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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

JWST Mirror Technology Development

Since the initial Design Studies leading to JWST, Mirror Technology was identified as a (if not the) critical capability necessary to enable the next generation of large aperture space telescopes required to achieve the science goals of imaging the earliest galaxies and proto-galaxies after the big bang. Specific telescope architectures were explored via three independent design concept studies conducted during the summer of 1996. Achieving the desired science objectives required a never before demonstrated space telescope capability, one with an 8 meter class primary mirror that is diffraction limited at 2 micrometers and operating in deep space at temperatures well below 70K. Beryllium was identified in the NASA "Yardstick" design as the preferred material because of its ability to provide stable optical performance in the anticipated thermal environment as well as its excellent specific stiffness. Because of launch vehicle constraints, two very significant architectural constraints were placed upon the telescope: segmentation and areal density. Each of these directly resulted in specific technology capability requirements. First, because the maximum launch vehicle payload fairing diameter is approximately 4.5 meters, the only way to launch an 8 meter class mirror is to segment it, fold it and deploy it on orbit - resulting in actuation and control requirements. Second, because of launch vehicle mass limits, the primary mirror allocation was only 1000 kg - resulting in a maximum areal density specification of 20 kilograms per square meter.

Stahl, H. Philip↗
NASA NTRS2017

Ground Demonstration on the Autonomous Docking of Two 3U CubeSats Using a Novel Permanent-Magnet Docking Mechanism

Small spacecraft autonomous rendezvous and docking is an essential technology for future space structure assembly missions. A novel magnetic capture and latching mechanism is analyzed that allows for docking of two CubeSats without precise sensors and actuators. The proposed magnetic docking hardware not only provides the means to latch the CubeSats but it also significantly increases the likelihood of successful docking in the presence of relative attitude and position errors. The simplicity of the design allows it to be implemented on many CubeSat rendezvous missions. A CubeSat 3-DOF ground demonstration effort is on-going at NASA Langley Research Center that enables hardware-in-the loop testing of the autonomous approach and docking of a follower CubeSat to an identical leader CubeSat. The test setup consists of a 3 meter by 4 meter granite table and two nearly frictionless air bearing systems that support the two CubeSats. Four cold-gas on-off thrusters are used to translate the follower towards the leader, while a single reaction wheel is used to control the attitude of each CubeSat. An innovative modified pseudo inverse control allocation scheme was developed to address interactions between control effectors. The docking procedure requires relatively high actuator precision, a novel minimal impulse bit mitigation algorithm was developed to minimize the undesirable deadzone effects of the thrusters. Simulation of the ground demonstration shows that the Guidance, Navigation, and Control system along with the docking subsystem leads to successful docking under 3-sigma dispersions for all key system parameters. Extensive simulation and ground testing will provide sufficient confidence that the proposed docking mechanism along with the choosen suite of sensors and actuators will perform successful docking in the space environment.

Pei, Jing↗
NASA NTRS2013

Motion-Based Piloted Simulation Evaluation of a Control Allocation Technique to Recover from Pilot Induced Oscillations

This paper describes the maturation of a control allocation technique designed to assist pilots in the recovery from pilot induced oscillations (PIOs). The Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) is designed to enable next generation high efficiency aircraft designs. Energy efficient next generation aircraft require feedback control strategies that will enable lowering the actuator rate limit requirements for optimal airframe design. One of the common issues flying with actuator rate limits is PIOs caused by the phase lag between the pilot inputs and control surface response. CAPIO utilizes real-time optimization for control allocation to eliminate phase lag in the system caused by control surface rate limiting. System impacts of the control allocator were assessed through a piloted simulation evaluation of a non-linear aircraft simulation in the NASA Ames Vertical Motion Simulator. Results indicate that CAPIO helps reduce oscillatory behavior, including the severity and duration of PIOs, introduced by control surface rate limiting.

pilot induced oscillation↗
NASA NTRS2015

Linear Covariance Analysis For Proximity Operations Around Asteroid 2008 EV5

The NASA initiative to collect an asteroid, the Asteroid Robotic Redirect Mission (ARRM), is currently investigating the option of retrieving a boulder from an asteroid, demonstrating planetary defense with an enhanced gravity tractor technique, and returning it to a lunar orbit. Techniques for accomplishing this are being investigated by the Satellite Servicing Capabilities Office (SSCO) at NASA GSFC in collaboration with JPL, NASA JSC, LaRC, and Draper Laboratory, Inc. Two critical phases of the mission are the descent to the boulder and the Enhanced Gravity Tractor demonstration. A linear covariance analysis is done for these phases to assess the feasibility of these concepts with the proposed design of the sensor and actuator suite of the Asteroid Redirect Vehicle (ARV). The sensor suite for this analysis includes a wide field of view camera, LiDAR, and an IMU. The proposed asteroid of interest is currently the C-type asteroid 2008 EV5, a carbonaceous chondrite that is of high interest to the scientific community. This paper presents an overview of the linear covariance analysis techniques and simulation tool, provides sensor and actuator models, and addresses the feasibility of descending to the surface of the asteroid within allocated requirements as well as the possibility of maintaining a halo orbit to demonstrate the Enhanced Gravity Tractor technique.

Navigation↗
NASA NTRS2009

Sensitivity Analysis of Linear Programming and Quadratic Programming Algorithms for Control Allocation

The Next Generation (NextGen) transport aircraft configurations being investigated as part of the NASA Aeronautics Subsonic Fixed Wing Project have more control surfaces, or control effectors, than existing transport aircraft configurations. Conventional flight control is achieved through two symmetric elevators, two antisymmetric ailerons, and a rudder. The five effectors, reduced to three command variables, produce moments along the three main axes of the aircraft and enable the pilot to control the attitude and flight path of the aircraft. The NextGen aircraft will have additional redundant control effectors to control the three moments, creating a situation where the aircraft is over-actuated and where a simple relationship does not exist anymore between the required effector deflections and the desired moments. NextGen flight controllers will incorporate control allocation algorithms to determine the optimal effector commands and attain the desired moments, taking into account the effector limits. Approaches to solving the problem using linear programming and quadratic programming algorithms have been proposed and tested. It is of great interest to understand their relative advantages and disadvantages and how design parameters may affect their properties. In this paper, we investigate the sensitivity of the effector commands with respect to the desired moments and show on some examples that the solutions provided using the l2 norm of quadratic programming are less sensitive than those using the l1 norm of linear programming.

Frost, Susan A.↗
NASA NTRS2011

Implementation of CAPIO for Composite Adaptive Control of Cross-Coupled Unstable Aircraft

This paper presents an implementation of a recently developed control allocation algorithm CAPIO (a Control Allocation technique to recover from Pilot Induced Oscillations) for composite adaptive control of an inertially cross coupled unstable aircraft. When actuators are rate-saturated due to either an aggressive pilot command, high gain of the flight control system or some anomaly in the system, the effective delay in the control loop may increase due to the phase shifting between the desired and the achieved system states. This effective time delay may deteriorate the performance or even destabilize the system in some cases, depending on the severity of rate saturation. CAPIO reduces the effective time delay by minimizing the phase shift between the commanded and the actual attitude accelerations. We present simulation results for an unstable aircraft with cross-coupling controlled with a composite adaptive controller in the presence of rate saturation. The simulations demonstrate the potential of CAPIO serving as an effective rate saturation compensator in adverse conditions.

Yildiz, Yildiray↗
NASA NTRS2015

Generalized Nanosatellite Avionics Testbed Lab

The Generalized Nanosatellite Avionics Testbed (G-NAT) lab at NASA Ames Research Center provides a flexible, easily accessible platform for developing hardware and software for advanced small spacecraft. A collaboration between the Mission Design Division and the Intelligent Systems Division, the objective of the lab is to provide testing data and general test protocols for advanced sensors, actuators, and processors for CubeSat-class spacecraft. By developing test schemes for advanced components outside of the standard mission lifecycle, the lab is able to help reduce the risk carried by advanced nanosatellite or CubeSat missions. Such missions are often allocated very little time for testing, and too often the test facilities must be custom-built for the needs of the mission at hand. The G-NAT lab helps to eliminate these problems by providing an existing suite of testbeds that combines easily accessible, commercial-offthe- shelf (COTS) processors with a collection of existing sensors and actuators.

Testing data and general test protocols↗
NASA NTRS2002

On-Line Computation of a Local Attainable Moment Set for Reusable Launch Vehicles

Traditional attitude control design of reusable launch vehicles involves independent design of autopilot and control allocation modules [SBB99], [SK97], [SHJ00], [PS00], [Hod00]. Unfortunately, this results in the potential for overly aggressive commands in the autopilot resulting in a loss of performance due to actuator saturation, particularly if the autopilot may suffer from integrator wind-up [HH01].

Hodel, A. S.↗
NASA NTRS2006

Controlling Attitude of a Solar-Sail Spacecraft Using Vanes

A paper discusses a concept for controlling the attitude and thrust vector of a three-axis stabilized Solar Sail spacecraft using only four single degree-of-freedom articulated spar-tip vanes. The vanes, at the corners of the sail, would be turned to commanded angles about the diagonals of the square sail. Commands would be generated by an adaptive controller that would track a given trajectory while rejecting effects of such disturbance torques as those attributable to offsets between the center of pressure on the sail and the center of mass. The controller would include a standard proportional + derivative part, a feedforward part, and a dynamic component that would act like a generalized integrator. The controller would globally track reference signals, and in the presence of such control-actuator constraints as saturation and delay, the controller would utilize strategies to cancel or reduce their effects. The control scheme would be embodied in a robust, nonlinear algorithm that would allocate torques among the vanes, always finding a stable solution arbitrarily close to the global optimum solution of the control effort allocation problem. The solution would include an acceptably small angle, slow limit-cycle oscillation of the vanes, while providing overall thrust vector pointing stability and performance.

Mettler, Edward↗
NASA NTRS2004

A Flight Control Approach for Small Reentry Vehicles

Flight control of small crew return vehicles during atmospheric reentry will be an important technology in any human space flight mission undertaken in the future. The control system presented in this paper is applicable to small crew return vehicles in which reaction control system (RCS) thrusters are the only actuators available for attitude control. The control system consists of two modules: (i) the attitude controller using the trajectory linearization control (TLC) technique, and (ii) the reaction control system (RCS) control allocation module using a dynamic table-lookup technique. This paper describes the design and implementation of the TLC attitude control and the dynamic table-lookup RCS control allocation for nonimal flight along with design verification test results.

Bevacqoa, Tim↗
NASA NTRS1977

The optimal control frequency response problem in manual control

An optimal control frequency response problem is defined within the context of the optimal pilot model. The problem is designed to specify pilot model control frequencies reflective of important aircraft system properties, such as control feel system dynamics, airframe dynamics, and gust environment, as well as man machine properties, such as task and attention allocation. This is accomplished by determining a bounded set of control frequencies which minimize the total control cost. The bounds are given by zero and the neuromuscular control frequency response for each control actuator. This approach is fully adaptive, i.e., does not depend upon user entered estimates. An algorithm is developed to solve this optimal control frequency response problem. The algorithm is then applied to an attitude hold task for a bare airframe fighter aircraft case with interesting dynamic properties.

Harrington, W. W.↗
NASA NTRS1989

Precision Segmented Reflector figure control system architecture

A control system architecture for an actively controlled segmented reflector is described along with a design realization for achieving precision alignment of reflector panels. Performance requirements are derived in part from the Large Deployable Reflector, which is a representative mission, and error allocations are made which consider mirror panel surface errors, position measurement and figure estimation, and position control of both quasi-static and dynamic disturbances. The design uses multiple wavelength interferometric edge sensors and voice coil actuators in conjunction with a hybrid control strategy to correct panel position errors. A unit cell shown to be central to the concept is analyzed. The cell integrates the sensing, actuation, and mechanical functions of a control module together with a reflector panel to form a unitized assembly.

Mettler, E.↗
NASA NTRS2023

Reinforcement Learning Approach to Flight Control Allocation with Distributed Electric Propulsion

The flight control system of the SUSAN Electrofan concept aircraft achieves attitude control using both conventional flight control surfaces and differential thrust through distributed electric propulsion (DEP) from sixteen wing-mounted electric engines. The introduction of eight pairs of wing fans for attitude control creates a highly actuated system. Such a system requires more sophisticated control to operate, especially in the presence of wingfan failures where the loss of a single wingfan can result in a thrust imbalance. This paper investigates the use of deep reinforcement learning (RL) using proximal policy optimization (PPO) to achieve attitude control through a combination of DEP and control surface deflections. First, the paper examines the aircraft undergoing a coordinated turn. Then, it examines the aircraft experiencing a wingfan failure during cruise conditions. It is shown that deep reinforcement learning can be a potential avenue for nonlinear flight control design.

Distributed Electric Propulsion↗
NASA NTRS1980

Asynchronous interactive control systems

A class of interactive control systems is derived by generalizing interactive manipulator control systems. The general structural properties of such systems are discussed and an appropriate general software implementation is proposed. This is based on the fact that tasks of interactive control systems can be represented as a network of a finite set of actions which have specific operational characteristics and specific resource requirements, and which are of limited duration. This has enabled the decomposition of the overall control algorithm into a set of subalgorithms, called subcontrollers, which can operate simultaneously and asynchronously. Coordinate transformations of sensor feedback data and actuator set-points have enabled the further simplification of the subcontrollers and have reduced their conflicting resource requirements. The modules of the decomposed control system are implemented as parallel processes with disjoint memory space communicating only by I/O. The synchronization mechanisms for dynamic resource allocation among subcontrollers and other synchronization mechanisms are also discussed in this paper. Such a software organization is suitable for the general form of multiprocessing using computer networks with distributed storage.

Vuskovic, M. I.↗
NASA NTRS2003

NASA Tech Briefs, December 2003

Topics covered include: Organic/Inorganic Hybrid Polymer/Clay Nanocomposites; Less-Toxic Coatings for Inhibiting Corrosion of Aluminum; Liquid Coatings for Reducing Corrosion of Steel in Concrete; Processable Polyimides Containing APB and Reactive End Caps; Rod/Coil Block Copolyimides for Ion-Conducting Membranes; Techniques for Characterizing Microwave Printed Antennas; Cylindrical Antenna With Partly Adaptive Phased-Array Feed; Command Interface ASIC - Analog Interface ASIC Chip Set; Predicting Accumulations of Ice on Aerodynamic Surfaces; Analyzing Aeroelasticity in Turbomachines; Software for Allocating Resources in the Deep Space Network; Expert Seeker; High-Speed Recording of Test Data on Hard Disks; Functionally Graded Nanophase Beryllium/Carbon Composites; Thin Thermal-Insulation Blankets for Very High Temperatures; Aerostructures Test Wing; Flight-Test Evaluation of Flutter-Prediction Methods; Piezoelectrically Actuated Microvalve for Liquid Effluents; Larger-Stroke Piezoelectrically Actuated Microvalve; Innovative, High-Pressure, Cryogenic Control Valve: Short Face-to-Face, Reduced Cost; Safer Roadside Crash Walls Would Limit Deceleration; Improved Interactive Medical-Imaging System; Scanning Microscopes Using X Rays and Microchannels; Slotting Fins of Heat Exchangers to Provide Thermal Breaks; Methane Clathrate Hydrate Prospecting; Automated Monitoring with a BSP Fault-Detection Test; Automated Monitoring with a BCP Fault-Decision Test; Vector-Ordering Filter Procedure for Data Reduction; Remote Sensing and Information Technology for Large Farms; Developments at the Advanced Design Technologies Testbed; Spore-Forming Bacteria that Resist Sterilization; and Acoustical Applications of the HHT Method.

Source record↗
NASA NTRS1994

Overview of the Miniature Sensor Technology Integration (MSTI) spacecraft attitude control system

Msti2 is a small, 164 kg (362 lb), 3-axis stabilized, low-Earth-orbiting satellite whose mission is missile booster tracking. The spacecraft is actuated by 3 reaction wheels and 12 hot gas thrusters. It carries enough fuel for a projected life of 6 months. The sensor complement consists of a Horizon Sensor, a Sun Sensor, low-rate gyros, and a high rate gyro for despin. The total pointing control error allocation is 6 mRad (.34 Deg), and this is while tracking a target on the Earth's surface. This paper describes the Attitude Control System (ACS) algorithms which include the following: attitude acquisition (despin, Sun and Earth acquisition), attitude determination, attitude control, and linear stability analysis.

Mcewen, Rob↗
NASA NTRS2018

Thermal Operability Improvements for the Mars 2020 Rover Surface Mission

The Mars 2020 Rover is scheduled to land on Mars on February 18, 2021. One of the primary mission objectives for the Mars 2020 Rover is to perform in-situ science and collect a set of Martian regolith samples for possible future return to Earth. In order to meet mission requirements, 20 samples must be collected, assessed, and sealed during the prime mission (1.5 Martian years, approximately 1000 Sols). This requires that the Mars 2020 Rover operate in a much more efficient and autonomous manner than its predecessor, the Mars Science Laboratory (MSL) Rover, Curiosity. The thermal designs of both Curiosity and the Mars 2020 Rover utilize warmup heaters to bring the actuators and cameras, located on the outside of the vehicle, up to their operating temperatures prior to use. These heaters consume energy during the mission. The Rover energy balance, between energy production and consumption, must be maintained in order to keep the mission moving safely forward. Increased efficiency in the way this warmup heater energy is allocated and used in the Mars 2020 Rover operations plan will result in more energy available for science and engineering activities. This paper discusses the improvements that were made in both hardware and software to improve the way the Mars 2020 Rover will operate thermally on Mars.

Lee, Chern-Jiin↗
DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗