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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Navier-Stokes Analysis of the Flowfield Characteristics of an Ice Contaminated Aircraft Wing

An analytical study was performed as part of the NASA Lewis support of a National Transportation Safety Board (NTSB) aircraft accident investigation. The study was focused on the performance degradation associated with ice contamination on the wing of a commercial turbo-prop-powered aircraft. Based upon the results of an earlier numerical study conducted by the authors, a prominent ridged-ice formation on the subject aircraft wing was selected for detailed flow analysis using 2-dimensional (2-D), as well as, 3-dimensional (3-D) Navier-Stokes computations. This configuration was selected because it caused the largest lift decrease and drag increase among all the ice shapes investigated in the earlier study. A grid sensitivity test was performed to find out the influence of grid spacing on the lift, drag, and associated angle-of-attack for the maximum lift (C(sub lmax)). This study showed that grid resolution is important and a sensitivity analysis is an essential element of the process in order to assure that the final solution is independent of the grid. The 2-D results suggested that a severe stability and control difficulty could have occurred at a slightly higher angle-of-attack (AOA) than the one recorded by the Flight Data Recorder (FDR). This stability and control problem was thought to have resulted from a decreased differential lift on the wings with respect to the normal loading for the configuration. The analysis also indicated that this stability and control problem could have occurred whether or not natural ice shedding took place. Numerical results using an assumed 3-D ice shape showed an increase of the angle at which this phenomena occurred of about 4 degrees. As it occurred with the 2-D case, the trailing edge separation was observed but started only when the AOA was very close to the angle at which the maximum lift occurred.

Chung, J.↗
NASA NTRS1977

Performance and safety aspects of the XV-15 tilt rotor research aircraft

Aircraft performance is presented illustrating the flexibility and capability of the XV-15 to conduct its planned proof-of-concept flight research in the areas of dynamics, stability and control, and aerodynamics. Additionally, the aircraft will demonstrate mission-type performance typical of future operational aircraft. The aircraft design is described and discussed with emphasis on the safety and fail-operate features of the aircraft and its systems. Two or more levels of redundancy are provided in the dc and ac electrical systems, hydraulics, conversion, flaps, landing gear extension, SCAS, and force-feel. RPM is maintained by a hydro-electrical blade pitch governor that consists of a primary and standby governor with a cockpit wheel control for manual backup. The two engines are interconnected for operation on a single engine. In the event of total loss of power, the aircraft can enter autorotation starting from the airplane as well as the helicopter mode of flight.

Wernicke, K. G.↗
NASA NTRS2018

Towards a Rigorous Basis for Specific Operations Risk Assessment of UAS

The Specific Operations Risk Assessment (SORA) guidance represents the consensus of various national aviation authorities on a common process to identify, qualitatively assess, and manage the safety risk posed by unmanned aircraft systems (UAS), when preparing the safety case required for regulatory approval to conduct certain types of operations. As such, it can be considered a de facto standard, being increasingly adopted by various relevant stakeholders. This paper first gives an overview of the SORA process and associated methods, identifying a number of inconsistencies in risk identification and assessment, also discussing plausible strategies to close the associated gaps. Then, we give a well-founded basis for the applicable concepts, such as barrier integrity, assurance, and robustness, following which we present a preliminary and simple probabilistic formalization of the underpinning barrier-based safety model. We illustrate our overall approach through a worked example, also discussing how a Bayesian framework can facilitate extending and enhancing our initial formalization. We conclude with a discussion of the opportunities afforded by our approach, such as a well-founded basis for barrier selection, whilst addressing the associated challenges. The main objective of this work is to complement the current SORA guidance through a principled, mathematicallybased approach to risk assessment, particularly when it is applied to higher-risk operational concepts that warrant greater rigor in safety assessment and assurance.

Safety Cases↗
NASA NTRS2012

Aircraft Design Considerations to Meet One Engine Inoperative (OEI) Safety Requirements

Commercial airlines are obligated to operate such that an aircraft can suffer an engine failure at any point in its mission and terminate the flight without an accident. Only minimal aircraft damage is allowable, such as brake replacement due to very heavy application, or an engine inspection and/or possible removal due to use of an emergency rating. Such performance criteria are often referred to as zero exposure, referring to zero accident exposure to an engine failure. The critical mission segment for meeting one engine inoperative (OEI) criteria is takeoff. For a given weight, wind, and ambient condition, fixed wing aircraft require a balanced field length. This is the longer of the distance to take off if an engine fails at a predetermined critical point in the takeoff profile, or the distance to reject the takeoff and brake to a stop. Rotorcraft have requirements for horizontal takeoff procedures that are equivalent to a balanced field length requirements for fixed wing aircraft. Rotorcraft also perform vertical procedures where no runway or heliport distance is available. These were developed primarily for elevated heliports as found on oil rigs or rooftops. They are also used for ground level operations as might be found at heliports at the end of piers or other confined areas.

Scott, Mark W.↗
NASA NTRS2016

Certification Strategies using Run-Time Safety Assurance for Part 23 Autopilot Systems

Part 23 aircraft operation, and in particular general aviation, is relatively unsafe when compared to other common forms of vehicle travel. Currently, there exists technologies that could increase safety statistics for these aircraft; however, the high burden and cost of performing the requisite safety critical certification processes for these systems limits their proliferation. For this reason, many entities, including the Federal Aviation Administration, NASA, and the US Air Force, are considering new options for certification for technologies that will improve aircraft safety. Of particular interest, are low cost autopilot systems for general aviation aircraft, as these systems have the potential to positively and significantly affect safety statistics. This paper proposes new systems and techniques, leveraging run-time verification, for the assurance of general aviation autopilot systems, which would be used to supplement the current certification process and provide a viable path for near-term low-cost implementation. In addition, discussions on preliminary experimentation and building the assurance case for a system, based on these principles, is provided.

automatic collision avoidance↗
NASA NTRS2003

Associations between errors and contributing factors in aircraft maintenance

In recent years cognitive error models have provided insights into the unsafe acts that lead to many accidents in safety-critical environments. Most models of accident causation are based on the notion that human errors occur in the context of contributing factors. However, there is a lack of published information on possible links between specific errors and contributing factors. A total of 619 safety occurrences involving aircraft maintenance were reported using a self-completed questionnaire. Of these occurrences, 96% were related to the actions of maintenance personnel. The types of errors that were involved, and the contributing factors associated with those actions, were determined. Each type of error was associated with a particular set of contributing factors and with specific occurrence outcomes. Among the associations were links between memory lapses and fatigue and between rule violations and time pressure. Potential applications of this research include assisting with the design of accident prevention strategies, the estimation of human error probabilities, and the monitoring of organizational safety performance.

Professional Competence↗
NASA NTRS1996

A Program in Air Transportation Technology (Joint University Program)

The Joint University Program on Air Transportation Technology was conducted at Princeton University from 1971 to 1995. Our vision was to further understanding of the design and operation of transport aircraft, of the effects of atmospheric environment on aircraft flight, and of the development and utilization of the National Airspace System. As an adjunct, the program emphasized the independent research of both graduate and undergraduate students. Recent principal goals were to develop and verify new methods for design and analysis of intelligent flight control systems, aircraft guidance logic for recovery from wake vortex encounter, and robust flight control systems. Our research scope subsumed problems associated with multidisciplinary aircraft design synthesis and analysis based on flight physics, providing a theoretical basis for developing innovative control concepts that enhance aircraft performance and safety. Our research focus was of direct interest not only to NASA but to manufacturers of aircraft and their associated systems. Our approach, metrics, and future directions described in the remainder of the report.

Stengel, Robert F.↗
NASA NTRS2017

Prognostics and Health Monitoring: Application to Electric Vehicles

As more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. determine state-of-charge in batteries. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Prognostics↗
NASA NTRSDate not supplied

Systems Health Management and Decision Making

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Discuss research approach to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms. Note - This presentation is for the short workshop conducted at the same conference and contains all previously approved and published information.

Systems Health Managent↗
NASA NTRS2018

Systems Health Monitoring and Prognostics Using Model Based Approach

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms.

Electronics Prognostics↗
NASA NTRS2020

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗
NASA NTRSDate not supplied

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Batteries↗
NASA NTRSDate not supplied

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Battery Prognostics↗
NASA NTRS2020

Model Based Diagnostics and Prognostics Framework for Systems Health Management

In order to tackle and solve the system health prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. This presentation will cover a physics based-modeling approach implemented for case-studies in battery and composite structures for prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Banerjee, Portia↗
NASA NTRSDate not supplied

Evaluation of Initial and Mid-Term Air Traffic Procedures for Urban Air Mobility Operations

Urban air mobility (UAM) operations are expected to expand in scale over the next several years as novel aircraft types, including electric vertical takeoff and landing aircraft, are certified and begin operations. These new aircraft may increase safety, decrease noise, and lower operating costs compared with helicopters, allowing them to operate in ways existing aircraft do not. It is vital that these expanded operations are compatible with and do not disrupt existing operations or the air traffic management system. To study the ways in which scaled UAM operations can best integrate in the national airspace system, NASA and Joby Aviation partnered to conduct a high-fidelity air traffic controller-in-the-loop study. Building on air traffic procedures used to manage high tempo operations in other parts of the airspace, new procedures, routes, and communications protocols were developed and tested by retired controllers in NASA’s Future Flight Central tower simulation facility. In addition, new cooperative airspace constructs in the form of corridors were developed to understand their potential contributions to even greater scales of operation. The controllers managed traffic scenarios in the Dallas-Fort Worth and Dallas Love Field airports consisting of fleets of up to 100 UAM aircraft operating alongside traditional traffic . Metrics for air traffic controller workload, duration of communications, departure delays, and other measures of allowable aircraft throughput were collected. The analysis indicates that using today’s procedures for initial UAM operations under nominal conditions could enable up to 40 operations per hour to an airport’s central terminal area if that involved crossing a runway and up to 55operations per hour if reaching the central terminal did not involve crossing a runway. Operations at these tempos did not delay or otherwise interfere with simulated runway traffic and were rated acceptable by the air traffic controllers. The new corridor constructs dramatically lowered controller workload in certain circumstances, suggesting they may be effective in further increasing the allowable scale of operations.

Urban Air Mobility↗
NASA NTRSDate not supplied

Evaluation of Initial and Mid-Term Air Traffic Procedures for Urban Air Mobility

Urban air mobility (UAM) operations are expected to expand in scale over the next several years as novel aircraft types, including electric vertical takeoff and landing aircraft, are certified and begin operations. These new aircraft may increase safety, decrease noise, and lower operating costs compared with helicopters, allowing them to operate in ways existing aircraft do not. It is vital that these expanded operations are compatible with and do not disrupt existing operations or the air traffic management system. To study the ways in which scaled UAM operations can best integrate in the national airspace system, NASA and Joby Aviation partnered to conduct a high-fidelity air traffic controller-in-the-loop study. Building on air traffic procedures used to manage high tempo operations in other parts of the airspace, new procedures, routes, and communications protocols were developed and tested by retired controllers in NASA’s Future Flight Central tower simulation facility. In addition, new cooperative airspace constructs in the form of corridors were developed to understand their potential contributions to even greater scales of operation. The controllers managed traffic scenarios in the Dallas-Fort Worth and Dallas Love Field airports consisting of fleets of up to 100 UAM aircraft operating alongside traditional traffic. Metrics for air traffic controller workload, duration of communications, departure delays, and other measures of allowable aircraft throughput were collected. The analysis indicates that using today’s procedures for initial UAM operations under nominal conditions could enable up to 40 operations per hour to an airport’s central terminal area if that involved crossing a runway and up to 55 operations per hour if reaching the central terminal did not involve crossing a runway. Operations at these tempos did not delay or otherwise interfere with simulated runway traffic and were rated acceptable by the air traffic controllers. The new corridor constructs dramatically lowered controller workload in certain circumstances, suggesting they may be effective in further increasing the allowable scale of operations.

Advanced Air Mobility↗
NASA NTRS2006

In-Flight Validation of a Pilot Rating Scale for Evaluating Failure Transients in Electronic Flight Control Systems

Engineering development and qualification of a Research Flight Control System (RFCS) for the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-60A has motivated the development of a pilot rating scale for evaluating failure transients in fly-by-wire flight control systems. The RASCAL RFCS includes a highly-reliable, dual-channel Servo Control Unit (SCU) to command and monitor the performance of the fly-by-wire actuators and protect against the effects of erroneous commands from the flexible, but single-thread Flight Control Computer. During the design phase of the RFCS, two piloted simulations were conducted on the Ames Research Center Vertical Motion Simulator (VMS) to help define the required performance characteristics of the safety monitoring algorithms in the SCU. Simulated failures, including hard-over and slow-over commands, were injected into the command path, and the aircraft response and safety monitor performance were evaluated. A subjective Failure/Recovery Rating (F/RR) scale was developed as a means of quantifying the effects of the injected failures on the aircraft state and the degree of pilot effort required to safely recover the aircraft. A brief evaluation of the rating scale was also conducted on the Army/NASA CH-47B variable stability helicopter to confirm that the rating scale was likely to be equally applicable to in-flight evaluations. Following the initial research flight qualification of the RFCS in 2002, a flight test effort was begun to validate the performance of the safety monitors and to validate their design for the safe conduct of research flight testing. Simulated failures were injected into the SCU, and the F/RR scale was applied to assess the results. The results validate the performance of the monitors, and indicate that the Failure/Recovery Rating scale is a very useful tool for evaluating failure transients in fly-by-wire flight control systems.

Kalinowski, Kevin F.↗