A general, lumped-parameter, control volume equation is developed to describe the rapid loss of pressure associated with a launch vehicle fairing jettison event in its initial phase. Beginning with a general mass conservation statement, a sonic constraint is applied to the expanding gap between receding fairing halves to produce a statement for transient density. This is related to fairing pressure by assuming the expansion may be described by a polytropic process. A generic, single-step, lateral fairing half separation case is created and explored for illustrative purposes.

fairing depressurization, jettison, venting↗

Spectroscopic Online Monitoring: Using a Multi-Track Visible Spectrometer to Facilitate a Mass Balance Study in a Simulated TALSPEAK Process

Nuclear energy is a promising low-carbon energy candidate to meet the increased demand for green energy, where the integration of fuel recycling can have significant benefits for material usage and waste reduction. Utilizing in situ monitoring tools can provide ample opportunities to better control and safeguard nuclear material recycle processes while also offering knowledge and insight into real-time solution properties. The simultaneous measurement of analytical targets in multiple process locations can enable real-time mass balance and material accountancy calculations. This is demonstrated here with a mass balance study of Nd 3+ on countercurrent aqueous/organic metal extraction within a single centrifugal contactor. The Nd 3+ concentration was simultaneously monitored at the inlets and outlets of both aqueous and organic phases using a visible absorbance detector that allowed for the simultaneous measurement of up to six locations. The Nd 3+ concentration was calculated by using chemical data science algorithms, where model training sets were collected on a single track of the detector. The discussion includes addressing the challenges of using a model collected on a single track and applying it as a model across the other tracks on the detector. Each track of the detector corresponds to one measurement location on the contactor. The difference in the integrated moles of Nd 3+ between the inlet and outlet at the end of the experiment was near zero, indicating that the mass balance of this experiment was maintained. Overall, the online spectroscopic monitoring was able to follow changing solution conditions and accurately measure the concentration of Nd 3+ in different locations within the contactor system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the transient large amplitude oscillatory shear behavior of yield stress fluids

A full understanding of the sequence of processes exhibited by yield stress fluids under large amplitude oscillatory shearing is developed using multiple experimental and analytical approaches. A novel component rate Lissajous curve, where the rates at which strain is acquired unrecoverably and recoverably are plotted against each other, is introduced and its utility is demonstrated by application to the analytical responses of four simple viscoelastic models. Using the component rate space, yielding and unyielding are identified by changes in the way strain is acquired, from recoverably to unrecoverably and back again. The behaviors are investigated by comparing the experimental results with predictions from the elastic Bingham model that is constructed using the Oldroyd–Prager formalism and the recently proposed continuous model by Kamani, Donley, and Rogers in which yielding is enhanced by rapid acquisition of elastic strain. The physical interpretation gained from the transient large amplitude oscillatory shear (LAOS) data is compared to the results from the analytical sequence of physical processes framework and a novel time-resolved Pipkin space. The component rate figures, therefore, provide an independent test of the interpretations of the sequence of physical processes analysis that can also be applied to other LAOS analysis frameworks. Each of these methods, the component rates, the sequence of physical processes analysis, and the time-resolved Pipkin diagrams, unambigiously identifies the same material physics, showing that yield stress fluids go through a sequence of physical processes that includes elastic deformation, gradual yielding, plastic flow, and gradual unyielding.

Kamani, Krutarth M. (ORCID:0000000338975420)↗