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Results for “Goal-oriented adaptivity”

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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12 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Mission Data System Java Edition Version 7

The Mission Data System framework defines closed-loop control system abstractions from State Analysis including interfaces for state variables, goals, estimators, and controllers that can be adapted to implement a goal-oriented control system. The framework further provides an execution environment that includes a goal scheduler, execution engine, and fault monitor that support the expression of goal network activity plans. Using these frameworks, adapters can build a goal-oriented control system where activity coordination is verified before execution begins (plan time), and continually during execution. Plan failures including violations of safety constraints expressed in the plan can be handled through automatic re-planning. This version optimizes a number of key interfaces and features to minimize dependencies, performance overhead, and improve reliability. Fault diagnosis and real-time projection capabilities are incorporated. This version enhances earlier versions primarily through optimizations and quality improvements that raise the technology readiness level. Goals explicitly constrain system states over explicit time intervals to eliminate ambiguity about intent, as compared to command-oriented control that only implies persistent intent until another command is sent. A goal network scheduling and verification process ensures that all goals in the plan are achievable before starting execution. Goal failures at runtime can be detected (including predicted failures) and handled by adapted response logic. Responses can include plan repairs (try an alternate tactic to achieve the same goal), goal shedding, ignoring the fault, cancelling the plan, or safing the system.

Reinholtz, William K.↗
NASA NTRSDate not supplied

Nearfield Anisotropic Mesh Adaptivity for the Third AIAA Sonic Boom Workshop

The Third AIAA Sonic Boom Workshop provides a unique opportunity to verify nearfield Computational Fluid Dynamics (CFD) tools. The workshop gathered nearfield CFD pressures from families of Mach-aligned, manually-tailored meshes on the C608 Low Boom Flight Test Demonstrator and the shock-plume interaction wind tunnel model. Here two classical adaptive strategies, multiscale and goal-oriented, are compared to the results obtained on tailored grids. The multiscale strategy is implemented independently in two separate toolsets. Details of the adapted mesh density are shown that resolve the complex interaction of boundary layers, shocks, expansions, and vortical structures. Mesh convergence of nearfield pressure signatures and their integral is shown. These detailed comparisons between adapted and manually-tailored meshes and independent implementations of mesh adaptation demonstrate the readiness of these methods for controlling the discretization error of nearfield sonic boom predication.

Julien Vanharen↗
NASA NTRS2014

Toward Automatic Verification of Goal-Oriented Flow Simulations

We demonstrate the power of adaptive mesh refinement with adjoint-based error estimates in verification of simulations governed by the steady Euler equations. The flow equations are discretized using a finite volume scheme on a Cartesian mesh with cut cells at the wall boundaries. The discretization error in selected simulation outputs is estimated using the method of adjoint-weighted residuals. Practical aspects of the implementation are emphasized, particularly in the formulation of the refinement criterion and the mesh adaptation strategy. Following a thorough code verification example, we demonstrate simulation verification of two- and three-dimensional problems. These involve an airfoil performance database, a pressure signature of a body in supersonic flow and a launch abort with strong jet interactions. The results show reliable estimates and automatic control of discretization error in all simulations at an affordable computational cost. Moreover, the approach remains effective even when theoretical assumptions, e.g., steady-state and solution smoothness, are relaxed.

Simulations↗
NASA NTRSDate not supplied

FUN3D Mesh Adaptation Simulations of 4th AIAA High-Lift Prediction Workshop Case 1a

This paper describes in detail the FUN3D Mesh adaptation simulation results for Case 1a of the 4th AIAA High-Lift Prediction Workshop (HLPW-4). The Stabilized Finite Element library with FUN3D is used along with the Negative Spalart-Allmaras One-Equation Model to simulate fully turbulent free-air flow around the High Lift version of the Common Research Model at three flap settings. Meshes are adapted using multi-scale and goal-oriented metrics. The results are presented and the discussion focuses on the predicted differences between the three flap settings. Coefficients of lift, drag, and pitching moment are predicted within 7% of values measured in the QinetiQ 5m Wind Tunnel at each flap setting. Predicted surface pressures and skin friction distributions show inconsistent discrepancies with measurements across the flap settings. Consequently, flap increments for these figures of merit are not well predicted. These predictions are consistent with submissions to the HLPW-4 from other RANS-SA methods. Visualizations of Liutex vortex cores colored by angular velocity are presented as possible new quantitative and qualitative perspective for solution evaluation.

High-Lift Prediction Workshop↗
NASA NTRSDate not supplied

Verification of Viscous Goal-Based Anisotropic Mesh Adaptation

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics. A key ingredient for the broader acceptance of unstructured mesh adaptation is the verification of these implementations. Anisotropic metric construction methods are evaluated with analytically defined primal fields and the corresponding entropy variables as adjoint fields. This allows the comparison of different metric formulations and different implementations of the same formulation without the complications of a flow and adjoint solution method. The convergence of the output associated with the entropy variable adjoint is studied for mesh adaptation to these fields and a manufactured solution. Mesh adapted drag output is studied for two simple wings in compressible laminar flow to show fine-mesh convergence of multiple metric construction methods to less than a single drag count. The documentation of these verification exercises helps to prepare these goal-based methods for routine use in more complex simulations for production workflows.

mesh adaptation↗
NASA NTRS2018

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating the tool Playbook, a mission planning and scheduling tool used for analog missions and research experiments at NASA. We are adapting Playbook to support an unmanned aerial vehicle (UAV) demonstration that will simulate a "search and recover" mission. To support this demonstration, we need to test this software and its usability with human subjects. Playbook will be used to plan, edit, and monitor simulated UAV swarms, and we are interested in evaluating these capabilities. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between these two agents. When guiding swarms the user should not be concerned with moving waypoints, adjusting heading and altitude or any other small actions that traditional pilots control. Providing situational awareness through sensor data including radar, heat, live camera feed, and topographic information are key when managing multiple UAVs together. First responders need a good picture of disaster areas in order to make informed decisions. These sensors can initiate movements in the mission that indicate when the human should take control of single aircraft.

UAV swarms↗
NASA NTRS2018

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating Playbook for CASAS (Connected Autonomous Smart Aerospace Systems), a tool designed to aid first responders in disaster relief efforts. We are adapting an existing tool, Playbook, to support a future unmanned aircraft system (UAS) swarm demonstration. Playbook for CASAS will be used to plan, edit, and monitor simulated UAS swarms, and we are interested in evaluating the user experience of this prototype as well as developing recommendations for future UAS interfaces. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between users and automation. Future interfaces, however, must allow for adaptive management of the swarm not a constant split in human-automation control. Our early research indicates that when a single pilot is controlling swarms of robotic agents, such as UAS or ground rovers, operators require a higher level, goal-based interface with usability at its core. Along with that high-level control, users can leverage sensors within the swarm to be notified when lower level actions must be taken by the pilot. First responders working in disaster relief efforts require a high level of situational awareness (SA) and precise control at key moments within a mission. This balance in operator workload paired with SA can lead to improved safety and mission outcomes. Our research below outlines leverage points as well as the balance between human involvement and autonomy in UAS interfaces.

UAS↗
NASA NTRS2016

Near-Body Grid Adaption for Overset Grids

A solution adaption capability for curvilinear near-body grids has been implemented in the OVERFLOW overset grid computational fluid dynamics code. The approach follows closely that used for the Cartesian off-body grids, but inserts refined grids in the computational space of original near-body grids. Refined curvilinear grids are generated using parametric cubic interpolation, with one-sided biasing based on curvature and stretching ratio of the original grid. Sensor functions, grid marking, and solution interpolation tasks are implemented in the same fashion as for off-body grids. A goal-oriented procedure, based on largest error first, is included for controlling growth rate and maximum size of the adapted grid system. The adaption process is almost entirely parallelized using MPI, resulting in a capability suitable for viscous, moving body simulations. Two- and three-dimensional examples are presented.

Buning, Pieter G.↗
NASA NTRSDate not supplied

Nearfield Anisotropic Mesh Adaptation for the Third AIAA Sonic Boom Workshop

Sonic boom prediction is critical for the development of low-boom supersonic aircraft and encouraging a replacement of the overland commercial supersonic ban with a certification standard. The Third AIAA Sonic Boom Workshop nearfield test cases provide a unique opportunity to review anisotropic adaptive-mesh strategies for complex geometries with important propulsion interaction effects. Anisotropic metrics formulated to control estimated Mach interpolation and integrated nearfield pressure signature (goal-oriented) errors are compared with the results obtained on workshop-provided meshes. Detailed flow solutions and mesh renderings are combined with computational schlieren images to reveal the complex interactions present in a shock-plume interaction wind tunnel model and a prototype of the Low-Boom Flight Demonstrator. A favorable comparison of independent implementations of the entire simulation process provides evidence that each process is implemented correctly and sets a solid foundation for confidence in the nearfield prediction of each method.

sonic boom↗
NASA NTRSDate not supplied

Goal-Oriented Discretization Error Control in Coupled Nearfield-Farfield Low-Boom Simulations

The method of adjoint weighted residuals is used to determine the level of discretization error in loudness predictions of sonic booms on the ground. We analyze the standard nearfied-farfield domain decomposition approach. In the nearfield domain, the three-dimensional Euler equations are solved to obtain a pressure signature generated by the aircraft. In the farfield, this waveform is propagated through the atmosphere to the ground by solving the augmented Burgers’ equation. Loudness is characterized using weighted sound-exposure-level metrics. We formulate discretization error estimates for the ground signature and loudness metrics for this one-way coupled system. Although the nearfield solution is independent of the farfield, the adjoint formulation for the coupled system provides feedback from the farfield to identify high-error regions in the nearfield. The results demonstrate that the discrete adjoint implementation is asymptotically consistent and provides reliable error estimates. Furthermore, we show how the error can be controlled through adaptive refinement of the nearfield mesh. The approach is evaluated on two- and three-dimensional problems, including the X-59 flight demonstration aircraft.

CST↗
NASA NTRSDate not supplied

An Oculometric Standard to Assess the Performance of the Ocular System for Long Duration Spaceflight

Changes in the human brain, due to spaceflight, have been a challenge to the space program since its inception; a challenge that is becoming more acute as extended International Space Station (ISS) missions become routine, a return to crewed lunar exploration is about to begin, and a multi-year crewed trip to Mars is being planned. Determining the extent to which neurophysiological adaptations may adversely impact performance in operational tasks, assessing the full-time course of these changes, and identifying/mitigating any potential long-term health consequences are crucial steps required to enable safe crew-autonomous, long-duration, deep-space missions. Vision is the predominant perceptual sense used to guide cognition and motor control in humans. Thus, it is critical for the success of any future, long-duration mission to understand how long-term exposure to microgravity and to other stressors of spaceflight and their interactions, impact visual function. This is an especially challenging task given the small and disparate samples from which we have been and will be able to collect human performance data. NASA has recently been carefully tracking spaceflight-induced ophthalmic changes, driven in large part by the fluid shifts related to microgravity. In particular, a recent study of Optical Coherence Tomography (OCT) postflight measures revealed that more than two-thirds of US crew members experience significant increases in retinal thickness after 6month or longer ISS missions. Space Associated Neuro-ocular Syndrome (SANS) also includes visual acuity decrements and other ocular structural changes that could adversely impact in-flight performance as missions become longer. However, the impact of spaceflight on the visual system is not limited to the retina. Recent comparisons of pre-and post-flight brain images have revealed structural changes throughout the brain that implicate visual, visuomotor, and visual-cognitive pathways, consistent with observed functional impacts (e.g., decreased speed/accuracy/timing of fine goal-oriented movements). Current limitations on inflight testing make it very difficult to determine when and under what conditions SANS and other disruptions of human neurological subsystems arise. Currently, one cannot anticipate the time course and extent of impairment and recovery. This study addresses this knowledge gap by creating an integrated framework of the relevant existing literature on visual and oculomotor function during spaceflight with an eye towards complementing current structural measures of visuomotor impairment with new oculometric standard measures. Using eye-movement based visual function assessment and diagnostics would provide a valuable enhancement of crew health and performance monitoring in support of deepspace exploration.

Vision↗