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At least 343 records · Page 19

AIRNOISE: A Tool for Preliminary Noise-Abatement Terminal Approach Route Design

Noise from aircraft in the airport vicinity is one of the leading aviation-induced environmental issues. The FAA developed the Integrated Noise Model (INM) and its replacement Aviation Environmental Design Tool (AEDT) software to assess noise impact resulting from all aviation activities. However, a software tool is needed that is simple to use for terminal route modification, quick and reasonably accurate for preliminary noise impact evaluation and flexible to be used for iterative design of optimal noise-abatement terminal routes. In this paper, we extend our previous work on developing a noise-abatement terminal approach route design tool, named AIRNOISE, to satisfy this criterion. First, software efficiency has been significantly increased by over tenfold using the C programming language instead of MATLAB. Moreover, a state-of-the-art high performance GPU-accelerated computing module is implemented that was tested to be hundreds time faster than the C implementation. Secondly, a Graphical User Interface (GUI) was developed allowing users to import current terminal approach routes and modify the routes interactively to design new terminal approach routes. The corresponding noise impacts are then calculated and displayed in the GUI in seconds. Finally, AIRNOISE was applied to Baltimore-Washington International Airport terminal approach route to demonstrate its usage.

aircraft noise↗

Asteroid Fragmentation Approaches for Modeling Atmospheric Energy Deposition

During asteroid entry, energy is deposited in the atmosphere through thermal ablation and momentum-loss due to aerodynamic drag. Analytic models of asteroid entry and breakup physics are used to compute the energy deposition, which can then be compared against measured light curves and used to estimate ground damage due to airburst events. This work assesses and compares energy deposition results from four existing approaches to asteroid breakup modeling, and presents a new model that combines key elements of those approaches. The existing approaches considered include a liquid drop or "pancake" model where the object is treated as a single deforming body, and a set of discrete fragment models where the object breaks progressively into individual fragments. The new model incorporates both independent fragments and aggregate debris clouds to represent a broader range of fragmentation behaviors and reproduce more detailed light curve features. All five models are used to estimate the energy deposition rate versus altitude for the Chelyabinsk meteor impact, and results are compared with an observationally derived energy deposition curve. Comparisons show that four of the five approaches are able to match the overall observed energy deposition profile, but the features of the combined model are needed to better replicate both the primary and secondary peaks of the Chelyabinsk curve.

Modeling↗

An Energy-Based Low-Order Approach for Mission Analysis of Air Vehicles in LEAPS

Mission analysis methods that allow rapid analysis of conceptual aircraft provide great benefits to designers because a large number of feasibility and optimization studies can be performed quickly. This paper presents a novel low-order mission analysis approach that will be included in a new aircraft analysis tool called the Layered and Extensible Aircraft Performance System, also known as LEAPS. This approach is based on the mission analysis method used in the Flight Optimization System, also known as FLOPS. FLOPS has been developed at NASA Langley Research Center for over 30 years, and it is mainly used to analyze conventional aircraft (e.g., gas turbine-powered aircraft). One of the main features of FLOPS is its ability to perform rapid mission analysis. This quick analysis turnaround makes FLOPS a suitable tool to perform a large number of trade studies and optimizations. For this reason, the main concepts applied in FLOPS will be used and expanded in LEAPS to allow the analysis of unconventional aircraft that use novel propulsion systems. This expanded approach includes the capability to handle electric propulsion systems as well as multiple propulsor classes at the same time. A novel hybrid-electric aircraft configuration is used to investigate the potential benefits of the proposed mission analysis approach. The results show that the design space increases which can potentially lead to better designs.

Capristan, Francisco M.↗

Agile Approach to Assuring the Safety-Critical Embedded Software for NASA's Orion Spacecraft

Human-rated missions like those in NASA's Orion Program continue to grow in complexity. The role of software in achieving ambitious mission objectives has expanded dramatically in the last few decades. Assuring the safety and performance of the embedded flight software is quickly growing beyond the reach of traditional methods and resource levels. The methods used to build these software-dominant systems evolve in an on-going attempt to keep pace with the scope of our ambitions. Agile software development is now commonplace. The long timelines and large batches of work associated with traditional methods are being replaced by rapid delivery of small increments _ as system capabilities are realized in waves. Assurance of these critical software capabilities must therefore conquer an ever-expanding frontier of challenges, and do so with an approach matched to the evolving development methods. This paper recounts the journey of the Orion Independent Verification and Validation (IV&V) team as we addressed this dynamic environment. Widening our aperture to encompass a dramatically larger mission scope, while adjusting our cadence to synchronize with the rapid pace of agile software development, a new approach to IV&V is emerging. This approach is characterized by a sharper focus on mission capabilities, matched with a method to dynamically _follow the risk' as the IV&V team delivers more compelling assurance data in waves. Traditional methods prevalent in IV&V tend to scope the work using artifacts of the development process as they evolve from preliminary to final versions, and the pace of delivery was synchronized with the development timelines prevalent in the waterfall lifecycle. That more static approach is out of phase with the demands of the new environment. Scoping work according to the critical capabilities of the system (rather than artifacts of development) and synchronizing with the rapid pace of agile development, we are moving toward more effective parity with the demands of the environment. We explain the concrete steps we took, the principles that motivated our choices, and the results we have achieved to date.

Capability based assurance↗

Dawn Safing Approach to Ceres Re-Design

In mid-2014 the Dawn team finalized preparations for the spacecraft’s approach to Ceres. The design was the product of careful planning that began several years in advance, when the spacecraft left Vesta in September 2012. However, a few months prior to the anticipated start of approach, the spacecraft entered a safe mode. While temporary loss of thrust for ion propulsion missions is usually not mission-critical, it still presents many challenges. The safing event occurred at a time when thrusting to match Ceres’ orbital velocity was most effective, which meant the spacecraft must fly past Ceres before capturing into orbit. The new approach geometry changed the team’s strategy for navigating the spacecraft safely into orbit around Ceres with optical data. In this paper we describe the challenges of navigating the Dawn spacecraft into orbit around Ceres, including the safing event and re-design of the approach architecture.

Grebow, Daniel J.↗

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, A.↗

Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence

In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.

Mashiku, Alinda↗

Dawn Safing Approach to Ceres Re-Design

In mid-2014 the Dawn team finalized preparations for the spacecraft’s approach to Ceres. The design was the product of careful planning that began several years in advance, when the spacecraft left Vesta in September 2012. However, a few months prior to the anticipated start of approach, the spacecraft entered a safe mode. While temporary loss of thrust for ion propulsion missions is usually not mission-critical, it still presents many challenges. The safing event occurred at a time when thrusting to match Ceres’ orbital velocity was most effective, which meant the spacecraft must fly past Ceres before capturing into orbit. The new approach geometry changed the team’s strategy for navigating the spacecraft safely into orbit around Ceres with optical data. In this paper we describe the challenges of navigating the Dawn spacecraft into orbit around Ceres, including the safing event and re-design of the approach architecture.

Grebow, Dan↗

Face- and Cell-Averaged Nodal-Gradient Approach to Cell-Centered Finite-Volume Method on Mixed Grids

In this paper, the averaged nodal-gradient approach previously developed for triangular grids is extended to mixed triangular-quadrilateral grids. It is shown that the face- averaged approach leads to deteriorated iterative convergence on quadrilateral grids. To develop a convergent solver, we consider cell-averaging instead of face-averaging for quadri- lateral cells. We show that the cell-averaged approach leads to a convergent solver and can be efficiently combined with the face-averaged approach on mixed grids. The method is demonstrated for various inviscid and viscous problems from low to high Mach numbers on two-dimensional mixed grids.

Nishikawa, Hiroaki↗

Enabling Advanced Air Mobility Operations through Appropriate Trust in Human-Autonomy Teaming: Foundational Research Approaches and Applications

Emerging Advanced Air Mobility(AAM)operations will be enabled by increasingly autonomous systems, requiring technologies to take on more responsibilities and fundamentally altering traditional human-automation interaction paradigms. The growing reliance on higher levels of automation will necessitate research to identify capabilities and principles that facilitate humans and machines working and thinking better together, i.e., human-autonomy teaming (HAT). Trust is an inherent requirement in effective teams because when members work interdependently, those agents (human, automation) must be willing to accept a level of risk to rely upon each other to reach goals and contribute to team tasks. This work provides an initial approach to enabling AAM operations through appropriate trust within HAT. The main contributions of this approach resides in connecting the construct of trust to mental models. Using the outlined mental model approach, we propose novel HAT strategies, such as Adaptive Trust Calibration, and preview planned research activities derived from this approach. Additionally, we propose several practical applications that can currently be employed by AAM development communities.

Eric T Chancey↗

An Agile-Like Approach to Hardware Development: The Ejectable Data Recorder (EDR) for Orion's Ascent Abort 2 (AA-2) Test Flight

On July 2, 2019, the Ascent Abort 2 (AA-2) Flight Test Vehicle was launched from Cape Canaveral, with the goal of demonstrating the performance of Orion’s Launch Abort System (LAS) and collecting data from hundreds of sensors throughout the vehicle. The data collected during this test flight is of paramount importance, as it will be used to certify the Orion vehicle for human spaceflight. Originally, the data was to be downlinked via a single string network of antennas on the LAS, with the associated risk of potential data dropouts, as well as loss of data once the LAS was jettisoned. Thus, additional antennas were added onto the crew module (CM) to support data downlink post-LAS jettison, a buffer rebroadcast capability was added to fill in any gaps in data downlink transmissions, and an ejectable data recorder (EDR) subsystem was added to the CM as a redundant measure to collect all the instrumentation data. The EDR subsystem was added to the project about one year after the project commenced, which significantly reduced the available development time when compared with the other subsystems of the AA-2 Test Flight. The project was further accelerated by six months, around the critical design review gate. Due to the schedule compression challenge and the fact that the EDR subsystem was a backup system and not flight critical, the EDR subsystem was further challenged to find a new and more efficient way to develop hardware. Thus, the EDR subsystem experimented with different management and systems engineering processes, team sizes, communication methods, and tools. Some examples are novel uses of SharePoint as a Data-centric Project Management & Systems Engineering environment, a continuous testing approach through the lifecycle, and a Skunkworks approach to managing the team. The EDR subsystem blended Commercial Off The Shelf (COTS) hardware with in-house developed hardware and software to create a novel data retrieval capability. The capability evolved rapidly through a hardware in the loop simulation environment that enabled incremental component updates for not only the EDR subsystem but across the entire Crew Module. This paper will present an overview of how the EDR subsystem was managed and compare it to an Agile approach to managing projects. The paper will further provide a recommended approach to future Agile-like hardware development that incorporates lessons learned from the EDR experience.

Agile↗

A Systematic Approach to Hardware Qualification

A systematic approach for the development of a hardware qualification approach is described. This approach stems from the need to break the "Catch-22" of not being able to fly new technology because it hasn't flown. A physics of failure approach is used to identify failure modes and the impact and likelihood of these failures on the mission requirements is plotted in a Requirements Matrix. These same failure modes are plotted against the effectiveness of the available Preventions, Analyses, Control and Tests (PACTs) at screening for, or eliminating, these failure modes in a Test Effectiveness Matrix. Matrix multiplication results in a ranked set of PACTs which can be sorted according to cost and redundancy with other PACTs. This, and other information which results from the process, will allow project managers to make more informed decisions regarding the cost and risk tradeoffs inherent in any qualification program.

hardware↗

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

Urban Air Mobility: A Control-Centric Approach to Addressing Technical Challenges

Urban Air Mobility (UAM) is an emerging aviation sector and is playing an integral part in the on-demand mobility revolution. UAM is powered by the convergence of advances in distributed electrical propulsion (DEP) and vehicle autonomy. The complexity of operations in the urban environment and the unconventional vehicle configurations designed to take advantage of new propulsion technologies, result in numerous challenges that benefit from a control-centric approach. In this talk we outline some of these challenges and present our current approach to addressing them. For example, in order to achieve full market potential and access to UAM, vehicle autonomous flight is required. A key barrier to autonomous flight in a large multi-agent system is dealing with off-nominal situations and contingencies in a safe and predictable manner. We present our approach to intelligent contingency management, and share recent results and open problems. Additionally, we discuss another major barrier to ubiquitous UAM – the noise signature produced by vehicles with multiple rotors. We present our approach to minimizing such noise within the framework of the acoustically-aware vehicle.

UAM↗

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗

Adopting an Objectives-Driven Assurance Case Approach for Achieving Space Flight Mission Planetary Protection Objectives

Traditionally, NASA has utilized prescriptive technical and process requirements to ensure safety and mission assurance performance objectives for space flight missions are achieved. While prescriptive re-quirements may be easier to communicate and manage throughout the systems engineering process, the highly-constrained nature of prescriptive requirements can limit the ability to take advantage of cost-saving opportunities and offer limited ability to explore other options or alternative designs, processes, and methods. It can also be difficult to develop prescriptive requirements for objectives that are prob-abilistic in nature or that cannot be satisfied by direct verification. In contrast, the development of an assurance case allows for a compelling, comprehensible, and valid argument to be developed with support-ing evidence that shows safety and mission assurance objectives have been satisfied. Analogous to how patent applications are constructed for inventions, an assurance case has a high-level claim of meeting a safety and mission assurance objective, followed by a more specific set of sub-claims and technical evidence which supports the claims. The objectives-driven assurance case approach allows for a better understand-ing and exploration of the trade space, more flexibility to balance trades, and the ability to realize and implement technical and process innovations for resource, time, and cost savings. The assurance case is a living case that evolves over the entire program life cycle. Recently, NASA’s Office of Planetary Pro-tection (OPP) has adopted the assurance case approach as an acceptable methodology for demonstrating avoidance of contamination of target solar system bodies explored by NASA space flight missions. This methodology has been incorporated into NASA’s new technical standard for planetary protection and is currently being utilized by the Mars Sample Return campaign for safe sample containment during sample return. This presentation will explore the development and implementation of an assurance case approach in the context of planetary protection, the shift from prescriptive requirements and the ongoing culture change in the technical community, and the support and guidance from NASA’s OPP in adopting the assurance case approach for achieving planetary protection objectives on NASA’s space flight missions.

Elaine Seasly↗

Extensive Characterization of Aerosol Optical Properties and Chemical Component Concentrations: Application of the GRASP/Component Approach to Long-term AERONET Measurements

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93–1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Xindan Zhang↗

Distributed Sensing and Computer Vision Methods for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.

Evan Kawamura↗