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CCSDS Spacecraft Monitor and Control Service Framework

This CCSDS paper presents a reference architecture and service framework for spacecraft monitoring and control. It has been prepared by the Spacecraft Monitoring and Control working group of the CCSDS Mission Operations and Information Management Systems (MOIMS) area. In this context, Spacecraft Monitoring and Control (SM&C) refers to end-to-end services between on- board or remote applications and ground-based functions responsible for mission operations. The scope of SM&C includes: 1) Operational Concept: definition of an operational concept that covers a set of standard operations activities related to the monitoring and control of both ground and space segments. 2) Core Set of Services: definition of an extensible set of services to support the operational concept together with its information model and behaviours. This includes (non exhaustively) ground systems such as Automatic Command and Control, Data Archiving and Retrieval, Flight Dynamics, Mission Planning and Performance Evaluation. 3) Application-layer information: definition of the standard information set to be exchanged for SM&C purposes.

Merri, Mario↗

Mode Transitions for the ST7 Disturbance Reduction System Experiment

The Space Technology 7 Disturbance Reduction System experiment will perform an on-orbit system-level validation of two technologies: a gravitational reference sensor employing a free-floating test mass and a set of colloidal micronewton thrusters. The Disturbance Reduction System is designed to maintain the spacecraft s position with respect to a free floating test mass to less than 10 nm/& over the frequency range of 1 to 30 m= mi paper presents the modes that compose the Disturbance Reduction System spacecraft control as well as the strategy used to transition between modes. A high-fidelity model of the system, which incorporates rigid-body models of the spacecraft and two test masses (18 degrees of freedom), is developed and used to evaluate the performance of each mode and the efficacy of the transition strategy.

Hsu, Oscar C.↗

Risk Assessment Using the Three Dimensions of Probability (Likelihood), Severity, and Level of Control

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the twodimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and threedimensional charting gives a visual confirmation of the relationship between causes and their controls

Watson, Clifford↗

Predicting Lifetime of a Thermomechanically Loaded Component

NASALIFE is a computer program for predicting the lifetime, as affected by low cycle fatigue (LCF) and creep rupture, of a structural component subject to temporally varying, multiaxial thermomechanical loads. The component could be, for example, part of an aircraft turbine engine. Empirical data from LCF tests, creep rupture tests, and static tensile tests are used as references for predicting the number of missions the component can withstand under a given thermomechanical loading condition. The user prepares an input file containing the creep-rupture and cyclic-fatigue information, temperature-dependent material properties, and mission loading and control flags. The creep rupture information can be entered in tabular form as stress versus life or by means of parameters of the Larson-Miller equation. The program uses the Walker mean-stress model to adjust predicted life for ranges of the ratio between the maximum and minimum stresses. Data representing complex load cycles are reduced by the rainflow counting method. Miner's rule is utilized to combine the damage at different load levels. Finally, the program determines the total damage due to creep and combines it with the fatigue damage due to the cyclic loading and predicts the approximate number of missions a component can endure before failing.

Murthy, Pappu L. N.↗

ICESat 2/ATLAS Onboard Flight Science Receiver Algorithms: Purpose, Process, and Performance

The Advanced Topographic Laser Altimetry System (ATLAS) is the sole instrument on the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2). Without some method of reducing the transmitted data, the volume of ATLAS telemetry would far exceed the normal X-band downlink capability or require many more ground station contacts. The ATLAS Onboard Flight Science Receiver Algorithms (hereinafter Receiver Algorithms or Algorithms) control the amount of science data that is telemetered from the instrument, limiting the data volume by distinguishing surface echoes from background noise, and allowing the instrument to telemeter data from only a small vertical region about the signal. This is accomplished through the transfer of the spacecraft's location and attitude to the instrument every second, use of an onboard Digital Elevation Model, implementation of signal processing techniques, and use of onboard relief and surface type reference maps. Extensive ground testing verified the performance of the Algorithms. On-orbit analysis shows that the Algorithms are working as expected from the ground testing; they are performing well and meeting the mission requirements.

Algoritms, Signal Processing, Optimization, Flight↗

Semispan Test Results of an Active Flow Control Enabled High-Lift Common Research Model in Landing Configuration

A 10%-scale semispan, Active Flow Control (AFC) enabled, simplified high-lift version of the Common Research Model (CRM-SHL-AFC) was tested in the 14- by 22-Foot Subsonic Tunnel at the NASA Langley Research Center. The main objective of the test was to develop an AFC system that can provide the necessary lift recovery on a simple-hinged flap high-lift system while minimizing its pneumatic power requirement. Three new types of AFC approaches were examined: Double-Row Sweeping Jets (DRSWJ), Alternating Pulsed Jets (APJ), and High Efficiency Low Power (HELP) actuators. The DRSWJ and the APJ actuators used two rows of unsteady jets, whereas the HELP actuators used an upstream row of sweeping jets combined with a downstream row of steady jets to overcome strong adverse pressure gradients. The test was conducted mostly at a freestream Mach number of 0.20. For exploration purposes, a limited number of runs were made at lower Mach numbers or using vortex generators (VGs). Minimal sensitivity to Mach number or VGs, for the cases evaluated, were observed. The AFC-induced lift coefficient increment was maintained over the AFC-off case for most flow-control cases examined. The CRM-SHL-AFC configuration equipped with HELP actuation was the only actuator configuration able to match or exceed the targeted lift performance of a reference conventional high-lift configuration. The presented aerodynamic data include lift, drag, and pitching moment coefficients as a function of angle of attack, with and without the Transonic Wall Interference Correction System (TWICS) method applied. Lift increments as a function of AFC pneumatic power usage (i.e., nozzle pressure ratio, mass flow, momentum coefficient, and power coefficient) are also presented at a lower angle of attack (α = 8.9°) and at maximum lift (α= 17.1°). At the two angles of attack, the surface pressure distributions and autospectral densities from the unsteady pressure transducers for the AFC-off case and the best HELP actuation case are compared.

high-lift↗

Cross coupling in pilot/vehicle systems

Multiloop pilot/vehicle analysis is applied to the problem of determining crossfeed techniques which may be employed by pilots in minimizing the effects of vehicle cross coupling. As used here, cross coupling refers to unwanted vehicle motion which occurs in one control axis or loop as the result of pilot control actuation in another control axis or loop. The minimization or elimination of such cross coupling can contribute significantly to the 'workload' associated with tasks like nap-of-the-earth helicopter flight. In contrast, situations arise in which pilot's may use vehicle cross coupling to improve performance by coordinating two control actuations in the control of a single response variable. A crossfeed model is developed based upon simple control system design principles and configured in a manner amenable to pilot pursuit or precognitive control activity. A handling qualities theory developed to analyze single loop tasks is applied to the multiloop problem. The crossfeed model is applied to five different vehicles/configurations ranging from helicopters to fighter aircraft. Results indicate relatively simple crossfeed commands can significantly reduce cross coupling and, in some improve handling qualities as predicted by the single loop theory.

Hess, R. A.↗

Flight Path Control Analysis for Parker Solar Probe

An unprecedented NASA mission to study the Sun, known as Parker Solar Probe (PSP), is under development. The primary objective of the PSP mission is to gather new data within 10 solar radii of the Sun’s center. The purpose of this paper is to review the statistical analysis of trajectory correction maneuvers (TCMs) for PSP’s baseline trajectory. The baseline mission includes a total of 42 TCMs that will be accomplished with a monopropellant propulsion system that consists of twelve 4.4 N thrusters. Assuming current navigation models, statistical analyses for each reference trajectory during the 20-day launch period result in a total V99 of less than 100 m/s.

Mottinger, Neil↗

Dynamic Stability Testing of the Mars Science Laboratory Entry Capsule

Results from a 26 shot ballistic range test of the Mars Science Laboratory (MSL) entry capsule are presented. The supersonic pitch damping properties of the MSL capsule were characterized between Mach 1.35 and Mach 3.5 and total angles-of-attack from 0 to 30 degrees. In flight, the MSL entry capsule will utilize a radial center-of-gravity offset to produce a non-zero trim angle-of-attack. This offset trim angle will produce lift, enabling the capsule to fly a guided entry and reducing the landing footprint dimensions to within 10 km of the desired landing site. A lifting configuration could not be tested at the ballistic range used for this test as the models would swerve into the range walls, possibly damaging cameras, the coordinate reference system or other facility assets. Ballistic (non-lifting) data was extracted and will be implemented in a conservative fashion to ensure that the dynamic stability characteristics of the flight vehicle are bounded. A comparison between the MSL pitch damping results and the dynamic model of the Mars Exploration Rover capsule shows generally close agreement with no significant differences in damping characteristics due to the change in backshell geometry. Dynamic moments are also compared to the MSL reaction control system (RCS) control authority to show the controller has sufficient margin to easily damp any dynamic stability effects.

Schroenenberger, Mark↗

Risk Presentation Using the Three Dimensions of Likelihood, Severity, and Level of Control

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the leastwell-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Watson, Clifford↗

Risk Assessment Using the Three Dimensions of Probability (Likelihood), Severity, and Level of Control

Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.

Watson, Clifford C.↗

DYGABCD: A program for calculating linear A, B, C, and D matrices from a nonlinear dynamic engine simulation

A digital computer program, DYGABCD, was developed that generates linearized, dynamic models of simulated turbofan and turbojet engines. DYGABCD is based on an earlier computer program, DYNGEN, that is capable of calculating simulated nonlinear steady-state and transient performance of one- and two-spool turbojet engines or two- and three-spool turbofan engines. Most control design techniques require linear system descriptions. For multiple-input/multiple-output systems such as turbine engines, state space matrix descriptions of the system are often desirable. DYGABCD computes the state space matrices commonly referred to as the A, B, C, and D matrices required for a linear system description. The report discusses the analytical approach and provides a users manual, FORTRAN listings, and a sample case.

Geyser, L. C.↗

Effect of model uncertainty on failure detection - The threshold selector

The performance of all failure detection, isolation, and accomodation (DIA) algorithms is influenced by the presence of model uncertainty. A unique framework is presented to incorporate a knowledge of modeling error in the analysis and design of failure detection systems. The tools being used are very similar to those in robust control theory. A concept is introduced called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals. The threshold selector represents an innovative tool for analysis and synthesis of DIA algorithms. It identifies the optimal threshold to be used in innovations-based DIA algorithms. The optimal threshold is shown to be a function of the bound on modeling errors, the noise properties, the speed of DIA filters, and the classes of reference and failure signals. The size of the smallest detectable failure is also determined. The results are applied to a multivariable turbofan jet engine example, which demonstrates improvements compared to previous studies.

Emami-Naeini, Abbas↗

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

Rubaai, Ahmed↗

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

Active Flow Control Enhanced Aileron of the High-Lift Common Research Model at Takeoff Condition

An experimental investigation was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel on the NASA 10% scale High-Lift Common Research Model (CRM-HL) to improve the high-lift aerodynamic performance of the takeoff configuration. Active flow control (AFC) was applied at the aileron hinge line to control flow separation at high aileron deflection angles to increase lift-to-drag ratio (L/D). Improvements in low speed L/D can increase vehicle payload and/or range resulting in a more efficient vehicle. Aileron deflection angles of 0°, 7.5°, 16°, and 25° were investigated. Flow control was applied to the two largest aileron deflections, which are considered the high-lift (HL) improved takeoff configurations. A companion paper will discuss baseline flow characteristics of the CRM-HL at the three takeoff conditions: reference, nominal, and HL-improved. In this paper, we focus on the aerodynamic improvement obtained when AFC was applied to an aileron deflected at 16° relative to the nominal configuration of 7.5° deflection. Multiple flow control parameters, including actuator type, spacing, and intensity, were investigated to evaluate the efficiency of the actuation system. The different AFC configurations tested were assessed with tuft visualization, steady surface pressure data, and force and moment data. The results indicated that all actuation types and spacings examined led to an increase in lift across the range of angles of attack investigated. Flow separation was mitigated with the injection of momentum at the aileron hinge line. The configurations with the smallest spacing produced the highest improvement in L/D. Steady jet actuation showed higher efficiency but similar aerodynamic performance when compared to the sweeping jet actuators. This work was performed in support of the NASA Advanced Air Transport Technology (AATT) Project.

CRM-HL↗

Cumulative creep-fatigue damage evolution in an austenitic stainless steel

A model of cumulative creep-fatigue damage has been developed which is based on the use of damage curve equations to describe the evolution of creep-fatigue damage for four basic creep-fatigue cycle types. These cycle types correspond to the four fundamental cycles of the Strain Range Partitioning Life Prediction approach of Manson, Halford, and Hirschberg. A concept referred to as Damage Coupling is introduced to analytically account for the differences in the nature of the damage introduced by each cycle type. For application of this model, the cumulative creep-fatigue damage behavior of type 316 stainless steel at 816 C has been experimentally established for the two-level loading cases involving fatigue and creep-fatigue, in various permutations. The tests were conducted such that the lower life (high strain) cycling was applied first, for a controlled number of cycles, and the higher life (lower strain) cycling was conducted at the second level, to failure. The proposed model correlated the majority of the observed cumulative creep-fatigue data.

Mcgaw, Michael A.↗

Utilizing Mars Global Reference Atmospheric Model (Mars-GRAM 2005) to Evaluate Entry Probe Mission Sites

Engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM s perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL)1. Traditional Mars-GRAM options for representing the mean atmosphere along entry corridors include: a) TES Mapping Years 1 and 2, with Mars-GRAM data coming from MGCM model results driven by observed TES dust optical depth; and b) TES Mapping Year 0, with user-controlled dust optical depth and Mars-GRAM data interpolated from MGCM model results driven by selected values of globally-uniform dust optical depth. From the surface to 80 km altitude, Mars-GRAM is based on NASA Ames Mars General Circulation Model (MGCM). Mars-GRAM and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA), with altitudes referenced to the MOLA areoid, or constant potential surface. Mars-GRAM 2005 has been validated2 against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES)

Justh, Hilary L.↗