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NASA NTRSDate not supplied

High Fidelity Adaptively Refined CFD and Reduced Order Models of a High Aspect Ratio Aeroelastic Wing Wind-Tunnel Model

The NASA Advanced Air Transport Technology (AATT) goal of reduced fuel burn for transport aircraft has led to the NASA N+3 High Aspect Ratio Wing (HARW) subproject. This project requires identifying, developing, and demonstrating key technologies and integrated multidisciplinary solutions to enable a safe, high performance, aeroelastic wing. Since this aircraft will have a high aspect ratio wing, aeroelasticity is expected to be a major issue in the design. In this paper high fidelity computational fluid dynamics (CFD) is performed with flow adapted meshes. A system identification of the aerodynamics is developed using both a multi-modal multi-sine time-marching and a multi-mode linear frequency domain method. GLA, MLA and flutter suppression simulations will be performed.

Robert Bartels↗
NASA NTRS2000

A Very High Order, Adaptable MESA Implementation for Aeroacoustic Computations

Since computational efficiency and wave resolution scale with accuracy, the ideal would be infinitely high accuracy for problems with widely varying wavelength scales. Currently, many of the computational aeroacoustics methods are limited to 4th order accurate Runge-Kutta methods in time which limits their resolution and efficiency. However, a new procedure for implementing the Modified Expansion Solution Approximation (MESA) schemes, based upon Hermitian divided differences, is presented which extends the effective accuracy of the MESA schemes to 57th order in space and time when using 128 bit floating point precision. This new approach has the advantages of reducing round-off error, being easy to program. and is more computationally efficient when compared to previous approaches. Its accuracy is limited only by the floating point hardware. The advantages of this new approach are demonstrated by solving the linearized Euler equations in an open bi-periodic domain. A 500th order MESA scheme can now be created in seconds, making these schemes ideally suited for the next generation of high performance 256-bit (double quadruple) or higher precision computers. This ease of creation makes it possible to adapt the algorithm to the mesh in time instead of its converse: this is ideal for resolving varying wavelength scales which occur in noise generation simulations. And finally, the sources of round-off error which effect the very high order methods are examined and remedies provided that effectively increase the accuracy of the MESA schemes while using current computer technology.

Dydson, Roger W.↗
NASA NTRS1993

A solution-adaptive hybrid-grid method for the unsteady analysis of turbomachinery

A solution-adaptive method for the time-accurate analysis of two-dimensional flows in turbomachinery is described. The method employs a hybrid structured-unstructured zonal grid topology in conjunction with appropriate modeling equations and solution techniques in each zone. The viscous flow region in the immediate vicinity of the airfoils is resolved on structured O-type grids while the rest of the domain is discretized using an unstructured mesh of triangular cells. Implicit, third-order accurate, upwind solutions of the Navier-Stokes equations are obtained in the inner regions. In the outer regions, the Euler equations are solved using an explicit upwind scheme that incorporates a second-order reconstruction procedure. An efficient and robust grid adaptation strategy, including both grid refinement and coarsening capabilities, is developed for the unstructured grid regions. Grid adaptation is also employed to facilitate information transfer at the interfaces between unstructured grids in relative motion. Results for grid adaptation to various features pertinent to turbomachinery flows are presented. Good comparisons between the present results and experimental measurements and earlier structured-grid results are obtained.

Mathur, Sanjay R.↗
NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗
NASA NTRS1997

Solution adaptive Cartesian grid methods for aerodynamic flows with complex geometries

Cartesian methods for computational fluid dynamics are considered to offer an accurate and robust approach for the simulation of aerodynamic flows around geometrically complex bodies. A part of the ongoing research in this domain is reviewed with the aim of providing insight into the fundamental challenges faced by the practitioners of this approach, and a guide to further research. The integration schemes used in Cartesian solvers are similar to those used in other approaches. The emphasis is on the geometric algorithms, surface modeling and boundary conditions required to design a successful Cartesian mesh scheme.

Aftosmis, Michael J.↗
NASA NTRSDate not supplied

Standards Roadmapping for Mission Assurance in Commercial Spaceflight

This paper explores the application of established roadmapping approaches in standards planning and roadmap development to support mission assurance objectives. Mission assurance requires proactive planning across multiple domains including technical, schedule, cost, organizational, and policy. The intersection of these domains happens at the enterprise level, and enterprise systems engineering processes can systematically guide mission assurance activities, including development of standards roadmaps. Standards planning and development is a critical contributor to an effective mission assurance strategy, although standards are often developed and adopted reactively. Technology and standards planning is a key Enterprise Process Management activity, as identified by the Systems Engineering Body of Knowledge, and technology and standards roadmaps are strategic tools used to enable that process. Technology roadmapping has proven effective in guiding enterprise architecture and concept design, and standards planning supports enterprise requirements definition and management. However, there are limited methodologies to guide such standards planning activities. The application of technology roadmapping principles to standards planning formalizes the process and establishes a repeatable framework for standards development and integration. The framework development described in this paper fills a methodological gap by adapting proven roadmapping techniques to standards planning. Through a comparison of roadmapping methodologies and a case study analysis, this approach outlines a systematic process for anticipating and planning standards needs. In the case of developing a standards integration roadmap for NASA’s Office of Safety and Mission Assurance (OSMA), technology roadmapping principles were adapted to develop a roadmap framework to allow NASA and OSMA to define an agency-wide standards integration plan for commercial and industry safety and mission assurance standards. The outcome highlights key adaptations required for roadmapping in a standards context and describes the process steps to formalize a standards planning activity. The roadmapping framework adapted for standards development and integration enables more strategic, forward-looking standards planning and allows for better alignment between evolving capabilities and mission assurance requirements. Beyond its application to mission assurance, this methodology can be transferred to other domains requiring standards development, providing a systematic approach that integrates systems engineering principles into policy strategy and decision-making processes.

Enterprise Systems Engineering↗
NASA NTRS1987

An adaptive finite element scheme for the Euler and Navier-Stokes equations

The implementation of two explicit finite element schemes for the solution of the compressible Euler and Navier-Stokes equations is presented. The schemes can be employed with general unstructured triangular meshes in two dimensions. Either scheme can therefore be used as the basic solver in a solution adaptive mesh procedure in a direct manner. The particular adaptive approach which is advocated here is intended for the solution of steady state problems only and involves an adaptive regeneration of the grid at prescribed stages during the false transient. The grid regeneration is accomplished by a mesh generator which has the capability of generating triangular grids over computational domains of arbitrary shape. The procedure is illustrated by solving transonic flows over multi-airfoil configurations and high speed flows, involving shock interactions, past circular cylinders.

Morgan, K.↗
NASA NTRS1987

A linear quadratic Gaussian with loop transfer recovery proximity operations autopilot for spacecraft

An automatic control scheme for spacecraft proximity operations is presented. The controller is capable of holding the vehicle at a prescribed location relative to a target, or maneuvering it to a different relative position using straight line-of-sight translations. The autopilot uses a feedforward loop to initiate and terminate maneuvers, and for operations at nonequilibrium set-points. A multivariate feedback loop facilitates precise position and velocity control in the presence of sensor noise. The feedback loop is formulated using the Linear Quadratic Gaussian (LQG) with Loop Transfer Recovery (LTR) design procedure. Linear models of spacecraft dynamics, adapted from Clohessey-Wiltshire Equations, are augmented and loop shaping techniques are applied to design a target feedback loop. The loop transfer recovery procedure is used to recover the frequency domain properties of the target feedback loop. The resulting compensator is integrated into an autopilot which is tested in a high fidelity Space Shuttle Simulator. The autopilot performance is evaluated for a variety of proximity operations tasks envisioned for future Shuttle flights.

Chen, George T.↗
NASA NTRS1992

Intelligent data management for real-time spacecraft monitoring

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Schwuttke, Ursula M.↗
NASA NTRS1980

Grid generation for general three-dimensional configurations

A suitable grid system for complex three dimensional configurations such as wing/body/nacelle shape for the solution of nonlinear transonic flow problems was constructed. Two approaches were explored based on Thompson's body fitted coordinate concept. The most general approach was to divide the computational domain into multiple rectangular blocks where the configuration itself was also represented by a set of blocks whose structure follows the natural lines of the configuration. The block structured grid system was adaptable to complex configurations and gives good grid quality near physical corners. However, it introduced algorithm issues for the flow solution concerning the treatment of nonanalytic grid block boundaries and nonstandard grid cells. These issues were explored in relation to the grid generation. A more limited approach treats a wing/body configuration with only a single rectangular block in computational space. The issues involving nonstandard cells were avoided, but other limitations on grid resolution appear. Both a linear and a nonlinear system of grid generation equations were developed including methods of grid control.

Lee, K. D.↗
NASA NTRS1987

A full potential flow analysis with realistic wake influence for helicopter rotor airload prediction

A 3-D, quasi-steady, full potential flow solver was adapted to include realistic wake influence for the aerodynamic analysis of helicopter rotors. The method is based on a finite difference solution of the full potential equation, using an inner and outer domain procedure for the blade flowfield to accommodate wake effects. The nonlinear flow is computed in the inner domain region using a finite difference solution method. The wake is modeled by a vortex lattice using prescribed geometry techniques to allow for the inclusion of realistic rotor wakes. The key feature of the analysis is that vortices contained within the finite difference mesh (inner domain) were treated with a vortex embedding technique while the influence of the remaining portion of the wake (in the outer domain) is impressed as a boundary condition on the outer surface of the finite difference mesh. The solution procedure couples the wake influence with the inner domain solution in a consistent and efficient solution process. The method has been applied to both hover and forward flight conditions. Correlation with subsonic and transonic hover airload data is shown which demonstrates the merits of the approach.

Egolf, T. Alan↗
NASA NTRS1991

Euler calculations of unsteady transonic flow in cascades

In the present paper, Euler calculations of unsteady transonic flow in cascades are presented. A finite volume scheme is used to discretize the equations, which are implemented on a blade-fitted deformable mesh. The space-discretized equations are integrated forward in time using a multistage Runge-Kutta scheme. Adaptive dissipation terms of the type proposed by Jameson and Baker are added to capture shocks and to suppress nonphysical oscillations. Phase-shifted boundary conditions are used to reduce the computational domain to a single reference passage. No assumptions of small amplitudes or small flow deflections are made. Thus, the present code makes it possible to carry out aeroelastic calculations for cases where the shock strengths and oscillation amplitudes exceed the inherent limitations of potential flow codes.

Bendiksen, Oddvar O.↗
NASA NTRS2022

Event Report for The Ethical Artificial Intelligence Quantification Workshop

Artificial Intelligence (AI) is a powerful emerging technology area which requires special attention to using it ethically. AI ethics is still an emerging field, and the partners for this workshop and report seek to move AI ethics discussion ahead by experimenting with ways to measure AI ethics criteria. The following document describes the outcomes and learnings from The Ethical Artificial Intelligence Quantification Workshop held at the National Institute for Aerospace (NIA), Hampton, Virginia on May 12th, 2022. The purpose of the workshop was for participants to evaluate and experiment-with the methodology and process presented by AIEthics.World in cooperation with Intel Corporation. The meeting participants learned about the Ethical AI Certification and Maturity Model™ and applied the methodology to selected notional AI systems. The workshop facilitated the evaluation of the maturity of the AI system according to ethical considerations relevant to NASA, NIA and other participants. The workshop consisted of three main phases. The first phase focused on understanding and summarizing NASA’s ethical approaches, mission and values based on published documentation, discussions and individual insights & opinions of participants. This information was prioritized, weighted, ordered, and quantified in phase two, to formulate an alignment between human values (ethics) and their applicability to AI systems during all lifecycle phases. The first two phases were summarized as a form of ethical genealogy for artificial intelligence, specific to NASA’s ethical approaches. In the third and last phase of the workshop the participants evaluated notional examples of artificial intelligence to qualify and quantify its ability to adhere to the organizational ethics approaches, using the Ethical AI Certification and Maturity Model™. The workshop uses the concept of genealogy, in the traditional sense: the study and traceability of lines of ancestors in the process of evolutionary development from earlier forms. However, as it is applied to an Ethical AI definition, it is providing the insights to the necessary and mandatory traceability of content, data, metrics, telemetry, elements, and structures which are used in the AI’s lifecycle to foster and measure AI ethics in all steps of its lifecycle. The Ethical Artificial Intelligence Quantification Workshop provided NASA with the opportunity to apply the Ethical AI Certification and Maturity Model™, in combination with existing and well-known decision-making and quality control methods to identify the metrics and measurements for an Ethical AI and assess its ethical condition and quality aligned with NASA ethics approaches. The result of the workshop is the capacity for NASA to apply the maturity model assessment to its AI Systems as desired and if necessary, publish the ability of these AI Systems to adhere to the organizational ethical goals. AI ethics frameworks need to be customized for each application domain, for example, individual NASA Mission Directorates. General principles that work in one area such as AI/Machine Learning-based text analysis (the ethics of information-extraction) may need to be adapted for another such as sense-and-avoid decision-making in a flight environment. The workshop was conducted among approximately twenty NASA subject matter experts, so the elements noted above should be considered examples, not definitive NASA ethical AI principles, genealogy, etc. Generating a definitive AI ethics framework for an organization as diverse as NASA would require far more discussion, debate, review, etc. However, the workshop provided valuable insight into mechanisms and processes for quantifying AI ethical qualities.

Artificial Intelligence↗
NASA NTRSDate not supplied

Adaptive mesh refinement and turbulence modeling

Adaptive mesh refinement is shown to be essential in turbulence modeling. Adaptive Mesh Refinement (AMR) is a more computationally efficient means to obtain a discrete approximation to a continuous boundary value problem of a specified accuracy than classic isotropic grid refinement. Previous application of this methodology in the assessment of turbulence models suggested that the field variable solution on the interior of the domain was more sensitive to grid refinement than would be suggested by the sensitivity to grid refinement of surface quantities. Revisiting challenging high speed flow field revealed that issues believed to be fundamental turbulence model issues appear to be related to an under-resolved boundary layer edge – a flow detail previously considered unimportant.

Hypersonics↗
NASA NTRS2017

Evaluating the Stability of NASA's Space Launch System with Adaptive Augmenting Control

NASA's baseline Space Launch System (SLS) flight control system (FCS) design includes an adaptive augmenting control (AAC) component that modifies the attitude control system response to provide the classical gain-scheduled control architecture with additional performance and robustness. The NASA Engineering and Safety Center (NESC) teamed with the Space Launch System (SLS) Program to perform a comprehensive assessment of the stability and robustness of the FCS with AAC. This paper provides an overview of the approach, specific analysis techniques, and outcomes that were particularly relevant for the SLS Program. Multiple analysis techniques that specifically target the nonlinear AAC were commissioned as part of this assessment, which was completed outside of the Program's standard design analysis cycle. The following analyses were included, with each technique adding its own valuable insights: Lyapunov-based stability analysis, classical stability analysis with static AAC gain variations, circle criterion-based analysis of the FCS with a time-varying element, time-domain stability margin assessment, Monte Carlo simulations with expanded dispersions, and an extensive set of stressing cases. Several of the completed analyses focused on determining whether the inclusion of AAC introduced risk to the FCS, while others quantified the benefits of the adaptive augmentation.

Tannen S Vanzwieten↗
NASA NTRS1988

Genetic algorithms for adaptive real-time control in space systems

Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.

Vanderzijp, J.↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

reinforcement learning↗