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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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Site characterization benefits from imaging spectrometry to determine spectral bi-directional reflectance of a well-understood surface. Cross calibration approaches, uncertainties, role of imaging spectrometry, model-based site characterization, and application to product validation.
This is the presentation for the AIAA Space conference in September 2017. It highlights key information from Using Model-Based Systems Engineering to Provide Artifacts for NASA Project Life-cycle and Technical Reviews paper.
An investigation was made to determine some of the effects of various arrangements of slotted and round jet exits on the lift and pitching-moment characteristics of a rectangular-base model at zero forward speed. Jet-exit slots near the perimeter of the model usually gave larger lift-thrust ratios than slots nearer the center line when the model was near the ground, but away from the ground perimeter jets forming almost a closed jet curtain induced negative pressures on the bottom of the model and resulted in less lift than that obtained with more centrally located jets or jets with large gaps in the jet curtain. Most models with jet slots symmetrical about the pitch axis gave approximately zero pitching moments through the range of ground-board distances, but under some conditions unstable flow direction caused positive or negative pitching moments to occur. With wings attached to the models, the lift close to the ground was 10 to 20 percent less than the lift away from the ground for various configurations. The round jets gave poorer lift-thrust ratios than the slotted jets in the region of ground effect. Out of the region of ground effect the round jets gave the greatest lift-thrust ratio per unit of weight rate of flow of air, for equal jet-exit areas, and the thinnest slotted jet gave the least.
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Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.
Exposure of microbial populations to galactic cosmic radiation (GCR) in the deep-space radiation environment may lead to intracellular damage that compromises the ability of cells to repair and replicate. While simulation programs of deep-space radiation do exist, they focus primarily on single-cell damage, rather than population-wide effects. In this work, a new application and graphical user interface, Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is presented, which simulates the effects of proton-based GCR on Saccharomyces cerevisiae population growth. AMMPER consists of a 50x50x50 µm simulation space, analogous to an aqueous culture medium with non-limiting nutrient and pH buffering, in a microwell plate or microfluidic culture card. This model utilizes Relativistic Ion Tracks (RITRACKS) to create detailed track structures of the radiation traversals. AMMPER then calculates the radiation dose present at each cell, and subsequently determines the damage (chromosomal aberrations, oxidative stress, etc.) and resulting loss of cell viability from both primary and secondary radiative effects. Through implementing cell replication, repair, damage, and death, the effect of radiation exposure on the population growth can be determined. With AMMPER, long-duration effects of the deep space environment on entire populations can be determined and used to assess the feasibility of sustaining life in space.
It is well established that the head and eye velocity axes do not always align during compensatory vestibular slow phases. It has been shown that the eye velocity axis systematically tilts away from the head velocity axis in a manner that is dependent on eye-in-head position. The mechanisms responsible for producing these axis tilts are unclear. In this model-based study, we aimed to determine whether muscle pulleys could be involved in bringing about these phenomena. The model presented incorporates semicircular canals, central vestibular pathways, and an ocular motor plant with pulleys. The pulleys were modeled so that they brought about a rotation of the torque axes of the extraocular muscles that was a fraction of the angle of eye deviation from primary position. The degree to which the pulleys rotated the torque axes was altered by means of a pulley coefficient. Model input was head velocity and initial eye position data from passive and active yaw head impulses with fixation at 0 degrees, 20 degrees up and 20 degrees down, obtained from a previous experiment. The optimal pulley coefficient required to fit the data was determined by calculating the mean square error between data and model predictions of torsional eye velocity. For active head impulses, the optimal pulley coefficient varied considerably between subjects. The median optimal pulley coefficient was found to be 0.5, the pulley coefficient required for producing saccades that perfectly obey Listing's law when using a two-dimensional saccadic pulse signal. The model predicted the direction of the axis tilts observed in response to passive head impulses from 50 ms after onset. During passive head impulses, the median optimal pulley coefficient was found to be 0.21, when roll gain was fixed at 0.7. The model did not accurately predict the alignment of the eye and head velocity axes that was observed early in the response to passive head impulses. We found that this alignment could be well predicted if the roll gain of the angular vestibuloocular reflex was modified during the initial period of the response, while pulley coefficient was maintained at 0.5. Hence a roll gain modification allows stabilization of the retinal image without requiring a change in the pulley effect. Our results therefore indicate that the eye position-dependent velocity axis tilts could arise due to the effects of the pulleys and that a roll gain modification in the central vestibular structures may be responsible for countering the pulley effect.
A model for worldwide cloud cover using a satellite data set containing infrared radiation measurements is proposed. The satellite data set containing day IR, night IR and incoming and absorbed solar radiation measurements on a 2.5 degree latitude-longitude grid covering a 45 month period was converted to estimates of cloud cover. The global area was then classified into homogeneous cloud cover regions for each of the four seasons. It is noted that the developed maps can be of use to the practicing climatologist who can obtain a considerable amount of cloud cover information without recourse to large volumes of data.
Fault Protection (FP) is a distinct and separate systems engineering sub-discipline that is concerned with the off-nominal behavior of a system. Flight system fault protection is an important part of the overall flight system systems engineering effort, with its own products and processes. As with other aspects of systems engineering, the FP domain is highly amenable to expression and management in models. However, while there are standards and guidelines for performing FP related analyses, there are not standards or guidelines for formally relating the FP analyses to each other or to the system hardware and software design. As a result, the material generated for these analyses are effectively creating separate models that are only loosely-related to the system being designed. Development of approaches that enable modeling of FP concerns in the same model as the system hardware and software design enables establishment of formal relationships that has great potential for improving the efficiency, correctness, and verification of the implementation of flight system FP. This paper begins with an overview of the FP domain, and then continues with a presentation of a SysML/UML model of the FP domain and the particular analyses that it contains, by way of showing a potential model-based approach to flight system fault protection, and an exposition of the use of the FP models in FSW engineering. The analyses are small examples, inspired by current real-project examples of FP analyses.
A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.
A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.
The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.