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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

The influence of vehicle aerodynamic and control response characteristics on driver-vehicle performance

The effects of changes in understeer, control sensitivity, and location of the lateral aerodynamic center of pressure (c.p.) of a typical passenger car on the driver's opinion and on the performance of the driver-vehicle system were studied in a moving-base driving simulator. Twelve subjects with no prior experience on the simulator and no special driving skills performed regulation tasks in the presence of both random and step wind gusts.

Alexandridis, A. A.↗
NASA NTRS1999

X-33 Attitude Control Using the XRS-2200 Linear Aerospike Engine

The Vehicle Control Systems Team at Marshall Space Flight Center, Structures and Dynamics Laboratory, Guidance and Control Systems Division is designing, under a cooperative agreement with Lockheed Martin Skunkworks, the Ascent, Transition, and Entry flight attitude control systems for the X-33 experimental vehicle. Test flights, while suborbital, will achieve sufficient altitudes and Mach numbers to test Single Stage To Orbit, Reusable Launch Vehicle technologies. Ascent flight control phase, the focus of this paper, begins at liftoff and ends at linear aerospike main engine cutoff (MECO). The X-33 attitude control system design is confronted by a myriad of design challenges: a short design cycle, the X-33 incremental test philosophy, the concurrent design philosophy chosen for the X-33 program, and the fact that the attitude control system design is, as usual, closely linked to many other subsystems and must deal with constraints and requirements from these subsystems. Additionally, however, and of special interest, the use of the linear aerospike engine is a departure from the gimbaled engines traditionally used for thrust vector control (TVC) in launch vehicles and poses certain design challenges. This paper discusses the unique problem of designing the X-33 attitude control system with the linear aerospike engine, requirements development, modeling and analyses that verify the design.

Hall, Charles E.↗
NASA NTRS2015

Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach

Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.

Pei, Jing↗
NASA NTRS1974

Fracture control methods for space vehicles. Volume 1: Fracture control design methods

A systematic approach for applying methods for fracture control in the structural components of space vehicles consists of four major steps. The first step is to define the primary load-carrying structural elements and the type of load, environment, and design stress levels acting upon them. The second step is to identify the potential fracture-critical parts by means of a selection logic flow diagram. The third step is to evaluate the safe-life and fail-safe capabilities of the specified part. The last step in the sequence is to apply the control procedures that will prevent damage to the fracture-critical parts. The fracture control methods discussed include fatigue design and analysis methods, methods for preventing crack-like defects, fracture mechanics analysis methods, and nondestructive evaluation methods. An example problem is presented for evaluation of the safe-crack-growth capability of the space shuttle crew compartment skin structure.

Liu, A. F.↗
NASA NTRS1971

Nonflammable coolants for space vehicle environmental control systems Compatibility of component materials with selected dielectric fluids.

This paper summarizes a 4-year effort to evaluate and implement a nonflammable substitute coolant for application in the Saturn instrument unit (IU) environmental control system (ECS). Discussed are candidate material evaluations, detailed investigations of the properties of the coolant selected, and a summary of the implementation into a flight vehicle.

Howard, R. T.↗
NASA NTRS1987

Optoelectronic Docking System

Sensors and computers control approach and coupling. Proposed optoelectronic system with no moving parts automatically controls approach of two spacecraft as they closed from distance of about 1 km to within few cm. System concept modified for use on Earth in robotic assembly, to control docking of large ships, or to guide placement of large structural components. Optoelectronic docking system automatically controls approach of active vehicle or mechanism to passive vehicle or object. Maneuvers of approaching vehicle controlled in response to optoelectronically sensed relative position of approached vehicle.

Ward, S. M.↗
NASA NTRS2014

An Overview of the Characterization of the Space Launch Vehicle Aerodynamic Environments

Aerodynamic environments are some of the rst engineering data products that are needed to design a space launch vehicle. These products are used in performance predic- tions, vehicle control algorithm design, as well as determing loads on primary and secondary structures in multiple discipline areas. When the National Aeronautics and Space Admin- istration (NASA) Space Launch System (SLS) Program was established with the goal of designing a new, heavy-lift launch vehicle rst capable of lifting the Orion Program Multi- Purpose Crew Vehicle (MPCV) to low-earth orbit and preserving the potential to evolve the design to a 200 metric ton cargo launcher, the data needs were no di erent. Upon commencement of the new program, a characterization of aerodynamic environments were immediately initiated. In the time since, the SLS Aerodynamics Team has produced data describing the majority of the aerodynamic environment de nitions needed for structural design and vehicle control under nominal ight conditions. This paper provides an overview of select SLS aerodynamic environments completed to date.

Blevins, John A.↗
NASA NTRS1995

Helicopter Human Factors

Even under optimal conditions, helicopter flight is a most demanding form of human-machine interaction, imposing continuous manual, visual, communications, and mental demands on pilots. It is made even more challenging by small margins for error created by the close proximity of terrain in NOE flight and missions flown at night and in low visibility. Although technology advances have satisfied some current and proposed requirements, hardware solutions alone are not sufficient to ensure acceptable system performance and pilot workload. However, human factors data needed to improve the design and use of helicopters lag behind advances in sensor, display, and control technology. Thus, it is difficult for designers to consider human capabilities and limitations when making design decisions. This results in costly accidents, design mistakes, unrealistic mission requirements, excessive training costs, and challenge human adaptability. NASA, in collaboration with DOD, industry, and academia, has initiated a program of research to develop scientific data bases and design principles to improve the pilot/vehicle interface, optimize training time and cost, and maintain pilot workload and system performance at an acceptable level. Work performed at Ames, and by other research laboratories, will be reviewed to summarize the most critical helicopter human factors problems and the results of research that has been performed to: (1) Quantify/model pilots use of visual cues for vehicle control; (2) Improve pilots' performance with helmet displays of thermal imagery and night vision goggles for situation awareness and vehicle control; (3) Model the processes by which pilots encode maps and compare them to the visual scene to develop perceptually and cognitively compatible electronic map formats; (4) Evaluate the use of spatially localized auditory displays for geographical orientation, target localization, radio frequency separation; (5) Develop and flight test control/display concepts; (6) Quantify, model, predict, and improve pilots, workload-management strategies; and (7) Design computer-game trainers to reduce training time and cost.

Hart, Sandra G.↗
NASA NTRS2012

Integrated Simulation Design Challenges to Support TPS Repair Operations

During the Orbiter Repair Maneuver (ORM) operations planned for Return to Flight (RTF), the Shuttle Remote Manipulator System (SRMS) must grapple the International Space Station (ISS), undock the Orbiter, maneuver it through a long duration trajectory, and orient it to an EVA crewman poised at the end of the Space Station Remote Manipulator System (SSRMS) to facilitate the repair of the Thermal Protection System (TPS). Once repair has been completed and confirmed, then the SRMS proceeds back through the trajectory to dock the Orbiter to the Orbiter Docking System. In order to support analysis of the complex dynamic interactions of the integrated system formed by the Orbiter, ISS, SRMS, and SSMS during the ORM, simulation tools used for previous ‘nominal’ mission support required substantial enhancements. These upgrades were necessary to provide analysts with the capabilities needed to study integrated system performance. Prevalent throughout this ORM operation is a dynamically varying topology. In other words, the ORM starts with the SRMS grappled to the mated Shuttle/ISS stack (closed loop topology), moves to an open loop chain topology consisting of the Shuttle, SRMS, and ISS, and then, at the repair configuration, extends the chain topology to one consisting of the Shuttle, SMS, ISS, and SSRMS/EVA crewman. The resulting long dynamic chain of vehicles and manipulators may exhibit significant motion between the Shuttle worksite and the EVA crewman due to the system flexibility throughout the topology (particularly within the SRMS/SSRMS joints and links). Since the attachment points of both manipulators span the flexible structure of the ISS, simulation analysis may also need to take that into consideration. Moreover, due to the lengthy time duration associated with the maneuver and repair, orbital effects become a factor and require the ISS vehicle control system to maintain active attitude control. Several facets of the ORM operation make the associated analytical efforts different from previous mission support, including: (1) the magnitude of the SRMS handled payload (Le., Orbiter class), (2) the orbital effects induced on the integrated system consisting of the large Shuttle and ISS masses connected by a light flexible SRMS, (3) long duration environmental consequences due to the lengthy operational times associated with the maneuver and repair of the TPS, (4) active attitude control (as opposed to free drift) interacting with the SRMS and SSRMS manipulators (also due to the length of the maneuver and repair), (5) relative dynamics between the EVA crewman and thc worksite influenced by the extended flexible topology. In order to meet these analysis challenges, an ORM simulation architecture was developed leveraging upon numerous pre-existing simulation elements to analyze the various subsystems individually. For example, core manipulator subsystem simulations for both the SRMS and SSRMS were originally combined to provide the dual-arm dynamics topology simulation (in the absence of orbital dynamics and vehicle control). This capability was later merged with the simulation used to analyze SRMS loading with a heavy payload in the orbital environment with an active payload control system (in this case, the ISS Attitude Control System (ACS)), configured for the ORM. The resulting worksite dynamics simulation, based off of the modified ORM simulation, provided the extended topological chain of vehicles and manipulators, while taking into account the orbital effects of both the Shuttle and ISS (as well as its ACS). Verification and validation (V&V) of these integrated simulations became a challenge in itself. A systematic approach needed to be developed such that integration simulation results could be tested against previous constituent simulations upon which these simulations were built. General V&V categories included: (1) core orbital state propagation, (2), stand-alone SRMS, (3) stand-alone SSRMS, (4) stand-alone ISS ACS, (5) integrated Shuttle, SRMS, ISS (with active ACS) in the orbital environment, and (5) dual-arm SRMS/SSRMS dynamics topology. Integrated simulation V&V run suites were created and correlated to verification runs from subsystem simulations, in order to establish the validity of the results. This paper discusses the simulation design challenges encountered while developing simulation capabilities to mirror the ORM operations. The paper also describes the incremental build approach that was utilized, starting with the subsystem simulation elements and integration into increasing more complex simulations until the resulting ORM worksite dynamics simulation had been assembled. Furthermore, the paper presents an overall integrated simulation V&V methodology based upon a subsystem level testing, integrated comparisons, and phased checkout.

Thermal Protection System↗
DOE OSTI2024

Supervisory genset control in range-extended electric vehicle

A controls system for a range-extended electric vehicle comprising an overall system control unit, an engine control module configured to control a range extender of the range-extended electric vehicle, power electronics configured to control a generator of the range-extended electric vehicle, and a supervisory control module coupled between the overall system control unit and the engine control module and the power electronics, the supervisory control module configured to receive information from the overall system control unit and provide commands to the engine control module and the power electronics.

Li, Ke↗
NASA NTRS1994

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

guidepath position navigation control system↗
NASA NTRS1974

Manual control

Man's nonlinear characteristics and his use of control with compatible and incompatible multiple inputs, both visual and vestibular were studied. Experiments were also made with pulse and bang-bang controllers and the effects of sudden changes in control stick mechanical impedance. Closing the loop through the dynamics of the controlled vehicle allowed experiments on the limits of control of unstable vehicles with and without motion cues. The inverted pendulum controlled element, programmed as a self pacing element, was used extensively as a scalar performance index. In addition, the motorbike equations of motion were studied with regard to required human equalization. Abstracts are included for a series of published data on manual control.

Source record↗
DOE OSTI2021

Multimodal communication system

A multimodal communication system includes a vehicle controller that controls one or more systems or subsystems of an unmanned vehicle. The communication controller manages communication and logical access to the unmanned vehicle. One or more sensors in communication with the communication controller detects and measures physical properties in proximity to the unmanned vehicle. Transceivers receive the unmanned vehicle commands that are transmitted simultaneously or concurrently and a monotonic generator generates a monotonic object each time the unmanned vehicle's operating state changes. The communication controller executes the first unmanned vehicle command received that has the correct cryptographic hash validating knowledge of the unmanned vehicle's current operating state.

Duncan, Andrew M.↗