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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 145 records · Page 8

An Approach to Detect and Mitigate Ice Particle Accretion in Aircraft Engine Compression Systems

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8 percent of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗

An Approach to Detect and Mitigate Ice Particle Accretion in Aircraft Engine Compression Systems

The accretion of ice in the compression system of commercial gas turbine engines operating in high ice water content conditions is a safety issue being studied by the aviation sector. While most of the research focuses on the underlying physics of ice accretion and the meteorological conditions in which accretion can occur, a systems-level perspective on the topic lends itself to potential near-term operational improvements. This work focuses on developing an accurate and reliable algorithm for detecting the accretion of ice in the low pressure compressor of a generic 40,000 lbf thrust class engine. The algorithm uses only the two shaft speed sensors and works regardless of engine age, operating condition, and power level. In a 10,000-case Monte Carlo simulation, the detection approach was found to have excellent capability at determining ice accretion from sensor noise with detection occurring when ice blocks an average of 6.8% of the low pressure compressor area. Finally, an initial study highlights a potential mitigation strategy that uses the existing engine actuators to raise the temperature in the low pressure compressor in an effort to reduce the rate at which ice accretes.

May, Ryan D.↗

Development, Implementation, and Pilot Evaluation of a Model-Driven Envelope Protection System to Mitigate the Hazard of In-Flight Ice Contamination on a Twin-Engine Commuter Aircraft

Fatal loss-of-control accidents have been directly related to in-flight airframe icing. The prototype system presented in this report directly addresses the need for real-time onboard envelope protection in icing conditions. The combination of prior information and real-time aerodynamic parameter estimations are shown to provide sufficient information for determining safe limits of the flight envelope during inflight icing encounters. The Icing Contamination Envelope Protection (ICEPro) system was designed and implemented to identify degradations in airplane performance and flying qualities resulting from ice contamination and provide safe flight-envelope cues to the pilot. The utility of the ICEPro system for mitigating a potentially hazardous icing condition was evaluated by 29 pilots using the NASA Ice Contamination Effects Flight Training Device. Results showed that real time assessment cues were effective in reducing the number of potentially hazardous upset events and in lessening exposure to loss of control following an incipient upset condition. Pilot workload with the added ICEPro displays was not measurably affected, but pilot opinion surveys showed that real time cueing greatly improved their awareness of a hazardous aircraft state. The performance of ICEPro system was further evaluated by various levels of sensor noise and atmospheric turbulence.

simulation training↗

Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset

Benchmarking of prognostic algorithms has been challenging due to limited availability of common datasets suitable for prognostics. In an attempt to alleviate this problem several benchmarking datasets have been collected by NASA's prognostic center of excellence and made available to the Prognostics and Health Management (PHM) community to allow evaluation and comparison of prognostics algorithms. Among those datasets are five C-MAPSS datasets that have been extremely popular due to their unique characteristics making them suitable for prognostics. The C-MAPSS datasets pose several challenges that have been tackled by different methods in the PHM literature. In particular, management of high variability due to sensor noise, effects of operating conditions, and presence of multiple simultaneous fault modes are some factors that have great impact on the generalization capabilities of prognostics algorithms. More than 70 publications have used the C-MAPSS datasets for developing data-driven prognostic algorithms. The C-MAPSS datasets are also shown to be well-suited for development of new machine learning and pattern recognition tools for several key preprocessing steps such as feature extraction and selection, failure mode assessment, operating conditions assessment, health status estimation, uncertainty management, and prognostics performance evaluation. This paper summarizes a comprehensive literature review of publications using C-MAPSS datasets and provides guidelines and references to further usage of these datasets in a manner that allows clear and consistent comparison between different approaches.

Uncertainty↗

Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products

Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

Ocean↗

Effect of Vertical Rate Error on Recovery from Loss of Well Clear Between UAS and Non-Cooperative Intruders

When an Unmanned Aircraft System (UAS) encounters an intruder and is unable to maintain required temporal and spatial separation between the two vehicles, it is referred to as a loss of well-clear. In this state, the UAS must make its best attempt to regain separation while maximizing the minimum separation between itself and the intruder. When encountering a non-cooperative intruder (an aircraft operating under visual flight rules without ADS-B or an active transponder) the UAS must rely on the radar system to provide the intruders location, velocity, and heading information. As many UAS have limited climb and descent performance, vertical position andor vertical rate errors make it difficult to determine whether an intruder will pass above or below them. To account for that, there is a proposal by RTCA Special Committee 228 to prohibit guidance systems from providing vertical guidance to regain well-clear to UAS in an encounter with a non-cooperative intruder unless their radar system has vertical position error below 175 feet (95) and vertical velocity errors below 200 fpm (95). Two sets of fast-time parametric studies was conducted, each with 54000 pairwise encounters between a UAS and non-cooperative intruder to determine the suitability of offering vertical guidance to regain well clear to a UAS in the presence of radar sensor noise. The UAS was not allowed to maneuver until it received well-clear recovery guidance. The maximum severity of the loss of well-clear was logged and used as the primary indicator of the separation achieved by the UAS. One set of 54000 encounters allowed the UAS to maneuver either vertically or horizontally, while the second permitted horizontal maneuvers, only. Comparing the two data sets allowed researchers to see the effect of allowing vertical guidance to a UAS for a particular encounter and vertical rate error. Study results show there is a small reduction in the average severity of a loss of well-clear when vertical maneuvers are suppressed, for all vertical error rate thresholds examined. However, results also show that in roughly 35 of the encounters where a vertical maneuver was selected, forcing the UAS to do a horizontal maneuver instead increased the severity of the loss of well-clear for that encounter. Finally, results showed a small reduction in the number of severe losses of well-clear when the high performance UAS (2000 fpm climb and descent rate) was allowed to maneuver vertically, and the vertical rate error was below 500 fpm. Overall, the results show that using a single vertical rate threshold is not advisable, and that limiting a UAS to horizontal maneuvers when vertical rate errors are above 175 fpm can make a UAS less safe about a third of the time. It is suggested that the hard limit be removed, and system manufacturers instructed to account for their own UAS performance, as well as vertical rate error and encounter geometry, when determining whether or not to provide vertical guidance to regain well-clear.

detect and avoid↗

Linearity Analysis and Efficiency Testing of The Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) Science Cameras for Flight

To unveil the complexity of the solar atmosphere, measurement of the magnetic field in the upper chromosphere and transition region is fundamentally important, as this is where the forces transition from plasma to magnetic field dominated. Measurements of the field are also needed to elucidate the energy transport from the lower atmospheric regions to the corona beyond. Such an advance in heliospheric knowledge became possible with the first flight of the international solar sounding rocket mission, CLASP. For the first time, linear polarization was measured in Hydrogen Lyman-Alpha at 121.60 nm in September 2015. For linear polarization measurements in this emission line, high sensitivity is required due to the relatively weak polarization signal compared to the intensity. To achieve this high sensitivity, a low-noise sensor is required with good knowledge of its characterization, including linearity. This work presents further refinement of the linearity characterization of the cameras flown in 2015. We compared the current from a photodiode in the light path to the digital response of the detectors. Pre-flight CCD linearity measurements were taken for all three flight cameras and calculations of the linear fits and residuals were performed. However, the previous calculations included a smearing pattern and a digital saturation region on the detectors which were not properly taken into account. The calculations have been adjusted and were repeated for manually chosen sub-regions on the detectors that were found not to be affected. We present a brief overview of the instrument, the calibration data and procedures, and a comparison of the old and new linearity results. The CLASP cameras will be reused for the successor mission, CLASP2, which will measure the Magnesium II h & k emission lines between 279.45 nm and 280.35 nm. The new approach will help to better prepare for and to improve the camera characterization for CLASP2.

linearit↗

Linearity Analysis and Efficiency Testing of The Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) Science Cameras for Flight

To unveil the complexity of the solar atmosphere, measurement of the magnetic field in the upper chromosphere and transition region is fundamentally important, as this is where the forces transition from plasma to magnetic field dominated. Measurements of the field are also needed to elucidate the energy transport from the lower atmospheric regions to the corona beyond. Such an advance in heliospheric knowledge became possible with the first flight of the international solar sounding rocket mission, CLASP. For the first time, linear polarization was measured in Hydrogen Lyman-Alpha at 121.60 nm in September 2015. For linear polarization measurements in this emission line, high sensitivity is required due to the relatively weak polarization signal compared to the intensity. To achieve this high sensitivity, a low-noise sensor is required with good knowledge of its characterization, including linearity. This work presents further refinement of the linearity characterization of the cameras flown in 2015. We compared the current from a photodiode in the light path to the digital response of the detectors. Pre-flight CCD linearity measurements were taken for all three flight cameras and calculations of the linear fits and residuals were performed. However, the previous calculations included a smearing pattern and a digital saturation region on the detectors which were not properly taken into account. The calculations have been adjusted and were repeated for manually chosen sub-regions on the detectors that were found not to be affected. We present a brief overview of the instrument, the calibration data and procedures, and a comparison of the old and new linearity results. The CLASP cameras will be reused for the successor mission, CLASP2, which will measure the Magnesium II h & k emission lines between 279.45 nm and 280.35 nm. The new approach will help to better prepare for and to improve the camera characterization for CLASP2.

detector↗

Demonstration of Prognostics-Enabled Decision Making Algorithms on a Hardware Mobile Robot Test Platform

Prognostics-enabled Decision Making (PDM) is an emerging research area that aims to integrate prognostic health information and knowledge about the future operating conditions into the process of selecting subsequent actions for the system. Previous work developing and testing PDM algorithms has been done in simulation; this paper describes the effort leading to a successful demonstration of PDM algorithms on a hardware mobile robot platform. The hardware platform, based on the K11 planetary rover prototype, was modified to allow injection of selected fault modes related to the rover’s electrical power subsystem. The PDM algorithms were adapted to the hardware platform, including development of a software module framework, a new route planner, and modifications to increase the algorithms’ robustness to sensor noise and system timing issues. A set of test scenarios was chosen to demonstrate the algorithms’ capabilities. The modifications to run with a hardware platform, the test scenarios, and the test results are described in detail. The results show a successful use of PDM algorithms on a hardware test platform to optimize mission planning in the presence of electrical system faults.

Prognosis↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: ACAS Xu HITL Overview

This presentation provides an overview of a recently completed human-in-the-loop simulation, conducted as part of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. This study examined how to present resolution advisories (RAs) issued by Airborne Collision Avoidance System (ACAS) Xu, which can be in the vertical dimension, the horizontal dimension, or both (i.e., "blended"). The study varied the location of the ACAS Xu traffic information - it was either presented within an 'integrated' display or a 'standalone' display, where the traffic information was separated from the vehicle control interfaces and navigational information. The presentation covers the test set-up, scenario design, and facilities utilized in this experiment. The primary dependent variables are listed, but no detailed results are included in this outbrief since data analysis is still underway. Goal: assess ACAS Xu Run 5 in a HITL setting to measure pilot & system performance – RWC alerting and guidance – RA alerting and guidance • Horizontal-only, vertical-only, and blended RAs • Strengthening RAs, reversals and added/removed RAs during blended maneuvers – Incorporate realistic sensor noise into the simulation environment – Compare pilot and DAA system performance back to NASA’s Phase 1 DAA MOPS V&V HITL • We leveraged the findings of an engineering analysis conducted in March to help inform how to implement the Xu logic – Part 1 focused on how to display horizontal-only, vertical-only and blended RAs – Part 2 focused on how to display automated RA responses Xu Engineering Analysis Results Part 1 objectives: – Characterize pilot responses to (canned) ACAS Xu RAs in a variety of display configurations • With vs. Without text accompaniment • Simple vs. ‘Advanced’ aural alerting • Results – Pilots struggled to meet 5 seconds initial response requirement • Particularly against horizontal and blended RAs – Pilots failed to respond more quickly to secondary RAs • Expected response time to subsequent RAs = 2.5 seconds No clear effect of the different alerting conditions on response times – Response times primarily driven by RA type • Pilots demonstrated high level of compliance with RAs and self-reported Xu alerting and guidance as being acceptable – 1/5 reported text as being necessary – 4/5 wanted the aural alert to retain the original RA sequence (i.e., issue a follow-on RA second rather than first) – 4/5 wanted to retain the “Maintain Heading/Vertical Speed” aural alert in the event that the pilot reached their target response at the time of secondary RA Based on these results, we decided on the following for the HITL experimental design: – Incorporated an ‘auto-fill’ feature in Vigilant Spirit that removes the need for pilots to manually enter a heading or altitude for RAs • Pilots only have to click ‘Send’ to upload the RA target heading/altitude – Did not include an RA ‘text box’ • The auto-fill feature largely replaces the purpose of the text box – Using a combination of the ‘Basic’ and ‘Advanced’ aural alerting • In case of blended maneuvers will issue “Maintain Heading/Vertical Rate” if pilot has reached 1st RA target at the time the 2nd RA is issued • Integration and testing with Xu Run 5 also resulted in us adding display logic to modify how horizontal RAs are presented – Target heading was shown to update at approx. 1 Hz making it difficult for pilots to implement – Display logic limited horizontal RA strengthening to once every 5 seconds • Did not impact timing of reversals, new RAs (i.e., blended), or CoC Engineering Analysis Results

human systems integration↗

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

Applicability of a Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

As improvements are made to the accuracy and reliability of modeling and simulation techniques, certification by analysis becomes a more attractive alternative compared to traditional aircraft flight testing. Certification by analysis is especially cost-effective when one considers modifications to a previously certified aircraft. However, it is important that the models and methods used are applicable and accurate throughout the intended use domain. A framework for estimating the performance and associated uncertainty was introduced in an earlier paper. The factors and limitations of this framework for estimating the performance and associated model form uncertainty are explored to determine the range of applicability of the framework, particularly with respect to model form, process and sensor noise, and quality of available flight test data. This paper focuses on the general limitations and applicability of the framework and not the applicability of the individual methods to a range of modified configurations, which requires a large number of modified configurations and is an area for future work. The effects of these factors on the performance and uncertainty results are demonstrated using NASA’s Generic Transport Model aircraft.

uncertainty quantification↗

Gust Load Alleviation Control and Gust Estimation for a High Aspect Ratio Wing Wind Tunnel Model

This paper presents the gust load alleviation (GLA) study of the aspect ratio 13.5 Common Research Model (CRM) wind-tunnel model. This study details the design of the GLA controller in preparation for wind-tunnel testing in the Transonic Dynamics Tunnel at NASA Langley Research Center. An aeroservolastic (ASE) model was first reduced using a model reduction method that takes advantage of the sinusoidal steady-state response. Then, the reduced model was used to design an extended-state Kalman filter which estimates the states and the sinusoidal gust input. The GLA control was then derived using the optimal control solution to a multi-objective cost function. The results of the GLA controller indicate a 75.6% reduction in wing-root strain while maintaining robust stability margins. The final paper will include performance under sub-optimal conditions, e.g., sensor noise, uncertainty in gust frequency, etc..

Christopher Forte↗

Uncertainty in Servicing and Assembly Tasks for Space Robotic Manipulators

This presentation will discuss a subset of the sources of uncertainty that impact autonomous in-space servicing, assembly, and manufacturing missions. These include robotic manipulator modeling uncertainties in both kinematics and dynamics, perception error associated machine learning models for pose estimation, and sensor noise. Mitigation strategies will be discussed including the incorporation of capture envelopes in the design of robotic tools and selection of robot goal poses to minimize end-effector sensitivity in manipulators with redundant degrees of freedom.

robotics↗

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Hybrid Feedforward-Feedback Noise Control Using Virtual Sensors

Several approaches to active noise control using virtual sensors are evaluated for eventual use in an active headrest. Specifically, adaptive feedforward, feedback, and hybrid control structures are compared. Each controller incorporates the traditional filtered-x least mean squares algorithm. The feedback controller is arranged in an internal model configuration to draw comparisons with standard feedforward control theory results. Simulation and experimental results are presented that illustrate each controllers ability to minimize the pressure at both physical and virtual microphone locations. The remote microphone technique is used to obtain pressure estimates at the virtual locations. It is shown that a hybrid controller offers performance benefits over the traditional feedforward and feedback controllers. Stability issues associated with feedback and hybrid controllers are also addressed. Experimental results show that 15-20 dB reduction in broadband disturbances can be achieved by minimizing the measured pressure, whereas 10-15 dB reduction is obtained when minimizing the estimated pressure at a virtual location.

Bean, Jacob↗

An ultrahigh-accuracy body pointing system for the Large Space Telescope

The Large Space Telescope (LST) program is aimed at placing a three-meter diffraction-limited telescope in a 270-nm orbit to perform astronomical observations that are not possible with earth-based telescopes. A complex simulation model is described which was developed to determine whether the stringent pointing stability requirements could be met. The model (programmed on a hybrid computer) included detailed dynamic representation of control moment gyros (CMGs) and reaction wheels (RWs), including their noise characteristics; dynamic sensor representation (including noise); shockmounts for the CMG actuators; detailed representation of an image motion compensation system; and a detailed flexible body vehicle model. Stability and performance studies based on the simulation model showed that the body pointing system will meet LST requirements in the presence of CMG vibrational disturbances and sensor noise. The recommended system consists of three orthogonally mounted RWs for primary short-term control, and a cluster of CMG actuators for continuous RW desaturation and vehicle maneuvering.

Rybak, S. C.↗