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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Schwabacher, Mark A.↗
NASA NTRS2009

Introductions to Mission Operations and Ground Data Systems

This slide presentation discusses how in the early concept studies the communications architecture plays an important part: The communications architecture is the arrangement, or configuration of satellites and ground systems in a space system, and the network of communications links that transfers information between them.

Stewart, Helen J.↗
NASA NTRS2019

Liftoff and Transition Database Generation for Launch Vehicles Using Data-Fusion-Based Modeling

A data fusion technique for merging multiple data sources with differing fidelity and resolution was developed to support the production of aerodynamic line load databases for the Liftoff and Transition (LOT) flight phase of the Space Launch System (SLS). The technique uses a reduced order model based on a high-fidelity line load data set from Computational Fluid Dynamics (CFD) to predict solutions for a much larger solution space. Even higher-fidelity force and moment information (from wind-tunnel tests) is then used to adjust the model. The adjustment uses constrained optimization through the method of Lagrange multipliers in order to minimize the deviation of the line load distribution from the spatially-dense CFD solution, while ensuring that the integrated force and moment values match those observed in physical wind tunnel measurements. Though the wind-tunnel data are operationally-dense (available at many flow conditions), they are spatially coarse (as only the overall forces and moments are available). Conversely, CFD for such complex configurations is expensive, and thus operationally sparse. Data fusion techniques are necessary to make the most efficient use of available information, delivering accurate results within time and resource constraints.

Wignall, T. J.↗
NASA NTRSDate not supplied

Limitations on the Use of Eye-Tracking Data to Understand Operator Awareness

Safety events in commercial aviation have implicated failures of attention and awareness, and the need for improved attention and awareness has pushed trainers toward eye-tracking systems as a primary tool for evaluating monitoring performance. Further, in the last 15 years, eye-tracking technology has become easier to acquire and use in operationally realistic settings. Although we believe that eye-tracking can be a useful evaluation tool, this paper describes basic limitations on relying on eye-tracking as the sole means for evaluating attention and awareness. A set of other measures are offered that can better identify where performance breakdowns occur.

aviation↗
NASA NTRSDate not supplied

Operational and Archive Data Records: Surface Elevation Measurements of Lakes, Wetlands, and Rivers for Resources and Hazards

A NASA/USDA funded program offers satellite-derived products for lakes, reservoirs, river reaches, and wetland zones. These are currently being derived from the 10-day and monthly-resolution radar altimeter series. However, observational parameters from the laser based ICESat-2 mission, and the enhanced SWOT KaRIn instrument will also be integrated to meet various end user requirements. The resulting measurements will ultimately be a combination of surface water level and slope, surface water extent, water storage and basin bathymetry, plus a suite of Status Indicators which highlight deviations from long-term and seasonal averages. The main stakeholders are the USDA/Foreign Agricultural Service, the US Geological Survey, USACE/NGA, and various Wetland-related organizations. Applications centre on water and energy resources and fish-catch potential, and on natural hazards (floods and droughts). There is a demand for a global monitoring service, but primary focus is on regions where gauge measurement access is restricted or delayed, or where gauge deployment is hazardous. Ongoing surface acquisition checks and feedback to CNES focusses on the success or failure of the on-board DEM’s on a case-by-case basis. Multiple projects are also underway to improve the surface elevations measurements and the along track resolution (minimum water body width) via exploration of the high resolution (Doppler) Range estimates, the FF-SAR technique, and the high- resolution radiometer based wet tropospheric correction. And while Level3+4 surface water products are being directed by end user requirements, the overriding NASA objectives are the formation of high quality Earth Data Records with high accuracy and uniformity across multiple decades.

Lakes↗
NASA NTRS1975

Computer program compatible with a laser nephelometer

The laser nephelometer data system was updated to provide magnetic tape recording of data, and real time or near real time processing of data to provide particle size distribution and liquid water content. Digital circuits were provided to interface the laser nephelometer to a Data General Nova 1200 minicomputer. Communications are via a teletypewriter. A dual Linc Magnetic Tape System is used for program storage and data recording. Operational programs utilize the Data General Real-Time Operating System (RTOS) and the ERT AIRMAP Real-Time Operating System (ARTS). The programs provide for acquiring data from the laser nephelometer, acquiring data from auxiliary sources, keeping time, performing real time calculations, recording data and communicating with the teletypewriter.

Paroskie, R. M.↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

The Space Station end-to-end data system - Linking architecture and operations

The paper describes tha data system designed for linking and integrating the Space Station Freedom (SSF) space and ground architecture and for providing instrument data to the user and discusses the operations of the system. Particular attention is given to the objectives, the organization, and the schedule of the SSF Program, the infrastructure elements of the end-to-end data system, the key active functional areas of the system, the types of data, the user scenario, and the SSF's space, space-to-ground, and ground infrastructures as they are active in support of the stipulated user scenario.

Fishkind, Stanley↗
NASA NTRS2015

Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight

Control of vehicles and other complex systems is a high-level integrative function of the central nervous system (CNS). It requires well-functioning subsystem performance, including good visual acuity, eye-hand coordination, spatial and geographic orientation perception, and cognitive function. Evidence from space flight research demonstrates that the function of each of these subsystems is altered by removing gravity, a fundamental orientation reference, which is sensed by vestibular, proprioceptive, and haptic receptors and used by the CNS for spatial orientation, posture, navigation, and coordination of movements. The available evidence also shows that the degree of alteration of each subsystem depends on a number of crew- and mission-related factors. There is only limited operational evidence that these alterations cause functional impacts on mission-critical vehicle (or complex system) control capabilities. Furthermore, while much of the operational performance data collected during space flight has not been available for independent analysis, those that have been reviewed are somewhat equivocal owing to uncontrolled (and/or unmeasured) environmental and/or engineering factors. Whether this can be improved by further analysis of previously inaccessible operational data or by development of new operational research protocols remains to be seen. The true operational risks will be estimable only after we have filled the knowledge gaps and when we can accurately assess integrated performance in off-nominal operational settings (Paloski et al. 2008). Thus, our current understanding of the Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight is limited primarily to extrapolation of scientific research findings, and, since there are limited ground-based analogs of the sensorimotor and vestibular changes associated with space flight, observation of their functional impacts is limited to studies performed in the space flight environment. Fortunately, many sensorimotor and vestibular experiments have been performed during and/or after space flight missions since 1959 (Reschke et al. 2007). While not all of these experiments were directly relevant to the question of vehicle/complex system control, most provide insight into changes in aspects of sensorimotor control that might bear on the physiological subsystems underlying this high-level integrated function.

Bloomberg, Jacob J.↗