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At least 289 records · Page 16

A self-contained, automated methodology for optimal flow control validated for transition delay

This paper describes a self-contained, automated methodology for flow control along with a validation of the methodology for the problem of boundary layer instability suppression. The objective of control is to match the stress vector along a portion of the boundary to a given vector; instability suppression is achieved by choosing the given vector to be that of a steady base flow, e.g., Blasius boundary layer. Control is effected through the injection or suction of fluid through a single orifice on the boundary. The present approach couples the time-dependent Navier-Stokes system with an adjoint Navier-Stokes system and optimality conditions from which optimal states, i.e., unsteady flow fields, and control, e.g., actuators, may be determined. The results demonstrate that instability suppression can be achieved without any a priori knowledge of the disturbance, which is significant because other control techniques have required some knowledge of the flow unsteadiness such as frequencies, instability type, etc.

Joslin, Ronald D.↗

Advanced Method to Estimate Fuel Slosh Simulation Parameters

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the estimation approach to a simple, accurately modeled system, its effectiveness and accuracy can be evaluated. The same experimental setup can then be used with fluid-filled tanks to further evaluate the effectiveness of the process. Ultimately, the proven process can be applied to the full-sized spinning experimental setup to quickly and accurately determine the slosh model parameters for a particular spacecraft mission. Automating the parameter identification process will save time, allow more changes to be made to proposed designs, and lower the cost in the initial design stages.

Schlee, Keith↗

Evaluation of Doppler radar for airport wind shear detection

The utility of Doppler radar measurement techniques for detecting low-level wind shear at airports is examined. The Doppler radar data of the Joint Airport Weather Studies (JAWS) for windshear microburst features are analyzed, in order to determine the optimal resolution, sensitivity, and scanning strategy for a standard system. The performance of three separate systems for measuring wind shear at heights of less than 200 meters is compared. The three systems included a dual-Doppler system, a single off-airport Doppler system, and a single on-airport Doppler system. On the basis of the comparison the following recommendations are offered concerning the optimal performance of a Doppler radar system in the airport environment: (1) the system should be able to measure radial velocities over a range of reflectivity of -10-80 dBZ; (2) ground clutter should be reduced; and techniques for identifying and disseminating wind shear information should be automated.

Wilson, J.↗

Framework for Multidisciplinary Analysis, Design, and Optimization with High-Fidelity Analysis Tools

A plan is presented for the development of a high fidelity multidisciplinary optimization process for rotorcraft. The plan formulates individual disciplinary design problems, identifies practical high-fidelity tools and processes that can be incorporated in an automated optimization environment, and establishes statements of the multidisciplinary design problem including objectives, constraints, design variables, and cross-disciplinary dependencies. Five key disciplinary areas are selected in the development plan. These are rotor aerodynamics, rotor structures and dynamics, fuselage aerodynamics, fuselage structures, and propulsion / drive system. Flying qualities and noise are included as ancillary areas. Consistency across engineering disciplines is maintained with a central geometry engine that supports all multidisciplinary analysis. The multidisciplinary optimization process targets the preliminary design cycle where gross elements of the helicopter have been defined. These might include number of rotors and rotor configuration (tandem, coaxial, etc.). It is at this stage that sufficient configuration information is defined to perform high-fidelity analysis. At the same time there is enough design freedom to influence a design. The rotorcraft multidisciplinary optimization tool is built and substantiated throughout its development cycle in a staged approach by incorporating disciplines sequentially.

Orr, Stanley A.↗

A Framework for Optimization-Based ISRU Tool Design Using Discrete Element Modeling

Novel robotic excavation technologies are needed to perform in-situ resource utilization (ISRU) tasks at levels required to sustain a long-term presence on the lunar surface. Developing and testing multiple iterations of functional hardware is time and cost prohibitive, thus slowing down the pace of progress and delaying humanity’s settlement of the Moon. High-fidelity, physics-based simulation can reduce the time and effort required to develop and deploy robotic systems [1]. We have adopted this approach to create high-fidelity models of robotic test hardware to enable rapid virtual design and optimization of excavation technologies [2]. Such models can leverage modern computational tools like Discrete Element Method (DEM) simulations that can be coupled with automated design approaches like topology optimization to reduce the amount of prototyping and physical testing needed to realize useful tools.

ISRU↗

Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. NASA’s current concept of the future of lunar communication, LunaNet, outlines a complex network of networks. Challenges such as scalability, interoperability and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. The application of machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study three main areas a means to further develop cognitive networking capabilities: networking and flight software development, analysis of wireless data for modeling and simulation, and development of algorithms for a multi-agent system.

Rachel Dudukovich↗

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases.3 As noted in [4] work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points.

Zwack, Mathew R.↗

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗

Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. NASA’s current concept of the future of lunar communication, LunaNet [1], outlines a complex network of networks. Challenges such as scalability, interoperability and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. The application of machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study three main areas a means to further develop cognitive networking capabilities: networking and flight software development, analysis of wireless data for modeling and simulation, and development of algorithms for a multi-agent system.

Cognitive Networking↗

Data system architecture considerations for a space station

The functions that a space station could serve are outlined and details of the data systems requirements are discussed. The data system design will be guided by an overall space systems plan, and will feature distributed, layered architecture, user friendliness, hierarchical control, technology transparency, standard interfaces, and automated engineering tools. The station would begin with a limited core capability and evolve to serve functions defined thereafter. The automation of the engineering tools will be necessary to permit an optimized, minimized crew to control all functions of the space station, while at the same time freeing the crew from being actively involved in maintaining the nominal life support functions of the equipment. One major criterion is that the software must be error free, while another is adaptibility to changing space station configurations and demands.

Connell, E. B.↗

Sensitivity and optimization of composite structures using MSC/NASTRAN

Design sensitivity analysis for composites will soon be available in MSC/NASTRAN. The design variables for composites can be lamina thicknesses, orientation angles, material properties or a combination of all three. With the increasing use of composites in aerospace and automotive industries, this general capability can be used in its own right for carrying out sensitivity analysis of complicated real-life structures. As part of a research effort, the sensitivity analysis was coupled with a general purpose optimizer. This preliminary version of the optimizer is capable of dealing with minimum weight structural design with a rather general design variable linking capability at the element level or system level. Only sizing type of design variables (i.e., lamina thicknesses) can be handled by the optimizer. Test cases were run and validated by comparison with independent finite element packages. The linking of design sensitivity capability for composites in MSC/NASTRAN with an optimizer would give designers a powerful automated tool to carry out practical opitmization design of real-life complicated composite structures.

Nagendra, Gopal K.↗

Applications of integrated design/analysis systems in aerospace structural design

Integrated structural analysis and design systems and structural optimization procedures are being used in a production environment. Successful use of these systems requires experienced personnel. Interactive computer graphics can and will play a significant role in the analysis, optimization, design and manufacturing areas. Practical structural optimization procedures are tools that must be made available to the team. Much work still needs to be done to tie finite-element modeling to actual design details which are being tracked on systems such as CADAM or CATIA. More work needs to be done to automate the detailed design and analysis process. More emphasis should be placed on the real design problems.

Mason, Philip↗

Modeling and managing risk early in software development

In order to improve the quality of the software development process, we need to be able to build empirical multivariate models based on data collectable early in the software process. These models need to be both useful for prediction and easy to interpret, so that remedial actions may be taken in order to control and optimize the development process. We present an automated modeling technique which can be used as an alternative to regression techniques. We show how it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize 'high risk' components in several Ada systems. Finally, we evaluate the effectiveness of our technique based on a comparison with logistic regression based models.

Briand, Lionel C.↗

Transitioning from Free-Flight to TRACON Airspace: The Ground Perspective of User-Preferred Descents

Free-flight is considered to play a major role in the future air traffic environment. Studies are underway addressing different concepts for free-flight and self separation in enroute airspace. One common opinion throughout the different concepts is that the airspace surrounding major airports, the Terminal Radar Approach CONtrol (TRACON) will not be a free flight area. This means that aircraft in this area are completely controlled by air traffic controllers, who may be supported by decision support system like the Center TRACON Automation System (CTAS). How the transition from the free-flight area (enroute airspace) to the terminal area will take place is currently unclear, This paper describes a study at NASA Ames Research Center addressing the perspective of air traffic controllers handling user-preferred (FMS-optimized) descent trajectories during this transition phase. Two major issues in enabling user preferred descents from the controllers' point of view are predictability and controllability. In an environment in which the air traffic services are highly responsive to user preferences controllers need to know, where and when aircraft will change their trajectory and they need to have appropriate means and procedures at hand to control the aircraft according to the overall traffic situation. Predictability shall be enhanced by: 1) Indicating airspace corridors for descending aircraft; 2) Modify the controller interface; 3) Using a ground based conflict probe; 4) Making use of downlinked intent information from the aircraft FMS; and 5) Requiring to fly pilots on user preferred trajectories coupled to the FMS in the lateral and vertical axis. Additional controllability shall be achieved by supporting the controllers with CTAS center tools: 1) Traffic Management Advisor (TMA); 2) Conflict Probing and Trial Planning (CP/TP); and 3) Enroute Descent Advisor (E/DA). The paper describes the general concept and the modifications to current systems required to enable the concept. It explains the experiment design and discusses the results with regard to controller acceptability and usability. Potential benefits and drawbacks of the overall concept are indicated.

Prevot, Thomas↗

Adaptive Shape Control for Aerodynamic Design

We present an approach to aerodynamic optimization in which the shape control is adaptively parameterized. Starting from a coarse set of design variables, a sequence of higher-dimensional nested search spaces is automatically generated. Refinement can be either uniform or adaptive, in which case only the most important shape control is added. The relative importance of candidate design variables is determined by comparing objective and constraint gradients, computed at low cost via adjoint solutions. A search procedure for finding an effective ensemble of shape parameters is also given. We first demonstrate this system on a multipoint drag miminization problem in 2D with many constraints, showing that an adaptive parameterization approach consistently achieves smoother, more robust, and faster design improvement than fixed parameterizations. We also establish a 3D shape- matching benchmark, where we demonstrate that our approach automatically discovers the necessary parameters to match a target shape. By largely automating shape parameterization, this work also aims to remove a time-consuming aspect of shape optimization.

Aerodynamic Design↗

Fault Management Techniques in Human Spaceflight Operations

This paper discusses human spaceflight fault management operations. Fault detection and response capabilities available in current US human spaceflight programs Space Shuttle and International Space Station are described while emphasizing system design impacts on operational techniques and constraints. Preflight and inflight processes along with products used to anticipate, mitigate and respond to failures are introduced. Examples of operational products used to support failure responses are presented. Possible improvements in the state of the art, as well as prioritization and success criteria for their implementation are proposed. This paper describes how the architecture of a command and control system impacts operations in areas such as the required fault response times, automated vs. manual fault responses, use of workarounds, etc. The architecture includes the use of redundancy at the system and software function level, software capabilities, use of intelligent or autonomous systems, number and severity of software defects, etc. This in turn drives which Caution and Warning (C&W) events should be annunciated, C&W event classification, operator display designs, crew training, flight control team training, and procedure development. Other factors impacting operations are the complexity of a system, skills needed to understand and operate a system, and the use of commonality vs. optimized solutions for software and responses. Fault detection, annunciation, safing responses, and recovery capabilities are explored using real examples to uncover underlying philosophies and constraints. These factors directly impact operations in that the crew and flight control team need to understand what happened, why it happened, what the system is doing, and what, if any, corrective actions they need to perform. If a fault results in multiple C&W events, or if several faults occur simultaneously, the root cause(s) of the fault(s), as well as their vehicle-wide impacts, must be determined in order to maintain situational awareness. This allows both automated and manual recovery operations to focus on the real cause of the fault(s). An appropriate balance must be struck between correcting the root cause failure and addressing the impacts of that fault on other vehicle components. Lastly, this paper presents a strategy for using lessons learned to improve the software, displays, and procedures in addition to determining what is a candidate for automation. Enabling technologies and techniques are identified to promote system evolution from one that requires manual fault responses to one that uses automation and autonomy where they are most effective. These considerations include the value in correcting software defects in a timely manner, automation of repetitive tasks, making time critical responses autonomous, etc. The paper recommends the appropriate use of intelligent systems to determine the root causes of faults and correctly identify separate unrelated faults.

O'Hagan, Brian↗

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

Kopp, H.↗

Automatic routing module

Automatic Routing Module (ARM) is a tool to partially automate Air Launched Cruise Missile (ALCM) routing. For any accessible launch point or target pair, ARM creates flyable routes that, within the fidelity of the models, are optimal in terms of threat avoidance, clobber avoidance, and adherence to vehicle and planning constraints. Although highly algorithmic, ARM is an expert system. Because of the heuristics applied, ARM generated routes closely resemble manually generated routes in routine cases. In more complex cases, ARM's ability to accumulate and assess threat danger in three dimensions and trade that danger off with the probability of ground clobber results in the safest path around or through difficult areas. The tools available prior to ARM did not provide the planner with enough information or present it in such a way that ensured he would select the safest path.

Malin, Janice A.↗